(upbeat jingle) >> The history of Exadata in the platform is really unique. And from my vantage point, it started earlier this century as a skunkworks inside of Oracle called Project Sage back when grid computing was the next big thing. Oracle saw that betting on standard hardware would put it on an industry curve that would rapidly evolve. Last April, for example, Oracle announced the availability of Exadata X9M in OCI, Oracle Cloud Infrastructure. One thing that hasn't been as well publicized is that Exadata on OCI is using AMD's EPYC processors in the database service. EPYC is not Eastern Pacific Yacht Club for all you sailing buffs, rather it stands for Extreme Performance Yield Computing, the enterprise grade version of AMD's Zen architecture which has been a linchpin of AMD's success in terms of penetrating enterprise markets. And to focus on the innovations that AMD and Oracle are bringing to market, we have with us today, Juan Loaiza, who's executive vice president of mission critical technologies at Oracle, and Mark Papermaster, who's the CTO and EVP of technology and engineering at AMD. Juan, welcome back to the show. Mark, great to have you on The Cube in your first appearance, thanks for coming on. Juan, let's start with you. You've been on The Cube a number of times, as I said, and you've talked about how Exadata is a top platform for Oracle database. We've covered that extensively. What's different and unique from your point of view about Exadata Cloud Infrastructure X9M on OCI? >> So as you know, Exadata, it's designed top down to be the best possible platform for database. It has a lot of unique capabilities, like we make extensive use of RDMA, smart storage. We take advantage of everything we can in the leading hardware platforms. X9M is our next generation platform and it does exactly that. We're always wanting to be, to get all the best that we can from the available hardware that our partners like AMD produce. And so that's what X9M in it is, it's faster, more capacity, lower latency, more iOS, pushing the limits of the hardware technology. So we don't want to be the limit, the software database software should not be the limit, it should be the actual physical limits of the hardware. That that's what X9M's all about. >> Why, Juan, AMD chips in X9M? >> We're introducing AMD chips. We think they provide outstanding performance, both for OTP and for analytic workloads. And it's really that simple, we just think the performance is outstanding in the product. >> Mark, your career is quite amazing. I could riff on history for hours but let's focus on the Oracle relationship. Mark, what are the relevant capabilities and key specs of the AMD chips that are used in Exadata X9M on Oracle's cloud? >> Well, thanks. It's really the basis of the great partnership that we have with Oracle on Exadata X9M and that is that the AMD technology uses our third generation of Zen processors. Zen was architected to really bring high performance back to X86, a very strong roadmap that we've executed on schedule to our commitments. And this third generation does all of that, it uses a seven nanometer CPU that is a core that was designed to really bring throughput, bring really high efficiency to computing and just deliver raw capabilities. And so for Exadata X9M, it's really leveraging all of that. It's really a balanced processor and it's implemented in a way to really optimize high performance. That is our whole focus of AMD. It's where we've reset the company focus on years ago. And again, great to see the super smart database team at Oracle really partner with us, understand those capabilities and it's been just great to partner with them to enable Oracle to really leverage the capabilities of the Zen processor. >> Yeah. It's been a pretty amazing 10 or 11 years for both companies. But Mark, how specifically are you working with Oracle at the engineering and product level and what does that mean for your joint customers in terms of what they can expect from the collaboration? >> Well, here's where the collaboration really comes to play. You think about a processor and I'll say, when Juan's team first looked at it, there's general benchmarks and the benchmarks are impressive but they're general benchmarks. And they showed the base processing capability but the partnership comes to bear when it means optimizing for the workloads that Exadata X9M is really delivering to the end customers. And that's where we dive down and as we learn from the Oracle team, we learn to understand where bottlenecks could be, where is there tuning that we could in fact really boost the performance above that baseline that you get in the generic benchmarks. And that's what the teams have done, so for instance, you look at optimizing latency to our DMA, you look at optimizing throughput on oil TP and database processing. When you go through the workloads and you take the traces and you break it down and you find the areas that are bottlenecking and then you can adjust, we have thousands of parameters that can be adjusted for a given workload. And that's the beauty of the partnership. So we have the expertise on the CPU engineering, Oracle Exadata team knows innately what the customers need to get the most out of their platform. And when the teams came together, we actually achieved anywhere from 20% to 50% gains on specific workloads, it is really exciting to see. >> Mark, last question for you is how do you see this relationship evolving in the future? Can you share a little roadmap for the audience? >> You bet. First off, given the deep partnership that we've had on Exadata X9M, it's really allowed us to inform our future design. So in our current third generation, EPYC is that is really what we call our epic server offerings. And it's a 7,003 third gen and Exadara X9M. So what about fourth gen? Well, fourth gen is well underway, ready for the future, but it incorporates learning that we've done in partnership with Oracle. It's going to have even more through capabilities, it's going to have expanded memory capabilities because there's a CXL connect express link that'll expand even more memory opportunities. And I could go on. So that's the beauty of a deep partnership as it enables us to really take that learning going forward. It pays forward and we're very excited to fold all of that into our future generations and provide even a better capabilities to Juan and his team moving forward. >> Yeah, you guys have been obviously very forthcoming. You have to be with Zen and EPYC. Juan, anything you'd like to add as closing comments? >> Yeah. I would say that in the processor market there's been a real acceleration in innovation in the last few years, there was a big move 10, 15 years ago when multicore processors came out. And then we were on that for a while and then things started stagnating, but in the last two or three years, AMD has been leading this, there's been a dramatic acceleration in innovation so it's very exciting to be part of this and customers are getting a big benefit from this. >> All right. Hey, thanks for coming back on The Cube today. Really appreciate your time. >> Thanks. Glad to be here. >> All right and thank you for watching this exclusive Cube conversation. This is Dave Vellante from The Cube and we'll see you next time. (upbeat jingle)

[Music] the history of exadata in the platform is really unique and from my vantage point it started earlier this century as a skunk works inside of oracle called project sage back when grid computing was the next big thing oracle saw that betting on standard hardware would put it on an industry curve that would rapidly evolve and i remember the oracle hp database machine which was announced at oracle open world almost 15 years ago and then exadata kept evolving after the sun acquisition it became a platform that had tightly integrated hardware and software and today exadata it keeps evolving almost like a chameleon to address more workloads and reach new performance levels last april for example oracle announced the availability of exadata x9m in oci oracle cloud infrastructure and introduced the ability to run the autonomous database service or the exa data database service you know oracle often talks about they call it stock exchange performance level kind of no description needed and sort of related capabilities the company as we know is fond of putting out benchmarks and comparisons with previous generations of product and sometimes competitive products that underscore the progress that's being made with exadata such as 87 percent more iops with metrics for latency measured in microseconds mics instead of milliseconds and many other numbers that are industry-leading and compelling especially for mission-critical workloads one thing that hasn't been as well publicized is that exadata on oci is using amd's epyc processors in the database service epyc is not eastern pacific yacht club for all your sailing buffs rather it stands for extreme performance yield computing the enterprise grade version of amd's zen architecture which has been a linchpin of amd's success in terms of penetrating enterprise markets and to focus on the innovations that amd and oracle are bringing to market we have with us today juan loyza who's executive vice president of mission critical technologies at oracle and mark papermaster who's the cto and evp of technology and engineering at amd juan welcome back to the show mark great to have you on thecube and your first appearance thanks for coming on yep happy to be here thank you all right juan let's start with you you've been on thecube a number of times as i said and you've talked about how exadata is a top platform for oracle database we've covered that extensively what's different and unique from your point of view about exadata cloud infrastructure x9m on oci yeah so as you know exadata it's designed top down to be the best possible platform for database uh it has a lot of unique capabilities like we make extensive use of rdma smart storage we take advantage of you know everything we can in the leading uh hardware platforms and x9m is our next generation platform and it does exactly that we're always wanting to be to get all the best that we can from the available hardware that our partners like amd produce and so that's what x9 in it is it's faster more capacity lower latency more ios pushing the limits of the hardware technology so we don't want to be the limit the software the database software should not be the limit it should be uh the actual physical limits of the hardware and that that's what x9m is all about why won amd chips in x9m uh yeah so we're we're uh introducing uh amd chips we think they provide outstanding performance uh both for oltp and for analytic workloads and it's really that simple we just think that performance is outstanding in the product yeah mark your career is quite amazing i've been around long enough to remember the transition to cmos from emitter coupled logic in the mainframe era back when you were at ibm that was an epic technology call at the time i was of course steeped as an analyst at idc in the pc era and like like many witnessed the tectonic shift that apple's ipod and iphone caused and the timing of you joining amd is quite important in my view because it coincided with the year that pc volumes peaked and marked the beginning of what i call a stagflation period for x86 i could riff on history for hours but let's focus on the oracle relationship mark what are the relevant capabilities and key specs of the amd chips that are used in exadata x9m on oracle's cloud well thanks and and uh it's really uh the basis of i think the great partnership that we have with oracle on exadata x9m and that is that the amd technology uses our third generation of zen processors zen was you know architected to really bring high performance you know back to x86 a very very strong road map that we've executed you know on schedule to our commitments and this third generation does all of that it uses a seven nanometer cpu that is a you know core that was designed to really bring uh throughput uh bring you know really high uh efficiency uh to computing uh and just deliver raw capabilities and so uh for uh exadata x9m uh it's really leveraging all of that it's it's a uh implemented in up to 64 cores per socket it's got uh you know really anywhere from 128 to 168 pcie gen 4 io connectivity so you can you can really attach uh you know all of the uh the necessary uh infrastructure and and uh storage uh that's needed uh for exadata performance and also memory you have to feed the beast for those analytics and for the oltp that juan was talking about and so it does have eight lanes of memory for high performance ddr4 so it's really as a balanced processor and it's implemented in a way to really optimize uh high performance that that is our whole focus of uh amd it's where we've you know reset the company focus on years ago and uh again uh you know great to see uh you know the the super smart uh you know database team at oracle really a partner with us understand those capabilities and it's been just great to partner with them to uh you know to you know enable oracle to really leverage the capabilities of the zen processor yeah it's been a pretty amazing 10 or 11 years for both companies but mark how specifically are you working with oracle at the engineering and product level you know and what does that mean for your joint customers in terms of what they can expect from the collaboration well here's where the collaboration really comes to play you think about a processor and you know i'll say you know when one's team first looked at it there's general benchmarks and the benchmarks are impressive but they're general benchmarks and you know and they showed you know the i'll say the you know the base processing capability but the partnership comes to bear uh when it when it means optimizing for the workloads that exadata x9m is really delivering to the end customers and that's where we dive down and and as we uh learn from the oracle team we learned to understand where bottlenecks could be uh where is there tuning that we could in fact in fact really boost the performance above i'll say that baseline that you get in the generic benchmarks and that's what the teams have done so for instance you look at you know optimizing latency to rdma you look at just throughput optimizing throughput on otp and database processing when you go through the workloads and you take the traces and you break it down and you find the areas that are bottlenecking and then you can adjust we have you know thousands of parameters that can be adjusted for a given workload and that's again that's the beauty of the partnership so we have the expertise on the cpu engineering uh you know oracle exudated team knows innately what the customers need to get the most out of their platform and when the teams came together we actually achieved anywhere from 20 percent to 50 gains on specific workloads it's really exciting to see so okay so so i want to follow up on that is that different from the competition how are you driving customer value you mentioned some you know some some percentage improvements are you measuring primarily with with latency how do you look at that well uh you know we are differentiated with the uh in the number of factors we bring a higher core density we bring the highest core density certainly in x86 and and moreover what we've led the industry is how to scale those cores we have a very high performance fabric that connects those together so as as a customer needs more cores again we scale anywhere from 8 to 64 cores but what the trick is uh that is you add more cores you want the scale the scale to be as close to linear as possible and so that's a differentiation we have and we enable that again with that balanced computer of cpu io and memory that we design but the key is you know we pride ourselves at amd of being able to partner in a very deep fashion with our customers we listen very well i think that's uh what we've had the opportunity uh to do with uh juan and his team we appreciate that and and that is how we got the kind of performance benefits that i described earlier it's working together almost like one team and in bringing that best possible capability to the end customers great thank you for that one i want to come back to you can both the exadata database service and the autonomous database service can they take advantage of exadata cloud x9m capabilities that are in that platform yeah absolutely um you know autonomous is basically our self-driving version of the oracle database but fundamentally it is the same uh database course so both of them will take advantage of the tremendous performance that we're getting now you know when when mark takes about 64 cores that's for chip we have two chips you know it's a two socket server so it's 128 128-way processor and then from our point of view there's two threads so from the database point there's 200 it's a 256-way processor and so there's a lot of raw performance there and we've done a lot of work with the amd team to make sure that we deliver that to our customers for all the different kinds of workload including otp analytics but also including for our autonomous database so yes absolutely allah takes advantage of it now juan you know i can't let you go without asking about the competition i've written extensively about the big four hyperscale clouds specifically aws azure google and alibaba and i know that don't hate me sometimes it angers some of my friends at oracle ibm too that i don't include you in that list but but i see oracle specifically is different and really the cloud for the most demanding applications and and top performance databases and not the commodity cloud which of course that angers all my friends at those four companies so i'm ticking everybody off so how does exadata cloud infrastructure x9m compare to the likes of aws azure google and other database cloud services in terms of oltp and analytics value performance cost however you want to frame it yeah so our architecture is fundamentally different uh we've architected our database for the scale out environment so for example we've moved intelligence in the storage uh we've put uh remote direct memory access we put persistent memory into our product so we've done a lot of architectural changes that they haven't and you're starting to see a little bit of that like if you look at some of the things that amazon and google are doing they're starting to realize that hey if you're gonna achieve good results you really need to push some database uh processing into the storage so so they're taking baby steps toward that you know you know roughly 15 years after we we've had a product and again at some point they're gonna realize you really need rdma you really need you know more uh direct access to those capabilities so so they're slowly getting there but you know we're well ahead and what you know the way this is delivered is you know better availability better performance lower latency higher iops so and this is why our customers love our product and you know if you if you look at the global fortune 100 over 90 percent of them are running exit data today and even in the in our cloud uh you know over 60 of the global 100 are running exadata in the oracle cloud because of all the differentiated uh benefits that they get uh from the product uh so yeah we're we're well ahead in the in the database space mark last question for you is how do you see this relationship evolving in the future can you share a little road map for the audience you bet well first off you know given the deep partnership that we've had on exudate x9m uh it it's really allowed us to inform our future design so uh in our current uh third generation epic epyc is uh that is really uh what we call our epic server offerings and it's a 7003 third gen in and exudate x9m so what about fourth gen well fourth gen is well underway uh you know it and uh and uh you know ready to you know for the for the future but it incorporates learning uh that we've done in partnership with with oracle uh it's gonna have even more through capabilities it's gonna have expanded memory capabilities because there's a cxl connect express link that'll expand even more memory opportunities and i could go on so you know that's the beauty of a deep partnership as it enables us to really take that learning going forward it pays forward and we're very excited to to fold all of that into our future generations and provide even a better capabilities to one and his team moving forward yeah you guys have been obviously very forthcoming you have to be with with with zen and epic juan anything you'd like to add as closing comments yeah i would say that in the processor market there's been a real acceleration in innovation in the last few years um there was you know a big move 10 15 years ago when multi-core processors came out and then you know we were on that for a while and then things started staggering but in the last two or three years and amd has been leading this um there's been a dramatic uh acceleration in innovation in this space so it's very exciting to be part of this and and customers are getting a big benefit from this all right chance hey thanks for coming back in the cube today really appreciate your time thanks glad to be here all right thank you for watching this exclusive cube conversation this is dave vellante from thecube and we'll see you next time [Music]

(upbeat music) >> The stampede to cloud and massive VC investments has led to the emergence of a new generation of object store based data lakes. And with them two important trends, actually three important trends. First, a new category that combines data lakes and data warehouses aka the lakehouse is emerged as a leading contender to be the data platform of the future. And this novelty touts the ability to address data engineering, data science, and data warehouse workloads on a single shared data platform. The other major trend we've seen is query engines and broader data fabric virtualization platforms have embraced NextGen data lakes as platforms for SQL centric business intelligence workloads, reducing, or somebody even claim eliminating the need for separate data warehouses. Pretty bold. However, cloud data warehouses have added complimentary technologies to bridge the gaps with lakehouses. And the third is many, if not most customers that are embracing the so-called data fabric or data mesh architectures. They're looking at data lakes as a fundamental component of their strategies, and they're trying to evolve them to be more capable, hence the interest in lakehouse, but at the same time, they don't want to, or can't abandon their data warehouse estate. As such we see a battle royale is brewing between cloud data warehouses and cloud lakehouses. Is it possible to do it all with one cloud center analytical data platform? Well, we're going to find out. My name is Dave Vellante and welcome to the data platform's power panel on theCUBE. Our next episode in a series where we gather some of the industry's top analysts to talk about one of our favorite topics, data. In today's session, we'll discuss trends, emerging options, and the trade offs of various approaches and we'll name names. Joining us today are Sanjeev Mohan, who's the principal at SanjMo, Tony Baers, principal at dbInsight. And Doug Henschen is the vice president and principal analyst at Constellation Research. Guys, welcome back to theCUBE. Great to see you again. >> Thank guys. Thank you. >> Thank you. >> So it's early June and we're gearing up with two major conferences, there's several database conferences, but two in particular that were very interested in, Snowflake Summit and Databricks Data and AI Summit. Doug let's start off with you and then Tony and Sanjeev, if you could kindly weigh in. Where did this all start, Doug? The notion of lakehouse. And let's talk about what exactly we mean by lakehouse. Go ahead. >> Yeah, well you nailed it in your intro. One platform to address BI data science, data engineering, fewer platforms, less cost, less complexity, very compelling. You can credit Databricks for coining the term lakehouse back in 2020, but it's really a much older idea. You can go back to Cloudera introducing their Impala database in 2012. That was a database on top of Hadoop. And indeed in that last decade, by the middle of that last decade, there were several SQL on Hadoop products, open standards like Apache Drill. And at the same time, the database vendors were trying to respond to this interest in machine learning and the data science. So they were adding SQL extensions, the likes Hudi and Vertical we're adding SQL extensions to support the data science. But then later in that decade with the shift to cloud and object storage, you saw the vendor shift to this whole cloud, and object storage idea. So you have in the database camp Snowflake introduce Snowpark to try to address the data science needs. They introduced that in 2020 and last year they announced support for Python. You also had Oracle, SAP jumped on this lakehouse idea last year, supporting both the lake and warehouse single vendor, not necessarily quite single platform. Google very recently also jumped on the bandwagon. And then you also mentioned, the SQL engine camp, the Dremios, the Ahanas, the Starbursts, really doing two things, a fabric for distributed access to many data sources, but also very firmly planning that idea that you can just have the lake and we'll help you do the BI workloads on that. And then of course, the data lake camp with the Databricks and Clouderas providing a warehouse style deployments on top of their lake platforms. >> Okay, thanks, Doug. I'd be remiss those of you who me know that I typically write my own intros. This time my colleagues fed me a lot of that material. So thank you. You guys make it easy. But Tony, give us your thoughts on this intro. >> Right. Well, I very much agree with both of you, which may not make for the most exciting television in terms of that it has been an evolution just like Doug said. I mean, for instance, just to give an example when Teradata bought AfterData was initially seen as a hardware platform play. In the end, it was basically, it was all those after functions that made a lot of sort of big data analytics accessible to SQL. (clears throat) And so what I really see just in a more simpler definition or functional definition, the data lakehouse is really an attempt by the data lake folks to make the data lake friendlier territory to the SQL folks, and also to get into friendly territory, to all the data stewards, who are basically concerned about the sprawl and the lack of control in governance in the data lake. So it's really kind of a continuing of an ongoing trend that being said, there's no action without counter action. And of course, at the other end of the spectrum, we also see a lot of the data warehouses starting to edit things like in database machine learning. So they're certainly not surrendering without a fight. Again, as Doug was mentioning, this has been part of a continual blending of platforms that we've seen over the years that we first saw in the Hadoop years with SQL on Hadoop and data warehouses starting to reach out to cloud storage or should say the HDFS and then with the cloud then going cloud native and therefore trying to break the silos down even further. >> Now, thank you. And Sanjeev, data lakes, when we first heard about them, there were such a compelling name, and then we realized all the problems associated with them. So pick it up from there. What would you add to Doug and Tony? >> I would say, these are excellent points that Doug and Tony have brought to light. The concept of lakehouse was going on to your point, Dave, a long time ago, long before the tone was invented. For example, in Uber, Uber was trying to do a mix of Hadoop and Vertical because what they really needed were transactional capabilities that Hadoop did not have. So they weren't calling it the lakehouse, they were using multiple technologies, but now they're able to collapse it into a single data store that we call lakehouse. Data lakes, excellent at batch processing large volumes of data, but they don't have the real time capabilities such as change data capture, doing inserts and updates. So this is why lakehouse has become so important because they give us these transactional capabilities. >> Great. So I'm interested, the name is great, lakehouse. The concept is powerful, but I get concerned that it's a lot of marketing hype behind it. So I want to examine that a bit deeper. How mature is the concept of lakehouse? Are there practical examples that really exist in the real world that are driving business results for practitioners? Tony, maybe you could kick that off. >> Well, put it this way. I think what's interesting is that both data lakes and data warehouse that each had to extend themselves. To believe the Databricks hype it's that this was just a natural extension of the data lake. In point of fact, Databricks had to go outside its core technology of Spark to make the lakehouse possible. And it's a very similar type of thing on the part with data warehouse folks, in terms of that they've had to go beyond SQL, In the case of Databricks. There have been a number of incremental improvements to Delta lake, to basically make the table format more performative, for instance. But the other thing, I think the most dramatic change in all that is in their SQL engine and they had to essentially pretty much abandon Spark SQL because it really, in off itself Spark SQL is essentially stop gap solution. And if they wanted to really address that crowd, they had to totally reinvent SQL or at least their SQL engine. And so Databricks SQL is not Spark SQL, it is not Spark, it's basically SQL that it's adapted to run in a Spark environment, but the underlying engine is C++, it's not scale or anything like that. So Databricks had to take a major detour outside of its core platform to do this. So to answer your question, this is not mature because these are all basically kind of, even though the idea of blending platforms has been going on for well over a decade, I would say that the current iteration is still fairly immature. And in the cloud, I could see a further evolution of this because if you think through cloud native architecture where you're essentially abstracting compute from data, there is no reason why, if let's say you are dealing with say, the same basically data targets say cloud storage, cloud object storage that you might not apportion the task to different compute engines. And so therefore you could have, for instance, let's say you're Google, you could have BigQuery, perform basically the types of the analytics, the SQL analytics that would be associated with the data warehouse and you could have BigQuery ML that does some in database machine learning, but at the same time for another part of the query, which might involve, let's say some deep learning, just for example, you might go out to let's say the serverless spark service or the data proc. And there's no reason why Google could not blend all those into a coherent offering that's basically all triggered through microservices. And I just gave Google as an example, if you could generalize that with all the other cloud or all the other third party vendors. So I think we're still very early in the game in terms of maturity of data lakehouses. >> Thanks, Tony. So Sanjeev, is this all hype? What are your thoughts? >> It's not hype, but completely agree. It's not mature yet. Lakehouses have still a lot of work to do, so what I'm now starting to see is that the world is dividing into two camps. On one hand, there are people who don't want to deal with the operational aspects of vast amounts of data. They are the ones who are going for BigQuery, Redshift, Snowflake, Synapse, and so on because they want the platform to handle all the data modeling, access control, performance enhancements, but these are trade off. If you go with these platforms, then you are giving up on vendor neutrality. On the other side are those who have engineering skills. They want the independence. In other words, they don't want vendor lock in. They want to transform their data into any number of use cases, especially data science, machine learning use case. What they want is agility via open file formats using any compute engine. So why do I say lakehouses are not mature? Well, cloud data warehouses they provide you an excellent user experience. That is the main reason why Snowflake took off. If you have thousands of cables, it takes minutes to get them started, uploaded into your warehouse and start experimentation. Table formats are far more resonating with the community than file formats. But once the cost goes up of cloud data warehouse, then the organization start exploring lakehouses. But the problem is lakehouses still need to do a lot of work on metadata. Apache Hive was a fantastic first attempt at it. Even today Apache Hive is still very strong, but it's all technical metadata and it has so many different restrictions. That's why we see Databricks is investing into something called Unity Catalog. Hopefully we'll hear more about Unity Catalog at the end of the month. But there's a second problem. I just want to mention, and that is lack of standards. All these open source vendors, they're running, what I call ego projects. You see on LinkedIn, they're constantly battling with each other, but end user doesn't care. End user wants a problem to be solved. They want to use Trino, Dremio, Spark from EMR, Databricks, Ahana, DaaS, Frink, Athena. But the problem is that we don't have common standards. >> Right. Thanks. So Doug, I worry sometimes. I mean, I look at the space, we've debated for years, best of breed versus the full suite. You see AWS with whatever, 12 different plus data stores and different APIs and primitives. You got Oracle putting everything into its database. It's actually done some interesting things with MySQL HeatWave, so maybe there's proof points there, but Snowflake really good at data warehouse, simplifying data warehouse. Databricks, really good at making lakehouses actually more functional. Can one platform do it all? >> Well in a word, I can't be best at breed at all things. I think the upshot of and cogen analysis from Sanjeev there, the database, the vendors coming out of the database tradition, they excel at the SQL. They're extending it into data science, but when it comes to unstructured data, data science, ML AI often a compromise, the data lake crowd, the Databricks and such. They've struggled to completely displace the data warehouse when it really gets to the tough SLAs, they acknowledge that there's still a role for the warehouse. Maybe you can size down the warehouse and offload some of the BI workloads and maybe and some of these SQL engines, good for ad hoc, minimize data movement. But really when you get to the deep service level, a requirement, the high concurrency, the high query workloads, you end up creating something that's warehouse like. >> Where do you guys think this market is headed? What's going to take hold? Which projects are going to fade away? You got some things in Apache projects like Hudi and Iceberg, where do they fit Sanjeev? Do you have any thoughts on that? >> So thank you, Dave. So I feel that table formats are starting to mature. There is a lot of work that's being done. We will not have a single product or single platform. We'll have a mixture. So I see a lot of Apache Iceberg in the news. Apache Iceberg is really innovating. Their focus is on a table format, but then Delta and Apache Hudi are doing a lot of deep engineering work. For example, how do you handle high concurrency when there are multiple rights going on? Do you version your Parquet files or how do you do your upcerts basically? So different focus, at the end of the day, the end user will decide what is the right platform, but we are going to have multiple formats living with us for a long time. >> Doug is Iceberg in your view, something that's going to address some of those gaps in standards that Sanjeev was talking about earlier? >> Yeah, Delta lake, Hudi, Iceberg, they all address this need for consistency and scalability, Delta lake open technically, but open for access. I don't hear about Delta lakes in any worlds, but Databricks, hearing a lot of buzz about Apache Iceberg. End users want an open performance standard. And most recently Google embraced Iceberg for its recent a big lake, their stab at having supporting both lakes and warehouses on one conjoined platform. >> And Tony, of course, you remember the early days of the sort of big data movement you had MapR was the most closed. You had Horton works the most open. You had Cloudera in between. There was always this kind of contest as to who's the most open. Does that matter? Are we going to see a repeat of that here? >> I think it's spheres of influence, I think, and Doug very much was kind of referring to this. I would call it kind of like the MongoDB syndrome, which is that you have... and I'm talking about MongoDB before they changed their license, open source project, but very much associated with MongoDB, which basically, pretty much controlled most of the contributions made decisions. And I think Databricks has the same iron cloud hold on Delta lake, but still the market is pretty much associated Delta lake as the Databricks, open source project. I mean, Iceberg is probably further advanced than Hudi in terms of mind share. And so what I see that's breaking down to is essentially, basically the Databricks open source versus the everything else open source, the community open source. So I see it's a very similar type of breakdown that I see repeating itself here. >> So by the way, Mongo has a conference next week, another data platform is kind of not really relevant to this discussion totally. But in the sense it is because there's a lot of discussion on earnings calls these last couple of weeks about consumption and who's exposed, obviously people are concerned about Snowflake's consumption model. Mongo is maybe less exposed because Atlas is prominent in the portfolio, blah, blah, blah. But I wanted to bring up the little bit of controversy that we saw come out of the Snowflake earnings call, where the ever core analyst asked Frank Klutman about discretionary spend. And Frank basically said, look, we're not discretionary. We are deeply operationalized. Whereas he kind of poo-pooed the lakehouse or the data lake, et cetera, saying, oh yeah, data scientists will pull files out and play with them. That's really not our business. Do any of you have comments on that? Help us swing through that controversy. Who wants to take that one? >> Let's put it this way. The SQL folks are from Venus and the data scientists are from Mars. So it means it really comes down to it, sort that type of perception. The fact is, is that, traditionally with analytics, it was very SQL oriented and that basically the quants were kind of off in their corner, where they're using SaaS or where they're using Teradata. It's really a great leveler today, which is that, I mean basic Python it's become arguably one of the most popular programming languages, depending on what month you're looking at, at the title index. And of course, obviously SQL is, as I tell the MongoDB folks, SQL is not going away. You have a large skills base out there. And so basically I see this breaking down to essentially, you're going to have each group that's going to have its own natural preferences for its home turf. And the fact that basically, let's say the Python and scale of folks are using Databricks does not make them any less operational or machine critical than the SQL folks. >> Anybody else want to chime in on that one? >> Yeah, I totally agree with that. Python support in Snowflake is very nascent with all of Snowpark, all of the things outside of SQL, they're very much relying on partners too and make things possible and make data science possible. And it's very early days. I think the bottom line, what we're going to see is each of these camps is going to keep working on doing better at the thing that they don't do today, or they're new to, but they're not going to nail it. They're not going to be best of breed on both sides. So the SQL centric companies and shops are going to do more data science on their database centric platform. That data science driven companies might be doing more BI on their leagues with those vendors and the companies that have highly distributed data, they're going to add fabrics, and maybe offload more of their BI onto those engines, like Dremio and Starburst. >> So I've asked you this before, but I'll ask you Sanjeev. 'Cause Snowflake and Databricks are such great examples 'cause you have the data engineering crowd trying to go into data warehousing and you have the data warehousing guys trying to go into the lake territory. Snowflake has $5 billion in the balance sheet and I've asked you before, I ask you again, doesn't there has to be a semantic layer between these two worlds? Does Snowflake go out and do M&A and maybe buy ad scale or a data mirror? Or is that just sort of a bandaid? What are your thoughts on that Sanjeev? >> I think semantic layer is the metadata. The business metadata is extremely important. At the end of the day, the business folks, they'd rather go to the business metadata than have to figure out, for example, like let's say, I want to update somebody's email address and we have a lot of overhead with data residency laws and all that. I want my platform to give me the business metadata so I can write my business logic without having to worry about which database, which location. So having that semantic layer is extremely important. In fact, now we are taking it to the next level. Now we are saying that it's not just a semantic layer, it's all my KPIs, all my calculations. So how can I make those calculations independent of the compute engine, independent of the BI tool and make them fungible. So more disaggregation of the stack, but it gives us more best of breed products that the customers have to worry about. >> So I want to ask you about the stack, the modern data stack, if you will. And we always talk about injecting machine intelligence, AI into applications, making them more data driven. But when you look at the application development stack, it's separate, the database is tends to be separate from the data and analytics stack. Do those two worlds have to come together in the modern data world? And what does that look like organizationally? >> So organizationally even technically I think it is starting to happen. Microservices architecture was a first attempt to bring the application and the data world together, but they are fundamentally different things. For example, if an application crashes, that's horrible, but Kubernetes will self heal and it'll bring the application back up. But if a database crashes and corrupts your data, we have a huge problem. So that's why they have traditionally been two different stacks. They are starting to come together, especially with data ops, for instance, versioning of the way we write business logic. It used to be, a business logic was highly embedded into our database of choice, but now we are disaggregating that using GitHub, CICD the whole DevOps tool chain. So data is catching up to the way applications are. >> We also have databases, that trans analytical databases that's a little bit of what the story is with MongoDB next week with adding more analytical capabilities. But I think companies that talk about that are always careful to couch it as operational analytics, not the warehouse level workloads. So we're making progress, but I think there's always going to be, or there will long be a separate analytical data platform. >> Until data mesh takes over. (all laughing) Not opening a can of worms. >> Well, but wait, I know it's out of scope here, but wouldn't data mesh say, hey, do take your best of breed to Doug's earlier point. You can't be best of breed at everything, wouldn't data mesh advocate, data lakes do your data lake thing, data warehouse, do your data lake, then you're just a node on the mesh. (Tony laughs) Now you need separate data stores and you need separate teams. >> To my point. >> I think, I mean, put it this way. (laughs) Data mesh itself is a logical view of the world. The data mesh is not necessarily on the lake or on the warehouse. I think for me, the fear there is more in terms of, the silos of governance that could happen and the silo views of the world, how we redefine. And that's why and I want to go back to something what Sanjeev said, which is that it's going to be raising the importance of the semantic layer. Now does Snowflake that opens a couple of Pandora's boxes here, which is one, does Snowflake dare go into that space or do they risk basically alienating basically their partner ecosystem, which is a key part of their whole appeal, which is best of breed. They're kind of the same situation that Informatica was where in the early 2000s, when Informatica briefly flirted with analytic applications and realized that was not a good idea, need to redouble down on their core, which was data integration. The other thing though, that raises the importance of and this is where the best of breed comes in, is the data fabric. My contention is that and whether you use employee data mesh practice or not, if you do employee data mesh, you need data fabric. If you deploy data fabric, you don't necessarily need to practice data mesh. But data fabric at its core and admittedly it's a category that's still very poorly defined and evolving, but at its core, we're talking about a common meta data back plane, something that we used to talk about with master data management, this would be something that would be more what I would say basically, mutable, that would be more evolving, basically using, let's say, machine learning to kind of, so that we don't have to predefine rules or predefine what the world looks like. But so I think in the long run, what this really means is that whichever way we implement on whichever physical platform we implement, we need to all be speaking the same metadata language. And I think at the end of the day, regardless of whether it's a lake, warehouse or a lakehouse, we need common metadata. >> Doug, can I come back to something you pointed out? That those talking about bringing analytic and transaction databases together, you had talked about operationalizing those and the caution there. Educate me on MySQL HeatWave. I was surprised when Oracle put so much effort in that, and you may or may not be familiar with it, but a lot of folks have talked about that. Now it's got nowhere in the market, that no market share, but a lot of we've seen these benchmarks from Oracle. How real is that bringing together those two worlds and eliminating ETL? >> Yeah, I have to defer on that one. That's my colleague, Holger Mueller. He wrote the report on that. He's way deep on it and I'm not going to mock him. >> I wonder if that is something, how real that is or if it's just Oracle marketing, anybody have any thoughts on that? >> I'm pretty familiar with HeatWave. It's essentially Oracle doing what, I mean, there's kind of a parallel with what Google's doing with AlloyDB. It's an operational database that will have some embedded analytics. And it's also something which I expect to start seeing with MongoDB. And I think basically, Doug and Sanjeev were kind of referring to this before about basically kind of like the operational analytics, that are basically embedded within an operational database. The idea here is that the last thing you want to do with an operational database is slow it down. So you're not going to be doing very complex deep learning or anything like that, but you might be doing things like classification, you might be doing some predictives. In other words, we've just concluded a transaction with this customer, but was it less than what we were expecting? What does that mean in terms of, is this customer likely to turn? I think we're going to be seeing a lot of that. And I think that's what a lot of what MySQL HeatWave is all about. Whether Oracle has any presence in the market now it's still a pretty new announcement, but the other thing that kind of goes against Oracle, (laughs) that they had to battle against is that even though they own MySQL and run the open source project, everybody else, in terms of the actual commercial implementation it's associated with everybody else. And the popular perception has been that MySQL has been basically kind of like a sidelight for Oracle. And so it's on Oracles shoulders to prove that they're damn serious about it. >> There's no coincidence that MariaDB was launched the day that Oracle acquired Sun. Sanjeev, I wonder if we could come back to a topic that we discussed earlier, which is this notion of consumption, obviously Wall Street's very concerned about it. Snowflake dropped prices last week. I've always felt like, hey, the consumption model is the right model. I can dial it down in when I need to, of course, the street freaks out. What are your thoughts on just pricing, the consumption model? What's the right model for companies, for customers? >> Consumption model is here to stay. What I would like to see, and I think is an ideal situation and actually plays into the lakehouse concept is that, I have my data in some open format, maybe it's Parquet or CSV or JSON, Avro, and I can bring whatever engine is the best engine for my workloads, bring it on, pay for consumption, and then shut it down. And by the way, that could be Cloudera. We don't talk about Cloudera very much, but it could be one business unit wants to use Athena. Another business unit wants to use some other Trino let's say or Dremio. So every business unit is working on the same data set, see that's critical, but that data set is maybe in their VPC and they bring any compute engine, you pay for the use, shut it down. That then you're getting value and you're only paying for consumption. It's not like, I left a cluster running by mistake, so there have to be guardrails. The reason FinOps is so big is because it's very easy for me to run a Cartesian joint in the cloud and get a $10,000 bill. >> This looks like it's been a sort of a victim of its own success in some ways, they made it so easy to spin up single note instances, multi note instances. And back in the day when compute was scarce and costly, those database engines optimized every last bit so they could get as much workload as possible out of every instance. Today, it's really easy to spin up a new node, a new multi node cluster. So that freedom has meant many more nodes that aren't necessarily getting that utilization. So Snowflake has been doing a lot to add reporting, monitoring, dashboards around the utilization of all the nodes and multi node instances that have spun up. And meanwhile, we're seeing some of the traditional on-prem databases that are moving into the cloud, trying to offer that freedom. And I think they're going to have that same discovery that the cost surprises are going to follow as they make it easy to spin up new instances. >> Yeah, a lot of money went into this market over the last decade, separating compute from storage, moving to the cloud. I'm glad you mentioned Cloudera Sanjeev, 'cause they got it all started, the kind of big data movement. We don't talk about them that much. Sometimes I wonder if it's because when they merged Hortonworks and Cloudera, they dead ended both platforms, but then they did invest in a more modern platform. But what's the future of Cloudera? What are you seeing out there? >> Cloudera has a good product. I have to say the problem in our space is that there're way too many companies, there's way too much noise. We are expecting the end users to parse it out or we expecting analyst firms to boil it down. So I think marketing becomes a big problem. As far as technology is concerned, I think Cloudera did turn their selves around and Tony, I know you, you talked to them quite frequently. I think they have quite a comprehensive offering for a long time actually. They've created Kudu, so they got operational, they have Hadoop, they have an operational data warehouse, they're migrated to the cloud. They are in hybrid multi-cloud environment. Lot of cloud data warehouses are not hybrid. They're only in the cloud. >> Right. I think what Cloudera has done the most successful has been in the transition to the cloud and the fact that they're giving their customers more OnRamps to it, more hybrid OnRamps. So I give them a lot of credit there. They're also have been trying to position themselves as being the most price friendly in terms of that we will put more guardrails and governors on it. I mean, part of that could be spin. But on the other hand, they don't have the same vested interest in compute cycles as say, AWS would have with EMR. That being said, yes, Cloudera does it, I think its most powerful appeal so of that, it almost sounds in a way, I don't want to cast them as a legacy system. But the fact is they do have a huge landed legacy on-prem and still significant potential to land and expand that to the cloud. That being said, even though Cloudera is multifunction, I think it certainly has its strengths and weaknesses. And the fact this is that yes, Cloudera has an operational database or an operational data store with a kind of like the outgrowth of age base, but Cloudera is still based, primarily known for the deep analytics, the operational database nobody's going to buy Cloudera or Cloudera data platform strictly for the operational database. They may use it as an add-on, just in the same way that a lot of customers have used let's say Teradata basically to do some machine learning or let's say, Snowflake to parse through JSON. Again, it's not an indictment or anything like that, but the fact is obviously they do have their strengths and their weaknesses. I think their greatest opportunity is with their existing base because that base has a lot invested and vested. And the fact is they do have a hybrid path that a lot of the others lack. >> And of course being on the quarterly shock clock was not a good place to be under the microscope for Cloudera and now they at least can refactor the business accordingly. I'm glad you mentioned hybrid too. We saw Snowflake last month, did a deal with Dell whereby non-native Snowflake data could access on-prem object store from Dell. They announced a similar thing with pure storage. What do you guys make of that? Is that just... How significant will that be? Will customers actually do that? I think they're using either materialized views or extended tables. >> There are data rated and residency requirements. There are desires to have these platforms in your own data center. And finally they capitulated, I mean, Frank Klutman is famous for saying to be very focused and earlier, not many months ago, they called the going on-prem as a distraction, but clearly there's enough demand and certainly government contracts any company that has data residency requirements, it's a real need. So they finally addressed it. >> Yeah, I'll bet dollars to donuts, there was an EBC session and some big customer said, if you don't do this, we ain't doing business with you. And that was like, okay, we'll do it. >> So Dave, I have to say, earlier on you had brought this point, how Frank Klutman was poo-pooing data science workloads. On your show, about a year or so ago, he said, we are never going to on-prem. He burnt that bridge. (Tony laughs) That was on your show. >> I remember exactly the statement because it was interesting. He said, we're never going to do the halfway house. And I think what he meant is we're not going to bring the Snowflake architecture to run on-prem because it defeats the elasticity of the cloud. So this was kind of a capitulation in a way. But I think it still preserves his original intent sort of, I don't know. >> The point here is that every vendor will poo-poo whatever they don't have until they do have it. >> Yes. >> And then it'd be like, oh, we are all in, we've always been doing this. We have always supported this and now we are doing it better than others. >> Look, it was the same type of shock wave that we felt basically when AWS at the last moment at one of their reinvents, oh, by the way, we're going to introduce outposts. And the analyst group is typically pre briefed about a week or two ahead under NDA and that was not part of it. And when they dropped, they just casually dropped that in the analyst session. It's like, you could have heard the sound of lots of analysts changing their diapers at that point. >> (laughs) I remember that. And a props to Andy Jassy who once, many times actually told us, never say never when it comes to AWS. So guys, I know we got to run. We got some hard stops. Maybe you could each give us your final thoughts, Doug start us off and then-- >> Sure. Well, we've got the Snowflake Summit coming up. I'll be looking for customers that are really doing data science, that are really employing Python through Snowflake, through Snowpark. And then a couple weeks later, we've got Databricks with their Data and AI Summit in San Francisco. I'll be looking for customers that are really doing considerable BI workloads. Last year I did a market overview of this analytical data platform space, 14 vendors, eight of them claim to support lakehouse, both sides of the camp, Databricks customer had 32, their top customer that they could site was unnamed. It had 32 concurrent users doing 15,000 queries per hour. That's good but it's not up to the most demanding BI SQL workloads. And they acknowledged that and said, they need to keep working that. Snowflake asked for their biggest data science customer, they cited Kabura, 400 terabytes, 8,500 users, 400,000 data engineering jobs per day. I took the data engineering job to be probably SQL centric, ETL style transformation work. So I want to see the real use of the Python, how much Snowpark has grown as a way to support data science. >> Great. Tony. >> Actually of all things. And certainly, I'll also be looking for similar things in what Doug is saying, but I think sort of like, kind of out of left field, I'm interested to see what MongoDB is going to start to say about operational analytics, 'cause I mean, they're into this conquer the world strategy. We can be all things to all people. Okay, if that's the case, what's going to be a case with basically, putting in some inline analytics, what are you going to be doing with your query engine? So that's actually kind of an interesting thing we're looking for next week. >> Great. Sanjeev. >> So I'll be at MongoDB world, Snowflake and Databricks and very interested in seeing, but since Tony brought up MongoDB, I see that even the databases are shifting tremendously. They are addressing both the hashtag use case online, transactional and analytical. I'm also seeing that these databases started in, let's say in case of MySQL HeatWave, as relational or in MongoDB as document, but now they've added graph, they've added time series, they've added geospatial and they just keep adding more and more data structures and really making these databases multifunctional. So very interesting. >> It gets back to our discussion of best of breed, versus all in one. And it's likely Mongo's path or part of their strategy of course, is through developers. They're very developer focused. So we'll be looking for that. And guys, I'll be there as well. I'm hoping that we maybe have some extra time on theCUBE, so please stop by and we can maybe chat a little bit. Guys as always, fantastic. Thank you so much, Doug, Tony, Sanjeev, and let's do this again. >> It's been a pleasure. >> All right and thank you for watching. This is Dave Vellante for theCUBE and the excellent analyst. We'll see you next time. (upbeat music)

(upbeat music) >> The ascendancy of cloud and SAS has shown new light on how organizations think about, pay for, and value hardware. Once sought after skills for practitioners with expertise in hardware troubleshooting, configuring ports, tuning storage arrays, and maximizing server utilization has been superseded by demand for cloud architects, DevOps pros, developers with expertise in microservices, container, application development, and like. Even a company like Dell, the largest hardware company in enterprise tech touts that it has more software engineers than those working in hardware. Begs the question, is hardware going the way of Coball? Well, not likely. Software has to run on something, but the labor needed to deploy, and troubleshoot, and manage hardware infrastructure is shifting. At the same time, we've seen the value flow also shifting in hardware. Once a world dominated by X86 processors value is flowing to alternatives like Nvidia and arm based designs. Moreover, other componentry like NICs, accelerators, and storage controllers are becoming more advanced, integrated, and increasingly important. The question is, does it matter? And if so, why does it matter and to whom? What does it mean to customers, workloads, OEMs, and the broader society? Hello and welcome to this week's Wikibon theCUBE Insights powered by ETR. In this breaking analysis, we've organized a special power panel of industry analysts and experts to address the question, does hardware still matter? Allow me to introduce the panel. Bob O'Donnell is president and chief analyst at TECHnalysis Research. Zeus Kerravala is the founder and principal analyst at ZK Research. David Nicholson is a CTO and tech expert. Keith Townson is CEO and founder of CTO Advisor. And Marc Staimer is the chief dragon slayer at Dragon Slayer Consulting and oftentimes a Wikibon contributor. Guys, welcome to theCUBE. Thanks so much for spending some time here. >> Good to be here. >> Thanks. >> Thanks for having us. >> Okay before we get into it, I just want to bring up some data from ETR. This is a survey that ETR does every quarter. It's a survey of about 1200 to 1500 CIOs and IT buyers and I'm showing a subset of the taxonomy here. This XY axis and the vertical axis is something called net score. That's a measure of spending momentum. It's essentially the percentage of customers that are spending more on a particular area than those spending less. You subtract the lesses from the mores and you get a net score. Anything the horizontal axis is pervasion in the data set. Sometimes they call it market share. It's not like IDC market share. It's just the percentage of activity in the data set as a percentage of the total. That red 40% line, anything over that is considered highly elevated. And for the past, I don't know, eight to 12 quarters, the big four have been AI and machine learning, containers, RPA and cloud and cloud of course is very impressive because not only is it elevated in the vertical access, but you know it's very highly pervasive on the horizontal. So what I've done is highlighted in red that historical hardware sector. The server, the storage, the networking, and even PCs despite the work from home are depressed in relative terms. And of course, data center collocation services. Okay so you're seeing obviously hardware is not... People don't have the spending momentum today that they used to. They've got other priorities, et cetera, but I want to start and go kind of around the horn with each of you, what is the number one trend that each of you sees in hardware and why does it matter? Bob O'Donnell, can you please start us off? >> Sure Dave, so look, I mean, hardware is incredibly important and one comment first I'll make on that slide is let's not forget that hardware, even though it may not be growing, the amount of money spent on hardware continues to be very, very high. It's just a little bit more stable. It's not as subject to big jumps as we see certainly in other software areas. But look, the important thing that's happening in hardware is the diversification of the types of chip architectures we're seeing and how and where they're being deployed, right? You refer to this in your opening. We've moved from a world of x86 CPUs from Intel and AMD to things like obviously GPUs, DPUs. We've got VPU for, you know, computer vision processing. We've got AI-dedicated accelerators, we've got all kinds of other network acceleration tools and AI-powered tools. There's an incredible diversification of these chip architectures and that's been happening for a while but now we're seeing them more widely deployed and it's being done that way because workloads are evolving. The kinds of workloads that we're seeing in some of these software areas require different types of compute engines than traditionally we've had. The other thing is (coughs), excuse me, the power requirements based on where geographically that compute happens is also evolving. This whole notion of the edge, which I'm sure we'll get into a little bit more detail later is driven by the fact that where the compute actually sits closer to in theory the edge and where edge devices are, depending on your definition, changes the power requirements. It changes the kind of connectivity that connects the applications to those edge devices and those applications. So all of those things are being impacted by this growing diversity in chip architectures. And that's a very long-term trend that I think we're going to continue to see play out through this decade and well into the 2030s as well. >> Excellent, great, great points. Thank you, Bob. Zeus up next, please. >> Yeah, and I think the other thing when you look at this chart to remember too is, you know, through the pandemic and the work from home period a lot of companies did put their office modernization projects on hold and you heard that echoed, you know, from really all the network manufacturers anyways. They always had projects underway to upgrade networks. They put 'em on hold. Now that people are starting to come back to the office, they're looking at that now. So we might see some change there, but Bob's right. The size of those market are quite a bit different. I think the other big trend here is the hardware companies, at least in the areas that I look at networking are understanding now that it's a combination of hardware and software and silicon that works together that creates that optimum type of performance and experience, right? So some things are best done in silicon. Some like data forwarding and things like that. Historically when you look at the way network devices were built, you did everything in hardware. You configured in hardware, they did all the data for you, and did all the management. And that's been decoupled now. So more and more of the control element has been placed in software. A lot of the high-performance things, encryption, and as I mentioned, data forwarding, packet analysis, stuff like that is still done in hardware, but not everything is done in hardware. And so it's a combination of the two. I think, for the people that work with the equipment as well, there's been more shift to understanding how to work with software. And this is a mistake I think the industry made for a while is we had everybody convinced they had to become a programmer. It's really more a software power user. Can you pull things out of software? Can you through API calls and things like that. But I think the big frame here is, David, it's a combination of hardware, software working together that really make a difference. And you know how much you invest in hardware versus software kind of depends on the performance requirements you have. And I'll talk about that later but that's really the big shift that's happened here. It's the vendors that figured out how to optimize performance by leveraging the best of all of those. >> Excellent. You guys both brought up some really good themes that we can tap into Dave Nicholson, please. >> Yeah, so just kind of picking up where Bob started off. Not only are we seeing the rise of a variety of CPU designs, but I think increasingly the connectivity that's involved from a hardware perspective, from a kind of a server or service design perspective has become increasingly important. I think we'll get a chance to look at this in more depth a little bit later but when you look at what happens on the motherboard, you know we're not in so much a CPU-centric world anymore. Various application environments have various demands and you can meet them by using a variety of components. And it's extremely significant when you start looking down at the component level. It's really important that you optimize around those components. So I guess my summary would be, I think we are moving out of the CPU-centric hardware model into more of a connectivity-centric model. We can talk more about that later. >> Yeah, great. And thank you, David, and Keith Townsend I really interested in your perspectives on this. I mean, for years you worked in a data center surrounded by hardware. Now that we have the software defined data center, please chime in here. >> Well, you know, I'm going to dig deeper into that software-defined data center nature of what's happening with hardware. Hardware is meeting software infrastructure as code is a thing. What does that code look like? We're still trying to figure out but servicing up these capabilities that the previous analysts have brought up, how do I ensure that I can get the level of services needed for the applications that I need? Whether they're legacy, traditional data center, workloads, AI ML, workloads, workloads at the edge. How do I codify that and consume that as a service? And hardware vendors are figuring this out. HPE, the big push into GreenLake as a service. Dale now with Apex taking what we need, these bare bone components, moving it forward with DDR five, six CXL, et cetera, and surfacing that as cold or as services. This is a very tough problem. As we transition from consuming a hardware-based configuration to this infrastructure as cold paradigm shift. >> Yeah, programmable infrastructure, really attacking that sort of labor discussion that we were having earlier, okay. Last but not least Marc Staimer, please. >> Thanks, Dave. My peers raised really good points. I agree with most of them, but I'm going to disagree with the title of this session, which is, does hardware matter? It absolutely matters. You can't run software on the air. You can't run it in an ephemeral cloud, although there's the technical cloud and that's a different issue. The cloud is kind of changed everything. And from a market perspective in the 40 plus years I've been in this business, I've seen this perception that hardware has to go down in price every year. And part of that was driven by Moore's law. And we're coming to, let's say a lag or an end, depending on who you talk to Moore's law. So we're not doubling our transistors every 18 to 24 months in a chip and as a result of that, there's been a higher emphasis on software. From a market perception, there's no penalty. They don't put the same pressure on software from the market to reduce the cost every year that they do on hardware, which kind of bass ackwards when you think about it. Hardware costs are fixed. Software costs tend to be very low. It's kind of a weird thing that we do in the market. And what's changing is we're now starting to treat hardware like software from an OPEX versus CapEx perspective. So yes, hardware matters. And we'll talk about that more in length. >> You know, I want to follow up on that. And I wonder if you guys have a thought on this, Bob O'Donnell, you and I have talked about this a little bit. Marc, you just pointed out that Moore's laws could have waning. Pat Gelsinger recently at their investor meeting said that he promised that Moore's law is alive and well. And the point I made in breaking analysis was okay, great. You know, Pat said, doubling transistors every 18 to 24 months, let's say that Intel can do that. Even though we know it's waning somewhat. Look at the M1 Ultra from Apple (chuckles). In about 15 months increased transistor density on their package by 6X. So to your earlier point, Bob, we have this sort of these alternative processors that are really changing things. And to Dave Nicholson's point, there's a whole lot of supporting components as well. Do you have a comment on that, Bob? >> Yeah, I mean, it's a great point, Dave. And one thing to bear in mind as well, not only are we seeing a diversity of these different chip architectures and different types of components as a number of us have raised the other big point and I think it was Keith that mentioned it. CXL and interconnect on the chip itself is dramatically changing it. And a lot of the more interesting advances that are going to continue to drive Moore's law forward in terms of the way we think about performance, if perhaps not number of transistors per se, is the interconnects that become available. You're seeing the development of chiplets or tiles, people use different names, but the idea is you can have different components being put together eventually in sort of a Lego block style. And what that's also going to allow, not only is that going to give interesting performance possibilities 'cause of the faster interconnect. So you can share, have shared memory between things which for big workloads like AI, huge data sets can make a huge difference in terms of how you talk to memory over a network connection, for example, but not only that you're going to see more diversity in the types of solutions that can be built. So we're going to see even more choices in hardware from a silicon perspective because you'll be able to piece together different elements. And oh, by the way, the other benefit of that is we've reached a point in chip architectures where not everything benefits from being smaller. We've been so focused and so obsessed when it comes to Moore's law, to the size of each individual transistor and yes, for certain architecture types, CPUs and GPUs in particular, that's absolutely true, but we've already hit the point where things like RF for 5g and wifi and other wireless technologies and a whole bunch of other things actually don't get any better with a smaller transistor size. They actually get worse. So the beauty of these chiplet architectures is you could actually combine different chip manufacturing sizes. You know you hear about four nanometer and five nanometer along with 14 nanometer on a single chip, each one optimized for its specific application yet together, they can give you the best of all worlds. And so we're just at the very beginning of that era, which I think is going to drive a ton of innovation. Again, gets back to my comment about different types of devices located geographically different places at the edge, in the data center, you know, in a private cloud versus a public cloud. All of those things are going to be impacted and there'll be a lot more options because of this silicon diversity and this interconnect diversity that we're just starting to see. >> Yeah, David. David Nicholson's got a graphic on that. They're going to show later. Before we do that, I want to introduce some data. I actually want to ask Keith to comment on this before we, you know, go on. This next slide is some data from ETR that shows the percent of customers that cited difficulty procuring hardware. And you can see the red is they had significant issues and it's most pronounced in laptops and networking hardware on the far right-hand side, but virtually all categories, firewalls, peripheral servers, storage are having moderately difficult procurement issues. That's the sort of pinkish or significant challenges. So Keith, I mean, what are you seeing with your customers in the hardware supply chains and bottlenecks? And you know we're seeing it with automobiles and appliances but so it goes beyond IT. The semiconductor, you know, challenges. What's been the impact on the buyer community and society and do you have any sense as to when it will subside? >> You know, I was just asked this question yesterday and I'm feeling the pain. People question, kind of a side project within the CTO advisor, we built a hybrid infrastructure, traditional IT data center that we're walking with the traditional customer and modernizing that data center. So it was, you know, kind of a snapshot of time in 2016, 2017, 10 gigabit, ARISTA switches, some older Dell's 730 XD switches, you know, speeds and feeds. And we said we would modern that with the latest Intel stack and connected to the public cloud and then the pandemic hit and we are experiencing a lot of the same challenges. I thought we'd easily migrate from 10 gig networking to 25 gig networking path that customers are going on. The 10 gig network switches that I bought used are now double the price because you can't get legacy 10 gig network switches because all of the manufacturers are focusing on the more profitable 25 gig for capacity, even the 25 gig switches. And we're focused on networking right now. It's hard to procure. We're talking about nine to 12 months or more lead time. So we're seeing customers adjust by adopting cloud. But if you remember early on in the pandemic, Microsoft Azure kind of gated customers that didn't have a capacity agreement. So customers are keeping an eye on that. There's a desire to abstract away from the underlying vendor to be able to control or provision your IT services in a way that we do with VMware VP or some other virtualization technology where it doesn't matter who can get me the hardware, they can just get me the hardware because it's critically impacting projects and timelines. >> So that's a great setup Zeus for you with Keith mentioned the earlier the software-defined data center with software-defined networking and cloud. Do you see a day where networking hardware is monetized and it's all about the software, or are we there already? >> No, we're not there already. And I don't see that really happening any time in the near future. I do think it's changed though. And just to be clear, I mean, when you look at that data, this is saying customers have had problems procuring the equipment, right? And there's not a network vendor out there. I've talked to Norman Rice at Extreme, and I've talked to the folks at Cisco and ARISTA about this. They all said they could have had blowout quarters had they had the inventory to ship. So it's not like customers aren't buying this anymore. Right? I do think though, when it comes to networking network has certainly changed some because there's a lot more controls as I mentioned before that you can do in software. And I think the customers need to start thinking about the types of hardware they buy and you know, where they're going to use it and, you know, what its purpose is. Because I've talked to customers that have tried to run software and commodity hardware and where the performance requirements are very high and it's bogged down, right? It just doesn't have the horsepower to run it. And, you know, even when you do that, you have to start thinking of the components you use. The NICs you buy. And I've talked to customers that have simply just gone through the process replacing a NIC card and a commodity box and had some performance problems and, you know, things like that. So if agility is more important than performance, then by all means try running software on commodity hardware. I think that works in some cases. If performance though is more important, that's when you need that kind of turnkey hardware system. And I've actually seen more and more customers reverting back to that model. In fact, when you talk to even some startups I think today about when they come to market, they're delivering things more on appliances because that's what customers want. And so there's this kind of app pivot this pendulum of agility and performance. And if performance absolutely matters, that's when you do need to buy these kind of turnkey, prebuilt hardware systems. If agility matters more, that's when you can go more to software, but the underlying hardware still does matter. So I think, you know, will we ever have a day where you can just run it on whatever hardware? Maybe but I'll long be retired by that point. So I don't care. >> Well, you bring up a good point Zeus. And I remember the early days of cloud, the narrative was, oh, the cloud vendors. They don't use EMC storage, they just run on commodity storage. And then of course, low and behold, you know, they've trot out James Hamilton to talk about all the custom hardware that they were building. And you saw Google and Microsoft follow suit. >> Well, (indistinct) been falling for this forever. Right? And I mean, all the way back to the turn of the century, we were calling for the commodity of hardware. And it's never really happened because you can still drive. As long as you can drive innovation into it, customers will always lean towards the innovation cycles 'cause they get more features faster and things. And so the vendors have done a good job of keeping that cycle up but it'll be a long time before. >> Yeah, and that's why you see companies like Pure Storage. A storage company has 69% gross margins. All right. I want to go jump ahead. We're going to bring up the slide four. I want to go back to something that Bob O'Donnell was talking about, the sort of supporting act. The diversity of silicon and we've marched to the cadence of Moore's law for decades. You know, we asked, you know, is Moore's law dead? We say it's moderating. Dave Nicholson. You want to talk about those supporting components. And you shared with us a slide that shift. You call it a shift from a processor-centric world to a connect-centric world. What do you mean by that? And let's bring up slide four and you can talk to that. >> Yeah, yeah. So first, I want to echo this sentiment that the question does hardware matter is sort of the answer is of course it matters. Maybe the real question should be, should you care about it? And the answer to that is it depends who you are. If you're an end user using an application on your mobile device, maybe you don't care how the architecture is put together. You just care that the service is delivered but as you back away from that and you get closer and closer to the source, someone needs to care about the hardware and it should matter. Why? Because essentially what hardware is doing is it's consuming electricity and dollars and the more efficiently you can configure hardware, the more bang you're going to get for your buck. So it's not only a quantitative question in terms of how much can you deliver? But it also ends up being a qualitative change as capabilities allow for things we couldn't do before, because we just didn't have the aggregate horsepower to do it. So this chart actually comes out of some performance tests that were done. So it happens to be Dell servers with Broadcom components. And the point here was to peel back, you know, peel off the top of the server and look at what's in that server, starting with, you know, the PCI interconnect. So PCIE gen three, gen four, moving forward. What are the effects on from an interconnect versus on performance application performance, translating into new orders per minute, processed per dollar, et cetera, et cetera? If you look at the advances in CPU architecture mapped against the advances in interconnect and storage subsystem performance, you can see that CPU architecture is sort of lagging behind in a way. And Bob mentioned this idea of tiling and all of the different ways to get around that. When we do performance testing, we can actually peg CPUs, just running the performance tests without any actual database environments working. So right now we're at this sort of imbalance point where you have to make sure you design things properly to get the most bang per kilowatt hour of power per dollar input. So the key thing here what this is highlighting is just as a very specific example, you take a card that's designed as a gen three PCIE device, and you plug it into a gen four slot. Now the card is the bottleneck. You plug a gen four card into a gen four slot. Now the gen four slot is the bottleneck. So we're constantly chasing these bottlenecks. Someone has to be focused on that from an architectural perspective, it's critically important. So there's no question that it matters. But of course, various people in this food chain won't care where it comes from. I guess a good analogy might be, where does our food come from? If I get a steak, it's a pink thing wrapped in plastic, right? Well, there are a lot of inputs that a lot of people have to care about to get that to me. Do I care about all of those things? No. Are they important? They're critically important. >> So, okay. So all I want to get to the, okay. So what does this all mean to customers? And so what I'm hearing from you is to balance a system it's becoming, you know, more complicated. And I kind of been waiting for this day for a long time, because as we all know the bottleneck was always the spinning disc, the last mechanical. So people who wrote software knew that when they were doing it right, the disc had to go and do stuff. And so they were doing other things in the software. And now with all these new interconnects and flash and things like you could do atomic rights. And so that opens up new software possibilities and combine that with alternative processes. But what's the so what on this to the customer and the application impact? Can anybody address that? >> Yeah, let me address that for a moment. I want to leverage some of the things that Bob said, Keith said, Zeus said, and David said, yeah. So I'm a bit of a contrarian in some of this. For example, on the chip side. As the chips get smaller, 14 nanometer, 10 nanometer, five nanometer, soon three nanometer, we talk about more cores, but the biggest problem on the chip is the interconnect from the chip 'cause the wires get smaller. People don't realize in 2004 the latency on those wires in the chips was 80 picoseconds. Today it's 1300 picoseconds. That's on the chip. This is why they're not getting faster. So we maybe getting a little bit slowing down in Moore's law. But even as we kind of conquer that you still have the interconnect problem and the interconnect problem goes beyond the chip. It goes within the system, composable architectures. It goes to the point where Keith made, ultimately you need a hybrid because what we're seeing, what I'm seeing and I'm talking to customers, the biggest issue they have is moving data. Whether it be in a chip, in a system, in a data center, between data centers, moving data is now the biggest gating item in performance. So if you want to move it from, let's say your transactional database to your machine learning, it's the bottleneck, it's moving the data. And so when you look at it from a distributed environment, now you've got to move the compute to the data. The only way to get around these bottlenecks today is to spend less time in trying to move the data and more time in taking the compute, the software, running on hardware closer to the data. Go ahead. >> So is this what you mean when Nicholson was talking about a shift from a processor centric world to a connectivity centric world? You're talking about moving the bits across all the different components, not having the processor you're saying is essentially becoming the bottleneck or the memory, I guess. >> Well, that's one of them and there's a lot of different bottlenecks, but it's the data movement itself. It's moving away from, wait, why do we need to move the data? Can we move the compute, the processing closer to the data? Because if we keep them separate and this has been a trend now where people are moving processing away from it. It's like the edge. I think it was Zeus or David. You were talking about the edge earlier. As you look at the edge, who defines the edge, right? Is the edge a closet or is it a sensor? If it's a sensor, how do you do AI at the edge? When you don't have enough power, you don't have enough computable. People were inventing chips to do that. To do all that at the edge, to do AI within the sensor, instead of moving the data to a data center or a cloud to do the processing. Because the lag in latency is always limited by speed of light. How fast can you move the electrons? And all this interconnecting, all the processing, and all the improvement we're seeing in the PCIE bus from three, to four, to five, to CXL, to a higher bandwidth on the network. And that's all great but none of that deals with the speed of light latency. And that's an-- Go ahead. >> You know Marc, no, I just want to just because what you're referring to could be looked at at a macro level, which I think is what you're describing. You can also look at it at a more micro level from a systems design perspective, right? I'm going to be the resident knuckle dragging hardware guy on the panel today. But it's exactly right. You moving compute closer to data includes concepts like peripheral cards that have built in intelligence, right? So again, in some of this testing that I'm referring to, we saw dramatic improvements when you basically took the horsepower instead of using the CPU horsepower for the like IO. Now you have essentially offload engines in the form of storage controllers, rate controllers, of course, for ethernet NICs, smart NICs. And so when you can have these sort of offload engines and we've gone through these waves over time. People think, well, wait a minute, raid controller and NVMe? You know, flash storage devices. Does that make sense? It turns out it does. Why? Because you're actually at a micro level doing exactly what you're referring to. You're bringing compute closer to the data. Now, closer to the data meaning closer to the data storage subsystem. It doesn't solve the macro issue that you're referring to but it is important. Again, going back to this idea of system design optimization, always chasing the bottleneck, plugging the holes. Someone needs to do that in this value chain in order to get the best value for every kilowatt hour of power and every dollar. >> Yeah. >> Well this whole drive performance has created some really interesting architectural designs, right? Like Nickelson, the rise of the DPU right? Brings more processing power into systems that already had a lot of processing power. There's also been some really interesting, you know, kind of innovation in the area of systems architecture too. If you look at the way Nvidia goes to market, their drive kit is a prebuilt piece of hardware, you know, optimized for self-driving cars, right? They partnered with Pure Storage and ARISTA to build that AI-ready infrastructure. I remember when I talked to Charlie Giancarlo, the CEO of Pure about when the three companies rolled that out. He said, "Look, if you're going to do AI, "you need good store. "You need fast storage, fast processor and fast network." And so for customers to be able to put that together themselves was very, very difficult. There's a lot of software that needs tuning as well. So the three companies partner together to create a fully integrated turnkey hardware system with a bunch of optimized software that runs on it. And so in that case, in some ways the hardware was leading the software innovation. And so, the variety of different architectures we have today around hardware has really exploded. And I think it, part of the what Bob brought up at the beginning about the different chip design. >> Yeah, Bob talked about that earlier. Bob, I mean, most AI today is modeling, you know, and a lot of that's done in the cloud and it looks from my standpoint anyway that the future is going to be a lot of AI inferencing at the edge. And that's a radically different architecture, Bob, isn't it? >> It is, it's a completely different architecture. And just to follow up on a couple points, excellent conversation guys. Dave talked about system architecture and really this that's what this boils down to, right? But it's looking at architecture at every level. I was talking about the individual different components the new interconnect methods. There's this new thing called UCIE universal connection. I forget what it stands answer for, but it's a mechanism for doing chiplet architectures, but then again, you have to take it up to the system level, 'cause it's all fine and good. If you have this SOC that's tuned and optimized, but it has to talk to the rest of the system. And that's where you see other issues. And you've seen things like CXL and other interconnect standards, you know, and nobody likes to talk about interconnect 'cause it's really wonky and really technical and not that sexy, but at the end of the day it's incredibly important exactly. To the other points that were being raised like mark raised, for example, about getting that compute closer to where the data is and that's where again, a diversity of chip architectures help and exactly to your last comment there Dave, putting that ability in an edge device is really at the cutting edge of what we're seeing on a semiconductor design and the ability to, for example, maybe it's an FPGA, maybe it's a dedicated AI chip. It's another kind of chip architecture that's being created to do that inferencing on the edge. Because again, it's that the cost and the challenges of moving lots of data, whether it be from say a smartphone to a cloud-based application or whether it be from a private network to a cloud or any other kinds of permutations we can think of really matters. And the other thing is we're tackling bigger problems. So architecturally, not even just architecturally within a system, but when we think about DPUs and the sort of the east west data center movement conversation that we hear Nvidia and others talk about, it's about combining multiple sets of these systems to function together more efficiently again with even bigger sets of data. So really is about tackling where the processing is needed, having the interconnect and the ability to get where the data you need to the right place at the right time. And because those needs are diversifying, we're just going to continue to see an explosion of different choices and options, which is going to make hardware even more essential I would argue than it is today. And so I think what we're going to see not only does hardware matter, it's going to matter even more in the future than it does now. >> Great, yeah. Great discussion, guys. I want to bring Keith back into the conversation here. Keith, if your main expertise in tech is provisioning LUNs, you probably you want to look for another job. So maybe clearly hardware matters, but with software defined everything, do people with hardware expertise matter outside of for instance, component manufacturers or cloud companies? I mean, VMware certainly changed the dynamic in servers. Dell just spun off its most profitable asset and VMware. So it obviously thinks hardware can stand alone. How does an enterprise architect view the shift to software defined hyperscale cloud and how do you see the shifting demand for skills in enterprise IT? >> So I love the question and I'll take a different view of it. If you're a data analyst and your primary value add is that you do ETL transformation, talk to a CDO, a chief data officer over midsize bank a little bit ago. He said 80% of his data scientists' time is done on ETL. Super not value ad. He wants his data scientists to do data science work. Chances are if your only value is that you do LUN provisioning, then you probably don't have a job now. The technologies have gotten much more intelligent. As infrastructure pros, we want to give infrastructure pros the opportunities to shine and I think the software defined nature and the automation that we're seeing vendors undertake, whether it's Dell, HP, Lenovo take your pick that Pure Storage, NetApp that are doing the automation and the ML needed so that these practitioners don't spend 80% of their time doing LUN provisioning and focusing on their true expertise, which is ensuring that data is stored. Data is retrievable, data's protected, et cetera. I think the shift is to focus on that part of the job that you're ensuring no matter where the data's at, because as my data is spread across the enterprise hybrid different types, you know, Dave, you talk about the super cloud a lot. If my data is in the super cloud, protecting that data and securing that data becomes much more complicated when than when it was me just procuring or provisioning LUNs. So when you say, where should the shift be, or look be, you know, focusing on the real value, which is making sure that customers can access data, can recover data, can get data at performance levels that they need within the price point. They need to get at those datasets and where they need it. We talked a lot about where they need out. One last point about this interconnecting. I have this vision and I think we all do of composable infrastructure. This idea that scaled out does not solve every problem. The cloud can give me infinite scale out. Sometimes I just need a single OS with 64 terabytes of RAM and 204 GPUs or GPU instances that single OS does not exist today. And the opportunity is to create composable infrastructure so that we solve a lot of these problems that just simply don't scale out. >> You know, wow. So many interesting points there. I had just interviewed Zhamak Dehghani, who's the founder of Data Mesh last week. And she made a really interesting point. She said, "Think about, we have separate stacks. "We have an application stack and we have "a data pipeline stack and the transaction systems, "the transaction database, we extract data from that," to your point, "We ETL it in, you know, it takes forever. "And then we have this separate sort of data stack." If we're going to inject more intelligence and data and AI into applications, those two stacks, her contention is they have to come together. And when you think about, you know, super cloud bringing compute to data, that was what Haduck was supposed to be. It ended up all sort of going into a central location, but it's almost a rhetorical question. I mean, it seems that that necessitates new thinking around hardware architectures as it kind of everything's the edge. And the other point is to your point, Keith, it's really hard to secure that. So when you can think about offloads, right, you've heard the stats, you know, Nvidia talks about it. Broadcom talks about it that, you know, that 30%, 25 to 30% of the CPU cycles are wasted on doing things like storage offloads, or networking or security. It seems like maybe Zeus you have a comment on this. It seems like new architectures need to come other to support, you know, all of that stuff that Keith and I just dispute. >> Yeah, and by the way, I do want to Keith, the question you just asked. Keith, it's the point I made at the beginning too about engineers do need to be more software-centric, right? They do need to have better software skills. In fact, I remember talking to Cisco about this last year when they surveyed their engineer base, only about a third of 'em had ever made an API call, which you know that that kind of shows this big skillset change, you know, that has to come. But on the point of architectures, I think the big change here is edge because it brings in distributed compute models. Historically, when you think about compute, even with multi-cloud, we never really had multi-cloud. We'd use multiple centralized clouds, but compute was always centralized, right? It was in a branch office, in a data center, in a cloud. With edge what we creates is the rise of distributed computing where we'll have an application that actually accesses different resources and at different edge locations. And I think Marc, you were talking about this, like the edge could be in your IoT device. It could be your campus edge. It could be cellular edge, it could be your car, right? And so we need to start thinkin' about how our applications interact with all those different parts of that edge ecosystem, you know, to create a single experience. The consumer apps, a lot of consumer apps largely works that way. If you think of like app like Uber, right? It pulls in information from all kinds of different edge application, edge services. And, you know, it creates pretty cool experience. We're just starting to get to that point in the business world now. There's a lot of security implications and things like that, but I do think it drives more architectural decisions to be made about how I deploy what data where and where I do my processing, where I do my AI and things like that. It actually makes the world more complicated. In some ways we can do so much more with it, but I think it does drive us more towards turnkey systems, at least initially in order to, you know, ensure performance and security. >> Right. Marc, I wanted to go to you. You had indicated to me that you wanted to chat about this a little bit. You've written quite a bit about the integration of hardware and software. You know, we've watched Oracle's move from, you know, buying Sun and then basically using that in a highly differentiated approach. Engineered systems. What's your take on all that? I know you also have some thoughts on the shift from CapEx to OPEX chime in on that. >> Sure. When you look at it, there are advantages to having one vendor who has the software and hardware. They can synergistically make them work together that you can't do in a commodity basis. If you own the software and somebody else has the hardware, I'll give you an example would be Oracle. As you talked about with their exit data platform, they literally are leveraging microcode in the Intel chips. And now in AMD chips and all the way down to Optane, they make basically AMD database servers work with Optane memory PMM in their storage systems, not MVME, SSD PMM. I'm talking about the cards itself. So there are advantages you can take advantage of if you own the stack, as you were putting out earlier, Dave, of both the software and the hardware. Okay, that's great. But on the other side of that, that tends to give you better performance, but it tends to cost a little more. On the commodity side it costs less but you get less performance. What Zeus had said earlier, it depends where you're running your application. How much performance do you need? What kind of performance do you need? One of the things about moving to the edge and I'll get to the OPEX CapEx in a second. One of the issues about moving to the edge is what kind of processing do you need? If you're running in a CCTV camera on top of a traffic light, how much power do you have? How much cooling do you have that you can run this? And more importantly, do you have to take the data you're getting and move it somewhere else and get processed and the information is sent back? I mean, there are companies out there like Brain Chip that have developed AI chips that can run on the sensor without a CPU. Without any additional memory. So, I mean, there's innovation going on to deal with this question of data movement. There's companies out there like Tachyon that are combining GPUs, CPUs, and DPUs in a single chip. Think of it as super composable architecture. They're looking at being able to do more in less. On the OPEX and CapEx issue. >> Hold that thought, hold that thought on the OPEX CapEx, 'cause we're running out of time and maybe you can wrap on that. I just wanted to pick up on something you said about the integrated hardware software. I mean, other than the fact that, you know, Michael Dell unlocked whatever $40 billion for himself and Silverlake, I was always a fan of a spin in with VMware basically become the Oracle of hardware. Now I know it would've been a nightmare for the ecosystem and culturally, they probably would've had a VMware brain drain, but what does anybody have any thoughts on that as a sort of a thought exercise? I was always a fan of that on paper. >> I got to eat a little crow. I did not like the Dale VMware acquisition for the industry in general. And I think it hurt the industry in general, HPE, Cisco walked away a little bit from that VMware relationship. But when I talked to customers, they loved it. You know, I got to be honest. They absolutely loved the integration. The VxRail, VxRack solution exploded. Nutanix became kind of a afterthought when it came to competing. So that spin in, when we talk about the ability to innovate and the ability to create solutions that you just simply can't create because you don't have the full stack. Dell was well positioned to do that with a potential span in of VMware. >> Yeah, we're going to be-- Go ahead please. >> Yeah, in fact, I think you're right, Keith, it was terrible for the industry. Great for Dell. And I remember talking to Chad Sakac when he was running, you know, VCE, which became Rack and Rail, their ability to stay in lockstep with what VMware was doing. What was the number one workload running on hyperconverged forever? It was VMware. So their ability to remain in lockstep with VMware gave them a huge competitive advantage. And Dell came out of nowhere in, you know, the hyper-converged market and just started taking share because of that relationship. So, you know, this sort I guess it's, you know, from a Dell perspective I thought it gave them a pretty big advantage that they didn't really exploit across their other properties, right? Networking and service and things like they could have given the dominance that VMware had. From an industry perspective though, I do think it's better to have them be coupled. So. >> I agree. I mean, they could. I think they could have dominated in super cloud and maybe they would become the next Oracle where everybody hates 'em, but they kick ass. But guys. We got to wrap up here. And so what I'm going to ask you is I'm going to go and reverse the order this time, you know, big takeaways from this conversation today, which guys by the way, I can't thank you enough phenomenal insights, but big takeaways, any final thoughts, any research that you're working on that you want highlight or you know, what you look for in the future? Try to keep it brief. We'll go in reverse order. Maybe Marc, you could start us off please. >> Sure, on the research front, I'm working on a total cost of ownership of an integrated database analytics machine learning versus separate services. On the other aspect that I would wanted to chat about real quickly, OPEX versus CapEx, the cloud changed the market perception of hardware in the sense that you can use hardware or buy hardware like you do software. As you use it, pay for what you use in arrears. The good thing about that is you're only paying for what you use, period. You're not for what you don't use. I mean, it's compute time, everything else. The bad side about that is you have no predictability in your bill. It's elastic, but every user I've talked to says every month it's different. And from a budgeting perspective, it's very hard to set up your budget year to year and it's causing a lot of nightmares. So it's just something to be aware of. From a CapEx perspective, you have no more CapEx if you're using that kind of base system but you lose a certain amount of control as well. So ultimately that's some of the issues. But my biggest point, my biggest takeaway from this is the biggest issue right now that everybody I talk to in some shape or form it comes down to data movement whether it be ETLs that you talked about Keith or other aspects moving it between hybrid locations, moving it within a system, moving it within a chip. All those are key issues. >> Great, thank you. Okay, CTO advisor, give us your final thoughts. >> All right. Really, really great commentary. Again, I'm going to point back to us taking the walk that our customers are taking, which is trying to do this conversion of all primary data center to a hybrid of which I have this hard earned philosophy that enterprise IT is additive. When we add a service, we rarely subtract a service. So the landscape and service area what we support has to grow. So our research focuses on taking that walk. We are taking a monolithic application, decomposing that to containers, and putting that in a public cloud, and connecting that back private data center and telling that story and walking that walk with our customers. This has been a super enlightening panel. >> Yeah, thank you. Real, real different world coming. David Nicholson, please. >> You know, it really hearkens back to the beginning of the conversation. You talked about momentum in the direction of cloud. I'm sort of spending my time under the hood, getting grease under my fingernails, focusing on where still the lions share of spend will be in coming years, which is OnPrem. And then of course, obviously data center infrastructure for cloud but really diving under the covers and helping folks understand the ramifications of movement between generations of CPU architecture. I know we all know Sapphire Rapids pushed into the future. When's the next Intel release coming? Who knows? We think, you know, in 2023. There have been a lot of people standing by from a practitioner's standpoint asking, well, what do I do between now and then? Does it make sense to upgrade bits and pieces of hardware or go from a last generation to a current generation when we know the next generation is coming? And so I've been very, very focused on looking at how these connectivity components like rate controllers and NICs. I know it's not as sexy as talking about cloud but just how these opponents completely change the game and actually can justify movement from say a 14th-generation architecture to a 15th-generation architecture today, even though gen 16 is coming, let's say 12 months from now. So that's where I am. Keep my phone number in the Rolodex. I literally reference Rolodex intentionally because like I said, I'm in there under the hood and it's not as sexy. But yeah, so that's what I'm focused on Dave. >> Well, you know, to paraphrase it, maybe derivative paraphrase of, you know, Larry Ellison's rant on what is cloud? It's operating systems and databases, et cetera. Rate controllers and NICs live inside of clouds. All right. You know, one of the reasons I love working with you guys is 'cause have such a wide observation space and Zeus Kerravala you, of all people, you know you have your fingers in a lot of pies. So give us your final thoughts. >> Yeah, I'm not a propeller heady as my chip counterparts here. (all laugh) So, you know, I look at the world a little differently and a lot of my research I'm doing now is the impact that distributed computing has on customer employee experiences, right? You talk to every business and how the experiences they deliver to their customers is really differentiating how they go to market. And so they're looking at these different ways of feeding up data and analytics and things like that in different places. And I think this is going to have a really profound impact on enterprise IT architecture. We're putting more data, more compute in more places all the way down to like little micro edges and retailers and things like that. And so we need the variety. Historically, if you think back to when I was in IT you know, pre-Y2K, we didn't have a lot of choice in things, right? We had a server that was rack mount or standup, right? And there wasn't a whole lot of, you know, differences in choice. But today we can deploy, you know, these really high-performance compute systems on little blades inside servers or inside, you know, autonomous vehicles and things. I think the world from here gets... You know, just the choice of what we have and the way hardware and software works together is really going to, I think, change the world the way we do things. We're already seeing that, like I said, in the consumer world, right? There's so many things you can do from, you know, smart home perspective, you know, natural language processing, stuff like that. And it's starting to hit businesses now. So just wait and watch the next five years. >> Yeah, totally. The computing power at the edge is just going to be mind blowing. >> It's unbelievable what you can do at the edge. >> Yeah, yeah. Hey Z, I just want to say that we know you're not a propeller head and I for one would like to thank you for having your master's thesis hanging on the wall behind you 'cause we know that you studied basket weaving. >> I was actually a physics math major, so. >> Good man. Another math major. All right, Bob O'Donnell, you're going to bring us home. I mean, we've seen the importance of semiconductors and silicon in our everyday lives, but your last thoughts please. >> Sure and just to clarify, by the way I was a great books major and this was actually for my final paper. And so I was like philosophy and all that kind of stuff and literature but I still somehow got into tech. Look, it's been a great conversation and I want to pick up a little bit on a comment Zeus made, which is this it's the combination of the hardware and the software and coming together and the manner with which that needs to happen, I think is critically important. And the other thing is because of the diversity of the chip architectures and all those different pieces and elements, it's going to be how software tools evolve to adapt to that new world. So I look at things like what Intel's trying to do with oneAPI. You know, what Nvidia has done with CUDA. What other platform companies are trying to create tools that allow them to leverage the hardware, but also embrace the variety of hardware that is there. And so as those software development environments and software development tools evolve to take advantage of these new capabilities, that's going to open up a lot of interesting opportunities that can leverage all these new chip architectures. That can leverage all these new interconnects. That can leverage all these new system architectures and figure out ways to make that all happen, I think is going to be critically important. And then finally, I'll mention the research I'm actually currently working on is on private 5g and how companies are thinking about deploying private 5g and the potential for edge applications for that. So I'm doing a survey of several hundred us companies as we speak and really looking forward to getting that done in the next couple of weeks. >> Yeah, look forward to that. Guys, again, thank you so much. Outstanding conversation. Anybody going to be at Dell tech world in a couple of weeks? Bob's going to be there. Dave Nicholson. Well drinks on me and guys I really can't thank you enough for the insights and your participation today. Really appreciate it. Okay, and thank you for watching this special power panel episode of theCube Insights powered by ETR. Remember we publish each week on Siliconangle.com and wikibon.com. All these episodes they're available as podcasts. DM me or any of these guys. I'm at DVellante. You can email me at David.Vellante@siliconangle.com. Check out etr.ai for all the data. This is Dave Vellante. We'll see you next time. (upbeat music)

(upbeat music) >> Once a staid and boring business dominated by IBM, Oracle, and at the time newcomer Microsoft, along with a handful of wannabes, the database business has exploded in the past decade and has become a staple of financial excellence, customer experience, analytic advantage, competitive strategy, growth initiatives, visualizations, not to mention compliance, security, privacy and dozens of other important use cases and initiatives. And on the vendor's side of the house, we've seen the rapid ascendancy of cloud databases. Most notably from Snowflake, whose massive raises leading up to its IPO in late 2020 sparked a spate of interest and VC investment in the separation of compute and storage and all that elastic resource stuff in the cloud. The company joined AWS, Azure and Google to popularize cloud databases, which have become a linchpin of competitive strategies for technology suppliers. And if I get you to put your data in my database and in my cloud, and I keep innovating, I'm going to build a moat and achieve a hugely attractive lifetime customer value in a really amazing marginal economics dynamic that is going to fund my future. And I'll be able to sell other adjacent services, not just compute and storage, but machine learning and inference and training and all kinds of stuff, dozens of lucrative cloud offerings. Meanwhile, the database leader, Oracle has invested massive amounts of money to maintain its lead. It's building on its position as the king of mission critical workloads and making typical Oracle like claims against the competition. Most were recently just yesterday with another announcement around MySQL HeatWave. An extension of MySQL that is compatible with on-premises MySQLs and is setting new standards in price performance. We're seeing a dramatic divergence in strategies across the database spectrum. On the far left, we see Amazon with more than a dozen database offerings each with its own API and primitives. AWS is taking a right tool for the right job approach, often building on open source platforms and creating services that it offers to customers to solve very specific problems for developers. And on the other side of the line, we see Oracle, which is taking the Swiss Army Knife approach, converging database functionality, enabling analytic and transactional workloads to run in the same data store, eliminating the need to ETL, at the same time adding capabilities into its platform like automation and machine learning. Welcome to this database Power Panel. My name is Dave Vellante, and I'm so excited to bring together some of the most respected industry analyst in the community. Today we're going to assess what's happening in the market. We're going to dig into the competitive landscape and explore the future of database and database platforms and decode what it means to customers. Let me take a moment to welcome our guest analyst today. Matt Kimball is a vice president and principal analysts at Moor Insights and Strategy, Matt. He knows products, he knows industry, he's got real world IT expertise, and he's got all the angles 25 plus years of experience in all kinds of great background. Matt, welcome. Thanks very much for coming on theCUBE. Holgar Mueller, friend of theCUBE, vice president and principal analyst at Constellation Research in depth knowledge on applications, application development, knows developers. He's worked at SAP and Oracle. And then Bob Evans is Chief Content Officer and co-founder of the Acceleration Economy, founder and principle of Cloud Wars. Covers all kinds of industry topics and great insights. He's got awesome videos, these three minute hits. If you haven't seen 'em, checking them out, knows cloud companies, his Cloud Wars minutes are fantastic. And then of course, Marc Staimer is the founder of Dragon Slayer Research. A frequent contributor and guest analyst at Wikibon. He's got a wide ranging knowledge across IT products, knows technology really well, can go deep. And then of course, Ron Westfall, Senior Analyst and Director Research Director at Futurum Research, great all around product trends knowledge. Can take, you know, technical dives and really understands competitive angles, knows Redshift, Snowflake, and many others. Gents, thanks so much for taking the time to join us in theCube today. It's great to have you on, good to see you. >> Good to be here, thanks for having us. >> Thanks, Dave. >> All right, let's start with an around the horn and briefly, if each of you would describe, you know, anything I missed in your areas of expertise and then you answer the following question, how would you describe the state of the database, state of platform market today? Matt Kimball, please start. >> Oh, I hate going first, but that it's okay. How would I describe the world today? I would just in one sentence, I would say, I'm glad I'm not in IT anymore, right? So, you know, it is a complex and dangerous world out there. And I don't envy IT folks I'd have to support, you know, these modernization and transformation efforts that are going on within the enterprise. It used to be, you mentioned it, Dave, you would argue about IBM versus Oracle versus this newcomer in the database space called Microsoft. And don't forget Sybase back in the day, but you know, now it's not just, which SQL vendor am I going to go with? It's all of these different, divergent data types that have to be taken, they have to be merged together, synthesized. And somehow I have to do that cleanly and use this to drive strategic decisions for my business. That is not easy. So, you know, you have to look at it from the perspective of the business user. It's great for them because as a DevOps person, or as an analyst, I have so much flexibility and I have this thing called the cloud now where I can go get services immediately. As an IT person or a DBA, I am calling up prevention hotlines 24 hours a day, because I don't know how I'm going to be able to support the business. And as an Oracle or as an Oracle or a Microsoft or some of the cloud providers and cloud databases out there, I'm licking my chops because, you know, my market is expanding and expanding every day. >> Great, thank you for that, Matt. Holgar, how do you see the world these days? You always have a good perspective on things, share with us. >> Well, I think it's the best time to be in IT, I'm not sure what Matt is talking about. (laughing) It's easier than ever, right? The direction is going to cloud. Kubernetes has won, Google has the best AI for now, right? So things are easier than ever before. You made commitments for five plus years on hardware, networking and so on premise, and I got gray hair about worrying it was the wrong decision. No, just kidding. But you kind of both sides, just to be controversial, make it interesting, right. So yeah, no, I think the interesting thing specifically with databases, right? We have this big suite versus best of breed, right? Obviously innovation, like you mentioned with Snowflake and others happening in the cloud, the cloud vendors server, where to save of their databases. And then we have one of the few survivors of the old guard as Evans likes to call them is Oracle who's doing well, both their traditional database. And now, which is really interesting, remarkable from that because Oracle it was always the power of one, have one database, add more to it, make it what I call the universal database. And now this new HeatWave offering is coming and MySQL open source side. So they're getting the second (indistinct) right? So it's interesting that older players, traditional players who still are in the market are diversifying their offerings. Something we don't see so much from the traditional tools from Oracle on the Microsoft side or the IBM side these days. >> Great, thank you Holgar. Bob Evans, you've covered this business for a while. You've worked at, you know, a number of different outlets and companies and you cover the competition, how do you see things? >> Dave, you know, the other angle to look at this from is from the customer side, right? You got now CEOs who are any sort of business across all sorts of industries, and they understand that their future success is going to be dependent on their ability to become a digital company, to understand data, to use it the right way. So as you outline Dave, I think in your intro there, it is a fantastic time to be in the database business. And I think we've got a lot of new buyers and influencers coming in. They don't know all this history about IBM and Microsoft and Oracle and you know, whoever else. So I think they're going to take a long, hard look, Dave, at some of these results and who is able to help these companies not serve up the best technology, but who's going to be able to help their business move into the digital future. So it's a fascinating time now from every perspective. >> Great points, Bob. I mean, digital transformation has gone from buzzword to imperative. Mr. Staimer, how do you see things? >> I see things a little bit differently than my peers here in that I see the database market being segmented. There's all the different kinds of databases that people are looking at for different kinds of data, and then there is databases in the cloud. And so database as cloud service, I view very differently than databases because the traditional way of implementing a database is changing and it's changing rapidly. So one of the premises that you stated earlier on was that you viewed Oracle as a database company. I don't view Oracle as a database company anymore. I view Oracle as a cloud company that happens to have a significant expertise and specialty in databases, and they still sell database software in the traditional way, but ultimately they're a cloud company. So database cloud services from my point of view is a very distinct market from databases. >> Okay, well, you gave us some good meat on the bone to talk about that. Last but not least-- >> Dave did Marc, just say Oracle's a cloud company? >> Yeah. (laughing) Take away the database, it would be interesting to have that discussion, but let's let Ron jump in here. Ron, give us your take. >> That's a great segue. I think it's truly the era of the cloud database, that's something that's rising. And the key trends that come with it include for example, elastic scaling. That is the ability to scale on demand, to right size workloads according to customer requirements. And also I think it's going to increase the prioritization for high availability. That is the player who can provide the highest availability is going to have, I think, a great deal of success in this emerging market. And also I anticipate that there will be more consolidation across platforms in order to enable cost savings for customers, and that's something that's always going to be important. And I think we'll see more of that over the horizon. And then finally security, security will be more important than ever. We've seen a spike (indistinct), we certainly have seen geopolitical originated cybersecurity concerns. And as a result, I see database security becoming all the more important. >> Great, thank you. Okay, let me share some data with you guys. I'm going to throw this at you and see what you think. We have this awesome data partner called Enterprise Technology Research, ETR. They do these quarterly surveys and each period with dozens of industry segments, they track clients spending, customer spending. And this is the database, data warehouse sector okay so it's taxonomy, so it's not perfect, but it's a big kind of chunk. They essentially ask customers within a category and buy a specific vendor, you're spending more or less on the platform? And then they subtract the lesses from the mores and they derive a metric called net score. It's like NPS, it's a measure of spending velocity. It's more complicated and granular than that, but that's the basis and that's the vertical axis. The horizontal axis is what they call market share, it's not like IDC market share, it's just pervasiveness in the data set. And so there are a couple of things that stand out here and that we can use as reference point. The first is the momentum of Snowflake. They've been off the charts for many, many, for over two years now, anything above that dotted red line, that 40%, is considered by ETR to be highly elevated and Snowflake's even way above that. And I think it's probably not sustainable. We're going to see in the next April survey, next month from those guys, when it comes out. And then you see AWS and Microsoft, they're really pervasive on the horizontal axis and highly elevated, Google falls behind them. And then you got a number of well funded players. You got Cockroach Labs, Mongo, Redis, MariaDB, which of course is a fork on MySQL started almost as protest at Oracle when they acquired Sun and they got MySQL and you can see the number of others. Now Oracle who's the leading database player, despite what Marc Staimer says, we know, (laughs) and they're a cloud player (laughing) who happens to be a leading database player. They dominate in the mission critical space, we know that they're the king of that sector, but you can see here that they're kind of legacy, right? They've been around a long time, they get a big install base. So they don't have the spending momentum on the vertical axis. Now remember this is, just really this doesn't capture spending levels, so that understates Oracle but nonetheless. So it's not a complete picture like SAP for instance is not in here, no Hana. I think people are actually buying it, but it doesn't show up here, (laughs) but it does give an indication of momentum and presence. So Bob Evans, I'm going to start with you. You've commented on many of these companies, you know, what does this data tell you? >> Yeah, you know, Dave, I think all these compilations of things like that are interesting, and that folks at ETR do some good work, but I think as you said, it's a snapshot sort of a two-dimensional thing of a rapidly changing, three dimensional world. You know, the incidents at which some of these companies are mentioned versus the volume that happens. I think it's, you know, with Oracle and I'm not going to declare my religious affiliation, either as cloud company or database company, you know, they're all of those things and more, and I think some of our old language of how we classify companies is just not relevant anymore. But I want to ask too something in here, the autonomous database from Oracle, nobody else has done that. So either Oracle is crazy, they've tried out a technology that nobody other than them is interested in, or they're onto something that nobody else can match. So to me, Dave, within Oracle, trying to identify how they're doing there, I would watch autonomous database growth too, because right, it's either going to be a big plan and it breaks through, or it's going to be caught behind. And the Snowflake phenomenon as you mentioned, that is a rare, rare bird who comes up and can grow 100% at a billion dollar revenue level like that. So now they've had a chance to come in, scare the crap out of everybody, rock the market with something totally new, the data cloud. Will the bigger companies be able to catch up and offer a compelling alternative, or is Snowflake going to continue to be this outlier. It's a fascinating time. >> Really, interesting points there. Holgar, I want to ask you, I mean, I've talked to certainly I'm sure you guys have too, the founders of Snowflake that came out of Oracle and they actually, they don't apologize. They say, "Hey, we not going to do all that complicated stuff that Oracle does, we were trying to keep it real simple." But at the same time, you know, they don't do sophisticated workload management. They don't do complex joints. They're kind of relying on the ecosystems. So when you look at the data like this and the various momentums, and we talked about the diverging strategies, what does this say to you? >> Well, it is a great point. And I think Snowflake is an example how the cloud can turbo charge a well understood concept in this case, the data warehouse, right? You move that and you find steroids and you see like for some players who've been big in data warehouse, like Sentara Data, as an example, here in San Diego, what could have been for them right in that part. The interesting thing, the problem though is the cloud hides a lot of complexity too, which you can scale really well as you attract lots of customers to go there. And you don't have to build things like what Bob said, right? One of the fascinating things, right, nobody's answering Oracle on the autonomous database. I don't think is that they cannot, they just have different priorities or the database is not such a priority. I would dare to say that it's for IBM and Microsoft right now at the moment. And the cloud vendors, you just hide that right through scripts and through scale because you support thousands of customers and you can deal with a little more complexity, right? It's not against them. Whereas if you have to run it yourself, very different story, right? You want to have the autonomous parts, you want to have the powerful tools to do things. >> Thank you. And so Matt, I want to go to you, you've set up front, you know, it's just complicated if you're in IT, it's a complicated situation and you've been on the customer side. And if you're a buyer, it's obviously, it's like Holgar said, "Cloud's supposed to make this stuff easier, but the simpler it gets the more complicated gets." So where do you place your bets? Or I guess more importantly, how do you decide where to place your bets? >> Yeah, it's a good question. And to what Bob and Holgar said, you know, the around autonomous database, I think, you know, part of, as I, you know, play kind of armchair psychologist, if you will, corporate psychologists, I look at what Oracle is doing and, you know, databases where they've made their mark and it's kind of, that's their strong position, right? So it makes sense if you're making an entry into this cloud and you really want to kind of build momentum, you go with what you're good at, right? So that's kind of the strength of Oracle. Let's put a lot of focus on that. They do a lot more than database, don't get me wrong, but you know, I'm going to short my strength and then kind of pivot from there. With regards to, you know, what IT looks at and what I would look at you know as an IT director or somebody who is, you know, trying to consume services from these different cloud providers. First and foremost, I go with what I know, right? Let's not forget IT is a conservative group. And when we look at, you know, all the different permutations of database types out there, SQL, NoSQL, all the different types of NoSQL, those are largely being deployed by business users that are looking for agility or businesses that are looking for agility. You know, the reason why MongoDB is so popular is because of DevOps, right? It's a great platform to develop on and that's where it kind of gained its traction. But as an IT person, I want to go with what I know, where my muscle memory is, and that's my first position. And so as I evaluate different cloud service providers and cloud databases, I look for, you know, what I know and what I've invested in and where my muscle memory is. Is there enough there and do I have enough belief that that company or that service is going to be able to take me to, you know, where I see my organization in five years from a data management perspective, from a business perspective, are they going to be there? And if they are, then I'm a little bit more willing to make that investment, but it is, you know, if I'm kind of going in this blind or if I'm cloud native, you know, that's where the Snowflakes of the world become very attractive to me. >> Thank you. So Marc, I asked Andy Jackson in theCube one time, you have all these, you know, data stores and different APIs and primitives and you know, very granular, what's the strategy there? And he said, "Hey, that allows us as the market changes, it allows us to be more flexible. If we start building abstractions layers, it's harder for us." I think also it was not a good time to market advantage, but let me ask you, I described earlier on that spectrum from AWS to Oracle. We just saw yesterday, Oracle announced, I think the third major enhancement in like 15 months to MySQL HeatWave, what do you make of that announcement? How do you think it impacts the competitive landscape, particularly as it relates to, you know, converging transaction and analytics, eliminating ELT, I know you have some thoughts on this. >> So let me back up for a second and defend my cloud statement about Oracle for a moment. (laughing) AWS did a great job in developing the cloud market in general and everything in the cloud market. I mean, I give them lots of kudos on that. And a lot of what they did is they took open source software and they rent it to people who use their cloud. So I give 'em lots of credit, they dominate the market. Oracle was late to the cloud market. In fact, they actually poo-pooed it initially, if you look at some of Larry Ellison's statements, they said, "Oh, it's never going to take off." And then they did 180 turn, and they said, "Oh, we're going to embrace the cloud." And they really have, but when you're late to a market, you've got to be compelling. And this ties into the announcement yesterday, but let's deal with this compelling. To be compelling from a user point of view, you got to be twice as fast, offer twice as much functionality, at half the cost. That's generally what compelling is that you're going to capture market share from the leaders who established the market. It's very difficult to capture market share in a new market for yourself. And you're right. I mean, Bob was correct on this and Holgar and Matt in which you look at Oracle, and they did a great job of leveraging their database to move into this market, give 'em lots of kudos for that too. But yesterday they announced, as you said, the third innovation release and the pace is just amazing of what they're doing on these releases on HeatWave that ties together initially MySQL with an integrated builtin analytics engine, so a data warehouse built in. And then they added automation with autopilot, and now they've added machine learning to it, and it's all in the same service. It's not something you can buy and put on your premise unless you buy their cloud customers stuff. But generally it's a cloud offering, so it's compellingly better as far as the integration. You don't buy multiple services, you buy one and it's lower cost than any of the other services, but more importantly, it's faster, which again, give 'em credit for, they have more integration of a product. They can tie things together in a way that nobody else does. There's no additional services, ETL services like Glue and AWS. So from that perspective, they're getting better performance, fewer services, lower cost. Hmm, they're aiming at the compelling side again. So from a customer point of view it's compelling. Matt, you wanted to say something there. >> Yeah, I want to kind of, on what you just said there Marc, and this is something I've found really interesting, you know. The traditional way that you look at software and, you know, purchasing software and IT is, you look at either best of breed solutions and you have to work on the backend to integrate them all and make them all work well. And generally, you know, the big hit against the, you know, we have one integrated offering is that, you lose capability or you lose depth of features, right. And to what you were saying, you know, that's the thing I found interesting about what Oracle is doing is they're building in depth as they kind of, you know, build that service. It's not like you're losing a lot of capabilities, because you're going to one integrated service versus having to use A versus B versus C, and I love that idea. >> You're right. Yeah, not only you're not losing, but you're gaining functionality that you can't get by integrating a lot of these. I mean, I can take Snowflake and integrate it in with machine learning, but I also have to integrate in with a transactional database. So I've got to have connectors between all of this, which means I'm adding time. And what it comes down to at the end of the day is expertise, effort, time, and cost. And so what I see the difference from the Oracle announcements is they're aiming at reducing all of that by increasing performance as well. Correct me if I'm wrong on that but that's what I saw at the announcement yesterday. >> You know, Marc, one thing though Marc, it's funny you say that because I started out saying, you know, I'm glad I'm not 19 anymore. And the reason is because of exactly what you said, it's almost like there's a pseudo level of witchcraft that's required to support the modern data environment right in the enterprise. And I need simpler faster, better. That's what I need, you know, I am no longer wearing pocket protectors. I have turned from, you know, break, fix kind of person, to you know, business consultant. And I need that point and click simplicity, but I can't sacrifice, you know, a depth of features of functionality on the backend as I play that consultancy role. >> So, Ron, I want to bring in Ron, you know, it's funny. So Matt, you mentioned Mongo, I often and say, if Oracle mentions you, you're on the map. We saw them yesterday Ron, (laughing) they hammered RedShifts auto ML, they took swipes at Snowflake, a little bit of BigQuery. What were your thoughts on that? Do you agree with what these guys are saying in terms of HeatWaves capabilities? >> Yes, Dave, I think that's an excellent question. And fundamentally I do agree. And the question is why, and I think it's important to know that all of the Oracle data is backed by the fact that they're using benchmarks. For example, all of the ML and all of the TPC benchmarks, including all the scripts, all the configs and all the detail are posted on GitHub. So anybody can look at these results and they're fully transparent and replicate themselves. If you don't agree with this data, then by all means challenge it. And we have not really seen that in all of the new updates in HeatWave over the last 15 months. And as a result, when it comes to these, you know, fundamentals in looking at the competitive landscape, which I think gives validity to outcomes such as Oracle being able to deliver 4.8 times better price performance than Redshift. As well as for example, 14.4 better price performance than Snowflake, and also 12.9 better price performance than BigQuery. And so that is, you know, looking at the quantitative side of things. But again, I think, you know, to Marc's point and to Matt's point, there are also qualitative aspects that clearly differentiate the Oracle proposition, from my perspective. For example now the MySQL HeatWave ML capabilities are native, they're built in, and they also support things such as completion criteria. And as a result, that enables them to show that hey, when you're using Redshift ML for example, you're having to also use their SageMaker tool and it's running on a meter. And so, you know, nobody really wants to be running on a meter when, you know, executing these incredibly complex tasks. And likewise, when it comes to Snowflake, they have to use a third party capability. They don't have the built in, it's not native. So the user, to the point that he's having to spend more time and it increases complexity to use auto ML capabilities across the Snowflake platform. And also, I think it also applies to other important features such as data sampling, for example, with the HeatWave ML, it's intelligent sampling that's being implemented. Whereas in contrast, we're seeing Redshift using random sampling. And again, Snowflake, you're having to use a third party library in order to achieve the same capabilities. So I think the differentiation is crystal clear. I think it definitely is refreshing. It's showing that this is where true value can be assigned. And if you don't agree with it, by all means challenge the data. >> Yeah, I want to come to the benchmarks in a minute. By the way, you know, the gentleman who's the Oracle's architect, he did a great job on the call yesterday explaining what you have to do. I thought that was quite impressive. But Bob, I know you follow the financials pretty closely and on the earnings call earlier this month, Ellison said that, "We're going to see HeatWave on AWS." And the skeptic in me said, oh, they must not be getting people to come to OCI. And then they, you remember this chart they showed yesterday that showed the growth of HeatWave on OCI. But of course there was no data on there, it was just sort of, you know, lines up and to the right. So what do you guys think of that? (Marc laughs) Does it signal Bob, desperation by Oracle that they can't get traction on OCI, or is it just really a smart tame expansion move? What do you think? >> Yeah, Dave, that's a great question. You know, along the way there, and you know, just inside of that was something that said Ellison said on earnings call that spoke to a different sort of philosophy or mindset, almost Marc, where he said, "We're going to make this multicloud," right? With a lot of their other cloud stuff, if you wanted to use any of Oracle's cloud software, you had to use Oracle's infrastructure, OCI, there was no other way out of it. But this one, but I thought it was a classic Ellison line. He said, "Well, we're making this available on AWS. We're making this available, you know, on Snowflake because we're going after those users. And once they see what can be done here." So he's looking at it, I guess you could say, it's a concession to customers because they want multi-cloud. The other way to look at it, it's a hunting expedition and it's one of those uniquely I think Oracle ways. He said up front, right, he doesn't say, "Well, there's a big market, there's a lot for everybody, we just want on our slice." Said, "No, we are going after Amazon, we're going after Redshift, we're going after Aurora. We're going after these users of Snowflake and so on." And I think it's really fairly refreshing these days to hear somebody say that, because now if I'm a buyer, I can look at that and say, you know, to Marc's point, "Do they measure up, do they crack that threshold ceiling? Or is this just going to be more pain than a few dollars savings is worth?" But you look at those numbers that Ron pointed out and that we all saw in that chart. I've never seen Dave, anything like that. In a substantive market, a new player coming in here, and being able to establish differences that are four, seven, eight, 10, 12 times better than competition. And as new buyers look at that, they're going to say, "What the hell are we doing paying, you know, five times more to get a poor result? What's going on here?" So I think this is going to rattle people and force a harder, closer look at what these alternatives are. >> I wonder if the guy, thank you. Let's just skip ahead of the benchmarks guys, bring up the next slide, let's skip ahead a little bit here, which talks to the benchmarks and the benchmarking if we can. You know, David Floyer, the sort of semiretired, you know, Wikibon analyst said, "Dave, this is going to force Amazon and others, Snowflake," he said, "To rethink actually how they architect databases." And this is kind of a compilation of some of the data that they shared. They went after Redshift mostly, (laughs) but also, you know, as I say, Snowflake, BigQuery. And, like I said, you can always tell which companies are doing well, 'cause Oracle will come after you, but they're on the radar here. (laughing) Holgar should we take this stuff seriously? I mean, or is it, you know, a grain salt? What are your thoughts here? >> I think you have to take it seriously. I mean, that's a great question, great point on that. Because like Ron said, "If there's a flaw in a benchmark, we know this database traditionally, right?" If anybody came up that, everybody will be, "Oh, you put the wrong benchmark, it wasn't audited right, let us do it again," and so on. We don't see this happening, right? So kudos to Oracle to be aggressive, differentiated, and seem to having impeccable benchmarks. But what we really see, I think in my view is that the classic and we can talk about this in 100 years, right? Is the suite versus best of breed, right? And the key question of the suite, because the suite's always slower, right? No matter at which level of the stack, you have the suite, then the best of breed that will come up with something new, use a cloud, put the data warehouse on steroids and so on. The important thing is that you have to assess as a buyer what is the speed of my suite vendor. And that's what you guys mentioned before as well, right? Marc said that and so on, "Like, this is a third release in one year of the HeatWave team, right?" So everybody in the database open source Marc, and there's so many MySQL spinoffs to certain point is put on shine on the speed of (indistinct) team, putting out fundamental changes. And the beauty of that is right, is so inherent to the Oracle value proposition. Larry's vision of building the IBM of the 21st century, right from the Silicon, from the chip all the way across the seven stacks to the click of the user. And that what makes the database what Rob was saying, "Tied to the OCI infrastructure," because designed for that, it runs uniquely better for that, that's why we see the cross connect to Microsoft. HeatWave so it's different, right? Because HeatWave runs on cheap hardware, right? Which is the breadth and butter 886 scale of any cloud provider, right? So Oracle probably needs it to scale OCI in a different category, not the expensive side, but also allow us to do what we said before, the multicloud capability, which ultimately CIOs really want, because data gravity is real, you want to operate where that is. If you have a fast, innovative offering, which gives you more functionality and the R and D speed is really impressive for the space, puts away bad results, then it's a good bet to look at. >> Yeah, so you're saying, that we versus best of breed. I just want to sort of play back then Marc a comment. That suite versus best of breed, there's always been that trade off. If I understand you Holgar you're saying that somehow Oracle has magically cut through that trade off and they're giving you the best of both. >> It's the developing velocity, right? The provision of important features, which matter to buyers of the suite vendor, eclipses the best of breed vendor, then the best of breed vendor is in the hell of a potential job. >> Yeah, go ahead Marc. >> Yeah and I want to add on what Holgar just said there. I mean the worst job in the data center is data movement, moving the data sucks. I don't care who you are, nobody likes it. You never get any kudos for doing it well, and you always get the ah craps, when things go wrong. So it's in- >> In the data center Marc all the time across data centers, across cloud. That's where the bleeding comes. >> It's right, you get beat up all the time. So nobody likes to move data, ever. So what you're looking at with what they announce with HeatWave and what I love about HeatWave is it doesn't matter when you started with it, you get all the additional features they announce it's part of the service, all the time. But they don't have to move any of the data. You want to analyze the data that's in your transactional, MySQL database, it's there. You want to do machine learning models, it's there, there's no data movement. The data movement is the key thing, and they just eliminate that, in so many ways. And the other thing I wanted to talk about is on the benchmarks. As great as those benchmarks are, they're really conservative 'cause they're underestimating the cost of that data movement. The ETLs, the other services, everything's left out. It's just comparing HeatWave, MySQL cloud service with HeatWave versus Redshift, not Redshift and Aurora and Glue, Redshift and Redshift ML and SageMaker, it's just Redshift. >> Yeah, so what you're saying is what Oracle's doing is saying, "Okay, we're going to run MySQL HeatWave benchmarks on analytics against Redshift, and then we're going to run 'em in transaction against Aurora." >> Right. >> But if you really had to look at what you would have to do with the ETL, you'd have to buy two different data stores and all the infrastructure around that, and that goes away so. >> Due to the nature of the competition, they're running narrow best of breed benchmarks. There is no suite level benchmark (Dave laughs) because they created something new. >> Well that's you're the earlier point they're beating best of breed with a suite. So that's, I guess to Floyer's earlier point, "That's going to shake things up." But I want to come back to Bob Evans, 'cause I want to tap your Cloud Wars mojo before we wrap. And line up the horses, you got AWS, you got Microsoft, Google and Oracle. Now they all own their own cloud. Snowflake, Mongo, Couchbase, Redis, Cockroach by the way they're all doing very well. They run in the cloud as do many others. I think you guys all saw the Andreessen, you know, commentary from Sarah Wang and company, to talk about the cost of goods sold impact of cloud. So owning your own cloud has to be an advantage because other guys like Snowflake have to pay cloud vendors and negotiate down versus having the whole enchilada, Safra Catz's dream. Bob, how do you think this is going to impact the market long term? >> Well, Dave, that's a great question about, you know, how this is all going to play out. If I could mention three things, one, Frank Slootman has done a fantastic job with Snowflake. Really good company before he got there, but since he's been there, the growth mindset, the discipline, the rigor and the phenomenon of what Snowflake has done has forced all these bigger companies to really accelerate what they're doing. And again, it's an example of how this intense competition makes all the different cloud vendors better and it provides enormous value to customers. Second thing I wanted to mention here was look at the Adam Selipsky effect at AWS, took over in the middle of May, and in Q2, Q3, Q4, AWS's growth rate accelerated. And in each of those three quotas, they grew faster than Microsoft's cloud, which has not happened in two or three years, so they're closing the gap on Microsoft. The third thing, Dave, in this, you know, incredibly intense competitive nature here, look at Larry Ellison, right? He's got his, you know, the product that for the last two or three years, he said, "It's going to help determine the future of the company, autonomous database." You would think he's the last person in the world who's going to bring in, you know, in some ways another database to think about there, but he has put, you know, his whole effort and energy behind this. The investments Oracle's made, he's riding this horse really hard. So it's not just a technology achievement, but it's also an investment priority for Oracle going forward. And I think it's going to form a lot of how they position themselves to this new breed of buyer with a new type of need and expectations from IT. So I just think the next two or three years are going to be fantastic for people who are lucky enough to get to do the sorts of things that we do. >> You know, it's a great point you made about AWS. Back in 2018 Q3, they were doing about 7.4 billion a quarter and they were growing in the mid forties. They dropped down to like 29% Q4, 2020, I'm looking at the data now. They popped back up last quarter, last reported quarter to 40%, that is 17.8 billion, so they more doubled and they accelerated their growth rate. (laughs) So maybe that pretends, people are concerned about Snowflake right now decelerating growth. You know, maybe that's going to be different. By the way, I think Snowflake has a different strategy, the whole data cloud thing, data sharing. They're not trying to necessarily take Oracle head on, which is going to make this next 10 years, really interesting. All right, we got to go, last question. 30 seconds or less, what can we expect from the future of data platforms? Matt, please start. >> I have to go first again? You're killing me, Dave. (laughing) In the next few years, I think you're going to see the major players continue to meet customers where they are, right. Every organization, every environment is, you know, kind of, we use these words bespoke in Snowflake, pardon the pun, but Snowflakes, right. But you know, they're all opinionated and unique and what's great as an IT person is, you know, there is a service for me regardless of where I am on my journey, in my data management journey. I think you're going to continue to see with regards specifically to Oracle, I think you're going to see the company continue along this path of being all things to all people, if you will, or all organizations without sacrificing, you know, kind of richness of features and sacrificing who they are, right. Look, they are the data kings, right? I mean, they've been a database leader for an awful long time. I don't see that going away any time soon and I love the innovative spirit they've brought in with HeatWave. >> All right, great thank you. Okay, 30 seconds, Holgar go. >> Yeah, I mean, the interesting thing that we see is really that trend to autonomous as Oracle calls or self-driving software, right? So the database will have to do more things than just store the data and support the DVA. It will have to show it can wide insights, the whole upside, it will be able to show to one machine learning. We haven't really talked about that. How in just exciting what kind of use case we can get of machine learning running real time on data as it changes, right? So, which is part of the E5 announcement, right? So we'll see more of that self-driving nature in the database space. And because you said we can promote it, right. Check out my report about HeatWave latest release where I post in oracle.com. >> Great, thank you for that. And Bob Evans, please. You're great at quick hits, hit us. >> Dave, thanks. I really enjoyed getting to hear everybody's opinion here today and I think what's going to happen too. I think there's a new generation of buyers, a new set of CXO influencers in here. And I think what Oracle's done with this, MySQL HeatWave, those benchmarks that Ron talked about so eloquently here that is going to become something that forces other companies, not just try to get incrementally better. I think we're going to see a massive new wave of innovation to try to play catch up. So I really take my hat off to Oracle's achievement from going to, push everybody to be better. >> Excellent. Marc Staimer, what do you say? >> Sure, I'm going to leverage off of something Matt said earlier, "Those companies that are going to develop faster, cheaper, simpler products that are going to solve customer problems, IT problems are the ones that are going to succeed, or the ones who are going to grow. The one who are just focused on the technology are going to fall by the wayside." So those who can solve more problems, do it more elegantly and do it for less money are going to do great. So Oracle's going down that path today, Snowflake's going down that path. They're trying to do more integration with third party, but as a result, aiming at that simpler, faster, cheaper mentality is where you're going to continue to see this market go. >> Amen brother Marc. >> Thank you, Ron Westfall, we'll give you the last word, bring us home. >> Well, thank you. And I'm loving it. I see a wave of innovation across the entire cloud database ecosystem and Oracle is fueling it. We are seeing it, with the native integration of auto ML capabilities, elastic scaling, lower entry price points, et cetera. And this is just going to be great news for buyers, but also developers and increased use of open APIs. And so I think that is really the key takeaways. Just we're going to see a lot of great innovation on the horizon here. >> Guys, fantastic insights, one of the best power panel as I've ever done. Love to have you back. Thanks so much for coming on today. >> Great job, Dave, thank you. >> All right, and thank you for watching. This is Dave Vellante for theCube and we'll see you next time. (soft music)

[Music] hello and welcome to this power panel where we go deep with three storage industry vets two from infinidat in an analyst view to find out what's happening in the high-end storage business and what's new with infinidat which has recently added significant depth to its executive ranks and we're going to review the progress on infinidat's infinibox ssa a low-latency all-solid state system designed for the most intensive enterprise workloads to do that we're joined by phil bullinger the chief executive officer of it finidet ken steinhardt is the field cto at infinidat and we bring in the analyst view with eric bergener who's the vice president of research infrastructure systems platforms and technologies group at idc all three cube alums gents welcome back to the cube good to see you thanks very much dave good to be here thanks david as always a pleasure phil let me start with you as i mentioned up top you've been top grading your team we covered the herzog news beefing up your marketing and also upping your game and emea and apj go to market recently give us the business update on the company since you became ceo earlier this year yeah dave i'd be happy to you know the uh i joined the company in january and it's been a it's been a fast 11 months uh exciting exciting times at infinidad as you know really beginning last fall the company has gone through quite a renaissance a change in the executive leadership team uh i was really excited to join the company we brought on you know a new cfo new chief human resources officer new chief legal officer operations head of operations and most recently as has been you know widely reported we brought in eric to head up our marketing organization as a cmo and then last week richard bradbury in in london to head up international sales so very excited about the team we brought together it's uh it's resulted in or it's been the culmination of a lot of work this year to accelerate the growth of infinidat and that's exactly what we've done it's the company has posted quarter after quarter of significant revenue growth we've been accelerating our rate and pace of adding large new fortune 500 global 2000 accounts and the results show it definitely the one of the most exciting things i think this year has been infinidat has pretty rapidly evolved from a single product line uh company around the infinibox architecture which is what made us unique at the start and still makes us very unique as a company and we've really expanded out from there on that same common software-defined architecture to the ssa the solid state array which we're going to talk about in some in some depth today and then our backup appliance our data protection appliance as well all running the same software and what we see now in the field uh many customers are expanding quickly beyond you know the traditional infinibox business uh to the other parts of our portfolio and our sales teams in turn are expanding their selling motion from kind of an infinibox approach to a portfolio approach and it's it's really helping accelerate the growth of the company yeah that's great to hear you really got a deep bench and of course you you know a lot of people in the industry so you're tapping a lot of your your colleagues okay let's get into the market i want to bring in uh the analyst perspective eric can you give us some context when we talk about things like ultra low latency storage what's the market look like to you help us understand the profile of the customer the workloads the market segment if you would well you bet so i'll start off with a macro trend which is clearly there's more real-time data being captured every year in fact by 2024 24 of all of the data captured and stored will be real-time and that puts very different performance requirements on the storage infrastructure than what we've seen in years past a lot of this is driven by digital transformation we've seen new workload types come in big data analytics real-time big data analytics and obviously we've got legacy workloads that need to be handled as well one other trend i'll mention that is really pointing up this need for low latency consistent low latency is workload consolidation we're seeing a lot of enterprises look to move to fewer storage platforms consolidate more storage workloads onto fewer systems and to do that they really need low latency consistent low latency platforms to be able to achieve that and continue to meet their service level agreements great thank you for that all right ken let's bring you into the conversation steiny what are the business impacts of of latency i want you to help us understand when and why is high latency a problem what are the positive impacts of having a consistent low latency uh opportunity or option and what kind of workloads and customers need that right the world has really changed i mean when when dinosaurs like me started in this industry the only people that really knew about performance were the people in the data center and then as things moved into online computing over the years then people within your own organization would care about performance if things weren't going well and it was really the erp revolution the 1990s that sort of opened uh people's eyes to the need for performance particularly for storage performance where now it's not just your internal users but your suppliers are now seeing what your systems look like fast forward to today in a web-based internet world everyone can see with customer facing applications whether you're delivering what they want or not and to answer your question it really comes down to competitive differentiation for the users that can deliver a better user customer experience if you and i'm sure everybody can relate if you go online and try to place an order especially with the holiday season coming up if there's one particular site that is able to give you instantaneous response you're more likely to do business there than somebody where you're going to be waiting and it literally is that simple it used to be that we cared about bandwidth and we used to care about ios per second and the third attribute latency really has become the only one that really matters going forward we found that most customers tell us that these days almost anyone can meet their requirements for bandwidth and ios per second with very few outlying cases where that's not true but the ever unachievable zero latency instantaneous response that's always going to be able to give people competitive differentiation in everything that they do and whoever can provide that is going to be in a very good position to help them serve their customers better yeah eric that stat you threw out of 24 real time uh and that that sort of underscores the need but phil i wonder how how this fits if you could talk about how that fits into your tam expansion strategy i think that's the job of of every ceo is to think about the expanding the tam it seems like you know a lot of people might say it's not necessarily the largest market but it's strategic and maybe opens up some downstream opportunities is that how you're thinking about it or based on what ken just said you expect this to to grow over time oh we definitely expect it to grow uh dave you know the the history of infinidat has been around our infinibox product targeting the primary storage market at the at the higher end of that market you know it's we've enjoyed operating in a eight nine 10 billion dollar tan through the years and that it continues to grow and we continue to outpace market growth within that tam which is exciting what this uh what the ssa really does is it opens up a tier of workload performance that we see more and more emerging in the primary data center the infinibox classic infinibox architecture we have very very fast as we say it typically outperforms most of our all-flash uh array competitors but clearly there there are a tier of workloads that are growing in the data center that require very very tight tail latencies and and that segment is certainly growing it's where some of the most demanding workloads are on the infinibox ssa was really built to expand our participation in those segments of the market and as i mentioned up front at the same time also taking that that software architecture and moving it into the the data protection space as well which is a whole nother market space that we're opening up for the company so we really see our tam this year with more of the this portfolio approach expanding quite a bit eric how how do you see it well those real-time applications that you talked about that require that consistent ultra-low latency grow kind of in in parallel with that that time curve you know will they become a bigger part of that the the overall storage team and and the workload mix how does idc see it yeah so so they actually are going to be growing over time and a lot of that's driven by the fact of the expectations that um steinhart mentioned a little bit earlier just on the part of customers right what they expect when they interact with your i.t infrastructure so we see that absolutely growing going forward i will make a quick comment about you know when all flash arrays first hit back in 2012 um in the 10 years since they started shipping they now generate over 80 of the primary revenues out there in in the primary storage arena so clearly they've taken over an interesting aspect of what's going on here is that a lot of companies now write rfps specifically requiring an all-flash array and what's going to be interesting for infinidat is despite the fact that they could deliver better performance than many of those systems in the past they couldn't really go after the business where that rfp was written for an afa spec well now they'll certainly have the opportunity to do that in my estimation that's going to give them access to about an additional 5 billion in tam by 2025 so this is big for them as a company yeah that's a 50 increase in tamp so okay well eric you just set up my my follow-up question to you ken was going to be the tougher questions uh which we've you and i have had some healthy debates about this but i know you'll have answers so so for years you've argued that your cached architecture and magic sauce algorithms if i caught that could outperform all flash arrays we're using spinning disks so eric talked about the sort of check off item but are there other reasons for the change of heart why and why does the world need another afa doesn't this cut against your petabyte scale messaging i wonder if you could sort of add some color to that sure a great question and the good news is infinibox still does typically outperform all flash arrays but usually that's for average of latency performance and we're tending to get because we're a a caching architecture not a tiered architecture and we're caching to dram which is an order of magnitude faster than flash or even storage class memory technologies it's our software magic and that software defined storage approach that we've had that now effectively is extended to solid state arrays and some customers told us that you know we love your performance it's incredible but if you could let us effectively be confident that we're seeing you know some millisecond sub half millisecond performance consistently for every single io you're going to give us competitive differentiation and this is one of the reasons why we chose to call the product a solid state array as opposed to merely an all-flash array the more common ubiquitous term and it's because we're not dependent on a specific technology we're using dram we can use virtually any technology on the back end and in this case we've chosen to use flash but it's the software that is able to provide that caching to the front end dram that makes things different so that's one aspect is it's the software that really makes the difference it's been the software all along and still on this architecture still mentions going to across the multiple products it's still the software it's also that in that class of ultra high performance architecturally because it is based on the infinibox architecture we're able to deliver 100 availability which is another aspect that the market has evolved to come to expect and it's not rocket science or magic how we do it the godfather of computer science john von neumann all the way back in the 1950s theorized all the way back then that the right way to do ultra high availability and integrity in i.t systems of any type is in threes triple redundancy and in our case amazingly we're the only architecture that uses triple redundant active active components for every single mission critical component on the system and that gives a level of confidence to people from an availability perspective to go with that performance that is just unmatched in the market and then bring all of that together with a set it and forget it mentality for ease of use and simplicity of management and as phil mentioned being able to have a single architecture that can address now not only the ultra high performance but across the entire swath of as eric mentioned consolidation which is a key aspect as well driving this in addition to those real-time applications that he mentioned and even being able to take it down into our our infiniguard data protection device but all with the same common base of software common interface common user experience and unmatched availability and we've got something that we really think people are going to like and they've certainly been proving that of late well i was going to ask you you know what makes the the infinibox ssa different but i think you just laid it out but your contention is this is totally unique in the marketplace is that right ken yes indeed this is a unique architecture and i i literally as a computer scientist myself truly am genuinely surprised that no other vendor in the market has taken the wisdom of the godfather of computer science john von neumann and put it into practice except in the storage world for this particular architecture which transcends our entire realm all the way from the performance down to the data protection phil i mean you have a very wide observation space in this industry and a good strong historical perspective do you think the expectations for performance and this notion of ultra low latencies you know becoming more demanding is is there a parallel so first of all why is that we've talked about a little bit but is there a parallel to the way availability remember you could have escalated over the years um because it was such a problem and now it's really become table stakes and that last mile is so hard but what are your thoughts on that i i think i think absolutely dave you know the the hallmark of infinidat is this white glove concierge level customer experience that we deliver and it's it's affirmed uh year after year in unsolicited enterprise customer feedback uh above every other competitor in our space uh infinidat sets itself apart for this um and i think that's a big part of what continues to drive and fuel the growth and success of the company i just want to touch on a couple things that ken and and eric mentioned the ssa absolutely opens up our tan because we get to we get a lot more at bats now but i think a lot of the industry looks at infinidat as well those guys are are hard drive zealots right they've their architecture is all based on rotating disk that's what they believe in and it's a hybrid versus afa world out there and they were increasingly not on the right bus and that's just absolutely not true in that our our neural cache and what ken talked about what made us unique at the start i think actually only increasingly differentiates us going forward in terms of the the set it and forget it the intelligence of our architecture the ability of that dram based cache to adapt so dynamically without any knobs and and configuration changes to massive changes in workload scale and user scale and it does it with no drama in fact most of our customers the most common feedback we get is that your platform just kind of disappears into our data infrastructure we don't think about it we don't worry about it when we install an infiniti an infinidat rack our intentions are never to come back you know we're not there showing up with trays of disk under our arms trying to upgrade a mission-critical platform that's just not our model what the ssa does is it gives our customers choice it's not about infinidat saying that used to be the shiny object now this is our new shiny object please everybody now go buy that what where where we position our ssa is it's a it's a tco latency sla choice that they can make between exactly identical customer experiences so instead of an old hybrid and a new afa we've got that same software architecture set it and forget it the neural cache and customers can choose what back-end persistent store they want based on the tco and the sla that they want to deliver to a given set of applications so probably the most significant thing that i've seen happen in the last six months at infinidat is a lot of our largest customers the the fortune 15s the fortune 50s the fortune 100s who have been long-standing infinidat customers are now on almost every sort of re-tranche of or trancha purchase orders into us we're now seeing a mix we're seeing a mix of some ssa and some classic infinibox because they're mixing and matching in a given data center down a given row these applications need this sla these applications need this la and we're able to give them that choice and frankly we don't we don't intentionally try to steer them one direction or the other they they're smart they do the math they can pick and choose what experience they want knowing that irrespective of what front door they go through into the infinidat portfolio they're going to get that same experience so i'm hearing it's not just a an rfp check off item it's more than that the market is heading in that direction eric's data on on real time and we're certainly seeing that the data-driven applications the injection of ai and you know systems making decisions in in real time um and i i'm also hearing phil that you're building on your core principles i'm hearing the white glove service the media agnostic the set it and forget it sort of principles that you guys were founded on is you're carrying that through to this this opportunity we absolutely are in the reason and you ask a good question before and i want to more completely answer it i think availability and customer experience are incredibly important today more so than ever because data center economics and data center efficiency um are more important than ever before is as customers evaluate what workloads belong in the public cloud what workloads do i want on-prem irrespective of those decisions they're trying to optimize their their operational expenses their capex expenses and so one thing that infinidat has always excelled at is consolidation bringing multiple users multiple workloads into the same common platform in the data center it says floor space and watts and and uh you know storage administration resources but to do consolidation well you've got to be incredibly reliable and incredibly predictable without a lot of fuss and drama associated with it and so i think the thing that has made infinidat really strong through the years with being a very good consolidation platform is more important now than ever before in in the enterprise storage space because it is really about data center efficiency and uh administration efficiency associated with that yeah thank you for that phil now actually ken let me come back to you i want to ask you a question about consolidation and you and i and and doc our business friend rest his soul have had some some great conversations about this over time but but as you consolidate people are sometimes worried about the blast radius could you address that concern sure well um phil alluded to software and uh it is the cornerstone of everything we bring to the table and it's not just that deep learning that transcends all the intelligence phil talked about in terms of that full wide range of product it's also protection of data across multiple sites and in multiple ways so we were very fortunate in that when we started to create this product since it is a modern product we got to start with a clean sheet of paper and basically look at everything that had been done before and even with some of the very people who created some of the original software for replication in the market were able to then say if i could do it again how would i do it today and how would it be better so we started with local replication and snapshot technology which is the foundation for being able to do full active active replication across two sites today where you can have true zero rpo no data loss even in the face of any kind of failure of a site of a server of a network of a storage device of a connection as well as zero rto immediate consistent operation with no human intervention and we can extend from that out to remote sites literally anywhere in the world in multiples where you can have additional copies of information and at any of them you can be using not only for protection against natural disasters and floods and things like that but from a cyber security perspective immutable snapshots being able to provide data that you know the bad actors can't compromise in multiple locations so we can protect today against virtually any kind of failure scenario across the swath of infinibox or infinibox ssa you can even connect infinite boxes and infinibox ssas because they are the same architecture exactly as phil said what we're seeing is people deploying mostly infinibox because it addresses the wide swath from a consolidation perspective and usually just infinibox ssa for those ultra high performance environments but the beauty of it is it looks feels runs and operates as that one single simple environment that's set it and forget it and just let it run okay so you can consolidate with with confidence uh let's end with the the independent analyst perspective eric you know how do you see this offering what do you think it means for the market is this a new category is it an extension to an existing space how do you look at that uh so i don't see it as a new category i mean it clearly falls into the current definition of afas i think it's more important from the point of view of the customer base that likes this architecture likes the availability the functionality the flexibility that it brings to the table and they can leverage it with tier zero workloads which was something that in the past they didn't have that latency consistency to do that you know i'll just make one one final comment on the software side as well so the reason software is eating the world mark andreessen is basically because of the flexibility the ease of use and the economics and if you take a look at how this particular vendor infinidat designed their product with a software-based definition they were able to swap out underneath and create a different set of characteristics with this new platform because of the flexibility in the software design and that's critical one if you think about how software is dominating so today for 2021 68 of the revenue in the external storage market that's the size of the software defined storage market that's going to be going to almost 80 by 2024 so clearly things are moving in the direction of systems that are defined in a software-defined manner yeah and data is eating software which is why you're going to need ultra low latency um okay we got to wrap it eric you've just published a piece uh this summer called enterprise storage vendor infinidat expands total available market opportunities with all flash system introduction i'm sure they can get that on your website here's a little graphic that shows you how to get that but so guys thanks so much for coming on the cube congratulations on the progress and uh we'll be watching thanks steve thanks very much dave thank you as always a pleasure all right thank you for watching this cube conversation everybody this is dave vellante and we'll see you next time [Music] you

(bright music) >> Hello and welcome to today's session of the 2021 AWS Global Public Sector Partner Awards for the award for Best Partner Transformation, Best Cybersecurity Solution. I'm now honored to welcome our next guests, General Keith Alexander, Founder, and Co-CEO of IronNet Cybersecurity, as well as Gil Quiniones, President and CEO of the New York Power Authority. Welcome to the program gentlemen, delighted to have you here. >> Good to be here. >> Terrific. Well, General Alexander, I'd like to start with you. Tell us about the collective defense program or platform and why is it winning awards? >> Well, great question and it's great to have Gil here because it actually started with the energy sector. And the issue that we had is how do we protect the grid? The energy sector CEOs came together with me and several others and said, how do we protect this grid together? Because we can't defend it each by ourselves. We've got to defend it together. And so the strategy that IronNet is using is to go beyond what the conventional way of sharing information known as signature-based solutions to behavioral-based so that we can see the events that are happening, the unknown unknowns, share those among companies and among both small and large in a way that helps us defend because we can anonymize that data. We can also share it with the government. The government can see a tax on our country. That's the future, we believe, of cybersecurity and that collective defense is critical for our energy sector and for all the companies within it. >> Terrific. Well, Gil, I'd like to shift to you. As the CEO of the largest state public power utility in the United States, why do you think it's so important now to have a collective defense approach for utility companies? >> Well, the utility sector lied with the financial sector as number one targets by our adversaries and you can't really solve cybersecurity in silos. We, NYPA, my company, New York Power Authority alone cannot be the only one and other companies doing this in silos. So what's really going to be able to be effective if all of the utilities and even other sectors, financial sectors, telecom sectors cooperate in this collective defense situation. And as we transform the grid, the grid is getting transformed and decentralized. We'll have more electric cars, smart appliances. The grid is going to be more distributed with solar and batteries charging stations. So the threat surface and the threat points will be expanding significantly and it is critical that we address that issue collectively. >> Terrific. Well, General Alexander, with collective defense, what industries and business models are you now disrupting? >> Well, we're doing the energy sector, obviously. Now the defense industrial base, the healthcare sector, as well as international partners along the way. And we have a group of what we call technical and other companies that we also deal with and a series of partner companies, because no company alone can solve this problem, no cybersecurity company alone. So partners like Amazon and others partner with us to help bring this vision to life. >> Terrific. Well, staying with you, what role does data and cloud scale now play in solving these security threats that face the businesses, but also nations? >> That's a great question. Because without the cloud, bringing collective security together is very difficult. But with the cloud, we can move all this information into the cloud. We can correlate and show attacks that are going on against different companies. They can see that company A, B, C or D, it's anonymized, is being hit with the same thing. And the government, we can share that with the government. They can see a tax on critical infrastructure, energy, finance, healthcare, the defense industrial base or the government. In doing that, what we quickly see is a radar picture for cyber. That's what we're trying to build. That's where everybody's coming together. Imagine a future where attacks are coming against our country can be seen at network speed and the same for our allies and sharing that between our nation and our allies begins to broaden that picture, broaden our defensive base and provide insights for companies like NYPA and others. >> Terrific. Well, now Gil, I'd like to move it back to you. If you could describe the utility landscape and the unique threats that both large ones and small ones are facing in terms of cybersecurity and the risks, the populous that live there. >> Well, the power grid is an amazing machine, but it is controlled electronically and more and more digitally. So as I mentioned before, as we transform this grid to be a cleaner grid, to be more of an integrated energy network with solar panels and electric vehicle charging stations and wind farms, the threat is going to be multiple from a cyber perspective. Now we have many smaller utilities. There are towns and cities and villages that own their poles and wires. They're called municipal utilities, rural cooperative systems, and they are not as sophisticated and well-resourced as a company like the New York Power Authority or our investor on utilities across the nation. But as the saying goes, we're only as strong as our weakest link. And so we need- >> Terrific. >> we need to address the issues of our smaller utilities as well. >> Yeah, terrific. Do you see a potential for more collaboration between the larger utilities and the smaller ones? What do you see as the next phase of defense? >> Well, in fact, General Alexander's company, IronNet and NYPA are working together to help bring in the 51 smaller utilities here in New York in their collective defense tool, the IronDefense or the IronDome as we call it here in New York. We had a meeting the other day, where even thinking about bringing in critical state agencies and authorities. The Metropolitan Transportation Authority, Port Authority of New York and New Jersey, and other relevant critical infrastructure state agencies to be in this cloud and to be in this radar of cybersecurity. And the beauty of what IronNet is bringing to this arrangement is they're trying to develop a product that can be scalable and affordable by those smaller utilities. I think that's important because if we can achieve that, then we can replicate this across the country where you have a lot of smaller utilities and rural cooperative systems. >> Yeah. Terrific. Well, Gil, staying with you. I'd love to learn more about what was the solution that worked so well for you? >> In cybersecurity, you need public-private partnerships. So we have private companies like IronNet that we're partnering with and others, but also partnering with state and federal government because they have a lot of resources. So the key to all of this is bringing all of that information together and being able to react, the General mentioned, network speed, we call it machine speed, has to be quick and we need to protect and or isolate and be able to recover it and be resilient. So that's the beauty of this solution that we're currently developing here in New York. >> Terrific. Well, thank you for those points. Shifting back to General Alexander. With your depth of experience in the defense sector, in your view, how can we stay in front of the attacks, mitigate them, and then respond to them before any damage is done? >> So having run our nations, the offense. I know that the offense has the upper hand almost entirely because every company and every agency defends itself as an isolated entity. Think about 50 mid-sized companies, each with 10 people, they're all defending themselves and they depend on that defense individually and they're being attacked individually. Now take those 50 companies and their 10 people each and put them together and collect the defense where they share information, they share knowledge. This is the way to get out in front of the offense, the attackers that you just asked about. And when people start working together, that knowledge sharing and crowdsourcing is a solution for the future because it allows us to work together where now you have a unified approach between the public and private sectors that can share information and defend each of the sectors together. That is the future of cybersecurity. What makes it possible is the cloud, by being able to share this information into the cloud and move it around the cloud. So what Amazon has done with AWS has exactly that. It gives us the platform that allows us to now share that information and to go at network speed and share it with the government in an anonymized way. I believe that will change radically how we think about cybersecurity. >> Yeah. Terrific. Well, you mention data sharing, but how is it now a common tactic to get the best out of the data? And now, how is it sharing data among companies accelerated or changed over the past year? And what does it look like going forward when we think about moving out of the pandemic? >> So first, this issue of sharing data, there's two types of data. One about the known threats. So sharing that everybody knows because they use a signature-based system and a set of rules. That shared and that's the common approach to it. We need to go beyond that and share the unknown. And the way to share the unknown is with behavioral analytics. Detect behaviors out there that are anonymous or anomalous, are suspicious and are malicious and share those and get an understanding for what's going on in company A and see if there's correlations in B, C and D that give you insights to suspicious activity. Like solar winds, recognizes solar winds at 18,000 companies, each defending themselves. None of them were able to recognize that. Using our tools, we did recognize it in three of our companies. So what you can begin to see is a platform that can now expand and work at network speed to defend against these types of attacks. But you have to be able to see that information, the unknown unknowns, and quickly bring people together to understand what that means. Is this bad? Is this suspicious? What do I need to know about this? And if I can share that information anonymized with the government, they can reach in and say, this is bad. You need to do something about it. And we'll take the responsibility from here to block that from hitting our nation or hitting our allies. I think that's the key part about cybersecurity for the future. >> Terrific. General Alexander, ransomware of course, is the hottest topic at the moment. What do you see as the solution to that growing threat? >> So I think, a couple things on ransomware. First, doing what we're talking about here to detect the phishing and the other ways they get in is an advanced way. So protect yourself like that. But I think we have to go beyond, we have to attribute who's doing it, where they're doing it from and hold them accountable. So helping provide that information to our government as it's going on and going after these guys, making them pay a price is part of the future. It's too easy today. Look at what happened with the DarkSide and others. They hit Colonial Pipeline and they said, oh, we're not going to do that anymore. Then they hit a company in Japan and prior to that, they hit a company in Norway. So they're attacking and they pretty much operate at will. Now, let's indict some of them, hold them accountable, get other governments to come in on this. That's the way we stop it. And that requires us to work together, both the public and private sector. It means having these advanced tools, but also that public and private partnership. And I think we have to change the rhetoric. The first approach everybody takes is, Colonial, why did you let this happen? They're a victim. If they were hit with missiles, we wouldn't be asking that, but these were nation state like actors going after them. So now our government and the private sector have to work together and we need to change that to say, they're victim, and we're going to go after the guys that did this as a nation and with our allies. I think that's the way to solve it. >> Yeah. Well, terrific. Thank you so much for those insights. Gil, I'd also like to ask you some key questions and of course, certainly people today have a lot of concerns about security, but also about data sharing. How are you addressing those concerns? >> Well, data governance is critical for a utility like the New York Power Authority. A few years ago, we declared that we aspire to be the first end-to-end digital utility. And so by definition, protecting the data of our system, our industrial controls, and the data of our customers are paramount to us. So data governance, considering data or treating data as an asset, like a physical asset is very, very important. So we in our cybersecurity, plans that is a top priority for us. >> Yeah. And Gil thinking about industry 4.0, how has the surface area changed with Cloud and IoT? >> Well, it's grown significantly. At the power authority, we're installing sensors and smart meters at our power plants, at our substations and transmission lines, so that we can monitor them real time, all the time, know their health, know their status. Our customers we're monitoring about 15 to 20,000 state and local government buildings across our states. So just imagine the amount of data that we're streaming real time, all the time into our integrated smart operations center. So it's increasing and it will only increase with 5G, with quantum computing. This is just going to increase and we need to be prepared and integrate cyber into every part of what we do from beginning to end of our processes. >> Yeah. And to both of you actually, as we see industry 4.0 develop even further, are you more concerned about malign actors developing more sophistication? What steps can we take to really be ahead of them? Let's start with General Alexander. >> So, I think the key differentiator and what the energy sector is doing, the approach to cybersecurity is led by CEOs. So you bring CEOs like Gil Quiniones in, you've got other CEOs that are actually bringing together forums to talk about cybersecurity. It is CEO led. That the first part. And then the second part is how do we train and work together, that collective defense. How do we actually do this? I think that's another one that NYPA is leading with West Point in the Army Cyber Institute. How can we start to bring this training session together and train to defend ourselves? This is an area where we can uplift our people that are working in this process, our cyber analysts if you will at the security operations center level. By training them, giving them hard tests and continuing to go. That approach will uplift our cybersecurity and our cyber defense to the point where we can now stop these types of attacks. So I think CEO led, bring in companies that give us the good and bad about our products. We'd like to hear the good, we need to hear the bad, and we needed to improve that, and then how do we train and work together. I think that's part of that solution to the future. >> And Gil, what are your thoughts as we embrace industry 4.0? Are you worried that this malign actors are going to build up their own sophistication and strategy in terms of data breaches and cyber attacks against our utility systems? What can we do to really step up our game? >> Well, as the General said, the good thing with the energy sector is that on the foundational level, we're the only sector with mandatory regulatory requirements that we need to meet. So we are regulated by the Federal Energy Regulatory Commission and the North American Electric Reliability Corporation to meet certain standards in cyber and critical infrastructure. But as the General said, the good thing with the utility is by design, just like storms, we're used to working with each other. So this is just an extension of that storm restoration and other areas where we work all the time together. So we are naturally working together when it comes to to cyber. We work very closely with our federal government partners, Department of Homeland Security, Department of Energy and the National Labs. The National Labs have a lot of expertise. And with the private sector, like great companies like IronNet, NYPA, we stood up an excellence, center of excellence with private partners like IronNet and Siemens and others to start really advancing the art of the possible and the technology innovation in this area. And as the governor mentioned, we partnered with West Point because just like any sporting or just any sport, actual exercises of the red team, green team, and doing that constantly, tabletop exercises, and having others try and breach your walls. Those are good exercises to really be ready against the adversaries. >> Yeah. Terrific. Thank you so much for those insights. General Alexander, now I'd like to ask you this question. Can you share the innovation strategy as the world moves out of the pandemic? Are we seeing new threats, new realities? >> Well, I think, it's not just coming out of the pandemic, but the pandemic actually brought a lot of people into video teleconferences like we are right here. So more people are working from home. You add in the 5G that Gil talked about that gives you a huge attack surface. You're thinking now about instead of a hundred devices per square kilometer up to a million devices. And so you're increasing the attack surface. Everything is changing. So as we come out of the pandemic, people are going to work more from home. You're going to have this attack surface that's going on, it's growing, it's changing, it's challenging. We have to be really good about now, how we trained together, how we think about this new area and we have to continue to innovate, not only what are the cyber tools that we need for the IT side, the internet and the OT side, operational technology. So those kinds of issues are facing all of us and it's a constantly changing environment. So that's where that education, that training, that communication, working between companies, the customers, the NYPA's and the IronNet's and others and then working with the government to make sure that we're all in sync. It's going to grow and is growing at an increased rate exponentially. >> Terrific. Thank you for that. Now, Gil, same question for you. As a result of this pandemic, do you see any kind of new realities emerging? What is your position? >> Well, as the General said, most likely, many companies will be having this hybrid setup. And for company's life like mine, I'm thinking about, okay, how many employees do I have that can access our industrial controls in our power plants, in our substations, and transmission system remotely? And what will that mean from a risk perspective, but even on the IT side, our business information technology. You mentioned about the Colonial Pipeline type situation. How do we now really make sure that our cyber hygiene of our employees is always up-to-date and that we're always vigilant from potential entry whether it's through phishing or other techniques that our adversaries are using. Those are the kinds of things that keep myself like a CEO of a utility up at night. >> Yeah. Well, shifting gears a bit, this question for General Alexander. How come supply chain is such an issue? >> Well, the supply chain, of course, for a company like NYPA, you have hundreds or thousands of companies that you work with. Each of them have different ways of communicating with your company. And in those communications, you now get threats. If they get infected and they reach out to you, they're normally considered okay to talk to, but at the same time that threat could come in. So you have both suppliers that help you do your job. And smaller companies that Gil has, he's got the 47 munis and four co-ops out there, 51, that he's got to deal with and then all the state agencies. So his ecosystem has all these different companies that are part of his larger network. And when you think about that larger network, the issue becomes, how am I going to defend that? And I think, as Gil mentioned earlier, if we put them all together and we operate and train together and we defend together, then we know that we're doing the best we can, especially for those smaller companies, the munis and co-ops that don't have the people and a security ops centers and other things to defend them. But working together, we can help defend them collectively. >> Terrific. And I'd also like to ask you a bit more on IronDefense. You spoke about its behavioral capabilities, it's behavioral detection techniques, excuse me. How is it really different from the rest of the competitive landscape? What sets it apart from traditional cybersecurity tools? >> So traditional cybersecurity tools use what we call a signature-based system. Think of that as a barcode for the threat. It's a specific barcode. We use that barcode to identify the threat at the firewall or at the endpoint. Those are known threats. We can stop those and we do a really good job. We share those indicators of compromise in those barcodes, in the rules that we have, Suricata rules and others, those go out. The issue becomes, what about the things we don't know about? And to detect those, you need behavioral analytics. Behavioral analytics are a little bit noisier. So you want to collect all the data and anomalies with behavioral analytics using an expert system to sort them out and then use collected defense to share knowledge and actually look across those. And the great thing about behavioral analytics is you can detect all of the anomalies. You can share very quickly and you can operate at network speed. So that's going to be the future where you start to share that, and that becomes the engine if you will for the future radar picture for cybersecurity. You add in, as we have already machine learning and AI, artificial intelligence, people talk about that, but in this case, it's a clustering algorithms about all those events and the ways of looking at it that allow you to up that speed, up your confidence in and whether it's malicious, suspicious or benign and share that. I think that is part of that future that we're talking about. You've got to have that and the government can come in and say, you missed something. Here's something you should be concerned about. And up the call from suspicious to malicious that gives everybody in the nation and our allies insights, okay, that's bad. Let's defend against it. >> Yeah. Terrific. Well, how does the type of technology address the President's May 2021 executive order on cybersecurity as you mentioned the government? >> So there's two parts of that. And I think one of the things that I liked about the executive order is it talked about, in the first page, the public-private partnership. That's the key. We got to partner together. And the other thing it went into that was really key is how do we now bring in the IT infrastructure, what our company does with the OT companies like Dragos, how do we work together for the collective defense for the energy sector and other key parts. So I think it is hit two key parts. It also goes on about what you do about the supply chain for software were all needed, but that's a little bit outside what we're talking about here today. The real key is how we work together between the public and private sector. And I think it did a good job in that area. >> Terrific. Well, thank you so much for your insights and to you as well, Gil, really lovely to have you both on this program. That was General Keith Alexander, Founder and Co-CEO of IronNet Cybersecurity, as well as Gil Quiniones, the President and CEO of the New York Power Authority. That's all for this session of the 2021 AWS Global Public Sector Partner Awards. I'm your host for theCUBE, Natalie Erlich. Stay with us for more coverage. (bright music)

>>President. >>Hello everyone and welcome to wien on 2021. My name is Dave Volonte and you're watching the cubes continuous coverage of the event. You know, VM is a company that made its mark riding the virtualization wave, but quite amazingly has continued to extend its product portfolio and catch the other major waves of the industry. Of course, we're talking about cloud backup. SaS data protection was one of the early players there making moves and containers. And this is the VM on power panel with me or Danny Allen, who is the Ceo and Senior vice president of product strategy at VM. Dave Russell is the vice President of enterprise Strategy, of course, said Vin and Rick Vanover, senior director of product strategy at VM. It's great to see you again. Welcome back to the cube. >>Good to be here. >>Well, it had to be here. >>Yeah, let's do it. >>Let's do this. So Danny, you know, we heard you kind of your keynotes and we saw the general sessions and uh sort of diving into the breakouts. But the thing that jumps out to me is this growth rate that you're on. Uh you know, many companies and we've seen this throughout the industry have really struggled, you know, moving from the traditional on prem model to an an A. R. R. Model. Uh they've had challenges doing so the, I mean, you're not a public company, but you're quite transparent and a lot of your numbers 25% a our our growth year of a year in the last quarter, You know, 400,000 plus customers. You're talking about huge numbers of downloads of backup and replication Danny. So what are your big takeaways from the last, You know, 6-12 months? I know it was a strange year obviously, but you guys just keep cranking. >>Yeah, so we're obviously hugely excited by this and it really is a confluence of various things. It's our, it's our partners, it's the channel. Um, it's our customers frankly that that guide us and give us direction on what to do. But I always focus in on the product because I, you know, we run product strategy here, this group and we're very focused on building good products and I would say there's three product areas that are on maximum thrust right now. One is in the data center. So we built a billion dollar business on being the very best in the data center for V sphere, hyper V, um, for Nutanix, HV and as we announced also with red hat virtualization. So data center obviously a huge thrust for us going forward. The second assess Office 3 65 is exploding. We already announced we're protecting 5.8 million users right now with being back up for Office 3 65 and there's a lot of room to grow there. There's 145 million daily users of Microsoft teams. So a lot of room to grow. And then the third areas cloud, we moved over 100 petabytes of data into the public cloud in Q one and there's a lot of opportunity there as well. So those three things are driving the growth, the data center SaAS and cloud >>Davis. I want to get your kind of former analyst perspective on this. Uh you know, I know, you know, it's kind of become cliche but you still got that D. N. A. And I'm gonna tap it. So when you think about and you were following beam, of course very closely during its ascendancy with virtualization. And back then you wouldn't just take your existing, you know, approaches to back up in your processes and just slap them on to virtualization. That that wouldn't have worked. You had to rethink your backup. And it seems like I want to ask you about cloud because people talk about lift and shift and what I hear from customers is, you know, if I just lift and shift to cloud, it's okay, but if I don't have a plan to change my operating model, you know, I don't get the real benefit out of it. And so I would think back up data protection, data management etcetera is a key part of that. So how are you thinking about cloud and the opportunity there? >>Yeah, that's a good point, David. You know, I think the key area right there is it's important to protect the workload of the environment. The way that that environment is naturally is best suited to be protected and also to interact in a way that the administrator doesn't have to rethink, doesn't have to change their process so early on. Um I think it was very successful because the interface is the work experience looked like what an active directory administrator was used to, seeing if they went to go and protect something with me where to go recover an item. Same is true in the cloud, You don't want to just take what's working well in one area and just force it, you know, around round peg into a square hole. This doesn't work well. So you've got to think about the environment and you've got to think about what's gonna be the real use case for getting access to this data. So you want to really tune things and there's obviously commonality involved, but from a workflow perspective, from an application perspective and then a delivery model perspective, Now, when it comes to hybrid cloud multi cloud, it's important to look like that you belong there, not a fish out of water. >>Well, so of course, Danny you were talking to talking about you guys have product first, Right? And so rick your your key product guy here. What's interesting to me is when you look at the history of the technology industry and disruption, it's it's so often that the the incumbent, which you knew now an incumbent, you know, you're not the startup anymore, but the incumbent has challenges riding these these new waves because you've got to serve the existing customer base, but you gotta ride the new momentum as well. So how rick do you approach that from a product standpoint? Because based on the numbers that we see it doesn't you seem to be winning in both the traditional business and the new business. So how do you adapt from a product standpoint? >>Well, Dave, that's a good question. And Danny set it up? Well, it's really the birth of the Wien platform and its relevance in the market. In my 11th year here at Wien, I've had all kinds of conversations. Right. You know, the perception was that, you know, this smb toy for one hyper Advisor those days are long gone. We can check the boxes across the data center and cloud and even cloud native apps. You know, one of the things that my team has done is invest heavily in both people and staff on kubernetes, which aligns to our casting acquisition, which was featured heavily here at V Mon. So I think that being able to have that complete platform conversation Dave has really given us incredible momentum but also credibility with the customers because more than ever, this fundamental promise of having data backed up and being able to drive a recovery for whatever may happen to data nowadays. You know, that's a real emotional, important thing for people and to be able to bring that kind of outcome across the data center, across the cloud, across changes in what they do kubernetes that's really aligned well to our success and you know, I love talking to customers now. It's a heck of a lot easier when you can say yes to so many things and get the technical win. So that kind of drives a lot of the momentum Dave, but it's really the platform. >>So let's talk about the future of it and I want all you guys to chime in here and Danny, you start up, How do you see it? I mean, I always say the last 10 years, the next 10 years ain't gonna be like the last 10 years whether it's in cloud or hybrid et cetera. But so how Danny do you see I. T. In the future of I. T. Where do you see VM fitting in, how does that inform your roadmap, your product strategy? Maybe you could kick that segment off? >>Yeah. I think of the kind of the two past decades that we've gone through starting back in 2000 we had a lot of digital services built for end users and it was built on physical infrastructure and that was fantastic. Obviously we could buy things online, we could order close we could order food, we we could do things interact with end users. The second era about a decade later was based on virtualization. Now that wasn't a benefit so much to the end user is a benefit to the business. The Y because you could put 10 servers on a single physical server and you could be a lot more flexible in terms of delivery. I really think this next era that we're going into is actually based on containers. That's why the cost of acquisition is so strategic to us. Because the unique thing about containers is they're designed for to be consumption friendly. You spin them up, you spin them down, you provision them, you d provisions and they're completely portable. You can move it >>from on >>premises if you're running open shift to e k s a k s G k E. And so I think the next big era that we're going to go through is this movement towards containerized infrastructure. Now, if you ask me who's running that, I still think there's going to be a data center operations team, platform ups is the way that I think about them who run that because who's going to take the call in the middle of the night. But it is interesting that we're going through this transformation and I think we're in the very early stages of this radical transformation to a more consumption based model. Dave. I don't know what you think about that. >>Yeah, I would say something pretty similar Danny. It sounds cliche day valenti, but I take everything back to digital transformation. And the reason I say that is to me, digital transformation is about improving customer intimacy and so that you can deliver goods and services that better resonate and you can deliver them in better time frame. So exactly what Danny said, you know, I think that the siloed approaches of the past where we built very hard in environments and we were willing to take a long time to stand those up and then we have very tight change control. I feel like 2020 sort of a metaphor for where the data center is going to throw all that out the window we're compiling today. We're shipping today and we're going to get experience today and we're going to refine it and do it again tomorrow. But that's the environment we live in. And to Danny's point why containers are so important. That notion of shift left meaning experience things earlier in the cycle. That is going to be the reality of the data center regardless of whether the data center is on prem hybrid cloud, multi cloud or for some of us potentially completely in the cloud. >>So rick when you think about some of your peeps like the backup admit right and how that role is changing in a big discussion in the economy now about the sort of skills gap we got all these jobs and and yet there's still all this unemployment now, you know the debate about the reasons why, but there's a there's a transition enrolls in terms of how people are using products and obviously containers brings that, what what are you seeing when you talk to like a guy called him your peeps? Yeah, it's >>an evolving conversation. Dave the audience, right. It has to be relevant. Uh you know, we were afforded good luxury in that data center wheelhouse that Danny mentioned. So virtualization platform storage, physical servers, that's a pretty good start. But in the software as a service wheelhouse, it's a different persona now, they used to talk to those types of people, there's a little bit of connection, but as we go farther to the cloud, native apps, kubernetes and some of the other SAAS platforms, it is absolutely an audience journey. So I've actually worked really hard on that in my team, right? Everything from what I would say, parachuting into a community, right? And you have to speak their language. Number one reason is just number one outcomes just be present. And if you're in these communities you can find these individuals, you can talk their language, you can resonate with their needs, right? So that's something uh you know, everything from Levin marketing strategy to the community strategy to even just seating products in the market, That's a recipe that beam does really well. So yeah, it's a moving target for sure. >>Dave you were talking about the cliche of digital transformation and I'll say this may be pre Covid, I really felt like it was a cliche, there was a lot of, you know, complacency, I'll call it, but then the force marks the digital change that uh and now we kind of understand if you're not a digital business, you're in trouble. Uh And so my question is how it relates to some of the trends that we've been talking about in terms of cloud containers, We've seen the SAs ification for the better part of a decade now, but specifically as it relates to migration, it's hard for customers to just migrate their application portfolio to the cloud. Uh It's hard to fund it. It takes a long time. It's complex. Um how do you see that cloud migration evolving? Maybe that's where hybrid comes in And again, I'm interested in how you guys think about it and how it affects your strategy. >>Yeah. Well it's a complex answer as you might imagine because 400,000 customers, we take the exact same code. The exact same ice so that I run on my laptop is the exact same being backup and replication image that a major bank protects almost 20,000 machines and a petabytes of data. And so what that means is that you have to look at things on a case by case basis for some of us continuing to operate proprietary systems on prem might be the best choice for a certain workload. But for many of us the Genie is kind of out of the bottle with 2020 we have to move faster. It's less about safety and a lot more about speed and favorable outcome. We'll fix it if it's broken but let's get going. So for organizations struggling with how to move to the cloud, believe it or not, backup and recovery is an excellent way to start to venture into that because you can start to move data backup ISm data movement engine. So we can start to see data there where it makes sense. But rick would be quick to point out we want to offer a safe return. We have instances of where people want to repatriate data back and having a portable data format is key to that Rick. >>Uh yeah, I had a conversation recently with an organization managing cloud sprawl. They decided to consolidate, we're going to use this cloud, so it was removing a presence from one cloud that starts with an A and migrating it to the other cloud that starts with an A. You know, So yeah, we've seen that need for portability repatriation on prem classic example going from on prem apps to software as a service models for critical apps. So data mobility is at the heart of VM and with all the different platforms, kubernetes comes into play as well. It's definitely aligning to the needs that we're seeing in the market for sure. >>So repatriation, I want to stay on that for a second because you're, you're an arms dealer, you don't care if they're in the cloud or on prem and I don't know, maybe you make more money in one or the other, but you're gonna ride whatever waves the market gives you so repatriation to me implies. Or maybe I'm just inferring that somebody's moved to the cloud and they feel like, wow, we've made a mistake, it was too fast, too expensive. It didn't work for us. So now we're gonna bring it back on prem. Is that what you're saying? Are you saying they actually want their data in both both places. As another layer of data protection Danny. I wonder if you could address that. What are you seeing? >>Well, one of the interesting things that we saw recently, Dave Russell actually did the survey on this is that customers will actually build their work laid loads in the cloud with the intent to bring it back on premises. And so that repatriation is real customers actually don't just accidentally fall into it, but they intend to do it. And the thing about being everyone says, hey, we're disrupting the market, we're helping you go through this transformation, we're helping you go forward. Actually take a slightly different view of this. The team gives them the confidence that they can move forward if they want to, but if they don't like it, then they can move back and so we give them the stability through this incredible pace, change of innovation. We're moving forward so so quickly, but we give them the ability to move forward if they want then to recover to repatriate if that's what they need to do in a very effective way. And Dave maybe you can touch on that study because I know that you talked to a lot of customers who do repatriate workloads after moving them to the cloud. >>Yeah, it's kind of funny Dave not in the analyst business right now, but thanks to Danny and our chief marketing Officer, we've got now half a dozen different research surveys that have either just completed or in flight, including the largest in the data protection industry's history. And so the survey that Danny alluded to, what we're finding is people are learning as they're going and in some cases what they thought would happen when they went to the cloud they did not experience. So the net kind of funny slide that we discovered when we asked people, what did you like most about going to the cloud and then what did you like least about going to the cloud? The two lists look very similar. So in some cases people said, oh, it was more stable. In other cases people said no, it was actually unstable. So rick I would suggest that that really depends on the practice that you bring to it. It's like moving from a smaller house to a larger house and hoping that it won't be messy again. Well if you don't change your habits, it's eventually going to end up in the same situation. >>Well, there's still door number three and that's data reuse and analytics. And I found a lot of organizations love the idea of at least manipulating data, running test f scenarios on yesterday's production, cloud workload completely removed from the cloud or even just analytics. I need this file. You know, those types of scenarios are very easy to do today with them. And you know, sometimes those repatriations, those portable recoveries, Sometimes people do that intentionally, but sometimes they have to do it. You know, whether it's fire, flood and blood and you know, oh, I was looks like today we're moving to the cloud because I've lost my data center. Right. Those are scenarios that, that portable data format really allows organizations to do that pretty easily with being >>it's a good discussion because to me it's not repatriation, it has this negative connotation, the zero sum game and it's not Danny what you describe and rick as well. It was kind of an experimentation, a purposeful. We're going to do it in the cloud because we can and it's cheap and low risk to spin it up and then we're gonna move it because we've always thought we're going to have it on prem. So, so you know, there is some zero sum game between the cloud and on prem. Clearly no question about it. But there's also this rising tide lifts all ship. I want to, I want to change the subject to something that's super important and and top of mind it's in the press and it ain't going away and that is cyber and specifically ransomware. I mean, since the solar winds hack and it seems to me that was a new milestone in the capabilities and aggressiveness of the adversary who is very well funded and quite capable. And what we're seeing is this idea of tucking into the supply chain of islands, so called island hopping. You're seeing malware that's self forming and takes different signatures very stealthy. And the big trend that we've seen in the last six months or so is that the bad guys will will lurk and they'll steal all kinds of sensitive data. And then when you have an incident response, they will punish you for responding. And they will say, okay, fine, you want to do that. We're going to hold you ransom. We're gonna encrypt your data. And oh, by the way, we stole this list of positive covid test results with names from your website and we're gonna release it if you don't pay their. I mean, it's like, so you have to be stealthy in your incident response. And this is a huge problem. We're talking about trillions of dollars lost each year in, in in cybercrime. And so, uh, you know, it's again, it's this uh the bad news is good news for companies like you. But how do you help customers deal with this problem? What are you seeing Danny? Maybe you can chime in and others who have thoughts? >>Well we're certainly seeing the rise of cyber like crazy right now and we've had a focus on this for a while because if you think about the last line of defense for customers, especially with ransomware, it is having secure backups. So whether it be, you know, hardened Linux repositories, but making sure that you can store the data, have it offline, have it, have it encrypted immutable. Those are things that we've been focused on for a long while. It's more than that. Um it's detection and monitoring of the environment, which is um certainly that we do with our monitoring tools and then also the secure recovery. The last thing that you want to do of course is bring your backups or bring your data back online only to be hit again. And so we've had a number of capabilities across our portfolio to help in all of these. But I think what's interesting is where it's going, if you think about unleashing a world where we're continuously delivering, I look at things like containers where you have continues delivery and I think every time you run that helm commander, every time you run that terra form command, wouldn't that be a great time to do a backup to capture your data so that you don't have an issue once it goes into production. So I think we're going towards a world where security and the protection against these cyber threats is built into the supply chain rather than doing it on just a time based uh, schedule. And I know rick you're pretty involved on the cyber side as well. Would you agree with that? I >>would. And you know, for organizations that are concerned about ransomware, you know, this is something that is taken very seriously and what Danny explained for those who are familiar with security, he kind of jumped around this, this universally acceptable framework in this cybersecurity framework there, our five functions that are a really good recipe on how you can go about this. And and my advice to IT professionals and decision makers across the board is to really align everything you do to that framework. Backup is a part of it. The security monitoring and user training. All those other things are are areas that that need to really follow that wheel of functions. And my little tip here and this is where I think we can introduce some differentiation is around detection and response. A lot of people think of backup product would shine in both protection and recovery, which it does being does, but especially on response and detection, you know, we have a lot of capabilities that become impact opportunities for organizations to be able to really provide successful outcomes through the other functions. So it's something we've worked on a lot. In fact we've covered here at the event. I'm pretty sure it will be on replay the updated white paper. All those other resources for different levels can definitely guide them through. >>So we follow up to the detection is what analytics that help you identify whatever lateral movement or people go in places they shouldn't go. I mean the hard part is is you know, the bad guys are living off the land, meaning they're using your own tooling to to hack you. So they're not it's not like they're introducing something new that shouldn't be there. They're they're just using making judo moves against you. So so specifically talk a little bit more about your your detection because that's critical. >>Sure. So I'll give you one example imagine we capture some data in the form of a backup. Now we have an existing advice that says, you know what Don't put your backup infrastructure with internet connectivity. Use explicit minimal permissions. And those three things right there and keep it up to date. Those four things right there will really hedge off a lot of the different threat vectors to the back of data, couple that with some of the mutability offline or air gapped capabilities that Danny mentioned and you have an additional level of resiliency that can really ensure that you can drive recovery from an analytic standpoint. We have an api that allows organizations to look into the backup data. Do more aggressive scanning without any exclusions with different tools on a flat file system. You know, the threats can't jump around in memory couple that with secure restore. When you reintroduce things into the environment From a recovery standpoint, you don't want to reintroduce threats. So there's protections, there's there's confidence building steps along the way with them and these are all generally available technologies. So again, I got this white paper, I think we're up to 50 pages now, but it's a very thorough that goes through a couple of those scenarios. But you know, it gets the uh, it gets quickly into things that you wouldn't expect from a backup product. >>Please send me a copy if you, if you don't mind. I this is a huge problem and you guys are global company. I admittedly have a bit of a US bias, but I was interviewing robert Gates one time the former defense secretary and we're talking about cyber war and I said, don't we have the best cyber, can't we let go on the offense? He goes, yeah, we can, but we got the most to lose. So this is really a huge problem for organizations. All right, guys, last question I gotta ask you. So what's life like under, under inside capital of the private equity? What's changed? What's, what's the same? Uh, do you hear from our good friend ratner at all? Give us the update there. >>Yes. Oh, absolutely fantastic. You know, it's interesting. So obviously acquired by insight partners in February of 2020, right, when the pandemic was hitting, but they essentially said light the fuse, keep the engine's going. And we've certainly been doing that. They haven't held us back. We've been hiring like crazy. We're up to, I don't know what the count is now, I think 4600 employees, but um, you know, people think of private equity and they think of cost optimizations and, and optimizing the business, That's not the case here. This is a growth opportunity and it's a growth opportunity simply because of the technology opportunity in front of us to keep, keep the engine's going. So we hear from right near, you know, on and off. But the new executive team at VM is very passionate about driving the success in the industry, keeping abreast of all the technology changes. It's been fantastic. Nothing but good things to say. >>Yes, insight inside partners, their players, we watched them watch their moves and so it's, you know, I heard Bill McDermott, the ceo of service now the other day talking about he called himself the rule of 60 where, you know, I always thought it was even plus growth, you know, add that up. And that's what he was talking about free cash flow. He's sort of changing the definition a little bit but but so what are you guys optimizing for you optimizing for growth? Are you optimising for Alberta? You optimizing for free cash flow? I mean you can't do All three. Right. What how do you think about that? >>Well, we're definitely optimizing for growth. No question. And one of the things that we've actually done in the past 12 months, 18 months is beginning to focus on annual recurring revenue. You see this in our statements, I know we're not public but we talk about the growth in A. R. R. So we're certainly focused on that growth in the annual recovering revenue and that that's really what we tracked too. And it aligns well with the cloud. If you look at the areas where we're investing in cloud native and the cloud and SAAS applications, it's very clear that that recurring revenue model is beneficial. Now We've been lucky, I think we're 13 straight quarters of double-digit growth. And and obviously they don't want to see that dip. They want to see that that growth continue. But we are optimizing on the growth trajectory. >>Okay. And you see you clearly have a 25% growth last quarter in A. R. R. Uh If I recall correctly, the number was evaluation was $5 billion last january. So obviously then, given that strategy, Dave Russell, that says that your tam is a lot bigger than just the traditional backup world. So how do you think about tam? I'll we'll close there >>and uh yeah, I think you look at a couple of different ways. So just in the backup recovery space or backup in replication to paying which one you want to use? You've got a large market there in excess of $8 billion $1 billion dollar ongoing enterprise. Now, if you look at recent i. D. C. Numbers, we grew and I got my handy HP calculator. I like to make sure I got this right. We grew 44.88 times faster than the market average year over year. So let's call that 45 times faster and backup. There's billions more to be made in traditional backup and recovery. However, go back to what we've been talking around digital transformation Danny talking about containers in the environment, deployment models, changing at the heart of backup and recovery where a data capture data management, data movement engine. We envision being able to do that not only for availability but to be able to drive the business board to be able to drive economies of scale faster for our organizations that we serve. I think the trick is continuing to do more of the same Danny mentioned, he knows the view's got lit. We haven't stopped doing anything. In fact, Danny, I think we're doing like 10 times more of everything that we used to be doing prior to the pandemic. >>All right, Danny will give you the last word, bring it home. >>So our goal has always been to be the most trusted provider of backup solutions that deliver modern data protection. And I think folks have seen at demon this year that we're very focused on that modern data protection. Yes, we want to be the best in the data center but we also want to be the best in the next generation, the next generation of I. T. So whether it be sas whether it be cloud VM is very committed to making sure that our customers have the confidence that they need to move forward through this digital transformation era. >>Guys, I miss flying. I mean, I don't miss flying, but I miss hanging with you all. We'll see you. Uh, for sure. Vim on 2022 will be belly to belly, but thanks so much for coming on the the virtual edition and thanks for having us. >>Thank you. >>All right. And thank you for watching everybody. This keeps continuous coverage of the mon 21. The virtual edition. Keep it right there for more great coverage. >>Mm

>>Okay. Okay. Now we're gonna go into the Green Lake Power Panel. Talk about the cloud landscape hybrid cloud and how the partner ecosystem and customers are thinking about cloud hybrid cloud as a service and, of course, Green Lake. And with me or CR Houdyshell, president of Advise X. Ron Nemecek, Who's the business Alliance manager at C B. T s. Harry Zaric is president of competition, and Benjamin Clay is VP of sales and alliances at Arrow Electronics. Great to see you guys. Thanks so much for coming on the Cube. >>Thanks for having us >>would be here. >>Okay, here's the deal. So I'm gonna ask you guys each to introduce yourselves and your company's add a little color to my brief intro and then answer the following question. How do you and your customers think about hybrid cloud and think about it in the context of where we are today and where we're going? Not just the snapshot, but where we are today and where we're going. CR, why don't you start, please? >>Sure. Thanks a lot. They appreciate it. And, uh, again cr Howdy Shell President of advising. I've been with the company for 18 years the last four years as president. So had the great great opportunity here to lead a 45 year old company with a very strong brand and great culture. Uh, as it relates to advise X and where we're headed to with hybrid Cloud is it's a journey, so we're excited to be leading that journey for the company as well as HP. We're very excited about where HP is going with Green Lake. We believe it's it's a very strong solution when it comes to hybrid. Cloud have been an HP partner since since 1980. So for 40 years it's our longest standing OM relationship, and we're really excited about where HP is going with Green Lake from a hybrid cloud perspective. Uh, we feel like we've been doing the hybrid cloud solutions in the past few years with everything that we've focused on from a VM Ware perspective. But now, with where HP is going, we think really changing the game and it really comes down to giving customers at cloud experience with the on Prem solution with Green Lake, and we've had great response from our customers and we think we're gonna continue to see how that kind of increased activity and reception. >>Great. Thank you. Cr and yeah, I totally agree. It is. It is a journey. And we've seen it really come a long way in the last decade. Ron, I wonder if you could kick off your little first intro there, please? >>Sure. Dave, thanks for having me today. And it's a pleasure being here with all of you. My name is Ron Nemecek, business Alliance manager at C B. T. S. In my role, I am responsible for RHP Green Lake relationship globally. I've enjoyed a 33 year career in the I T industry. I'm thankful for the opportunity to serve in multiple functional and senior leadership roles that have helped me gather a great deal of education and experience that could be used to aid our customers with their evolving needs for business outcomes. The best position them for sustainable and long term success. I'm honored to be part of the C B. T s and Annex Canada Organization, C B T s stands for consult Bill transform and support. We have a 35 year relationship with HP or a platinum and inner circle partner. We're headquartered in Cincinnati Ohio. We service 3000 customers, generating over a billion dollars in revenue, and we have over 2000 associates across the globe. Our focus is partnering with our customers to deliver innovative solutions and business results through thought leadership. We drive this innovation VR team of the best and brightest technology professionals in the industry that have secured over 2800 technical certifications 260 specifically with HP and in our hybrid cloud business. We have clearly found the technology new market demands for instant responses and experiences evolving economic considerations with detailed financial evaluation and, of course, the global pandemic have challenged each of our customers across all industries to develop an optimal cloud strategy we have. We now play an enhanced strategic role for our customers as there Technology Advisor and their guide to the right mix of cloud experiences that will maximize their organizational success with predictable outcomes. Our conversations have really moved from product roadmaps and speeds and feeds to return on investment, return on capital and financial statements, ratios and metrics. We collaborate regularly with our customers at all levels and all departments to find an effective, comprehensive cloud strategy for their workloads and applications, ensuring proper alignment and costs with financial return. >>Great. Thank you, Ron. Yeah, Today it's all about the business value. Harry, please, >>I Dave. Thanks for the opportunity and greetings from the Great White North, where Canadian based company headquartered in Toronto, with offices across the country. We've been in the tech industry for a very long time. What we would call a solution provider hard for my mother to understand what that means. But our goal is to help our customers realize the business value of their technology investments just to give you an example of what it is we try and do. We just finished a build out of a new networking and point in data center technology for a brand new hospital is now being mobilized for covid high risk patients. So talk about are all being an essential industry, providing essential services across the whole spectrum of technology. Now, in terms of what's happening in the marketplace, our customers are confused. No question about it. They hear about cloud and cloud first, and everyone goes to the cloud. But the reality is there's lots of technology, lots of applications that actually still have to run on premises for a whole bunch of reasons. And what customers want is solid senior serious advice as to how they leverage what they already have in terms of their existing infrastructure but modernized and updated So it looks and feels a lot like a cloud. But they have the security. They have the protection that they need to have for reasons that are dependent on their industry and business to allow them to run on from. And so the Green Lake philosophy is perfect. That allows customers to actually have 1 ft in the cloud, 1 ft in their traditional data center, but modernize it so it actually looks like one enterprise entity. And it's that kind of flexibility that gives us an opportunity collectively, ourselves, our partners, HP to really demonstrate that we understand how to optimize the use of technology across all of the business applications they need to rest >>your hair. It's interesting about what you said is is cloud is it is kind of chaotic. My word not yours, but but there is a lot of confusion out there. I mean, it's what's cloud right? Is it Public Cloud is a private cloud the hybrid cloud. Now, now it's the edge. And of course, the answer is all of the above. Ben, what's your perspective on all this? >>Um, from a cloud perspective. You know, I think as an industry, you know, I think we we've all accepted that public cloud is not necessarily gonna win the day and were, in fact, in a hybrid world, there's certainly been some some commentary impress. Um, you know, that would sort of validate that. Not that necessarily needs any validation. But I think it's the linkages between on Prem, Um, and cloud based services have increased. Its paved the way for customers to more effectively deploy hybrid solutions in the model that they want that they desired. You know, Harry was commenting on that a moment ago. Um, you know, as the trend continues, it becomes much easier for solution providers and service providers to drive there services, initiatives, uh, you know, in particular managed services. So, you know, from from an arrow perspective, as we think about how we can help scale in particular from Greenland perspective, we've got the ability to stand up some some cloud capabilities through our aero secure platform. um that can really help customers adopt Green Lake. Uh, and, uh, benefit to benefit from, um, some alliances, opportunities as well. And I'll talk more about that as we go through >>that. I didn't mean to squeeze you on a narrow. I mean, you got arrows. Been around longer than computers. I mean, if you google the history of arrow, it'll blow your mind. But give us a little, uh, quick commercial. >>Yeah, absolutely. So, um, I've been with arrow for about 20 years. I've got responsibility for alliances, organization, North America for Global value, added distribution, business consulting and channel enablement Company. Uh, you know, we bring scope, scale and and, uh, expertise as it relates to the I t industry. Um, you know, I love the fast paced, the fast paced that comes with the market, that we're all all in, and I love helping customers and suppliers both, you know, be positioned for long term success. And, you know, the subject matter here today is just a great example of that. So I'm happy to be here and or to the discussion. >>All right, We got some good brain power in the room. Let's let's cut right to the chase. Ron, Where's the pain? What are the main problems that C B. T s. I love the what it stands for. Consult Bill Transform and support the What's the main pain point that that customers are asking you to solve when it comes to their cloud strategies. >>Third day of our customers' concerns and associated risk come from the market demands to deliver their products, services and experiences instantaneously. And then the challenges is how do they meet those demands because they have aging infrastructure processes and fiscal constraints. Our customers really need us now more than ever to be excellent listeners so we can collaborate on an effective map for the strategic placement of workloads and applications in that spectrum of cloud experiences, while managing their costs and, of course, mitigating risk to their business. This collaboration with our customer customers often identify significant costs that have to be evaluated, justified or eliminated. We find significant development, migration and egress charges in their current public cloud experience, coupled with significant over provisioning, maintenance, operational and stranded asset costs in their on premise infrastructure environment. When we look at all these costs holistically through our customized workshops and assessments. We can identify the optimal cloud experience for the respective workloads and applications through our partnership with HP and the availability of the HP Green Lake Solutions. Our customers now have a choice to deliver SLA's economics and business outcomes for their workloads and applications that best reside on premise in a private cloud and have that experience. This is a rock solid solution that eliminates, you know, the development costs at the experience and the egress charges that are associated with the public cloud while utilizing HP Green Lake to eliminate over provisioning costs and the maintenance costs on aging infrastructure hardware. Lastly, our customers only have to pay for actual infrastructure usage with no upfront capital expense. And now that achieves true utilization to cost economics. You know, with HP Green Lake solution from C B. T s. >>I love to focus on the business case because it's measurable. That sort of follow the money. That's where it's where the opportunity is. Okay, See, I got a question for you thinking about advise X customers. How are they? Are they leaning into Green Lake? You know, what are they telling you? Is the business impact when they when they experience Green Lake, >>I think it goes back to what Ron was talking about. We have to solve the business challenges first, and so far the reception's been positive. When I say that is, customers are open, everybody wants to. The C suite wants to hear about cloud and hybrid cloud fits, but what we're hearing, what we're seeing from our customers is we're seeing more adoption from customers that it may be their first put in, if you will. But as importantly, we're able to share other customers with our potentially new clients that that say, What's the first thing that happens with regard to Green like Well, number one, it works. It works as advertised and as a as a service. That's a big step. There are a lot of people out there dabbling today, but when you can say we have a proven solution, it's working in in in our environment today. That's key. I think the second thing is is flexibility. You know, when customers are looking for this, this hybrid solution, you've got to be flexible for again. I think Ron said it well, you don't have a big capital outlay but also what customers want to be able to. We're gonna build for growth, but we don't want to pay for it, so we'll pay as we grow. Not as not as we have to use because we used to do It was upfront of the capital expenditure, and I will just pay as we grow and that really facilitates. In another great examples, you'll hear from a customer, uh, this afternoon, but you'll hear where one of the biggest benefits they just acquired a $570 million company, and their integration is going to be very seamless because of their investment in Green Lake. They're looking at the flexibility to add the Green Lake as a big opportunity to integrate for acquisitions and finally is really we see it really brings the cloud experience and as a service to our customers bring. And with HP Green Lake, it brings best to breathe. So it's not just what HP has to offer. When you look at hyper converged, they have Nutanix kohi city, so I really believe it brings best to breathe. So, uh to net it out and close it out with our customers thus far, the customer experience has been exceptional with Green Lake Central has interface. Customers have had a lot of success. We just had our first customer from about a year and a half ago, just re up, and it was a highly competitive situation. But they just said, Look, it's proven it works and it gives us that cloud experience So I had a lot of great success thus far, looking forward to more. >>Thank you. So, Harry, I want to pick up on something, CR said, And get your perspectives. So when you when I talk to the C suite, they do all want to hear about, you know, Cloud, they have a cloud agenda and and what they tell me is it's not just about their I t transformation. They want, they want that. But they also want to transform their business. So I wonder if you could talk Harry about competence, perspective on the potential business impact of Green Lake, and and also, you know, I'm interested in how you guys are thinking about workloads, how to manage work, you know how to cost optimize in i t. But also the business value that comes out of that capability. >>Yes. So, Dave, you know, if you were to talk to CFO and I have the good fortune to talk to lots of CFOs, they want to pay the cost. When they generate the revenue, they don't want to have all the cost up front and then wait for the revenue to come through. A good example of where that's happening right now is related to the pandemic. Employees that used to work at the office have now moved to working from home, and now they have to. They have to connect remotely to run the same application. So use this thing called VD virtual interfacing to allow them to connect to the applications that they need to run in the off. Don't want to get into too much detail. But to be able to support that from an at home environment, they needed to buy a lot more computing capacity to handle this. Now there's an expectation that hopefully six months from now, maybe sooner than that people will start returning to the office. They may not need that capacity so they can turn down on the cost. And so the idea of having the capacity available when you need it, But then turning it off when you don't need it is really a benefit of a variable cost model. Another example that I would use is one in new development if a customer is going to implement and you, let's say, line of business application essay P is very, very popular, you know, it actually, unfortunately takes six months to two years to actually get that application setup installed, validated, test it and then moves through production. You know what used to happen before they would buy all that capacity at front and basically sit there for two years? And then when they finally went to full production, then they were really getting value out of that investment. But they actually lost a couple of years of technology, literally sitting almost idle. And so, from a CFO perspective, his ability to support the development of those applications as he scales it perfect Green Lake is the ideal solution that allows them to do that. >>You know, technology has saved businesses in this pandemic. There's no question about it and what Harry was just talking about with regard to VD. You think about that. There's the dialing up and dialing down piece, which is awesome from an i t perspective and then the business impact. There is the productivity of Of of the end users, and most C suite executives I've talked to said Productivity actually went up during covid with work from home, which is kind of astounding if you think about it. Ben, you know Ben, I We said Arrow has been around for a long, long time, certainly before all of us were born and it's gone through many, many industry transitions during our lifetimes. How does arrow and how do How do your partners think about building cloud experience experiences? And where does Green Lake fit in from your perspective? >>A great question. So from a narrow perspective, when you think about cloud experience and, of course, us taking a view as a distribution partner, we want to be able to provide scale and efficiency to our network of partners. So we do that through our aero screw platform. Um, just just a bit of a you know, a bit of a commercial. I mean, you get single quote single bill auto provision compared multi supplier, if you will Subscription management utilization reporting from the platform itself. So if we pivot that directly to HP, you're going to get a bit of a scoop here, Dave. So we're excited today to have Green Lake live in our platform available for our part of community to consume in particular the swift solutions that HP has announced. So we're very excited to to share that today, Um, maybe a little bit more on Green Lake. I think at this point in time, there it's differentiated, Um, in a sense that if you think about some of the other offerings in the market today and further with, um uh, having the solutions himself available in a row sphere So, you know, I would say, Do we identify the uniqueness, um, and quickly partner with HP to to work with our atmosphere platform? One other sort of unique thing is, you know, when you think about platform itself, you've got to give a consistent experience the different geographies around the world. So, you know, we're available in north of 20 countries. There's thousands of resellers and transacting on the platform on a regular basis, and frankly, hundreds of thousands and customers are leveraging today, so that creates an opportunity for both Arrow HP and our partner community. So we're excited. >>Uh, you know, I just want to open it up and we don't have much time left, but thoughts on on on differentiation. You know, when people ask me Okay, what's really different about H P E and Green Lake? As others you know are doing things that with with as a service to me, it's a I I always say cultural. It starts from the top with Antonio, and it's like the company's all in. But But I wonder from your perspective because you guys are hands on. Are there other differential factors that you would point to let me just open that up to the group? >>Yeah, if I could make a comment. You know, Green Lake is really just the latest invocation of the as a service model. And what does that mean? What that actually means is you have a continuous ongoing relationship with the customer. It's not a cell. And forget not that we ever forget about customers, but there are highlights. Customer buys, it gets installed, and then for two or three years, you may have an occasional engagement with them. But it's not continuous. When you move to a Green Lake model, you're actually helping them manage that you are in the core in the heart of their business. No better place to be if you want to be sticky and you want to be relevant, and you want to be always there for them. >>You know, I wonder if somebody else could add to and and and in your in your remarks from your perspective as a partner because, you know, Hey, a lot of people made a lot of money selling boxes, but those days are pretty much gone. I mean, you have to transform into a services mindset. But other thoughts, >>I think I think Dad did that day. I think Harry's right on right. What he the way he positioned Exactly. You get on the customer. Even another step back for us is we're able to have the business conversation without leading with what you just said. You don't have to leave with a storage solution to leave with a compute. You can really have step back, have a business conversation, and we've done that where you don't even bring up hp Green Lake until you get to the point of the customer says, So you can give me an on prem cloud solution that gives me scalability, flexibility, all the things you're talking about. How does that work then? Then you bring up. It's all through this HP Green link tool. It really gives you the ability to have a business conversation. And you're solving the business problems versus trying to have a technology conversation. And to me, that's clear differentiation for HP. Green length. >>All right, guys. CR Ron. Harry. Ben. Great discussion. Thank you so much for coming on the program. Really appreciate it. >>Thanks for having us, Dave. >>All >>right. Keep it right there for more great content at Green Lake Day. Right back? Yeah.

>>Yeah, yeah. Welcome back to the third session in our building, A vibrant data ecosystem track. This session is unleash the power of your cloud data warehouse. So what comes after you've moved your data to the cloud in this session will explore White Enterprise Analytics is finally ready for the cloud, and we'll discuss how you can consume Enterprise Analytics in the very same way he would cloud services. We'll also explore where analytics meets cloud and see firsthand how thought spot is open for everyone. Let's get going. I'm happy to say we'll be hearing from two folks from thought spot today, Michael said Cassie, VP of strategic partnerships, and Vika Valentina, senior product marketing manager. And I'm very excited to welcome from our partner at AWS Gal Bar MIA, product engineering manager with Red Shift. We'll also be sharing a live demo of thought spot for BTC Marketing Analytics directly on Red Shift data. Gal, please kick us off. >>Thank you, Military. And thanks. The talks about team and everyone attending today for joining us. When we talk about data driven organizations, we hear that 85% of businesses want to be data driven. However, on Lee. 37% have been successful in We ask ourselves, Why is that and believe it or not, Ah, lot of customers tell us that they struggled with live in defining what being data driven it even means, and in particular aligning that definition between the business and the technology stakeholders. Let's talk a little bit. Let's look at our own definition. A data driven organization is an organization that harnesses data is an asset. The drive sustained innovation and create actionable insights. The super charge, the experience of their customers so they demand more. Let's focus on a few things here. One is data is an asset. Data is very much like a product needs to evolve sustained innovation. It's not just innovation innovation, it's sustained. We need to continuously innovate when it comes to data actionable insights. It's not just interesting insights these air actionable that the business can take and act upon, and obviously the actual experience we. Whether whether the customers are internal or external, we want them to request Mawr insights and as such, drive mawr innovation, and we call this the for the flywheel. We use the flywheel metaphor here where we created that data set. Okay, Our first product. Any focused on a specific use case? We build an initial NDP around that we provided with that with our customers, internal or external. They provide feedback, the request, more features. They want mawr insights that enables us to learn bringing more data and reach that actual data. And again we create MAWR insights. And as the flywheel spins faster, we improve on operational efficiencies, supporting greater data richness, and we reduce the cost of experimentation and legacy environments were never built for this kind of agility. In many cases, customers have struggled to keep momentum in their fleet, flywheel in particular around operational efficiency and experimentation. This is where Richie fits in and helps customer make the transition to a true data driven organization. Red Shift is the most widely used data warehouse with tens of thousands of customers. It allows you to analyze all your data. It is the only cloud data warehouse that sits, allows you to analyze data that sits in your data lake on Amazon, a street with no loading duplication or CTL required. It is also allows you to scale with the business with its hybrid architectures it also accelerates performance. It's a shared storage that provides the ability to scale toe unlimited concurrency. While the UN instant storage provides low late and say access to data it also provides three. Key asks that customers consistently tell us that matter the most when it comes to cost. One is usage based pricing Instead of license based pricing. Great value as you scale your data warehouse using, for example, reserved instances they can save up to 75% compared to on the mind demand prices. And as your data grows, infrequently accessed data can be stored. Cost effectively in S three encouraged through Amazon spectrum, and the third aspect is predictable. Month to month spend with no hitting charges and surprises. Unlike and unlike other cloud data warehouses, where you need premium versions for additional enterprise capabilities. Wretched spicing include building security compression and data transfer. >>Great Thanks. Scout um, eso. As you can see, everybody wins with the cloud data warehouses. Um, there's this evolution of movement of users and data and organizations to get value with these cloud data warehouses. And the key is the data has to be accessible by the users, and this data and the ability to make business decisions on the data. It ranges from users on the front line all the way up to the boardroom. So while we've seen this evolution to the Cloud Data Warehouse, as you can see from the statistic from Forrester, we're still struggling with how much of that data actually gets used for analytics. And so what is holding us back? One of the main reasons is old technology really trying to work with today's modern cloud data warehouses? They weren't built for it. So you run into issues of trying to do data replication, getting the data out of the cloud data warehouse. You can do analysis and then maintaining these middle layers of data so that you can access it quickly and get the answers you need. Another issue that's holding us back is this idea that you have to have your data in perfect shape with the perfect pipeline based on the exact dashboard unique. Um, this isn't true. Now, with Cloud data warehouse and the speed of important business data getting into those cloud data warehouses, you need a solution that allows you to access it right away without having everything to be perfect from the start, and I think this is a great opportunity for GAL and I have a little further discussion on what we're seeing in the marketplace. Um, one of the primary ones is like, What are the limiting factors, your Siegel of legacy technologies in the market when it comes to this cloud transformation we're talking about >>here? It's a great question, Michael and the variety of aspect when it comes to legacy, the other warehouses that are slowing down innovation for companies and businesses. I'll focus on 21 is performance right? We want faster insights. Companies want the ability to analyze MAWR data faster. And when it comes to on prem or legacy data warehouses, that's hard to achieve because the second aspect comes into display, which is the lack of flexibility, right. If you want to increase your capacity of your warehouse, you need to ensure request someone needs to go and bring an actual machine and install it and expand your data warehouse. When it comes to the cloud, it's literally a click of a button, which allows you to increase the capacity of your data warehouse and enable your internal and external users to perform analytics at scale and much faster. >>It falls right into the explanation you provided there, right as the speed of the data warehouses and the data gets faster and faster as it scales, older solutions aren't built toe leverage that, um, you know, they're either they're having to make technical, you know, technical cuts there, either looking at smaller amounts of data so that they can get to the data quicker. Um, or it's taking longer to get to the data when the data warehouse is ready, when it could just be live career to get the answers you need. And that's definitely an issue that we're seeing in the marketplace. I think the other one that you're looking at is things like governance, lineage, regulatory requirements. How is the cloud you know, making it easier? >>That's That's again an area where I think the cloud shines. Because AWS AWS scale allows significantly more investment in securing security policies and compliance, it allows customers. So, for example, Amazon redshift comes by default with suck 1 to 3 p. C. I. Aiso fared rampant HIPPA compliance, all of them out of the box and at our scale. We have the capacity to implement those by default for all of our customers and allow them to focus. Their very expensive, valuable ICTY resource is on actual applications that differentiate their business and transform the customer experience. >>That's a great point, gal. So we've talked about the, you know, limiting factors. Technology wise, we've mentioned things like governance. But what about the cultural aspect? Right? So what do you see? What do you see in team struggling in meeting? You know, their cloud data warehouse strategy today. >>And and that's true. One of the biggest challenges for large large organizations when they moved to the cloud is not about the technology. It's about people, process and culture, and we see differences between organizations that talk about moving to the cloud and ones that actually do it. And first of all, you wanna have senior leadership, drive and be aligned and committed to making the move to the cloud. But it's not just that you want. We see organizations sometimes Carol get paralyzed. If they can't figure out how to move each and every last work clothes, there's no need to boil the ocean, so we often work with organizations to find that iterative motion that relative process off identifying the use cases are date identifying workloads in migrating them one at a time and and through that allowed organization to grow its knowledge from a cloud perspective as well as adopt its tooling and learn about the new capabilities. >>And from an analytics perspective, we see the same right. You don't need a pixel perfect dashboard every single time to get value from your data. You don't need to wait until the data warehouse is perfect or the pipeline to the data warehouse is perfect. With today's technology, you should be able to look at the data in your cloud data warehouse immediately and get value from it. And that's the you know, that's that change that we're pushing and starting to see today. Thanks. God, that was That was really interesting. Um, you know, as we look through that, you know, this transformation we're seeing in analytics, um, isn't really that old? 20 years ago, data warehouses were primarily on Prem and the applications the B I tools used for analytics around them were on premise well, and so you saw things like applications like Salesforce. That live in the cloud. You start having to pull data from the cloud on Prem in order to do analytics with it. Um, you know, then we saw the shift about 10 years ago in the explosion of Cloud Data Warehouse Because of their scale, cost reduced, reduce shin reduction and speed. You know, we're seeing cloud data. Warehouses like Amazon Red Shift really take place, take hold of the marketplace and are the predominant ways of storing data moving forward. What we haven't seen is the B I tools catch up. And so when you have this new cloud data warehouse technology, you really need tools that were custom built for it to take advantage of it, to be able to query the cloud data warehouse directly and get results very quickly without having to worry about creating, you know, a middle layer of data or pipelines in order to manage it. And, you know, one company captures that really Well, um, chick fil A. I'm sure everybody has heard of is one of the largest food chains in America. And, you know, they made a huge investment in red shift and one of the purposes of that investment is they wanted to get access to the data mawr quickly, and they really wanted to give their business users, um, the ability to do some ad hoc analysis on the data that they were capturing. They found that with their older tools, the problems that they were finding was that all the data when they're trying to do this analysis was staying at the analyst level. So somebody needed to create a dashboard in order to share that data with a user. And if the user's requirements changed, the analysts were starting to become burdened with requests for changes and the time it took to reflect those changes. So they wanted to move to fought spot with embrace to connect to Red Shift so they could start giving business users that capability. Query the database right away. And with this, um, they were able to find, you know, very common things in in the supply chain analysis around the ability to figure out what store should get, what product that was selling better. The other part was they didn't have to wait for the data to get settled into some sort of repository or second level database. They were able to query it quickly. And then with that, they're able to make changes right in the red shift database that were then reflected to customers and the business users right away. So what they found from this is by adopting thought spot, they were actually able to arm business users with the ability to make decisions very quickly. And they cleared up the backlog that they were having and the delay with their analysts. And they're also putting their analysts toe work on different projects where they could get better value from. So when you look at the way we work with a cloud data warehouse, um, you have to think of thoughts about embrace as the tool that access that layer. The perfect analytic partner for the Cloud Data Warehouse. We will do the live query for the business user. You don't need to know how to script and sequel, um Thio access, you know, red shift. You can type the question that you want the answer to and thought spot will take care of that query. We will do the indexing so that the results come back faster for you and we will also do the analysis on. This is one of the things I wanted to cover, which is our spot i. Q. This is new for our ability to use this with embrace and our partners at Red Shift is now. We can give you the ability to do auto analysis to look at things like leading indicators, trends and anomalies. So to put this in perspective amount imagine somebody was doing forecasting for you know Q three in the western region. And they looked at how their stores were doing. And they saw that, you know, one store was performing well, Spot like, you might be able to look at that analysis and see if there's a leading product that is underperforming based on perhaps the last few quarters of data. And bring that up to the business user for analysis right away. They don't need to have to figure that out. And, um, you know, slice and dice to find that issue on their own. And then finally, all the work you do in data management and governance in your cloud data warehouse gets reflected in the results in embrace right away. So I've done a lot of talking about embrace, and I could do more, but I think it would be far better toe. Have Vika actually show you how the product works, Vika. >>Thanks, Michael. We learned a lot today about the power of leveraging your red shift data and thought spot. But now let me show you how it works. The coronavirus pandemic has presented extraordinary challenges for many businesses, and some industries have fared better than others. One industry that seems to weather the storm pretty well actually is streaming media. So companies like Netflix and who Lou. And in this demo, we're going to be looking at data from B to C marketing efforts. First streaming media company in 2020 lately, we've been running campaigns for comedy, drama, kids and family and reality content. Each of our campaigns last four weeks, and they're staggered on a weekly basis. Therefore, we always have four campaigns running, and we can focus on one campaign launch per >>week, >>and today we'll be digging into how our campaigns are performing. We'll be looking at things like impressions, conversions and users demographic data. So let's go ahead and look at that data. We'll see what we can learn from what's happened this year so far, and how we can apply those learnings to future decision making. As you can already see on the thoughts about homepage, I've created a few pin boards that I use for reporting purposes. The homepage also includes what others on my team and I have been looking at most recently. Now, before we dive into a search, will first take a look at how to make a direct connection to the customer database and red shift to save time. I've already pre built the connection Red Shift, but I'll show you how easy it is to make that connection in just three steps. So first we give the connection name and we select our connection type and was on red Shift. Then we enter our red shift credentials, and finally, we select the tables that we want to use Great now ready to start searching. So let's start in this data to get a better idea of how our marketing efforts have been affected either positively or negatively by this really challenging situation. When we think of ad based online marketing campaigns, we think of impressions, clicks and conversions. Let's >>look at those >>on a daily basis for our purposes. So all this data is available to us in Thought spot, and we can easily you search to create a nice line chart like this that shows US trends over the last few months and based on experience. We understand that we're going to have more clicks than impressions and more impressions and conversions. If we started the chart for a minute, we could see that while impressions appear to be pretty steady over the course of the year, clicks and especially conversions both get a nice boost in mid to late March, right around the time that pandemic related policies were being implemented. So right off the bat, we found something interesting, and we can come back to this now. There are few metrics that we're gonna focus on as we analyze our marketing data. Our overall goal is obviously to drive conversions, meaning that we bring new users into our streaming service. And in order to get a visitor to sign up in the first place, we need them to get into our sign up page. A compelling campaign is going to generate clicks, so if someone is interested in our ad, they're more likely to click on it, so we'll search for Click through Rape 5% and we'll look this up by campaign name. Now even compare all the campaigns that we've launched this year to see which have been most effective and bring visitors star site. And I mentioned earlier that we have four different types of campaign content, each one aligned with one of our most popular genres. So by adding campaign content, yeah, >>and I >>just want to see the top 10. I could limit my church. Just these top 10 campaigns automatically sorted by click through rate and assigned a color for each category so we could see right away that comedy and drama each of three of the top 10 campaigns by click through rate reality is, too, including the top spot and kids and family makes one appearance as well. Without spot. We know that any non technical user can ask a question and get an answer. They can explore the answer and ask another question. When you get an answer that you want to share, keep an eye on moving forward, you pin the answer to pin board. So the BBC Marketing Campaign Statistics PIN board gives us a solid overview of our campaign related activities and metrics throughout 2020. The visuals here keep us up to date on click through rate and cost per click, but also another really important metrics that conversions or cost proposition. Now it's important to our business that we evaluate the effectiveness of our spending. Let's do another search. We're going to look at how many new customers were getting so conversions and the price cost per acquisition that we're spending to get each of these by the campaign contact category. So >>this is a >>really telling chart. We can basically see how much each new users costing us, based on the content that they see prior to signing up to the service. Drama and reality users are actually relatively expensive compared to those who joined based on comedy and kids and family content that they saw. And if all the genres kids and family is actually giving us the best bang for our marketing >>buck. >>And that's good news because the genres providing the best value are also providing the most customers. We mentioned earlier that we actually saw a sizable uptick in conversions as stay at home policies were implemented across much of the country. So we're gonna remove cost per acquisition, and we're gonna take a daily look how our campaign content has trended over the years so far. Eso By doing this now, we can see a comparison of the different genres daily. Some campaigns have been more successful than others. Obviously, for example, kids and family contact has always fared pretty well Azaz comedy. But as we moved into the stay at home area of the line chart, we really saw these two genres begin to separate from the rest. And even here in June, as some states started to reopen, we're seeing that they're still trending up, and we're also seeing reality start to catch up around that time. And while the first pin board that we looked at included all sorts of campaign metrics, this is another PIN board that we've created so solely to focus on conversions. So not only can we see which campaigns drug significant conversions, we could also dig into the demographics of new users, like which campaigns and what content brought users from different parts of the country or from different age groups. And all this is just a quick search away without spot search directly on a red shift. Data Mhm. All right, Thank you. And back to you, Michael. >>Great. Thanks, Vika. That was excellent. Um, so as you can see, you can very quickly go from zero to search with thought Spot, um, connected to any cloud data warehouse. And I think it's important to understand that we mentioned it before. Not everything has to be perfect. In your doubt, in your cloud data warehouse, um, you can use thought spot as your initial for your initial tool. It's for investigatory purposes, A Z you can see here with star, Gento, imax and anthem. And a lot of these cases we were looking at billions of rows of data within minutes. And as you as your data warehouse maturity grows, you can start to add more and more thoughts about users to leverage the data and get better analysis from it. So we hope that you've enjoyed what you see today and take the step to either do one of two things. We have a free trial of thoughts about cloud. If you go to the website that you see below and register, we can get you access the thought spots so you can start searching today. Another option, by contacting our team, is to do a zero to search workshop where 90 minutes will work with you to connect your data source and start to build some insights and exactly what you're trying to find for your business. Um thanks, everybody. I would especially like to thank golf from AWS for joining us on this today. We appreciate your participation, and I hope everybody enjoyed what they saw. I think we have a few questions now. >>Thank you, Vika, Gal and Michael. It's always exciting to see a live demo. I know that I'm one of those comedy numbers. We have just a few minutes left, but I would love to ask a couple of last questions Before we go. Michael will give you the first question. Do I need to have all of my data cleaned and ready in my cloud data warehouse before I begin with thought spot? >>That's a great question, Mallory. No, you don't. You can really start using thought spot for search right away and start getting analysis and start understanding the data through the automatic search analysis and the way that we query the data and we've seen customers do that. Chick fil a example that we talked about earlier is where they were able to use thoughts bought to notice an anomaly in the Cloud Data Warehouse linking between product and store. They were able to fix that very quickly. Then that gets reflected across all of the users because our product queries the Cloud Data Warehouse directly so you can get started right away without it having to be perfect. And >>that's awesome. And gal will leave a fun one for you. What can we look forward to from Amazon Red Shift next year? >>That's a great question. And you know, the team has been innovating extremely fast. We released more than 200 features in the last year and a half, and we continue innovating. Um, one thing that stands out is aqua, which is a innovative new technology. Um, in fact, lovely stands for Advanced Square Accelerator, and it allows customers to achieve performance that up to 10 times faster, uh, than what they've seen really outstanding and and the way we've achieved that is through a shift in paradigm in the actual technological implementation section. Uh, aqua is a new distributed and hardware accelerated processing layer, which effectively allows us to push down operations analytics operations like compression, encryption, filtering and aggregations to the storage there layer and allow the aqua nodes that are built with custom. AWS designed analytics processors to perform these operations faster than traditional soup use. And we no longer need to bring, you know, scan the data and bring it all the way to the computational notes were able to apply these these predicates filtering and encourage encryption and compression and aggregations at the storage level. And likewise is going to be available for every are a three, um, customer out of the box with no changes to come. So I apologize for being getting out a little bit, but this is really exciting. >>No, that's why we invited you. Call. Thank you on. Thank you. Also to Michael and Vika. That was excellent. We really appreciate it. For all of you tuning in at home. The final session of this track is coming up shortly. You aren't gonna want to miss it. We're gonna end strong, come back and hear directly from our customer a T mobile on how T Mobile is building a data driven organization with thought spot in which >>pro, It's >>up next, see you then.

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. >>Hello and welcome back to the cubes Virtual coverage of AWS reinvent 2020. Um, John for your host with a cube virtual were not there in person, but we're gonna do it our job with the best remote we possibly can. Where? Wall to wall coverage on the AWS reinvent site as well as on demand on the Cube. Three new 3 65 platform. We got some great power panel analysts here to dig in and discuss Partner Day for a W S what it means for the customer. What it means for the enterprise, the buyer, the people trying to figure out who to buy from and possibly new partners. How can they re engineer and reinvent their company to partner better with Amazon, take advantage of the benefits, but ultimately get more sales? We got Tim Crawford, star Beat Joel and Day Volonte, Friends of the Cube. We all know him on Twitter, You guys, the posse, the Cube policy. Thanks for coming on. I'm sure it's good guys entertaining and we're >>hanging out drinking beer. Oh, my God. That'd be awesome. You guys. >>Great to have you on. I wanted to bring you on because it's unique. Cross section of perspectives. And this isn't This is from the end user perspective. And, Tim, you've been talking about the c x o s for years. You expert in this? Sorry. You're taking more from a cloud perspective. You've seen the under the hood. What's happening? Let's all put it together. If your partner Okay, first question to the group. I'm a partner. Do I win with Amazon, or do I lose with Amazon? First question. >>Yeah, I'll jump in. I'll say, you know, regardless you win, you win with Amazon. I think there's a lot of opportunity for partners with Amazon. Um, you have to pick your battles, though. You have to find the right places where you can carve out a space that isn't too congested but also isn't really kind of fettered with a number of incumbents. And so if you're looking at the enterprise space, I think that there is a ton of potential because, let's face it, >>Amazon >>doesn't have all of the services packaged in a way that the enterprise can consume. And I think that leaves a lot of fertile ground for s eyes and I SVS to jump in and be able to connect those dots so I'd say it's win, win >>start be if you're like a so cohesively onstage. Jackson's coming out talking about China, the chips and data. If you're like a vendor and I s V you're a startup or your company trying to reinvent How do you see Amazon as a partner? >>Yeah, I see Amazon as a big market for me. You know, it increased my sort of tam, if you will. Uh, the one big sort off trend is that the lines between technology providers and service providers are blurred. Actually, it's flipping. I believe it will flip at some time. We will put consume technology from service providers, and they are becoming technology providers. Actually, they're not just being pipe and power kind of cloud. They are purely software, very high sort of highly constructed machinery, if you will. Behind the scenes with software. >>That's >>what Amazon is, uh, big machine. If you are, and you can leverage that and then you can help your customers achieve their business called as a partner. I think's the women and the roll off. Actually, Assize is changing, I believe a size. Well, I thought they were getting slow, sidetracked by the service providers. But now they have to actually change their old the way they they used to get these, you know, shrink wrap software, and then install and configure and all that stuff. Now it's in a cloud >>on >>they have to focus a little more on services, and and some of the s eyes are building tools for multi cloud consumption and all that. So things are changing under under this whole big shift to go out. >>I mean, I think if you're in S I and you're lifting and shifting, you make a few bucks and helping people do that deal with the tech. But I think we're the rial. Money is the business transformation, and you find the technology is there, it's it's another tool in the bag. But if you can change your operating model, that's gonna drive telephone numbers to the bottom line. That's a boardroom discussion, and that's where the real dollars are for s eyes. That's like that's why guys like Accent you're leading leading into the cloud Big time >>e think I think you're absolutely right, David. I think that's that's one aspect that we have to kind of call out is you can be one of those partners that is focused on the transaction and you'll be successful doing that. But you're absolutely right. If you focus on the long game. I think that is just like I said, completely fertile ground. And there are a lot of opportunities because historically Amazon was ah was a Lego parts, uh, type of cloud provider, right? They provided you with the basic building blocks, which is great for Web scale and startups not so good for enterprise. And so now Amazon is starting to put together in package part, so it's more consumable by enterprises. But you still need that help. And as Sarpy just mentioned, you also have to consider that Amazon is not the only aspect that you're gonna be using. You're gonna be using other providers to. And so I think this again is where partners they pick a primary, and then they also bring in the others where appropriate. >>All right, I want to get into this whole riff. I have a cherry chin on day one. Hey, came on the special fireside chat with me and we talked about, um, cloud errors before cloud Amazon. And now I'll call postcode because we're seeing this kind of whole new, you know, in the cloud kind of generation. And so he said, OK, this pre cloud you had Amazon generation, whereas lift and shift. Ah, lot of hybrid And you have everything is in the cloud like a snowflake kind of thing. And he kind of call it the reptiles versus the amphibians you're on. See your inland, your hybrid, and then you're you're in the water. I mean, so So he kind of went on, Took that another level, meaning that. Okay, this is always gonna be hybrid. But there's a unique differentiation for being all in the cloud. You're seeing different patterns. Amazon certainly has an advantage. See, Dev Ops guru, that's just mining the data of their entire platform and saying Okay, Yeah, do this. There's advantages for being in the cloud that aren't available. Hybrid. So amphibian on land and sea hybrid. And then in the cloud. How do you guys see that if you're a partner. You wanna be on the new generation. What's the opportunity to capture value? He has hybrid certainly coexist. But in the new era, >>remember Scott McNealy used to talk about car makers and car dealers. And of course, Sun's gone. But he used to say, We want to be a carmaker. Car dealers. They got big houses and big boats, but we're gonna be a carmaker. Oh, I think it's some similarities here. I mean, there's a lot of money to be made as a as a car dealer. But you see, companies like Dell, H P E. You know, they want to be carmakers. Obviously Google Microsoft. But there are gonna be a lot of successful really big carmakers in this game. >>Yeah, I believe I believe I always call it Amazon Is the makers cloud right, So they are very developer friendly. They were very developer friendly for startups. Uh, a stem said earlier, but now they are very developer, friendly and operations friendly. Now, actually, in a way for enterprises, I believe, and that the that well, the jerry tend to sort of Are you all all in cloud are sitting just in the dry land. Right now, I think every sort off organization is in a different sort off mature, at different maturity level. But I think we're going all going towards a technology consumption as a service. Mostly, I think it will be off Prem. It can be on Prem in future because off age and all that. And on that note, I think EJ will be dominated by Tier one cloud providers like crazy people who think edge will be nominally but telcos and all that. I think they're just, uh, if >>I made Thio, if I may interject for a second for the folks watching, that might not be old enough to know who Scott McNealy is. He's the founder of Sun Microsystems, which was bought by Oracle years ago. Yeah, basically, because many computer, there's a lot of young kids out there that even though Scott McNealy's But remember, >>do your homework, Scott, you have to know who Scott Scott McNealy >>also said, because Bill Gates was dominant. Microsoft owns the tires and the gas to, and they want to own the road. So remember Microsoft was dominating at that time. So, Tim Gas data is that I mean, Amazon might have everything there. >>I was gonna go back to the to the comment. You know, McNeely came out with some really, really good analogies over his tenure. Um, it's son and you know, son had some great successes. But unfortunately, Cloud is not as simplistic as buying a car and having the dealership and the ecosystem of gas and tires. And the rest you have to think about the toll journey. And that journey is incredibly complicated, especially for the enterprise that's coming from legacy footprints, monolithic application stacks and trying to understand how to make that transition. It's almost it's almost, in a way mawr analogous to your used to riding a bike, and now you're gonna operate a semi. And so how do you start to put all of the pieces into place to be able to make that transition? And it's not trivial. You have to figure out how your culture changes, how your processes changes. There are a lot of connected parts. It's not a simple as the ecosystem of tires and gas. We have to think about how that data stream fits in with other data streams where analytics are gonna be done. What about tying back to that system of record that is going to stay on the legacy platform. Oh, and by the way, some of that has to still stay on Prem. It can't move to the cloud yet. So we have this really complicated, diverse environment that we have to manage, and it's only getting more complicated. And I think that's where the opportunity comes in for the size and s visas. Step into that. Understand that journey, understand the transitions. I don't believe that enterprises, at least in the near term, let alone short term, will be all in cloud. I think that that's more of a fantasy than reality. There is a hybrid state that that is going to be transitory for some period of time, and that's where the big opportunity is. >>I think you're right on time. I think just to double down on that point, just to bring that to another level is Dave. Remember back in the days when PCs where the boom many computers with most clients there was just getting started? There was a whole hype cycle on hard drives, right? Hard drives were the thing. Now, if you look out today, there's more. Observe, ability, startups and I could count, right? So to Tim's point, this monolithic breakdown and component izing decomposing, monolithic APs or environments with micro services is complex. So, to me, the thing that I see is that that I could relate to is when I was breaking in in the eighties, you had the mainframes. Is being the youngun I'm like, Okay, mainframes, old monolithic client server is a different paradigm thing. You had, uh, PCs and Internet working. I think all that change is happening so fast right now. It's not like over 10 years to Tim's points, like mainframes to iPhones. It's happening in like three years. Imagine crunching all that complexity and change down to a short window. I think Amazon has kind of brought that. I'm just riffing on that, But >>yeah, you're absolutely right, John. But I think there's another piece and we can use a very specific example to show this. But another piece that we have to look at is we're trying to simplify that environment, and so a good place to simplify that is when we look at server lis and specifically around databases, you know, historically, I had to pick the database architecture that the applications would ride on. Then I have to have the infrastructure underneath and manage that appropriately so that I have both the performance a swell, a security as well as architecture. Er and I have to scale that as needed. Today, you can get databases of service and not have to worry about the underpinnings. You just worry about the applications and how those data streams connect to other data streams. And so that's the direction that I think things were going is, and we see this across the enterprise we're looking for. Those packaged package might be a generalized term, but we're looking for um, or packaged scenario and opportunity for enterprises rather than just the most basic building blocks. We have to start putting together the preformed applications and then use those as larger chunks. And >>this is the opportunity for a size I was talking before about business transformation. If you take, take Tim's database example, you don't need somebody anymore. Toe, you know, set up your database to tune it. I mean, that's becoming autonomous. But if you think about the way data pipelines work in the way organizations are structured where everything because it goes into this monolithic data lake or and and And it's like generic content coming in generic data where the business owner has to get in line and beg a data scientist or quality engineered or thio ingest a new data source. And it's just like the old data warehouse days where I think there's tremendous opportunities for s eyes to go in a completely re architect. The data model. Sergeant, This is something you and I were talking about on Twitter. It's That's why I like what snowflakes doing. It's kind of a AWS is trying to do with lasted glue views, but there's a whole business transformation opportunity for s eyes, which I just think is huge. Number l >>e all talk. Go ahead. Sorry. Yeah, >>I think we >>all talk, but we know we all agree on one thing that the future is hybrid for at least for next. You know, 10 years, if not more. Uh, hybrid is hard. The data proximity is, uh, very important. That means Leighton see between different workloads, right? That's super important. And I talk about this all the time and almost in every conversation I have about about. It's just scenario, is that there three types of applications every every enterprise systems or fractured systems, systems of engagement and the systems of innovation and my theory of cloud consumption tells me that sooner or later, systems off record. We'll move into SAS SAS world. That's that's how I see it. There's no other way around, I believe, and the systems off engagement or systems off differentiation something and call it. They will leverage a lot off platforms, the service and in that context context, I have said it many times the to be a best of the breed platform. As a service, you have to be best off the breed, um, infrastructure as a service provider. And that's Amazon. And that is that's also a zero to a certain extent, and then and and Google is trying to do that, too. So the feature sort off gap between number one cloud and two and three is pretty huge. I believe I think Amazon is doing great data democratization through several less. I just love serving less for that Several things over. Unless there is >>a winning formula is no doubt about several times I totally agree. But I think one of the things that I miss it has done is they've taken server lists. They brought their putting all the I as and the chips, and they're moving all the value up to the service layer, which gives them the advantage over others. Because everyone else is trying to compete down here. They're gonna be purpose built. If you look what Apple is doing with the chips and what the Amazon is doing, they're gonna kind of have this chip to chip scenario and then the middle. Where in between is the container ization, the micro services and Lambda? So if you're a developer, you approach is it's programmable at that point that could that could be a lock spec. I think for Amazon, >>it absolutely could be John. But I think there's another aspect here that we have to touch on, especially as we think about partners and where the opportunities come in. And that is that We often talk about non cloud to cloud right, how to get from on Prem to cloud. But the piece that you also have thio bring into the conversation is Theo edge to cloud continuum and So I think if you start to look at some of the announcements this week from AWS, you start looking at some of the new instance types uh, that are very ai focused. You look at the two new form factors for outposts, which allows you to bring cloud to a smaller footprint within an on premise premises, situation, uh, different local zones. And then Thea other piece that I think is really interesting is is their announcements around PCs and eks anywhere being able to take cloud in kubernetes, you know, across the board. And so the challenge here is, as I mentioned earlier, complexity is paramount. It's concern for enterprises just moving to cloud. You start layering in the edge to cloud continuum, and it just it gets exponentially more complicated. And so Amazon is not going to be the one to help you go through that. Not because they can't, but frankly, just the scale of help that is going to be needed amongst enterprises is just not there. And so this is really where I think the opportunity lies for the s eyes and I SVS and partners. You >>heard how Jassy defined hybrid John in the article that you wrote when you did your one on one with him, Tim and the in the analyst call, you answered my question and then I want to bring in Antonio near his comment. But Jassy basically said, Look, we see the cloud bring We're gonna bring a W s to the edge and we see data centers. This is another edge node and San Antonio Neary after HP is pretty good quarter uh came out and said, Well, we heard the public cloud provider talking about hybrid welcome, you know? >>Yeah, they were going and then getting here jumped on that big time. But we'll be looking hybrid. Tim nailed The complexity is the is the evil is friction is a friction area. If the complexity could be mastered by the edge provider closest to the customer, that's gonna be valuable, um, for partners. And then we can do that. Amazon's gonna have to continue to remove the friction and putting that together, which is why I'm nervous about their channel partners. Because if I'm a partner, I asked myself, How do I make money with Amazon? Right? At the end of the day, it's money making right. So how can I be successful? Um, not gonna sell more in the marketplace. Will the customer consumer through there? Is it friction or is a complex So this notion of complexity and friction becomes a double edged sword Tim on both sides. So we have five minutes left. Let's talk about the bottom side Complexity, >>friction. So you're absolutely right, John. And you know, the other thing that that I would say is for the partner, you have to look beyond what Amazon is selling today. Look at where the customers are going. And you know, David, I think you and I were both in an analyst session with Andy Jassy several years ago where one of the analysts asked the question. So you know, what's your perspective on Hybrid Cloud? In his response, candidly was, while we have this particular service and really, what he was talking to is a service that helps you on board to Amazon's public cloud. There was there was not an acknowledgment of hybrid cloud at the time, But look at how things have changed just in a short few years, and I understand where Jassy is coming from, but this is just exemplifies the fact that if you're a partner, you have to look beyond what Amazon is saying and think toe how the customer is evolving, how the enterprise is evolving and get yourself ahead of them. That will position you best for both today. And as you're building for the future. >>That's a great point, Dave. Complexity on buying. I'm a customer. You can throw me a marketplace all you want, but if I'm not gonna be tied into my procurement, how I'm consuming technology. Tim's point. Amazon isn't the only game in town. I got other suppliers. >>Yeah, well, certainly for some technology suppliers, they're basically could bring their on prem estate if it's big enough into the cloud. Uh, you know what is big enough? That's the big question here. You know, our guys like your red hats big enough. Okay, we know that Nutanix pure. They're sort of the next layer down. Can they do? They have enough of a customer base that they could bring into the cloud, create that abstraction layer, and then you got the born in the cloud guy Snowflake, Colombia or two good examples. Eso They've got the technology partners and then they're the size and consultants. And again, I see that is the really big opportunity is 10 points out? Amazon is acknowledging that hybrid Israel in in a newly defined way, they're going out to the edge, find you wanna call data center the edge. How are they going to support those installations? How are they gonna make sure that they're running properly? That they're connected to the business process? Those air That's s I whitespace. Huge. >>Guys, we have to wrap it up right now. But I just end on, you know, we'll get everyone go A little lightning around quick soundbite on the phrase with him, which stands for what's in it from me. So if I'm a partner, I'm a customer. I look at Amazon, I think. What's in it for me? Yeah. What a za customer like what do I get out of this? >>Yeah, having done, like more than 100 data center audits, and I'm seeing what mess up messes out there and having done quite a few migrations to cloud migrations of the messy messages piece, right? And it doesn't matter if you're migrating 10% or 20 or 30 it doesn't matter that how much you're migrating? It's a messy piece, and you cannot do with our partners that work. Actually, you need that. Know how you need to infuse that that education into into your organization, how to consume cloud, how toe make sense of it, how you change your processes and how you train your people. So it touches all the products, people and processes. So on three years, you gotta have partners on your side to make it >>so Hey, I'll go quick. And, Tim, you give you the last word. Complexity is cash. Chaos is cash. Follow the complexity. You'll make cash. >>Yeah, you said it, David. I think anyway, that you can help an enterprise simplify. And if you're the enterprise, if you're the customer, look for those partners. They're gonna help you simplify the journey over time. That's where the opportunity really lies. >>Okay, guys, Expert power panel here on Cuba live program, part of AWS reinvent virtual coverage, bringing you all the analysis from the experts. Digital transformations here. What's in it for me is a partner and customer. Help me make some money, master complexity and serve my customer. Mister Cube. Thanks for watching >>que Yeah, from around the globe. It's the cute

>> From around the globe, it's theCUBE, with digital coverage of Exascale Day. Made possible by Hewlett Packard Enterprise. >> Hey, welcome back everybody Jeff Frick here with theCUBE. We are celebrating Exascale Day. 10, 18, I think it's the second year of celebrating Exascale Day, and we're really excited to have our next guest and talk about kind of what this type of compute scale enables, and really look a little bit further down the road at some big issues, big problems and big opportunities that this is going to open up. And I'm really excited to get in this conversation with our next guest. He is Bryan Pijanowski the Professor of Landscape and Soundscape Ecology at Purdue University. Bryan, great to meet you. >> Great to be here. >> So, in getting ready for this conversation, I just watched your TED Talk, and I just loved one of the quotes. I actually got one of quote from it that's basically saying you are exploring the world through sound. I just would love to get a little deeper perspective on that, because that's such a unique way to think about things and you really dig into it and explain why this is such an important way to enjoy the world, to absorb the world and think about the world. >> Yeah, that's right Jeff. So the way I see it, sound is kind of like a universal variable. It exists all around us. And you can't even find a place on earth where there's no sound, where it's completely silent. Sound is a signal of something that's happening. And we can use that information in ways to allow us to understand the earth. Just thinking about all the different kinds of sounds that exist around us on a daily basis. I hear the birds, I hear the insects, but there's just a lot more than that. It's mammals and some cases, a lot of reptiles. And then when you begin thinking outside the biological system, you begin to hear rain, wind, thunder. And then there's the sounds that we make, sounds of traffic, the sounds of church bells. All of this is information, some of it's symbolic, some of it's telling me something about change. As an ecologist that's what I'm interested in, how is the earth changing? >> That's great and then you guys set up at Purdue, the Purdue Center for Global Soundscapes. Tell us a little bit about the mission and some of the work that you guys do. >> Well, our mission is really to use sound as a lens to study the earth, but to capture it in ways that are meaningful and to bring that back to the public to tell them a story about how the earth kind of exists. There's an incredible awe of nature that we all experience when we go out and listen into to the wild spaces of the earth. I've gone to the Eastern Steppes of Mongolian, I've climbed towers in the Paleotropics of Borneo and listened at night. And ask the question, how are these sounds different? And what is a grassland really supposed to sound like, without humans around? So we use that information and bring it back and analyze it as a means to understand how the earth is changing and really what the biological community is all about, and how things like climate change are altering our spaces, our wild spaces. I'm also interested in the role that people play and producing sound and also using sound. So getting back to Mongolia, we have a new NSF funded project where we're going to be studying herders and the ways in which they use sonic practices. They use a lot of sounds as information sources about how the environment is changing, but also how they relate back to place and to heritage a special sounds that resonate, the sounds of a river, for example, are the resonance patterns that they tune their throat to that pay homage to their parents that were born at the side of that river. There's these special connections that people have with place through sound. And so that's another thing that we're trying to do. In really simple terms, I want to go out and, what I call it sounds rather simple, record the earth-- >> Right. >> What does that mean? I want to go to every major biome and conduct a research study there. I want to know what does a grassland sound like? What is a coral reef sound like? A kelp forest and the oceans, a desert, and then capture that as baseline and use that information-- >> Yeah. >> For scientific purposes >> Now, there's so much to unpack there Bryan. First off is just kind of the foundational role that sound plays in our lives that you've outlined in great detail and you talked about it's the first sense that's really activated as we get consciousness, even before we're born right? We hear the sounds of our mother's heartbeat and her voice. And even the last sense that goes at the end a lot of times, in this really intimate relationship, as you just said, that the sounds represent in terms of our history. We don't have to look any further than a favorite song that can instantly transport you, almost like a time machine to a particular place in time. Very, very cool. Now, it's really interesting that what you're doing now is taking advantage of new technology and just kind of a new angle to capture sound in a way that we haven't done before. I think you said you have sound listening devices oftentimes in a single location for a year. You're not only capturing sound, the right sound is changes in air pressure, so that you're getting changes in air pressure, you're getting vibration, which is kind of a whole different level of data. And then to be able to collect that for a whole year and then start to try to figure out a baseline which is pretty simple to understand, but you're talking about this chorus. I love your phrase, a chorus, because that sound is made up of a bunch of individual inputs. And now trying to kind of go under the covers to figure out what is that baseline actually composed of. And you talk about a bunch of really interesting particular animals and species that combine to create this chorus that now you know is a baseline. How did you use to do that before? I think it's funny one of your research papers, you reach out to the great bird followers and bird listeners, 'cause as you said, that's the easiest way or the most prolific way for people to identify birds. So please help us in a crowdsource way try to identify all the pieces that make this beautiful chorus, that is the soundscape for a particular area. >> Right, yeah, that's right. It really does take a team of scientists and engineers and even folks in the social sciences and the humanities to really begin to put all of these pieces together. Experts in many fields are extremely valuable. They've got great ears because that's the tools that they use to go out and identify birds or insects or amphibians. What we don't have are generalists that go out and can tell you what everything sounds like. And I'll tell you that will probably never ever happen. That's just way too much, we have millions of species that exist on this planet. And we just don't have a specific catalog of what everything sounds like, it's just not possible or doable. So I need to go out and discover and bring those discoveries back that help us to understand nature and understand how the earth is changing. I can't wait for us to eventually develop that catalog. So we're trying to develop techniques and tools and approaches that allow us to develop this electronic catalog. Like you're saying this chorus, and it doesn't necessarily have to be a species specific chorus, it can be a chorus of all these different kind of sounds that we think relate back to this kind of animal or that kind of animal based upon the animals instrument-- >> Right, great. >> And this is the sound. >> Now again, you know, keep it to the exascale theme, right? You're collecting a lot of data and you mentioned in one of the pieces I've dug up, that your longest study in a single location is 17 years. You've got over 4 million recordings. And I think you said over 230 years if you wanted to listen to them all back to back. I mean, this is a huge, a big data problem in terms of the massive amount of data that you have and need to run through an analysis. >> Yeah, that's right. We're collecting 48,000 data points per second. So that's 48 kilohertz. And then so you multiply everything and then you have a sense of how many data points you actually have to put them all together. When you're listening to a sound file over 10 minutes, you have hundreds of sounds that exist in them. Oftentimes you just don't know what they are, but you can more or less put some kind of measure on all of them and then begin to summarize them over space and time and try to understand it from a perspective of really science. >> Right, right. And then I just love to get your take as you progress down this kind of identification road, we're all very familiar with copyright infringement hits on YouTube or social media or whatever, when it picks up on some sound and the technology is actually really sophisticated to pick up some of those sound signatures. But to your point, it's a lot easier to compare against the known and to search for that known. Then when you've got this kind of undefined chorus that said we do know that there can be great analysis done that we've seen AI and ML applied, especially in the surveillance side on the video-- >> Right. >> With video that it can actually do a lot of computation and a lot of extracting signal from the noise, if you will. As you look down the road on the compute side for the algorithms that you guys are trying to build with the human input of people that know what you're listening to, what kind of opportunities do you see and where are we on that journey where you can get more leverage out of some of these technology tools? >> Well, I think what we're doing right now is developing the methodological needs, kind of describe what it is we need to move into that new space, which is going to require these computational, that computational infrastructure. So, for example, we have a study right now where we're trying to identify certain kinds of mosquitoes (chuckling) a vector-borne mosquitoes, and our estimates is that we need about maybe 900 to 1200 specific recordings per species to be able to put it into something like a convolutional neural network to be able to extract out the information, and look at the patterns and data, to be able to say indeed this is the species that we're interested in. So what we're going to need and in the future here is really a lot of information that allow us to kind of train these neural networks and help us identify what's in the sound files. As you can imagine the computational infrastructure needed to do that for data storage and CPU, GPU is going to be truly amazing. >> Right, right. So I want to get your take on another topic. And again the basis of your research is really all bound around the biodiversity crisis right? That's from the kind of-- >> Yeah. >> The thing that's started it and now you're using sound as a way to measure baseline and talk about loss of species, reduced abundancies and rampant expansion of invasive species as part of your report. But I'd love to get your take on cities. And how do you think cities fit the future? Clearly, it's an efficient way to get a lot of people together. There's a huge migration of people-- >> Right. >> To cities, but one of your themes in your Ted Talk is reconnecting with nature-- >> Yeah. >> Because we're in cities, but there's this paradox right? Because you don't want people living in nature can be a little bit disruptive. So is it better to kind of get them all in a tip of a peninsula in San Francisco or-- >> Yeah. >> But then do they lose that connection that's so important. >> Yeah. >> I just love to get your take on cities and the impacts that they're have on your core research. >> Yeah, I mean, it truly is a paradox as you just described it. We're living in a concrete jungle surrounded by not a lot of nature, really, honestly, occasional bird species that tend to be fairly limited, selected for limited environments. So many people just don't get out into the wild. But visiting national parks certainly is one of those kinds of experience that people oftentimes have. But I'll just say that it's getting out there and truly listening and feeling this emotional feeling, psychological feeling that wraps around you, it's a solitude. It's just you and nature and there's just no one around. >> Right. >> And that's when it really truly sinks in, that you're a part of this place, this marvelous place called earth. And so there are very few people that have had that experience. And so as I've gone to some of these places, I say to myself I need to bring this back. I need to tell the story, tell the story of the awe of nature, because it truly is an amazing place. Even if you just close your eyes and listen. >> Right, right. >> And it, the dawn chorus in the morning in every place tells me so much about that place. It tells me about all the animals that exist there. The nighttime tells me so much too. As a scientist that's spent most of his career kind of going out and working during the day, there's so much happening at night. Matter of fact-- >> Right. >> There's more sounds at night than there were during the day. So there is a need for us to experience nature and we don't do that. And we're not aware of these crises that are happening all over the planet. I do go to places and I listen, and I can tell you I'm listening for things that I think should be there. You can listen and you can hear the gaps, the gaps and that in that chorus, and you think what should be there-- >> Right. >> And then why isn't it there? And that's where I really want to be able to dig deep into my sound files and start to explore that more fully. >> It's great, it's great, I mean, I just love the whole concept of, and you identified it in the moment you're in the tent, the thunderstorm came by, it's really just kind of changing your lens. It's really twisting your lens, changing your focus, because that sound is there, right? It's been there all along, it's just, do you tune it in or do you tune it out? Do you pay attention? Do not pay attention is an active process or a passive process and like-- >> Right. >> I love that perspective. And I want to shift gears a little bit, 'cause another big environmental thing, and you mentioned it quite frequently is feeding the world's growing population and feeding it-- >> Yeah. >> In an efficient way. And anytime you see kind of factory farming applied to a lot of things you wonder is it sustainable, and then all the issues that come from kind of single output production whether that's pigs or coffee or whatever and the susceptibility to disease and this and that. So I wonder if you could share your thoughts on, based on your research, what needs to change to successfully and without too much destruction feed this ever increasing population? >> Yeah, I mean, that's one of the grand challenges. I mean, society is facing so many at the moment. In the next 20 years or so, 30 years, we're going to add another 2 billion people to the planet, and how do we feed all of them? How do we feed them well and equitably across the globe? I don't know how to do that. But I'll tell you that our crops and the ecosystem that supports the food production needs the animals and the trees and the microbes for the ecosystem to function. We have many of our crops that are pollinated by birds and insects and other animals, seeds need to be dispersed. And so we need the rest of life to exist and thrive for us to thrive too. It's not an either, it's not them or us, it has to be all of us together on this planet working together. We have to find solutions. And again, it's me going out to some of these places and bringing it back and saying, you have to listen, you have to listen to these places-- >> Right. >> They're truly a marvelous. >> So I know most of your listening devices are in remote areas and not necessarily in urban areas, but I'm curious, do you have any in urban areas? And if so, how has that signature changed since COVID? I just got to ask, (Bryan chuckling) because we went to this-- >> Yeah. >> Light switch moment in the middle of March, human activity slowed down-- >> Yeah. >> In a way that no one could have forecast ever on a single event, globally which is just fascinating. And you think of the amount of airplanes that were not flying and trains that we're not moving and people not moving. Did you have any any data or have you been able to collect data or see data as the impact of that? Not only directly in wherever the sensors are, but a kind of a second order impact because of the lack of pollution and the other kind of human activity that just went down. I mean, certainly a lot of memes (Bryan chuckling) on social media of all the animals-- >> Yeah. >> Come back into the city. But I'm just curious if you have any data in the observation? >> Yeah, we're part of actually a global study, there's couple of hundred of us that are contributing our data to what we call the Silent Cities project. It's being coordinated out of Europe right now. So we placed our sensors out in different areas, actually around West Lafayette area here in Indiana, near road crossings and that sort of thing to be able to kind of capture that information. We have had in this area here now, the 17 year study. So we do have studies that get into areas that tend to be fairly urban. So we do have a lot of information. I tell you, I don't need my sensors to tell me something that I already know and you suspect is true. Our cities were quiet, much quieter during the COVID situation. And it's continued to kind of get a little bit louder, as we've kind of released some of the policies that put us into our homes. And so yes, there is a major change. Now there have been a couple of studies that just come out that are pretty interesting. One, which was in San Francisco looking at the white-crowned sparrow. And they looked at historical data that went back something like 20 years. And they found that the birds in the cities were singing a much softer, 30% softer. >> Really? >> And they, yeah, and they would lower their frequencies. So the way sound works is that if you lower your frequencies that sound can travel farther. And so the males can now hear themselves twice as far just due to the fact that our cities are quieter. So it does have an impact on animals, truly it does. There was some studies back in 2001, during  the September, the 9/11 crisis as well, where people are going out and kind of looking at data, acoustic data, and discovering that things were much quieter. I'd be very interested to look at some of the data we have in our oceans, to what extent are oceans quieter. Our oceans sadly are the loudest part of this planet. It's really noisy, sound travels, five times farther. Generally the noise is lower frequencies, and we have lots of ships that are all over the planet and in our oceans. So I'd really be interested in those kinds of studies as well, to what extent is it impacting and helping our friends in the oceans. >> Right, right, well, I was just going to ask you that question because I think a lot of people clearly understand sound in the air that surrounds us, but you talk a lot about sound in ocean, and sound as an indicator of ocean health, and again, this concept of a chorus. And I think everybody's probably familiar with the sounds of the humpback whale right? He got very popular and we've all seen and heard that. But you're doing a lot of research, as you said, in oceans and in water. And I wonder if you can, again, kind of provide a little bit more color around that, because I don't think you people, maybe we're just not that tuned into it, think of the ocean or water as a rich sound environment especially to the degree as you're talking about where you can actually start to really understand what's going on. >> Yeah, I mean, some of us think that sound in the oceans is probably more important to animals than on land, on the terrestrial side. Sound helps animals to navigate through complex waterways and find food resources. You can only use site so far underwater especially when it gets to be kind of dark, once you get down to certain levels. So there many of us think that sound is probably going to be an important component to measuring the status of health in our oceans. >> It's great. Well, Bryan, I really enjoyed this conversation. I've really enjoyed your Ted Talk, and now I've got a bunch of research papers I want to dig into a little bit more as well. >> Okay.(chuckling) >> It's a fascinating topic, but I think the most important thing that you talked about extensively in your Ted Talk is really just taking a minute to take a step back from the individual perspective, appreciate what's around us, hear, that information and I think there's a real direct correlation to the power of exascale, to the power of hearing this data, processing this data, and putting intelligence on that data, understanding that data in a good way, in a positive way, in a delightful way, spiritual way, even that we couldn't do before, or we just weren't paying attention like with what you know is on your phone please-- >> Yeah, really. >> It's all around you. It's been there a whole time. >> Yeah. (both chuckling) >> Yeah, Jeff, I really encourage your viewers to count it, just go out and listen. As we say, go out and listen and join the mission. >> I love it, and you can get started by going to the Center for Global Soundscapes and you have a beautiful landscape. I had it going earlier this morning while I was digging through some of the research of Bryan. (Bryan chuckling) Thank you very much (Bryan murmurs) and really enjoyed the conversation best to you-- >> Okay. >> And your team and your continued success. >> Alright, thank you. >> Alright, thank you. All right, he's Bryan-- >> Goodbye. >> I'm Jeff, you're watching theCUBE. (Bryan chuckling) for continuing coverage of Exascale Day. Thanks for watching. We'll see you next time. (calm ambient music)

(upbeat music) >> Facilitator: From theCUBE studios in Palo Alto in Boston, connecting with other leaders all around the world. This is a CUBE conversation. >> Java is the world's most popular programming language. And it remains the leading application development platform. But what's the status of Java? What a customers doing? And very importantly, what is Oracle's and the community strategy with respect to Java? Welcome everybody to this Java power panel on theCUBE. I'm your host, Dave Vellante. Manish Gupta here, he's the Vice President of Global Marketing at Java for Oracle, Donald Smith is also on the panel, and he's the Senior Director of Product Management at Oracle and we're joined by David Floyd who is a CTO of Wikibon Research and has done a number of research activities on this very topic. Gentlemen, welcome to theCUBE, great to see you. >> Thank you. >> Thank you. >> Manish, I want to start with you. Can you help us understand really what dig into Oracle strategy with respect to Java. The technology, the licensing, the support. How has that evolved over time? Take us through that. >> Dave, with 51 billion JVMs deployed worldwide, Java has truly cemented its position as the language of innovation and the technology world. There's no question about that. In fact, I like to say it's really the language of empowerment. Given the the impact it has had numerous applications ranging from the Mars Rover to genomics and everything in between. As Oracle acquired sign over 10 years ago, it's really kept it front of mind, two aspects of what we want to do with the technology and the platform. The first one was to ensure there was broad accessibility to the technology and the platform for anybody that wanted to benefit from it. And the second one was to ensure that the ecosystem remained vibrant and thriving throughout. I managed to do both. And underpinning these two objectives were really three pillars of our strategy. The first one was around trust, ensuring that openness and transparency of the technology was as was before continued to be the case going forward. The second element of that within the trust pillar was to ensure that as enterprises invested in the technology that investment was protected, it was not, you invest and you lose over a period of time in a backward compatibility, interoperability, certifications, were all foundational to the platform itself to the features, to the innovation moving forward. And more recently as we have rethought to the support, the licensing and the overall structure of the pricing that we have ensured that ultimately the trust comes along in those dimensions as well. So the launch of the Java subscription came along with, pay as you go model, it's a transparent pricing structure and discuss structure published on the website. So you can go and see what it would cost for the desktop on servers or cloud deployment. So those were the things that made kind of the first pillar happen. The second one was Dunno innovation. Over the last 25 years, Java has stood the test of time. It has delivered the needs of today while preparing for the future. And that remains the case. It is not something that has sort of focused on the fat of the day and the hot thing for the day, but really more important that it is prepared to deal with the mission critical, massive scale deployments that can run for years, for decades, in some cases. And keeping that in mind, Oracle has continued to put more and more technology into the open source world with every release that comes out, you can see 80 plus percent of the contributions come from Oracle. So that's the second pillar around innovation. And the third piece of the strategy has been around predictability. Ensuring that Java, the technology and platform perform as advertised, and that goes into the feature releases, it goes into the release process, it goes into the fact that you were broadly within the open JDK environment for developing and executing the roadmap. From a CIO standpoint, it's important to know that the technology used to develop your applications has talent around. And your, if you're going to develop something like Java, you'll find the right Java engineers to do the job. That is not a question, right? And so that's part of predictability. And finally, again with the change in the six months release cadence that came about three years ago, with the release of Java 10, we've really made sure that it's not, no, a bunch of things come about. You don't know when they're going to be released, but you know, like clockwork, you'll have a new Java list every six months. And that's been the case every March and September, since Java 10, you've had a new release of Java with certain features that come up and we just launched Java 15. So trust innovation predictability, have really been the three pillars on which we've executed the strategy for Java. >> Excellent, thank you for that intro, and we're going to get into it now. I'm glad you mentioned the sun acquisition. I said at the time that Java was the linchpin of that acquisition, many people, of course, we looked at the integration piece with the hardware, but it was really Java and the capabilities that it brings. And of course, a lot of Oracle software written in Java and not the least of which is a fusion. But now let's get into the components of this. And I want to talk a little bit about the methodology of this and going to call on you David Floyer. But essentially my understanding is that Wikibon went through and David, you led this, you did a technical deep dive, which you always do, did a number of in depth interviews with Java customers. And then of course you also did a web survey and then you built from that data and economic model. So you can try to understand the sort of dimensions of the financials if you will. So what were your key findings there? >> So the key findings were that Java was in a good state that people were happy with the Java. The second key finding is that the business case itself for using the Oracle services, the subscription services was good. It didn't mean to say that that wasn't for every company, the right way to do it, but there was a very good return on that. And the third area was that there was a degree of confidence that the new way of doing things, the six-month cycle, as opposed to the three-year cycle was overall a benefit to the rate of change, the ability for them to introduce new features quickly. >> Okay, well, I mean, you know, and I read that research. And to me my takeaways where I saw the continued relevance of Java, which is kind of goes without saying, but a lot of times it gets lost in the headlines. That subscription piece is key. We're going to get into some of the economics as to how that affects customers and it saves you money. And the other piece was the roadmap becoming more transparent. And I don't want to dig into that a little bit, but before we do, let's get into that innovation component Manish, mentioned that several times, but Don, I want to go to you guys. We have a slide on the various components of the innovation. If you would bring this up and Don I wonder if you could talk to this and give us some examples if you would. >> Yeah, sure. So we were the number one development platform for the last 25 years. We want to be the number one development platform for the next 25 years. And in order to do that, we have to be constantly innovating and constantly innovating not only the business side in terms of the subscription and the support offerings and commercial features like Manish was talking about, but also the platform in general. And so the way we like to talk about innovation as we break it down by these pillars that you can see on the slide. And so the first pillar is continuous improvements to the language. So this is watching developers trying to write the same piece of code over and over again, and us asking, can we make you more efficient? Can we give you more language features that reduce the amount of boilerplate that you have to write? The second pillar is a project that we just announced a few months ago called Leyden. And the idea with Leyden is addressing the longterm pinpoints of Java slow startup time and time to peak performance. So if you go back 10 years ago, everybody knows about Java as an enterprise platform, Java EE application servers. They all had the notion of being very long lived. And so Java at that time would be optimized towards long lived applications, startup, and performance. Where if it took a little while to get there, it didn't matter as long as when it got there, it was super fast. And so we're trying to get that peak performance faster in the world of microservices. In a similar vein with project loom, we're looking at making concurrency simple again, looking at how developers are doing more reactive style programming and realizing that the threading model needs to be rethought from the ground up, that project is looking really, really good. Then we have project Panama. Project Panama is all about making it easier to connect Java with native libraries. Valhalla is all about improving, there's a couple of benefits, but it's all about improving memory density and being able to access and iterate and operate over primitive data types at super fast speeds by better optimizing how that information is stored in memory. And then the other pillar of the final pillar that we have been working on from an innovation perspective is ZGC. We introduced a new garbage collector technology a few years ago, G1GCE a generational garbage collector with the eye towards making garbage collection in Java pause lists. So if you, again, if you go back in time and look at the history of Java, memory management is awesome, but there's always that cost and risk of a garbage collection cycle, taking a bit of time away from a critical application. And ZGC is all about getting rid of that. So lots of innovation, lots of different pillars going on right now. >> Awesome, I'm impressed. There's something after Valhalla. I thought that was Nirvana. (laughing) But now, and these are all open source projects, right? And you guys obviously provide committers, there are other people in the open source world who provide that, is that correct Don? >> Yeah, that's correct. We have about 80% of the contributions in open JDK. We are the stewards of open JDK and lead the project. Most of the pillars I talked about here are you know Oracle folks working on that. >> Awesome. Okay, let's get into some of the data. David, I want to come back to you and talk about some of the survey results guys, if you bring up that next slide. Why David, why do people upgrade? What are the drivers? It's really talks to the large companies and what's different from the small company or mid-size companies? What are the takeaways here? >> David: Well, so this is interesting, and as you might expect, large enterprises, have very concerned about application stability. Whereas midsize or enterprises are much more concerned about the performance, making sure that the performance is good. They are both concerned about reliable performance and security, but it's interesting that from a regulation point of view, mid-size companies really want to make sure that they are obeying the regulations, that they are meeting those. Whereas larger organizations usually have their own security and regulation functions looking very hard at these things. So that looking less to the platform to provide those than their own people. >> Yeah, I think you're right. I think the midsize organizations don't have as many people running around taking care of security and it's harder for them to keep up with the edicts of the organization. So they want to stay more current. Don, I wonder if you can add anything to this data from an innovation standpoint. >> Yeah, well, and from a product management standpoint, and what we see here is when you look at just going from fortune 500 to global 2000, you see things that are important to one or less so than the other. You can extrapolate that all the way down to a small company or a startup. And that's why providing the most flexibility in terms of an offering to allow people to decide what, when, where, and how they would be going to upgrade their software so they can do it when they want, and on their own terms. You can see that that becomes really important. And also making sure that we're providing innovation in a broad way so that it'll appeal both to the enterprise and again extrapolating that forward down to even very small startups. >> You know, David, the other thing that struck me in the data, if we bring up that other piece is the upgrade strategy, and there was a stark difference between large enterprises and midsize organizations. Talk to this data, if you would. >> Yes, this is again, a pretty stark difference between them. When you're looking at large enterprises, they really wants stability and they don't want to upgrade so often. Whereas mid-size enterprises, are much more willing to both upgrade on a regular cadence and really have a much more up-to-date, or have always have the latest software. They're driving smaller applications, but they're much more agile about their approach to it. Again, emphasizing what Don was saying about the smaller enterprises wanting a different strategy and a different way of doing things than large enterprises. >> So Manish this says to me that you got it right from a strategy standpoint. I mean, any color you can add here. >> Yeah, it's very intuitive that whether you're a large organization, a mid-sized enterprise or a small business, right? You face competitive pressures, your dynamics are unique. What you're able to do with the resources, what you desire to do at the pace that is appropriate for your environment, are really unique to you, and to try to force one model across any one size or across any set of dynamics is just not appropriate. So we've always felt that giving the enterprises and the organization, the ability to move at the pace of their business is the right approach. And so when we designed the Oracle Java SE subscription, we truly have that front and center in our thought process. And that structure seems to be working well. >> David, what I like about the way you do research is you actually build an economic model. A lot of these business value projects. I know this well, having been in the business a long time, they'll go out to ask the customer what they got, and then the customer said, "Well, I got a 111% ROI, and boom, that's what it is. You actually construct an economic model, you bring in rules of thumb, it allows you to do what ifs you can test that model and calibrate it against the real world. So I commend you on that. You've done a lot of hard work there, but bottom line at forests, I mean, let's bring up the economics. I mean, that's what people ultimately want to know. Does this save me money? What's the bottom line here? >> Yeah. Yes, that's a very important question. And the way we go about it is to ask the questions so that we can extract from those questions, how much effort it took, for example, to upgrade things, how much effort it took for important applications and not so important applications. So we have a very detailed model driven by the survey itself and in the back of the research, I'm a great believer that you should be able to follow exactly what the research said, what the survey said and how it was applied to the model. So, and what were you focused on was, what was the return of using the Java subscription service or taking an upgrade every six months? Those were the two ways that we looked at it. And for large enterprises, the four-year costs for the enterprise was $11 million, but for taking the additional subscription service, and this was well well covered, the payback is within a year, well covered by the lower costs of managing in a lot of systems and environment. And we found a very similar result on those midsize services. There, it was 3 million, and again, they got that back the year in terms of payback. So, but that's one alternative. There is another alternative that may be worthwhile the extra money if you really want to be up-to-date and or if you want to drive a much more aggressive strategy for your organization. >> So these are huge numbers. I mean, he's talking about 30% savings on average for large and mid-sized enterprises in the percentage terms, but the absolute dollars are actually enormous. So, you know, large companies here, we're talking about $20 billion enterprises with 500 or more Java applications. And mid-size is, you're talking about a couple, two, $3 billion companies. Manish, what are you saying in the customer base in terms of the economics? >> Yeah, you know anytime an organization is looking at an offering and a solution, they want to make sure just giving them the value. And we all know that the priorities of businesses have, they want to focus on that. Managing the Java estate is important, but is it the thing where they want to invest the dollars? And if they are investing the dollars, are they getting the return? We find that if you can give the enterprises an ability where they can see the return, the cost is right for them. And if you can mirror that and you can map it also with reduce risk, then you put the right formula. And with the subscription, they're able to not only see the cost savings that the model indicates clearly, but they're also able to reduce the risk in terms of security protection and other things. So it's a really, really good combination for the enterprises. >> Well, thank you, I wonder Manish, if you could bring us home here and just kind of summarize from your thoughts, everything you've heard today, what are the key takeaways? >> You know Java has been around for 25 years, and we certainly believe it's really positioned well for what's required today. And perhaps more importantly, what is needed for the next decade and for the next 25 years. Having now served thousands of customers with the Java subscription, it's clear that it is meeting the needs of fortune 10 organizations all the way down to a 5% development house, for example. What we're hearing from across the board is really Java has been the go to platform and it continues to be the go to platform for mission critical development and deployment. However, the complexity as the Java estate becomes large when you've got tens to hundreds, in some cases over a thousand applications running across the enterprise, that complexity can be daunting. And the Java subscription is really serving the needs in three ways. One, it's getting them the best of class support from Oracle, which is a steward of Java, the company that is generating over 80% of innovation with every single release. The second thing they're getting the business flexibility. So they can move at the pace that works for them. And therapies is as a business model as indicated that they're getting it at a lower cost while having your list. So the combination of these things is the reason why we're seeing very high renewal rates, why we're seeing thousands of organization take it over. And I want to wrap it up by saying one final thing, that you can count on Oracle to be the transparent, to be the right steward or both technology innovation, as well as to ensuring the support for the vast ecosystem whether it's libraries, frameworks, user groups, educational services and so on. So Java is here, has been here for the enterprise, large and small, and it's ready for the next generation as well. >> Great, thank you for that. Well, one more question. What's the call to action? If I'm a mid-sized company or a large company, I've made investments in Java, what, what should I do next? >> I would say, take a look at the Oracle subscription. It will reduce your rates. It'll save you a cost and it'll give you a lower risk parameter for your organization. >> Great, nice and crisp, I like it. If you like, if you guys don't object, I'm going to give you my summary. I've been taking notes this whole time and so, we've explored two options. Customers can do it yourself or go with the subscription on a regular cadence. It's very clear to me that that Java remains relevant as we set up top. It's the world's most popular programming language we know about all that. The ecosystem is really moving fast. Of course, with the stewardship of Oracle cloud microservices, the development of, of modern applications. I think that the directional changes that Manish you guys and, and Don and Oracle have made were really the right call. The research that David you did, shows that it's serving customers better. It lowers costs, it's cutting down risk particularly for the mid-sized companies that maybe are, or don't have the security infrastructure and the talent to go chase those problems. And I love the roadmap piece. The more transparent roadmap really is going to give the industry and the community much more confidence to invest and move forward. So guys, thanks very much for coming on this CUBE Java power panel. It was great to have you. >> Thank you. >> Thank you. >> Thank you. >> All right, I thank you for watching everybody. This is Dave Vellante, for theCUBE, and we'll see you next time. (soft music)

(upbeat music) >> Facilitator: From theCUBE studios in Palo Alto in Boston, connecting with other leaders all around the world. This is a CUBE conversation. >> Java is the world's most popular programming language. And it remains the leading application development platform. But what's the status of Java? What a customers doing? And very importantly, what is Oracle's and the community strategy with respect to Java? Welcome everybody to this Java power panel on theCUBE. I'm your host, Dave Vellante. Manish Gupta here, he's the Vice President of Global Marketing at Java for Oracle, Donald Smith is also on the panel, and he's the Senior Director of Product Management at Oracle and we're joined by David Floyd who is a CTO of Wikibon Research and has done a number of research activities on this very topic. Gentlemen, welcome to theCUBE, great to see you. >> Thank you. >> Thank you. >> Manish, I want to start with you. Can you help us understand really what dig into Oracle strategy with respect to Java. The technology, the licensing, the support. How has that evolved over time? Take us through that. >> Dave, with 51 billion JVMs deployed worldwide, Java has truly cemented its position as the language of innovation and the technology world. There's no question about that. In fact, I like to say it's really the language of empowerment. Given the the impact it has had numerous applications ranging from the Mars Rover to genomics and everything in between. As Oracle acquired sign over 10 years ago, it's really kept it front of mind, two aspects of what we want to do with the technology and the platform. The first one was to ensure there was broad accessibility to the technology and the platform for anybody that wanted to benefit from it. And the second one was to ensure that the ecosystem remained vibrant and thriving throughout. I managed to do both. And underpinning these two objectives were really three pillars of our strategy. The first one was around trust, ensuring that openness and transparency of the technology was as was before continued to be the case going forward. The second element of that within the trust pillar was to ensure that as enterprises invested in the technology that investment was protected, it was not, you invest and you lose over a period of time in a backward compatibility, interoperability, certifications, were all foundational to the platform itself to the features, to the innovation moving forward. And more recently as we have rethought to the support, the licensing and the overall structure of the pricing that we have ensured that ultimately the trust comes along in those dimensions as well. So the launch of the Java subscription came along with, pay as you go model, it's a transparent pricing structure and discuss structure published on the website. So you can go and see what it would cost for the desktop on servers or cloud deployment. So those were the things that made kind of the first pillar happen. The second one was Dunno innovation. Over the last 25 years, Java has stood the test of time. It has delivered the needs of today while preparing for the future. And that remains the case. It is not something that has sort of focused on the fat of the day and the hot thing for the day, but really more important that it is prepared to deal with the mission critical, massive scale deployments that can run for years, for decades, in some cases. And keeping that in mind, Oracle has continued to put more and more technology into the open source world with every release that comes out, you can see 80 plus percent of the contributions come from Oracle. So that's the second pillar around innovation. And the third piece of the strategy has been around predictability. Ensuring that Java, the technology and platform perform as advertised, and that goes into the feature releases, it goes into the release process, it goes into the fact that you were broadly within the open JDK environment for developing and executing the roadmap. From a CIO standpoint, it's important to know that the technology used to develop your applications has talent around. And your, if you're going to develop something like Java, you'll find the right Java engineers to do the job. That is not a question, right? And so that's part of predictability. And finally, again with the change in the six months release cadence that came about three years ago, with the release of Java 10, we've really made sure that it's not, no, a bunch of things come about. You don't know when they're going to be released, but you know, like clockwork, you'll have a new Java list every six months. And that's been the case every March and September, since Java 10, you've had a new release of Java with certain features that come up and we just launched Java 15. So trust innovation predictability, have really been the three pillars on which we've executed the strategy for Java. >> Excellent, thank you for that intro, and we're going to get into it now. I'm glad you mentioned the sun acquisition. I said at the time that Java was the linchpin of that acquisition, many people, of course, we looked at the integration piece with the hardware, but it was really Java and the capabilities that it brings. And of course, a lot of Oracle software written in Java and not the least of which is a fusion. But now let's get into the components of this. And I want to talk a little bit about the methodology of this and going to call on you David Floria. But essentially my understanding is that Wikibon went through and David, you led this, you did a technical deep dive, which you always do, did a number of in depth interviews with Java customers. And then of course you also did a web survey and then you built from that data and economic model. So you can try to understand the sort of dimensions of the financials if you will. So what were your key findings there? >> So the key findings were that Java was in a good state that people were happy with the Java. The second key finding is that the business case itself for using the Oracle services, the subscription services was good. It didn't mean to say that that wasn't for every company, the right way to do it, but there was a very good return on that. And the third area was that there was a degree of confidence that the new way of doing things, the six-month cycle, as opposed to the three-year cycle was overall a benefit to the rate of change, the ability for them to introduce new features quickly. >> Okay, well, I mean, you know, and I read that research. And to me my takeaways where I saw the continued relevance of Java, which is kind of goes without saying, but a lot of times it gets lost in the headlines. That subscription piece is key. We're going to get into some of the economics as to how that affects customers and it saves you money. And the other piece was the roadmap becoming more transparent. And I don't want to dig into that a little bit, but before we do, let's get into that innovation component Manish, mentioned that several times, but Don, I want to go to you guys. We have a slide on the various components of the innovation. If you would bring this up and Don I wonder if you could talk to this and give us some examples if you would. >> Yeah, sure. So we were the number one development platform for the last 25 years. We want to be the number one development platform for the next 25 years. And in order to do that, we have to be constantly innovating and constantly innovating not only the business side in terms of the subscription and the support offerings and commercial features like Manish was talking about, but also the platform in general. And so the way we like to talk about innovation as we break it down by these pillars that you can see on the slide. And so the first pillar is continuous improvements to the language. So this is watching developers trying to write the same piece of code over and over again, and us asking, can we make you more efficient? Can we give you more language features that reduce the amount of boilerplate that you have to write? The second pillar is a project that we just announced a few months ago called Leyden. And the idea with Leyden is addressing the longterm pinpoints of Java slow startup time and time to peak performance. So if you go back 10 years ago, everybody knows about Java as an enterprise platform, Java EE application servers. They all had the notion of being very long lived. And so Java at that time would be optimized towards long lived applications, startup, and performance. Where if it took a little while to get there, it didn't matter as long as when it got there, it was super fast. And so we're trying to get that peak performance faster in the world of microservices. In a similar vein with project loom, we're looking at making concurrency simple again, looking at how developers are doing more reactive style programming and realizing that the threading model needs to be rethought from the ground up, that project is looking really, really good. Then we have project Panama. Project Panama is all about making it easier to connect Java with native libraries. Valhalla is all about improving, there's a couple of benefits, but it's all about improving memory density and being able to access and iterate and operate over primitive data types at super fast speeds by better optimizing how that information is stored in memory. And then the other pillar of the final pillar that we have been working on from an innovation perspective is ZGC. We introduced a new garbage collector technology a few years ago, G1GCE a generational garbage collector with the eye towards making garbage collection in Java pause lists. So if you, again, if you go back in time and look at the history of Java, memory management is awesome, but there's always that cost and risk of a garbage collection cycle, taking a bit of time away from a critical application. And ZGC is all about getting rid of that. So lots of innovation, lots of different pillars going on right now. >> Awesome, I'm impressed. There's something after Valhalla. I thought that was Nirvana. (laughing) But now, and these are all open source projects, right? And you guys obviously provide committers, there are other people in the open source world who provide that, is that correct Don? >> Yeah, that's correct. We have about 80% of the contributions in open JDK. We are the stewards of open JDK and lead the project. Most of the pillars I talked about here are you know Oracle folks working on that. >> Awesome. Okay, let's get into some of the data. David, I want to come back to you and talk about some of the survey results guys, if you bring up that next slide. Why David, why do people upgrade? What are the drivers? It's really talks to the large companies and what's different from the small company or mid-size companies? What are the takeaways here? >> David: Well, so this is interesting, and as you might expect, large enterprises, have very concerned about application stability. Whereas midsize or enterprises are much more concerned about the performance, making sure that the performance is good. They are both concerned about reliable performance and security, but it's interesting that from a regulation point of view, mid-size companies really want to make sure that they are obeying the regulations, that they are meeting those. Whereas larger organizations usually have their own security and regulation functions looking very hard at these things. So that looking less to the platform to provide those than their own people. >> Yeah, I think you're right. I think the midsize organizations don't have as many people running around taking care of security and it's harder for them to keep up with the edicts of the organization. So they want to stay more current. Don, I wonder if you can add anything to this data from an innovation standpoint. >> Yeah, well, and from a product management standpoint, and what we see here is when you look at just going from fortune 500 to global 2000, you see things that are important to one or less so than the other. You can extrapolate that all the way down to a small company or a startup. And that's why providing the most flexibility in terms of an offering to allow people to decide what, when, where, and how they would be going to upgrade their software so they can do it when they want, and on their own terms. You can see that that becomes really important. And also making sure that we're providing innovation in a broad way so that it'll appeal both to the enterprise and again extrapolating that forward down to even very small startups. >> You know, David, the other thing that struck me in the data, if we bring up that other piece is the upgrade strategy, and there was a stark difference between large enterprises and midsize organizations. Talk to this data, if you would. >> Yes, this is again, a pretty stark difference between them. When you're looking at large enterprises, they really wants stability and they don't want to upgrade so often. Whereas mid-size enterprises, are much more willing to both upgrade on a regular cadence and really have a much more up-to-date, or have always have the latest software. They're driving smaller applications, but they're much more agile about their approach to it. Again, emphasizing what Don was saying about the smaller enterprises wanting a different strategy and a different way of doing things than large enterprises. >> So Manish this says to me that you got it right from a strategy standpoint. I mean, any color you can add here. >> Yeah, it's very intuitive that whether you're a large organization, a mid-sized enterprise or a small business, right? You face competitive pressures, your dynamics are unique. What you're able to do with the resources, what you desire to do at the pace that is appropriate for your environment, are really unique to you, and to try to force one model across any one size or across any set of dynamics is just not appropriate. So we've always felt that giving the enterprises and the organization, the ability to move at the pace of their business is the right approach. And so when we designed the Oracle Java SE subscription, we truly have that front and center in our thought process. And that structure seems to be working well. >> David, what I like about the way you do research is you actually build an economic model. A lot of these business value projects. I know this well, having been in the business a long time, they'll go out to ask the customer what they got, and then the customer said, "Well, I got a 111% ROI, and boom, that's what it is. You actually construct an economic model, you bring in rules of thumb, it allows you to do what ifs you can test that model and calibrate it against the real world. So I commend you on that. You've done a lot of hard work there, but bottom line at forests, I mean, let's bring up the economics. I mean, that's what people ultimately want to know. Does this save me money? What's the bottom line here? >> Yeah. Yes, that's a very important question. And the way we go about it is to ask the questions so that we can extract from those questions, how much effort it took, for example, to upgrade things, how much effort it took for important applications and not so important applications. So we have a very detailed model driven by the survey itself and in the back of the research, I'm a great believer that you should be able to follow exactly what the research said, what the survey said and how it was applied to the model. So, and what were you focused on was, what was the return of using the Java subscription service or taking an upgrade every six months? Those were the two ways that we looked at it. And for large enterprises, the four-year costs for the enterprise was $11 million, but for taking the additional subscription service, and this was well well covered, the payback is within a year, well covered by the lower costs of managing in a lot of systems and environment. And we found a very similar result on those midsize services. There, it was 3 million, and again, they got that back the year in terms of payback. So, but that's one alternative. There is another alternative that may be worthwhile the extra money if you really want to be up-to-date and or if you want to drive a much more aggressive strategy for your organization. >> So these are huge numbers. I mean, he's talking about 30% savings on average for large and mid-sized enterprises in the percentage terms, but the absolute dollars are actually enormous. So, you know, large companies here, we're talking about $20 billion enterprises with 500 or more Java applications. And mid-size is, you're talking about a couple, two, $3 billion companies. Manish, what are you saying in the customer base in terms of the economics? >> Yeah, you know anytime an organization is looking at an offering and a solution, they want to make sure just giving them the value. And we all know that the priorities of businesses have, they want to focus on that. Managing the Java estate is important, but is it the thing where they want to invest the dollars? And if they are investing the dollars, are they getting the return? We find that if you can give the enterprises an ability where they can see the return, the cost is right for them. And if you can mirror that and you can map it also with reduce risk, then you put the right formula. And with the subscription, they're able to not only see the cost savings that the model indicates clearly, but they're also able to reduce the risk in terms of security protection and other things. So it's a really, really good combination for the enterprises. >> Well, thank you, I wonder Manish, if you could bring us home here and just kind of summarize from your thoughts, everything you've heard today, what are the key takeaways? >> You know Java has been around for 25 years, and we certainly believe it's really positioned well for what's required today. And perhaps more importantly, what is needed for the next decade and for the next 25 years. Having now served thousands of customers with the Java subscription, it's clear that it is meeting the needs of fortune 10 organizations all the way down to a 5% development house, for example. What we're hearing from across the board is really Java has been the go to platform and it continues to be the go to platform for mission critical development and deployment. However, the complexity as the Java estate becomes large when you've got tens to hundreds, in some cases over a thousand applications running across the enterprise, that complexity can be daunting. And the Java subscription is really serving the needs in three ways. One, it's getting them the best of class support from Oracle, which is a steward of Java, the company that is generating over 80% of innovation with every single release. The second thing they're getting the business flexibility. So they can move at the pace that works for them. And therapies is as a business model as indicated that they're getting it at a lower cost while having your list. So the combination of these things is the reason why we're seeing very high renewal rates, why we're seeing thousands of organization take it over. And I want to wrap it up by saying one final thing, that you can count on Oracle to be the transparent, to be the right steward or both technology innovation, as well as to ensuring the support for the vast ecosystem whether it's libraries, frameworks, user groups, educational services and so on. So Java is here, has been here for the enterprise, large and small, and it's ready for the next generation as well. >> Great, thank you for that. Well, one more question. What's the call to action? If I'm a mid-sized company or a large company, I've made investments in Java, what, what should I do next? >> I would say, take a look at the Oracle subscription. It will reduce your rates. It'll save you a cost and it'll give you a lower risk parameter for your organization. >> Great, nice and crisp, I like it. If you like, if you guys don't object, I'm going to give you my summary. I've been taking notes this whole time and so, we've explored two options. Customers can do it yourself or go with the subscription on a regular cadence. It's very clear to me that that Java remains relevant as we set up top. It's the world's most popular programming language we know about all that. The ecosystem is really moving fast. Of course, with the stewardship of Oracle cloud microservices, the development of, of modern applications. I think that the directional changes that Manish you guys and, and Don and Oracle have made were really the right call. The research that David you did, shows that it's serving customers better. It lowers costs, it's cutting down risk particularly for the mid-sized companies that maybe are, or don't have the security infrastructure and the talent to go chase those problems. And I love the roadmap piece. The more transparent roadmap really is going to give the industry and the community much more confidence to invest and move forward. So guys, thanks very much for coming on this CUBE Java power panel. It was great to have you. >> Thank you. >> Thank you. >> Thank you. >> All right, I thank you for watching everybody. This is Dave Vellante, for theCUBE, and we'll see you next time. (soft music)

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante over the past 150 days virtually everybody that i know in the technology industry has become an expert on covid in some way shape or form we've all lived the reality that covet 19 has accelerated by at least two years many trends that were in motion well before the virus hit the cyber security sector is no exception and one of the best examples where we have witnessed the accelerated change hello everyone and welcome to this week's episode of wikibon cube insights powered by etr in this breaking analysis we'll update you on the all-important security sector which remains one of the top spending priorities for organizations and i want to give you a shout out to my colleague eric bradley from etr who gave me some really good data and some macro insights as well as some anecdotal data from csos for this episode let's take a look at the big picture first now for many years we've talked about the shifting patterns in networking moving from what's often referred to as a north-south architecture meaning a hierarchical network that supports you know age-old organizational structures well today the network is flattening into what they often refer to as an east-west model and the moat or perimeter it's been vaporized the perimeter is now wherever the user is and users are at home or they're at their beach houses thanks to kovid now this is a bad actor's dream as the threat surfaced has expanded by orders of magnitude and as we've said in the past the adversary is well funded extremely capable and highly motivated because the roi of infiltration and exfiltration is outstanding the cso's job quite simply stated is to lower that return on investment now the other big trend that we see is that the cloud and sas are reducing reliance on hardware-based solutions like traditional firewalls because so many workers are now at home they're in their accessing sensitive data identity and endpoint security are exploding xdr or extended detection and response and zero trust networks are on the rise organizations are increasingly relying on analytics and automation to detect and remediate threats you know alerts just don't cut it anymore i need action and so to do so they're turning to a number of best of breed point products that have the potential to become the next great security platforms and this is setting up an epic battle between hot startups that are growing very very quickly and entrenched incumbents that really aren't going to go down without a fight finally while security is clearly a top spending priority customers and their cfos continue to be somewhat circumspect with respect to how much they allocate toward security budgets especially in the context of a shrinking i.t spending climate that we have said is dropping between five and eight percent in 2020. now security is critical but even in these times spending is governed by these tight budgets well cyber remains a top category in the etr taxonomy in terms of its presence in the data set what this chart tells us is that cios and i.t buyers have other priorities that they have to fund this data shows a comparison of net scores over three survey dates october of last year april and july net score remember is an indicator of momentum which is calculated by subtracting the percent of customers spending less on the technology from those spending more it's more complicated than that but that's that's the basics and you can see that at a 29 net score the security sector is just one of many priorities that i.t buyers face now remember this is the july survey and it's asking customers are you planning to spend more or less in the second half of 2020 relative to the first half and it's a forward-looking metric so what may be happening here is that the height of the lockdown and in the u.s anyway and the pivot to work from home organizations were spending heavily and are now fine-tuning those investments and maybe addressing other digital priorities let's look back and do some pre and post-covet assessments of various players within the etr data set i'm gonna go fairly quickly through these next slides but i want to give you a perspective as to how the security landscape and the vendor momentum has changed in the past eight months first i'm going to take you back to the january data set we actually originally did this exercise last year and then we updated it right at the beginning of 2020. the chart shows the top-ranked cyber security companies based on two metrics the left-hand side sorts the data and ranks companies based on net score or spending momentum and the right-hand side shows the ranking by shared n which is a measure of the pervasiveness of a company in the data set i.e the number of mentions that they get in the sector and what we did is we gave four stars to those companies that showed up in the top of both of those rankings and two stars to those that were close so you can see that microsoft splunk palo alto and proofpoint as well as octa and crowdstrike and then we added z scalar in january as new and then cyber arc software all got four stars then we gave cisco and fortinet two stars now this next chart shows the same thing at the height of the u.s lockdown now you may say okay what's the difference there's still microsoft palo alto proof point octa cyber arc z scaler and crowdstrike at four stars with cisco and fortnite having two star stars splunk fell off but that's it well what's different is instead of making the cut the top 22 which we did last time we narrowed it down to the top ten in order for a company to make that grade so if we had done that in january octa crowdstrike zscaler and cyberark they wouldn't have made the cut but in april they did as their presence in the dataset grew and we strongly believe this is a direct result of the work from home pivot crowdstrike endpoint octa identity access management z-scaler cloud security and they're disrupting traditional appliance-based firewalls now just to note we placed dell emc which was rsa and ibm in the list just for context now let's take a look at the most recent july survey now a lot of i'm out on a limb a little bit here because many of these companies they haven't reported yet so we don't have full visibility on their business outlook but we show the same data for the most recent survey the red line that you see there is the top 10 cutoff point and you can see splunk which didn't make the cut in april is back on the four-star list it's very possible buyers took a pause last quarter and focused attention on work from home but splunk continues to impress as it shifts toward the subscription model that we've talked about in the past splunk has a very strong hold on the sim space but everyone wants a piece of splunk especially some of the traditional firewall companies who they're seeing their hardware business dying so we're watching the competition from these players but also some other players like tennable now proof point fell off the four-star list because its net score didn't make the top ten crowdstrike cyber arc and zscaler also fell back because they dropped below the top 10 in shared in but we still really like these companies and expect them to continue to do well you know it could be some anomalies in the survey but we're trying to be as transparent as possible with you share the data listen to it interpret it and really adjust our models accordingly each quarter now let me make a few points and try to interpret what might be happening here first i want to point out octa pops to the top of the net score ranking overtaking crowdstrike's momentum from the last survey now one customer in the financial services sector told eric bradley on a recent then we're seeing amazing things from octa but the traditional firewall companies are stepping into identity they may not be best of breed but they have a level of integration and that's appealing to this individual this person also specifically called out palo alto and fortinet is trying to encroach on that space so keep your eyes on that now crowdstrike has declined noticeably which surprised us z z scalar is actually showing more momentum relative to the last survey so that's a positive palo alto and microsoft are consistently holding serve and continue to be leaders proof point and cyber arc are showing a bit of a velocity drop and sales point and tenable are also catching our attention in this survey and of course sales sale point which is identity management had a great quarter and reinstituted its guidance giving us the benefit of hindsight on its performance so it was actually pretty easy to give them two stars now just a side note by the way we've cut the data here with those companies that have more than 50 mentions in the sector we didn't do that the first time we did this we allowed companies with less than 50. so we're trying to tighten that up a bit so we still maintain strongly that you're seeing cloud endpoint and identity as the big security themes here csos need tools to be responsive they don't want to just get an alert secops pros would rather immediately shut off access and risk pissing off a user than getting hacked and companies are increasingly turning to ai to detect and they're relying on automation to remediate or protect and fence off critical resources let's now look at the two players or players in our two-dimensional view followers of this program know that we like to plot vendors within a sector across two of our favorite metrics net score or spending momentum which is a simple metric that tracks those spending more versus less on the technology and market share which measu measures a vendor's pervasiveness in the data set and it's calculated by taking the number of mentions a vendor gets within a sector divided by the total responses what we show here are the key security players that we've highlighted over the last several quarters let me start with microsoft microsoft has consistently performed well in the security sector as well as other parts of the etr taxonomy as you know they have a huge presence in the survey which is indicated on the horizontal axis and you can see they have a very solid net score which is shown on the y-axis impressive for a company their size now one interesting thing is you don't see aws in this chart and it's because aws and microsoft at least so far have somewhat different strategies with respect to security microsoft with its long application software history and sas presence across office 365 and sharepoint etc with active directory has been really focused on selling security solutions to directly protect its apps they have offerings like defender atp which is advanced threat protection sentinel which is microsoft sim cloud offering azure identity access management and the company's really going hard after this space now aws of course prioritizes security but they don't show an etr data set the same way microsoft does it's almost like aws is hiding in plain sight look aws has always put a great deal of emphasis on security and securing its infrastructure like the s3 buckets and it's you know it announced iam for ec2 way back in 2012. and last year at its reinforced conference you saw an impressive focus on security in a burgeoning security ecosystem in fact when you think of getting started in aws you really think about three things ec2 s3 and iam so i'd expect to see aws really become more prominent over time in the data set now i'll spend a minute talking about octa for the first time since we've been analyzing the security space with etr data octa has the highest net score at 58 percent it had consistently been crowdstrike with this moniker and the momentum lead the company though is dropped in this quarter survey and that's something that we're watching and by the way we're not implying that octa and crowdstrike are direct competitors they're not now as you can see nonetheless that crowdstrike z scalar and sales point sale sale point show very elevated net scores and we've plotted tenable here which is also showing some strength so you can see the respective positions of proof point and fortinet these are more mature companies they were founded in the early part of the century so you'd expect them to have somewhat lower net scores given their history and maturity and then there's cisco they've got a huge presence in the data and big in security cisco's doing really well in that space it consistently grows its security business in the double digits each quarter and it's a real feather in the cisco portfolio cap this is important because cisco's traditional hardware business continues to come under pressure splunk we talked about a lot and it's no surprise at their leadership position but i want to talk a little bit more about palo alto networks here's a company that we've talked about quite a bit in the past they are a tier one player in security they got great service csos want to work with them because they are thought leaders they're like a gold standard and have an impressive portfolio of great solutions but their traditional firewall business is coming under pressure for the reasons that we discussed earlier now palo alto has expanded its portfolio into the cloud and with prisma the company's suite of security services it will maintain a leadership position in our view but palo alto networks as we've discussed had some missteps with its product transition its sales execution and some of some challenges with its pricing models and it hurt their stock price but we've always said that they would work through these issues and that that was a buying opportunity the other thing about palo alto is you know they're considered the expensive choice you got to pay for that gold standard but that's what customers you know will tell us and so you're paying up for those top tier offerings but that's a sort of two-edged sword for palo alto here's an example why people often compare fortinet to palo alto and as we've shared in previous segments the valuation divergence between palo alto and fortinet where the the latter was making a smoother transition to its future and people often tell us that fortinet well you know maybe it's considered not as elite as palo alto they are a value choice their stuff just works and fortinet is a great alternative to palo alto and that has served them very well now let's take a closer look at the valuations of some of these companies we started off this segment by saying that the pandemic has affected every sector and especially cyber security so the next chart that we're showing here is the progression of key valuation metrics since earlier this year what we show are the valuations of nine of the companies in the sector since mid-february the data tracks their respective valuations their revenue multiples their growth rates in both value and revenue revenue growth is shown in the last column for the most recent quarterly report now the companies in red have yet to report the report any day now so he said i'm flying a little bit blind here and we'll have to take a look after the earnings to see how the survey data aligns with the actual results but let me make a few points here first here's the s p in nasdaq performance you see it in february in june and august pandemic recession what are you talking about you'd never know it looking at this data the nasdaq especially is up 14 said since mid february which is quite astounding next i want to come back to the discussion about palo alto and fortinet fortinet already has reported this quarter and palo alto has not but you can see based on the revenue multiples highlighted in red that the valuation divergence is starting to shrink a little bit and we'll see if that holds up after palo alto reports now the big eye popper in this chart is the valuation increases from february to august for octa crowdstrike and z scalar 52 67 and 104 percent increase respectively now you can't say we didn't warn you that these companies were all well positioned when we reported last year and in our january episode but i did say actually to be honest in the last episode that these three i thought were getting a little expensive that was a couple months ago and since then they've continued to run up so if you've been waiting for an entry point based on my advice well i'm sorry for that but look at the revenue multiples look at the expansion in the orange octa goes from 34x to 52x crowdstrike from 39x to 66x z scalar 25x to 43x i mean wow let's see what happens after these three report by this time i would have hoped that they'd taken a little breather maybe over the summer and you could have jumped in to these stocks but they just keep going up and despite the decline in net score for crowdstrike i still really like all three of these companies and feel that they're very well positioned from a product standpoint and customer feedback perspective and finally i want to mention sale point which we said last time was one to watch sale point crushed its quarter bringing in some large deals and providing forward guidance nearly a 50 percent valuation increase since february in a revenue multiple expansion from last quarter where the street last quarter wasn't really thrilled with their numbers but identity management is hot and so now is sales point from the streets perspective the last thing i'll say here is watch the growth rates expectations are very high for some of these companies and the street will cream any of them that misses now that may be your opportunity to jump in because i like these companies i think they're disruptors but as always do your research and watch out for the big whales trying to freeze the markets on these guys all right let's wrap up we've covered a lot of ground today and surf the landscape a little bit so look the trend is plain as day the move to sas is entrenched and by the way this isn't necessarily all good news for buyers cios and cfos tell me that the dark side of capex to opex is unpredictable bills but the flexibility and business value gained is outweighing the downside and every vendor in this space is transitioning into a sas and annual recurring revenue model we believe the remote work trend is here to stay organizations are re-architecting their business around work from home and we think that they're seeing some real benefits they've made investments and it's driving new modes of work and productivity they're not just going to throw away those investments why should they what just to go back to the old way it's not going to happen and if we as we've said previously look the internet it's like the new private network so you've got a question vpns and sd-wan they start to look like stop gaps and of course you know the cloud endpoint security cloud-based iam they are clearly winning in the marketplace you know we're also seeing new security regimes emerge where the cso and the secops team are not this island we we've seen even some csos falling back under the cio which used to be taboo he used to be thought of that's like the fox guarding the hen house but this idea of shared responsibility is not just between the cloud providers and the secops teams because security is a board level priority everyone in the business is becoming more aware more attuned and despite the millennials fascination with and undotted courage when it comes to tick tock i digress now the last two points are interesting i remember reading a post by john oltzek who was an esg security analyst and he predicted last year that integrated suites would win out over the buffet of point products on the market and you know generally i i agreed with that assessment but look at least in the near term and probably mid-term that doesn't seem to be happening as we we've seen these hot companies really take off the ones that we've highlighted now these companies have ambitions beyond selling products and they would bristle at me lumping them into point products their boards are going after platform plays so they're on a collision course with each other and the big guys this should be fun to watch because the big integrated companies are well funded they got great cash flow they got large customer bases and and i've said they're not going down without a fight so i would expect eventually there's going to be more of an equilibrium to what seems to be right now a bifurcated and unbalanced market today so you're going to see more m a activity expect that however at these valuations some of these companies that we've highlighted they're becoming acquisition proof as such they'd better keep innovating or they're going to be in big trouble all right that's it for today remember these episodes are all available as podcasts wherever you listen so please subscribe i publish weekly on wikibon.com we've added in the wikibon menu bar a breaking analysis link that has all the episodes in there i also publish on siliconangle.com so check that out and please do comment on my linkedin posts don't forget to check out etr.plus for all the survey action get in touch on twitter i'm at d vellante or email me at david.vellante at siliconangle.com this is dave vellante for the cube insights powered by etr thanks for watching everybody be well and we'll see you next time [Music] you

>>from around the globe. It's the Cube with digital coverage of CONMEBOL. Future ready 2020. Brought to you by combo. >>Hi and welcome back. I'm Stew Minuteman, and we're at the Cube's coverage of Con Volt Future Ready. You've got the power panel to really dig in on the product announcements that happened at the event today. Joining me? We have three guests. First of all, we have Brenda Rajagopalan. He's the vice president of products. Sitting next to him is Don Foster, vice president of Storage Solutions. And in the far piece of the panel Mersereau, vice president of Global Channels and Alliances. All three of them with Conn Volt. Gentlemen, thanks all three of you for joining us. Exactly. All right, so first of all, great job on the launch. You know, these days with a virtual event doing, you know, the announcements, the engagement with the press and analyst, you know, having demos, customer discussions. It's a challenge to put all those together. And it has been, you know, engaging in interesting watch today. So we're going to start with you. You've been quite busy today explaining all the pieces, so just at a very high level if you put this really looks like the culmination of the update with Conn Volt portfolio new team new products compared to kind of a year, year and 1/2 ago. So just if you could start us off with kind of the high points, >>thank you still, yeah, absolutely exciting day for us today. You did comrade multiple reasons for that excitement and go through that we announced an exciting new portfolio today knows to not the culmination. It's a continuation off our journey, a bunch of new products that we launched today Hyper scaler X as a new integrated data protection appliance. We've also announced new offerings in data protection, backup and recovery, disaster recovery and complete data protection and lots of exciting updates for Hedwig and a couple of weeks like we introduced updates for metallic. So, yes, it's been a really exciting pain. Also, today happens to be the data, and we got to know that we are the leader in Gartner Magic Quadrant for the ninth consecutive. I am so a lot of goodness today for us. >>Excellent. Lots of areas that we definitely want to dig deep in to the pieces done. You know, we just heard a little bit about Hedvig was an acquisition a year ago that everybody's kind of looking at and saying Okay, you know, will this make them compete against some of their traditional partners? How we get integrated in So, baby, just give us one level deeper on the Hedvig piece on what that means to the portfolio? Yeah, sure, So I >>guess I mean, one of the key things that the random mentioned was the fact that had hyper scale that's is built off the head Day files. So that's a huge milestone for us. As we teased out maybe 10 months ago. Remember, Tomball, Go on the Cube and talking about, you know, kind of what our vision and strategy was of unifying data and storage management. Those hyper hyper scale X applying is a definite milestone improving out that direction. But beyond just the hyper scale ECs, we've also been driving on some of the more primary or modern workloads such as containers and the really interesting stuff we've come out with your recently is the kubernetes native integration that ties in all of the advanced component of the head to distribute storage architecture on the platform itself across multi cloud and on premise environments, making it really easy and policy driven. Um, for Dev, ops users and infrastructure users, the tie ins applications from a group, Friction >>Great and Mercer. There's some updates to the partner program and help us understand how all of these product updates they're gonna affect the kind of the partnerships and alliances beasts that you want. >>Absolutely. So in the time since our last meeting that go in the fall, which is actually right after I had just doing combo, we spent a good portion of the following six months really talking with partners, understanding the understand the impact of the partner program that we introduced last summer, looking at the data and really looking at barriers to evolve the program, which fell around three difference specific. Once you bet one was simplicity of the simplicity of the program, simplicity of understanding, rewards, levers and so forth. The second was paying for value was really helping, helping our partners to be profitable around things like deal registration on other benefits and then third was around co investment. So making sure that we get the right members in place to support our partners and investing in practices. Another training, another enablement around combo and we launched in over these things last week is a part of an evolution of that program. Today is a great follow on because in addition to all of the program evolutions that we we launched last week now we have an opportunity with our partners to have many more opportunities or kind of a thin into the wedge to open up new discussions with our customers now around all of these different use cases and capabilities. So back to that simplification angle, really driving more and more opportunities for those partners toe specific conversations around use cases. >>Okay, for this next question, I think it makes sense for you to start. Maybe maybe Don, you can get some commentary in two. But when he's firstly the announcements, there are some new products in the piece that you discuss but trying to understand, you know, when you position it, you know, do you call the portfolio? Is it a platform? You know, if I'm an existing Conn Volt customer, you know, how do I approach this? If I use something like metallic, how does that interplay with some of the new pieces that were discussed today. >>Sure, I can take the business. I'm sure Don and mostly will have more data to it. The simplest way to think about it is as a port for you. But contrary to how you would think about portfolio as independent products, what we have is a set off data management services granular. We're very aligned to the use case, which can all inter operate with each other. So maybe launched backup and recovery and disaster recovery. These can be handled separately, purchased separately and deployed standalone or for customers who want a combination of those capabilities. We also have a complete data protection are fine storage optimization, data governance E discovery in complaints are data management services that build on top off any of these capabilities now a very differentiating factor in our platform owners. All the services that you're talking about are delivered off the same software to make it simpler to manage to the same year. So it's very easy to start with one service and then just turn on the license and go to other services so I can understand the confusion is coming from but it's all the same. The customer simplicity and flexibility in mind, and it's all delivered off the same platform. So it is a portfolio built on a single Don. Would you like to add more to it? >>Yeah, I think the interesting thing due to add on top of that is where we're going with Hedvig Infrastructure, the head of distributed storage platform, uh, to to run this point, how everything is integrated and feed and work off of one another. That's the same idea that we have. We talked about unifying data and storage manager. So the intricate storage architecture components the way data might be maneuvered, whether it's for kubernetes for virtual machines, database environments, secondary storage, you name it, um, we are. We're quickly working to continue driving that level of of unification and integration between the portfolio and heads storage, distribute storage platforms and also deliver. So what you're seeing today going back to, I think wrong his first point. It's definitely not the culmination. It's just another step in the direction as we continue to innovate and integrate this >>product, and I think for our partners what this really does, it allows them to sell around customer use cases because it'll ask now if I have a d. Our use case. I can go after just PR. If I have a backup use case, I can just go after backup, and I don't have to try to sell more than that. Could be on what the customer is looking for in parallel that we can steal these things in line with the customer use case. So the customer has a lot of remote offices. They want to scale Hedvig across those they want to use the art of the cloud. They can scale these things independently, and it really gives us a lot of optionality that we didn't have before when we had a few monolithic products. >>Excellent. Really reminds me more of how I look at products if I was gonna go buy it from some of the public cloud providers living in a hybrid cloud. World, of course, is what your customers are doing. Help us understand a little bit, you know, Mercer talked about metallic and the azure partnership, but for the rest of the products, the portfolio that we're talking about, you know, does this >>kind >>of work seamlessly across my own data center hosting providers Public Cloud, you know, how does this fit into the cloud environment for your customer? >>Yes, it does. And I can start with this one goes to, um it's our strategy is cloud first, right? And you see it in every aspect of our product portfolio. In fact, I don't know if you got to see a keynote today, but Ron from Johns Hopkins University was remarking that comment has the best cloud native architectures. And that's primarily because of the innovation that we drive into the multi cloud reality. We have very deep partnerships with pretty much all the cloud vendors, and we use that for delivering joint innovation, a few things that when you think of it from a hybrid customers perspective, the most important need for them is to continue working on pram while still leveraging the cloud. And we have a lot of optimization is built into that, and then the next step of the journey is of course, making sure that you can recover to the cloud would be it work load. Typically your data quality and there's a lot of automation that we provide to our solutions and finally, Of course, if you're already in the cloud, whether you're running a science parents or cloud native, our software protects across all those use cases, either true sass with metallic auto downloadable software, backup and recovery so we can cover the interest victims of actual presence. You. We do definitely help customers in every stage of their hybrid cloud acceleration journey. >>And if you take a look at the Hedvig protect if you take a look at the head back to, um, the ability to work in a cloud native fast, it is essentially a part of the DNA of that storage of the storage, right? So whether you're running on Prem, whether you're running it about adjacent, set up inside the cloud head, that can work with any compute environment and any storage environment that you went to essentially then feed, we build this distributed storage, and the reason that becomes important. It's pretty much highlighted with our announcement around the kubernetes and container support is that it makes it really easy to start maneuvering data from on Prem to the cloud, um, from cloud to cloud region to region, sort of that high availability that you know as customers make cloud first a reality and their organizations starts to become a critical requirement or ensuring the application of and some of the things that we've done now with kubernetes in making all of our integration for how we deliver storage for the kubernetes and container environments and being that they're completely kubernetes native and that they can support a Google in AWS and Azure. And of course, any on premises community set up just showcases the value that we can provide in giving them that level of data portability. And it basically provides a common foundation layer, or how any sort of the Dev ops teams will be operating in the way that those state full container state workloads. Donna Oh, sorry. Go >>ahead, mark area >>because you mentioned the metallic and azure partnership announcement and I just want to get on that. And one thing that run dimension, which is we are really excited about the announcement of partnership with Microsoft and all the different news cases that opens up that are SAS platform with Azure with office 3 65 and all of the great application stack it's on. If you're at the same time, to run this point. We are a multi cloud company. And whether that is other of the hyper scale clouds Mess GC, P. Ali at Oracle and IBM, etcetera, or Oliver, Great service writer burners. We continue to believe in customer choice, and we'll continue to drive unique event innovations across all of those platforms. >>All right, Don, I was wondering if we could just dig in a little bit more on some other kubernetes pieces you were talking about. Let me look at just the maturation of storage in general. You know, how do we had state back into containers in kubernetes environments? Help us see, You know what you're hearing from your customers. And you know how you how you're ready to meet their needs toe not only deliver storage, but as you say, Really? You know, full data protection in that environment? >>Certainly it So I mean, there's been a number of enhancements that happened in the kubernetes environment General over the last two years. One of the big ones was the creation of what the visit environment calls a persistent volume. And what that allows you to do is to really present storage to a a communities application. Do it be typically through what's called a CSR container storage interface that allows for state full data to be written, storage and be handled and reattached applications as you leverage them about that kubernetes. Um, as you can probably imagine that with the addition of the additional state full applications, some of the overall management now of stateless and state collapse become very talent. And that's primarily because many customers have been using some of the more traditional storage solutions to try to map that into these new state. Full scenario. And as you start to think about Dev ops organization, most Dev ops organizations want to work in the environment of their choice. Whether that's Google, whether that's AWS, Microsoft, uh, something that might be on Prem or a mix of different on Prem environments. What you typically find, at least in the kubernetes world, is there's seldom ever one single, very large kubernetes infrastructure cluster that's set to run, Dev asked. The way and production all at once. You usually have this spread out across a fairly global configuration, and so that's where some of these traditional mechanisms from traditional storage vendors really start to fall down because you can apply the same level of automation and controls in every single one of those environments. When you don't control the storage, let's say and that's really where interfacing Hedvig and allowing that sort of extension distribute storage platform brings about all of this automation policy control and really storage execution definition for the state. Full statehood workloads so that now managing the stateless and the state full becomes pretty easy and pretty easy to maintain when it comes to developing another Dev branch or simply trying to do disaster recovery or a J for production, >>any family actively do. That's a very interesting response, and the reality is customers are beginning to experiment with business. Very often they only have a virtual environment, and now they're also trying to expand into continuous. So Hedwig's ability to service primary storage for virtualization as well as containers actually gives their degree of flexibility and freedom for customers to try out containers and to start their contingent. Thank you familiar constructs. Everything is mellow where you just need to great with continuous >>Alright, bring a flexibility is something that I heard when you talk about the portfolio and the pricing as to how you put these pieces together. You actually talked about in the presentation this morning? Aggressive pricing. If you talk about, you know, kind of backup and recovery, help us understand, You know, convo 2020 how you're looking at your customers and you know how you put together your products, that to meet what they need at that. As you said, aggressive pricing? >>Absolutely. And you use this phrase a little bit earlier is to blow like flexibility. That's exactly what we're trying to get to the reason why we are reconstructing our portfolio so that we have these very granular use case aligned data management services to provide the cloud like flexibility. Customers don't have the same data management needs all the time. Great. So they can pick and choose the exact solution that need because there are delivered on the same platform that can enable out the solution investment, you know, And that's the reality. We know that many of our customers are going to start with one and keep adding more and more services, because that's what we see as ongoing conversations that gives us the ability to really praise the entry products very aggressively when compared to competition, especially when we go against single product windows. This uses a lot of slammed where we can start with a really aggressively priced product and enable more capabilities as we move forward to give you an idea, we launched disaster recovery today. I would say that compared to the so the established vendors India, we would probably come in at about 25 to 40% of the Priceline because it depends on the environment and what not. But you're going to see that that's the power of bringing to the table. You start small and then depending on what your needs are, you have the flexibility to run on either. More data management capabilities are more workloads, depending on what your needs will be. I think it's been a drag from a partner perspective, less with muscle. If you want a little bit more than that, >>yes, I mean, that goes back to the idea of being ableto simply scale across government use functionality. For example, things like the fact that our disaster recovery offering the Newman doesn't require backup really allows us to have those Taylor conversations around use cases, applications >>a >>zealous platforms. You think about one of the the big demands that we've had coming in from customers and partners, which is help me have a D R scenario or a VR set up in my environment that doesn't require people to go put their hands on boxes and cables, which was one of those things that a year ago we were having. This conversation would not necessarily have been as important as it is now, but that ability to target those specific, urgent use cases without having to go across on sort of sell things that aren't necessarily associated with the immediate pain points really makes those just makes us ineffective. Offer. >>Yeah, you bring up some changing priorities. I think almost everybody will agree that the number one priority we're hearing from customers is around security. So whether I'm adopting more cloud, I'm looking at different solutions out there. Security has to be front and center. Could we just kind of go down the line and give us the update as to how security fits and all the pieces we've been discussing? >>I guess I'm talking about change, right, so I'll start. The security for us is built into everything that we do the same view you're probably going to get from each of us because security is burden. It's not a board on, and you would see it across a lot of different images. If you take our backup and recovery and disaster recovery, for instance, a lot of ransomware protection capabilities built into the solution. For instance, we have anomaly detection that is built into the platform. If we see any kind of spurious activity happening all of a sudden, we know that that might be a potential and be reported so that the customer can take a quick look at air Gap isolation, encryption by default. So many features building. And when you come to disaster recovery, encryption on the wire, a lot of security aspects we've been to every part of the portfolio don't. >>Consequently, with Hedvig, it's probably no surprise that when that this platform was developed and as we've continued development, security has always been at the core of what we're doing is stored. So what? It's for something as simple as encryption on different volume, ensuring the communication between applications and the storage platform itself, and the way the distributors towards platform indicates those are all incredibly secured. Lock down almost such for our own our own protocols for ensuring that, um, you know, only we're able to talk within our own, our own system. Beyond that, though, I mean it comes down to ensure that data in rest data in transit. It's always it's always secure. It's also encrypted based upon the level of control that using any is there one. And then beyond just the fact of keeping the data secure. You have things like immutable snapshots. You have declared of data sovereignty to ensure that you can put essentially virtual fence barriers for where data can be transported in this highly distributed platform. Ah, and then, from a user perspective, there's always level security for providing all seeking roll on what groups organization and consume storage or leverage. Different resource is the storage platform and then, of course, from a service provider's perspective as well, providing that multi tenanted access s so that users can have access to what they want when they want it. It's all about self service, >>and the idea there is that obviously, we're all familiar with the reports of increased bad actors in the current environment to increased ransomware attacks and so forth. And be a part of that is addressed by what wrong and done said in terms of our core technology. Part of that also, though, is addressed by being able to work across platforms and environments because, you know, as we see the acceleration of state tier one applications or entire data center, evacuations into service provider or cloud environments has happened. You know, this could have taken 5 10 years in a in a normal cycle. But we've seen this happen overnight has cut this. Companies have needed to move those I T environments off science into managed environments and our ability to protect the applications, whether they're on premises, whether they're in the cloud or in the most difficult near where they live. In both cases, in both places at once, is something that it's really important to our customers to be able to ensure that in the end, security posture >>great Well, final thing I have for all three of you is you correctly noted that this is not the end, but along the journey that you're going along with your customers. So you know, with all three of you would like to get a little bit. Give us directionally. What should we be looking at? A convo. Take what was announced today and a little bit of look forward towards future. >>Directionally we should be looking at a place where we're delivering even greater simplicity to our customers. And that's gonna be achieved through multiple aspects. 1st 1 it's more technologies coming together. Integrating. We announced three important integration story. We announced the Microsoft partnership a couple of weeks back. You're gonna see us more longer direction. The second piece is technology innovation. We believe in it. That's what Differentiators has a very different company and we'll continue building it along the dimensions off data awareness, data, automation and agility. And the last one continued obsession with data. What more can we do with it? How can we drive more insights for our customers We're going to see is introducing more capabilities along those dimensions? No. >>And I think Rhonda tying directly into what you're highlighting there. I'm gonna go back to what we teased out 10 months ago at calm Bolt. Go there in Colorado in this very on this very program and talk about how, in the unification of ah ah, data and storage management, that vision, we're going to make more and more reality. I think the, uh, the announcements we've made here today let some of the things that we've done in between the lead up to this point is just proof of our execution. And ah, I can happily and excitedly tell you, we're just getting warmed up. It's going to be, ah, gonna be some fun future ahead. >>And I think studio in the running that out with the partner angle. Obviously, we're going to continue to produce great products and solutions that we're going to make our partners relevant. In those conversations with customers, I think we're also going to continue to invest in alternative business models, services, things like migration services, audit services, other things that build on top of this core technology to provide value for customers and additional opportunities for our partners >>to >>build out their their offerings around combo technologies. >>All right, well, thank you. All three of you for joining us. It was great to be able to dig in, understand those pieces. I know you've got lots of resources online for people to learn more. So thank you so much for joining us. Thank you too. Thank you. Alright, and stay with us. So we've got one more interview left for the Cube's coverage of con vault. Future Ready, students. Mannan. Thanks. As always for watching the Cube. Yeah, Yeah, yeah, yeah, yeah, yeah