>>In 2011, early Facebook employee and Cloudera co-founder Jeff Ocker famously said the best minds of my generation are thinking about how to get people to click on ads. And that sucks. Let's face it more than a decade later organizations continue to be frustrated with how difficult it is to get value from data and build a truly agile data-driven enterprise. What does that even mean? You ask? Well, it means that everyone in the organization has the data they need when they need it. In a context that's relevant to advance the mission of an organization. Now that could mean cutting cost could mean increasing profits, driving productivity, saving lives, accelerating drug discovery, making better diagnoses, solving, supply chain problems, predicting weather disasters, simplifying processes, and thousands of other examples where data can completely transform people's lives beyond manipulating internet users to behave a certain way. We've heard the prognostications about the possibilities of data before and in fairness we've made progress, but the hard truth is the original promises of master data management, enterprise data, warehouses, data marts, data hubs, and yes, even data lakes were broken and left us wanting from more welcome to the data doesn't lie, or doesn't a series of conversations produced by the cube and made possible by Starburst data. >>I'm your host, Dave Lanta and joining me today are three industry experts. Justin Borgman is this co-founder and CEO of Starburst. Richard Jarvis is the CTO at EMI health and Theresa tongue is cloud first technologist at Accenture. Today we're gonna have a candid discussion that will expose the unfulfilled and yes, broken promises of a data past we'll expose data lies, big lies, little lies, white lies, and hidden truths. And we'll challenge, age old data conventions and bust some data myths. We're debating questions like is the demise of a single source of truth. Inevitable will the data warehouse ever have featured parody with the data lake or vice versa is the so-called modern data stack, simply centralization in the cloud, AKA the old guards model in new cloud close. How can organizations rethink their data architectures and regimes to realize the true promises of data can and will and open ecosystem deliver on these promises in our lifetimes, we're spanning much of the Western world today. Richard is in the UK. Teresa is on the west coast and Justin is in Massachusetts with me. I'm in the cube studios about 30 miles outside of Boston folks. Welcome to the program. Thanks for coming on. Thanks for having us. Let's get right into it. You're very welcome. Now here's the first lie. The most effective data architecture is one that is centralized with a team of data specialists serving various lines of business. What do you think Justin? >>Yeah, definitely a lie. My first startup was a company called hit adapt, which was an early SQL engine for hit that was acquired by Teradata. And when I got to Teradata, of course, Teradata is the pioneer of that central enterprise data warehouse model. One of the things that I found fascinating was that not one of their customers had actually lived up to that vision of centralizing all of their data into one place. They all had data silos. They all had data in different systems. They had data on prem data in the cloud. You know, those companies were acquiring other companies and inheriting their data architecture. So, you know, despite being the industry leader for 40 years, not one of their customers truly had everything in one place. So I think definitely history has proven that to be a lie. >>So Richard, from a practitioner's point of view, you know, what, what are your thoughts? I mean, there, there's a lot of pressure to cut cost, keep things centralized, you know, serve the business as best as possible from that standpoint. What, what is your experience show? >>Yeah, I mean, I think I would echo Justin's experience really that we, as a business have grown up through acquisition, through storing data in different places sometimes to do information governance in different ways to store data in, in a platform that's close to data experts, people who really understand healthcare data from pharmacies or from, from doctors. And so, although if you were starting from a Greenfield site and you were building something brand new, you might be able to centralize all the data and all of the tooling and teams in one place. The reality is that that businesses just don't grow up like that. And, and it's just really impossible to get that academic perfection of, of storing everything in one place. >>Y you know, Theresa, I feel like Sarbanes Oxley kinda saved the data warehouse, you know, right. You actually did have to have a single version of the truth for certain financial data, but really for those, some of those other use cases, I, I mentioned, I, I do feel like the industry has kinda let us down. What's your take on this? Where does it make sense to have that sort of centralized approach versus where does it make sense to maybe decentralized? >>I, I think you gotta have centralized governance, right? So from the central team, for things like star Oxley, for things like security for certainly very core data sets, having a centralized set of roles, responsibilities to really QA, right. To serve as a design authority for your entire data estate, just like you might with security, but how it's implemented has to be distributed. Otherwise you're not gonna be able to scale. Right? So being able to have different parts of the business really make the right data investments for their needs. And then ultimately you're gonna collaborate with your partners. So partners that are not within the company, right. External partners, we're gonna see a lot more data sharing and model creation. And so you're definitely going to be decentralized. >>So, you know, Justin, you guys last, geez, I think it was about a year ago, had a session on, on data mesh. It was a great program. You invited Jamma, Dani, of course, she's the creator of the data mesh. And her one of our fundamental premises is that you've got this hyper specialized team that you've gotta go through. And if you want anything, but at the same time, these, these individuals actually become a bottleneck, even though they're some of the most talented people in the organization. So I guess question for you, Richard, how do you deal with that? Do you, do you organize so that there are a few sort of rock stars that, that, you know, build cubes and, and the like, and, and, and, or have you had any success in sort of decentralizing with, you know, your, your constituencies, that data model? >>Yeah. So, so we absolutely have got rockstar, data scientists and data guardians. If you like people who understand what it means to use this data, particularly as the data that we use at emos is very private it's healthcare information. And some of the, the rules and regulations around using the data are very complex and, and strict. So we have to have people who understand the usage of the data, then people who understand how to build models, how to process the data effectively. And you can think of them like consultants to the wider business, because a pharmacist might not understand how to structure a SQL query, but they do understand how they want to process medication information to improve patient lives. And so that becomes a, a consulting type experience from a, a set of rock stars to help a, a more decentralized business who needs to, to understand the data and to generate some valuable output. >>Justin, what do you say to a, to a customer or prospect that says, look, Justin, I'm gonna, I got a centralized team and that's the most cost effective way to serve the business. Otherwise I got, I got duplication. What do you say to that? >>Well, I, I would argue it's probably not the most cost effective and, and the reason being really twofold. I think, first of all, when you are deploying a enterprise data warehouse model, the, the data warehouse itself is very expensive, generally speaking. And so you're putting all of your most valuable data in the hands of one vendor who now has tremendous leverage over you, you know, for many, many years to come. I think that's the story at Oracle or Terra data or other proprietary database systems. But the other aspect I think is that the reality is those central data warehouse teams is as much as they are experts in the technology. They don't necessarily understand the data itself. And this is one of the core tenants of data mash that that jam writes about is this idea of the domain owners actually know the data the best. >>And so by, you know, not only acknowledging that data is generally decentralized and to your earlier point about SAR, brain Oxley, maybe saving the data warehouse, I would argue maybe GDPR and data sovereignty will destroy it because data has to be decentralized for, for those laws to be compliant. But I think the reality is, you know, the data mesh model basically says, data's decentralized, and we're gonna turn that into an asset rather than a liability. And we're gonna turn that into an asset by empowering the people that know the data, the best to participate in the process of, you know, curating and creating data products for, for consumption. So I think when you think about it, that way, you're going to get higher quality data and faster time to insight, which is ultimately going to drive more revenue for your business and reduce costs. So I think that that's the way I see the two, the two models comparing and contrasting. >>So do you think the demise of the data warehouse is inevitable? I mean, I mean, you know, there Theresa you work with a lot of clients, they're not just gonna rip and replace their existing infrastructure. Maybe they're gonna build on top of it, but what does that mean? Does that mean the E D w just becomes, you know, less and less valuable over time, or it's maybe just isolated to specific use cases. What's your take on that? >>Listen, I still would love all my data within a data warehouse would love it. Mastered would love it owned by essential team. Right? I think that's still what I would love to have. That's just not the reality, right? The investment to actually migrate and keep that up to date. I would say it's a losing battle. Like we've been trying to do it for a long time. Nobody has the budgets and then data changes, right? There's gonna be a new technology. That's gonna emerge that we're gonna wanna tap into. There's going to be not enough investment to bring all the legacy, but still very useful systems into that centralized view. So you keep the data warehouse. I think it's a very, very valuable, very high performance tool for what it's there for, but you could have this, you know, new mesh layer that still takes advantage of the things. I mentioned, the data products in the systems that are meaningful today and the data products that actually might span a number of systems, maybe either those that either source systems for the domains that know it best, or the consumer based systems and products that need to be packaged in a way that be really meaningful for that end user, right? Each of those are useful for a different part of the business and making sure that the mesh actually allows you to use all of them. >>So, Richard, let me ask you, you take, take Gemma's principles back to those. You got to, you know, domain ownership and, and, and data as product. Okay, great. Sounds good. But it creates what I would argue are two, you know, challenges, self-serve infrastructure let's park that for a second. And then in your industry, the one of the high, most regulated, most sensitive computational governance, how do you automate and ensure federated governance in that mesh model that Theresa was just talking about? >>Well, it absolutely depends on some of the tooling and processes that you put in place around those tools to be, to centralize the security and the governance of the data. And I think, although a data warehouse makes that very simple, cause it's a single tool, it's not impossible with some of the data mesh technologies that are available. And so what we've done at emus is we have a single security layer that sits on top of our data match, which means that no matter which user is accessing, which data source, we go through a well audited well understood security layer. That means that we know exactly who's got access to which data field, which data tables. And then everything that they do is, is audited in a very kind of standard way, regardless of the underlying data storage technology. So for me, although storing the data in one place might not be possible understanding where your source of truth is and securing that in a common way is still a valuable approach and you can do it without having to bring all that data into a single bucket so that it's all in one place. And, and so having done that and investing quite heavily in making that possible has paid dividends in terms of giving wider access to the platform and ensuring that only data that's available under GDPR and other regulations is being used by, by the data users. >>Yeah. So Justin, I mean, Democrat, we always talk about data democratization and you know, up until recently, they really haven't been line of sight as to how to get there. But do you have anything to add to this because you're essentially taking, you know, do an analytic queries and with data that's all dispersed all over the, how are you seeing your customers handle this, this challenge? >>Yeah. I mean, I think data products is a really interesting aspect of the answer to that. It allows you to, again, leverage the data domain owners, people know the data, the best to, to create, you know, data as a product ultimately to be consumed. And we try to represent that in our product as effectively a almost eCommerce like experience where you go and discover and look for the data products that have been created in your organization. And then you can start to consume them as, as you'd like. And so really trying to build on that notion of, you know, data democratization and self-service, and making it very easy to discover and, and start to use with whatever BI tool you, you may like, or even just running, you know, SQL queries yourself, >>Okay. G guys grab a sip of water. After this short break, we'll be back to debate whether proprietary or open platforms are the best path to the future of data excellence, keep it right there. >>Your company has more data than ever, and more people trying to understand it, but there's a problem. Your data is stored across multiple systems. It's hard to access and that delays analytics and ultimately decisions. The old method of moving all of your data into a single source of truth is slow and definitely not built for the volume of data we have today or where we are headed while your data engineers spent over half their time, moving data, your analysts and data scientists are left, waiting, feeling frustrated, unproductive, and unable to move the needle for your business. But what if you could spend less time moving or copying data? What if your data consumers could analyze all your data quickly? >>Starburst helps your teams run fast queries on any data source. We help you create a single point of access to your data, no matter where it's stored. And we support high concurrency, we solve for speed and scale, whether it's fast, SQL queries on your data lake or faster queries across multiple data sets, Starburst helps your teams run analytics anywhere you can't afford to wait for data to be available. Your team has questions that need answers. Now with Starburst, the wait is over. You'll have faster access to data with enterprise level security, easy connectivity, and 24 7 support from experts, organizations like Zolando Comcast and FINRA rely on Starburst to move their businesses forward. Contact our Trino experts to get started. >>We're back with Jess Borgman of Starburst and Richard Jarvis of EVAs health. Okay, we're gonna get to lie. Number two, and that is this an open source based platform cannot give you the performance and control that you can get with a proprietary system. Is that a lie? Justin, the enterprise data warehouse has been pretty dominant and has evolved and matured. Its stack has mature over the years. Why is it not the default platform for data? >>Yeah, well, I think that's become a lie over time. So I, I think, you know, if we go back 10 or 12 years ago with the advent of the first data lake really around Hudu, that probably was true that you couldn't get the performance that you needed to run fast, interactive, SQL queries in a data lake. Now a lot's changed in 10 or 12 years. I remember in the very early days, people would say, you you'll never get performance because you need to be column there. You need to store data in a column format. And then, you know, column formats we're introduced to, to data apes, you have Parque ORC file in aro that were created to ultimately deliver performance out of that. So, okay. We got, you know, largely over the performance hurdle, you know, more recently people will say, well, you don't have the ability to do updates and deletes like a traditional data warehouse. >>And now we've got the creation of new data formats, again like iceberg and Delta and Hodi that do allow for updates and delete. So I think the data lake has continued to mature. And I remember a, a quote from, you know, Kurt Monash many years ago where he said, you know, know it takes six or seven years to build a functional database. I think that's that's right. And now we've had almost a decade go by. So, you know, these technologies have matured to really deliver very, very close to the same level performance and functionality of, of cloud data warehouses. So I think the, the reality is that's become a line and now we have large giant hyperscale internet companies that, you know, don't have the traditional data warehouse at all. They do all of their analytics in a data lake. So I think we've, we've proven that it's very much possible today. >>Thank you for that. And so Richard, talk about your perspective as a practitioner in terms of what open brings you versus, I mean, look closed is it's open as a moving target. I remember Unix used to be open systems and so it's, it is an evolving, you know, spectrum, but, but from your perspective, what does open give you that you can't get from a proprietary system where you are fearful of in a proprietary system? >>I, I suppose for me open buys us the ability to be unsure about the future, because one thing that's always true about technology is it evolves in a, a direction, slightly different to what people expect. And what you don't want to end up is done is backed itself into a corner that then prevents it from innovating. So if you have chosen a technology and you've stored trillions of records in that technology and suddenly a new way of processing or machine learning comes out, you wanna be able to take advantage and your competitive edge might depend upon it. And so I suppose for us, we acknowledge that we don't have perfect vision of what the future might be. And so by backing open storage technologies, we can apply a number of different technologies to the processing of that data. And that gives us the ability to remain relevant, innovate on our data storage. And we have bought our way out of the, any performance concerns because we can use cloud scale infrastructure to scale up and scale down as we need. And so we don't have the concerns that we don't have enough hardware today to process what we want to do, want to achieve. We can just scale up when we need it and scale back down. So open source has really allowed us to maintain the being at the cutting edge. >>So Jess, let me play devil's advocate here a little bit, and I've talked to Shaak about this and you know, obviously her vision is there's an open source that, that the data meshes open source, an open source tooling, and it's not a proprietary, you know, you're not gonna buy a data mesh. You're gonna build it with, with open source toolings and, and vendors like you are gonna support it, but to come back to sort of today, you can get to market with a proprietary solution faster. I'm gonna make that statement. You tell me if it's a lie and then you can say, okay, we support Apache iceberg. We're gonna support open source tooling, take a company like VMware, not really in the data business, but how, the way they embraced Kubernetes and, and you know, every new open source thing that comes along, they say, we do that too. Why can't proprietary systems do that and be as effective? >>Yeah, well, I think at least with the, within the data landscape saying that you can access open data formats like iceberg or, or others is, is a bit dis disingenuous because really what you're selling to your customer is a certain degree of performance, a certain SLA, and you know, those cloud data warehouses that can reach beyond their own proprietary storage drop all the performance that they were able to provide. So it is, it reminds me kind of, of, again, going back 10 or 12 years ago when everybody had a connector to Haddo and that they thought that was the solution, right? But the reality was, you know, a connector was not the same as running workloads in Haddo back then. And I think similarly, you know, being able to connect to an external table that lives in an open data format, you know, you're, you're not going to give it the performance that your customers are accustomed to. And at the end of the day, they're always going to be predisposed. They're always going to be incentivized to get that data ingested into the data warehouse, cuz that's where they have control. And you know, the bottom line is the database industry has really been built around vendor lockin. I mean, from the start, how, how many people love Oracle today, but our customers, nonetheless, I think, you know, lockin is, is, is part of this industry. And I think that's really what we're trying to change with open data formats. >>Well, that's interesting reminded when I, you know, I see the, the gas price, the tees or gas price I, I drive up and then I say, oh, that's the cash price credit card. I gotta pay 20 cents more, but okay. But so the, the argument then, so let me, let me come back to you, Justin. So what's wrong with saying, Hey, we support open data formats, but yeah, you're gonna get better performance if you, if you keep it into our closed system, are you saying that long term that's gonna come back and bite you cuz you're gonna end up, you mentioned Oracle, you mentioned Teradata. Yeah. That's by, by implication, you're saying that's where snowflake customers are headed. >>Yeah, absolutely. I think this is a movie that, you know, we've all seen before. At least those of us who've been in the industry long enough to, to see this movie play over a couple times. So I do think that's the future. And I think, you know, I loved what Richard said. I actually wrote it down. Cause I thought it was an amazing quote. He said, it buys us the ability to be unsure of the future. Th that that pretty much says it all the, the future is unknowable and the reality is using open data formats. You remain interoperable with any technology you want to utilize. If you want to use spark to train a machine learning model and you want to use Starbust to query via sequel, that's totally cool. They can both work off the same exact, you know, data, data sets by contrast, if you're, you know, focused on a proprietary model, then you're kind of locked in again to that model. I think the same applies to data, sharing to data products, to a wide variety of, of aspects of the data landscape that a proprietary approach kind of closes you in and locks you in. >>So I, I would say this Richard, I'd love to get your thoughts on it. Cause I talked to a lot of Oracle customers, not as many te data customers, but, but a lot of Oracle customers and they, you know, they'll admit, yeah, you know, they're jamming us on price and the license cost they give, but we do get value out of it. And so my question to you, Richard, is, is do the, let's call it data warehouse systems or the proprietary systems. Are they gonna deliver a greater ROI sooner? And is that in allure of, of that customers, you know, are attracted to, or can open platforms deliver as fast in ROI? >>I think the answer to that is it can depend a bit. It depends on your businesses skillset. So we are lucky that we have a number of proprietary teams that work in databases that provide our operational data capability. And we have teams of analytics and big data experts who can work with open data sets and open data formats. And so for those different teams, they can get to an ROI more quickly with different technologies for the business though, we can't do better for our operational data stores than proprietary databases. Today we can back off very tight SLAs to them. We can demonstrate reliability from millions of hours of those databases being run at enterprise scale, but for an analytics workload where increasing our business is growing in that direction, we can't do better than open data formats with cloud-based data mesh type technologies. And so it's not a simple answer. That one will always be the right answer for our business. We definitely have times when proprietary databases provide a capability that we couldn't easily represent or replicate with open technologies. >>Yeah. Richard, stay with you. You mentioned, you know, you know, some things before that, that strike me, you know, the data brick snowflake, you know, thing is, oh, is a lot of fun for analysts like me. You've got data bricks coming at it. Richard, you mentioned you have a lot of rockstar, data engineers, data bricks coming at it from a data engineering heritage. You get snowflake coming at it from an analytics heritage. Those two worlds are, are colliding people like PJI Mohan said, you know what? I think it's actually harder to play in the data engineering. So I E it's easier to for data engineering world to go into the analytics world versus the reverse, but thinking about up and coming engineers and developers preparing for this future of data engineering and data analytics, how, how should they be thinking about the future? What, what's your advice to those young people? >>So I think I'd probably fall back on general programming skill sets. So the advice that I saw years ago was if you have open source technologies, the pythons and Javas on your CV, you commander 20% pay, hike over people who can only do proprietary programming languages. And I think that's true of data technologies as well. And from a business point of view, that makes sense. I'd rather spend the money that I save on proprietary licenses on better engineers, because they can provide more value to the business that can innovate us beyond our competitors. So I think I would my advice to people who are starting here or trying to build teams to capitalize on data assets is begin with open license, free capabilities, because they're very cheap to experiment with. And they generate a lot of interest from people who want to join you as a business. And you can make them very successful early, early doors with, with your analytics journey. >>It's interesting. Again, analysts like myself, we do a lot of TCO work and have over the last 20 plus years. And in world of Oracle, you know, normally it's the staff, that's the biggest nut in total cost of ownership, not an Oracle. It's the it's the license cost is by far the biggest component in the, in the blame pie. All right, Justin, help us close out this segment. We've been talking about this sort of data mesh open, closed snowflake data bricks. Where does Starburst sort of as this engine for the data lake data lake house, the data warehouse fit in this, in this world? >>Yeah. So our view on how the future ultimately unfolds is we think that data lakes will be a natural center of gravity for a lot of the reasons that we described open data formats, lowest total cost of ownership, because you get to choose the cheapest storage available to you. Maybe that's S3 or Azure data lake storage, or Google cloud storage, or maybe it's on-prem object storage that you bought at a, at a really good price. So ultimately storing a lot of data in a deal lake makes a lot of sense, but I think what makes our perspective unique is we still don't think you're gonna get everything there either. We think that basically centralization of all your data assets is just an impossible endeavor. And so you wanna be able to access data that lives outside of the lake as well. So we kind of think of the lake as maybe the biggest place by volume in terms of how much data you have, but to, to have comprehensive analytics and to truly understand your business and understand it holistically, you need to be able to go access other data sources as well. And so that's the role that we wanna play is to be a single point of access for our customers, provide the right level of fine grained access controls so that the right people have access to the right data and ultimately make it easy to discover and consume via, you know, the creation of data products as well. >>Great. Okay. Thanks guys. Right after this quick break, we're gonna be back to debate whether the cloud data model that we see emerging and the so-called modern data stack is really modern, or is it the same wine new bottle? When it comes to data architectures, you're watching the cube, the leader in enterprise and emerging tech coverage. >>Your data is capable of producing incredible results, but data consumers are often left in the dark without fast access to the data they need. Starers makes your data visible from wherever it lives. Your company is acquiring more data in more places, more rapidly than ever to rely solely on a data centralization strategy. Whether it's in a lake or a warehouse is unrealistic. A single source of truth approach is no longer viable, but disconnected data silos are often left untapped. We need a new approach. One that embraces distributed data. One that enables fast and secure access to any of your data from anywhere with Starburst, you'll have the fastest query engine for the data lake that allows you to connect and analyze your disparate data sources no matter where they live Starburst provides the foundational technology required for you to build towards the vision of a decentralized data mesh Starburst enterprise and Starburst galaxy offer enterprise ready, connectivity, interoperability, and security features for multiple regions, multiple clouds and everchanging global regulatory requirements. The data is yours. And with Starburst, you can perform analytics anywhere in light of your world. >>Okay. We're back with Justin Boardman. CEO of Starbust Richard Jarvis is the CTO of EMI health and Theresa tongue is the cloud first technologist from Accenture. We're on July number three. And that is the claim that today's modern data stack is actually modern. So I guess that's the lie it's it is it's is that it's not modern. Justin, what do you say? >>Yeah. I mean, I think new isn't modern, right? I think it's the, it's the new data stack. It's the cloud data stack, but that doesn't necessarily mean it's modern. I think a lot of the components actually are exactly the same as what we've had for 40 years, rather than Terra data. You have snowflake rather than Informatica you have five trend. So it's the same general stack, just, you know, a cloud version of it. And I think a lot of the challenges that it plagued us for 40 years still maintain. >>So lemme come back to you just, but okay. But, but there are differences, right? I mean, you can scale, you can throw resources at the problem. You can separate compute from storage. You really, you know, there's a lot of money being thrown at that by venture capitalists and snowflake, you mentioned it's competitors. So that's different. Is it not, is that not at least an aspect of, of modern dial it up, dial it down. So what, what do you say to that? >>Well, it, it is, it's certainly taking, you know, what the cloud offers and taking advantage of that, but it's important to note that the cloud data warehouses out there are really just separating their compute from their storage. So it's allowing them to scale up and down, but your data still stored in a proprietary format. You're still locked in. You still have to ingest the data to get it even prepared for analysis. So a lot of the same sort of structural constraints that exist with the old enterprise data warehouse model OnPrem still exist just yes, a little bit more elastic now because the cloud offers that. >>So Theresa, let me go to you cuz you have cloud first in your, in your, your title. So what's what say you to this conversation? >>Well, even the cloud providers are looking towards more of a cloud continuum, right? So the centralized cloud, as we know it, maybe data lake data warehouse in the central place, that's not even how the cloud providers are looking at it. They have news query services. Every provider has one that really expands those queries to be beyond a single location. And if we look at a lot of where our, the future goes, right, that that's gonna very much fall the same thing. There was gonna be more edge. There's gonna be more on premise because of data sovereignty, data gravity, because you're working with different parts of the business that have already made major cloud investments in different cloud providers. Right? So there's a lot of reasons why the modern, I guess, the next modern generation of the data staff needs to be much more federated. >>Okay. So Richard, how do you deal with this? You you've obviously got, you know, the technical debt, the existing infrastructure it's on the books. You don't wanna just throw it out. A lot of, lot of conversation about modernizing applications, which a lot of times is a, you know, a microservices layer on top of leg legacy apps. How do you think about the modern data stack? >>Well, I think probably the first thing to say is that the stack really has to include the processes and people around the data as well is all well and good changing the technology. But if you don't modernize how people use that technology, then you're not going to be able to, to scale because just cuz you can scale CPU and storage doesn't mean you can get more people to use your data, to generate you more, more value for the business. And so what we've been looking at is really changing in very much aligned to data products and, and data mesh. How do you enable more people to consume the service and have the stack respond in a way that keeps costs low? Because that's important for our customers consuming this data, but also allows people to occasionally run enormous queries and then tick along with smaller ones when required. And it's a good job we did because during COVID all of a sudden we had enormous pressures on our data platform to answer really important life threatening queries. And if we couldn't scale both our data stack and our teams, we wouldn't have been able to answer those as quickly as we had. So I think the stack needs to support a scalable business, not just the technology itself. >>Well thank you for that. So Justin let's, let's try to break down what the critical aspects are of the modern data stack. So you think about the past, you know, five, seven years cloud obviously has given a different pricing model. De-risked experimentation, you know that we talked about the ability to scale up scale down, but it's, I'm, I'm taking away that that's not enough based on what Richard just said. The modern data stack has to serve the business and enable the business to build data products. I, I buy that. I'm a big fan of the data mesh concepts, even though we're early days. So what are the critical aspects if you had to think about, you know, paying, maybe putting some guardrails and definitions around the modern data stack, what does that look like? What are some of the attributes and, and principles there >>Of, of how it should look like or, or how >>It's yeah. What it should be. >>Yeah. Yeah. Well, I think, you know, in, in Theresa mentioned this in, in a previous segment about the data warehouse is not necessarily going to disappear. It just becomes one node, one element of the overall data mesh. And I, I certainly agree with that. So by no means, are we suggesting that, you know, snowflake or Redshift or whatever cloud data warehouse you may be using is going to disappear, but it's, it's not going to become the end all be all. It's not the, the central single source of truth. And I think that's the paradigm shift that needs to occur. And I think it's also worth noting that those who were the early adopters of the modern data stack were primarily digital, native born in the cloud young companies who had the benefit of, of idealism. They had the benefit of it was starting with a clean slate that does not reflect the vast majority of enterprises. >>And even those companies, as they grow up mature out of that ideal state, they go buy a business. Now they've got something on another cloud provider that has a different data stack and they have to deal with that heterogeneity that is just change and change is a part of life. And so I think there is an element here that is almost philosophical. It's like, do you believe in an absolute ideal where I can just fit everything into one place or do I believe in reality? And I think the far more pragmatic approach is really what data mesh represents. So to answer your question directly, I think it's adding, you know, the ability to access data that lives outside of the data warehouse, maybe living in open data formats in a data lake or accessing operational systems as well. Maybe you want to directly access data that lives in an Oracle database or a Mongo database or, or what have you. So creating that flexibility to really Futureproof yourself from the inevitable change that you will, you won't encounter over time. >>So thank you. So there, based on what Justin just said, I, my takeaway there is it's inclusive, whether it's a data Mar data hub, data lake data warehouse, it's a, just a node on the mesh. Okay. I get that. Does that include there on Preem data? O obviously it has to, what are you seeing in terms of the ability to, to take that data mesh concept on Preem? I mean, most implementations I've seen in data mesh, frankly really aren't, you know, adhering to the philosophy. They're maybe, maybe it's data lake and maybe it's using glue. You look at what JPMC is doing. Hello, fresh, a lot of stuff happening on the AWS cloud in that, you know, closed stack, if you will. What's the answer to that Theresa? >>I mean, I, I think it's a killer case for data. Me, the fact that you have valuable data sources, OnPrem, and then yet you still wanna modernize and take the best of cloud cloud is still, like we mentioned, there's a lot of great reasons for it around the economics and the way ability to tap into the innovation that the cloud providers are giving around data and AI architecture. It's an easy button. So the mesh allows you to have the best of both worlds. You can start using the data products on-prem or in the existing systems that are working already. It's meaningful for the business. At the same time, you can modernize the ones that make business sense because it needs better performance. It needs, you know, something that is, is cheaper or, or maybe just tap into better analytics to get better insights, right? So you're gonna be able to stretch and really have the best of both worlds. That, again, going back to Richard's point, that is meaningful by the business. Not everything has to have that one size fits all set a tool. >>Okay. Thank you. So Richard, you know, talking about data as product, wonder if we could give us your perspectives here, what are the advantages of treating data as a product? What, what role do data products have in the modern data stack? We talk about monetizing data. What are your thoughts on data products? >>So for us, one of the most important data products that we've been creating is taking data that is healthcare data across a wide variety of different settings. So information about patients' demographics about their, their treatment, about their medications and so on, and taking that into a standards format that can be utilized by a wide variety of different researchers because misinterpreting that data or having the data not presented in the way that the user is expecting means that you generate the wrong insight. And in any business, that's clearly not a desirable outcome, but when that insight is so critical, as it might be in healthcare or some security settings, you really have to have gone to the trouble of understanding the data, presenting it in a format that everyone can clearly agree on. And then letting people consume in a very structured, managed way, even if that data comes from a variety of different sources in, in, in the first place. And so our data product journey has really begun by standardizing data across a number of different silos through the data mesh. So we can present out both internally and through the right governance externally to, to researchers. >>So that data product through whatever APIs is, is accessible, it's discoverable, but it's obviously gotta be governed as well. You mentioned you, you appropriately provided to internally. Yeah. But also, you know, external folks as well. So the, so you've, you've architected that capability today >>We have, and because the data is standard, it can generate value much more quickly and we can be sure of the security and, and, and value that that's providing because the data product isn't just about formatting the data into the correct tables, it's understanding what it means to redact the data or to remove certain rows from it or to interpret what a date actually means. Is it the start of the contract or the start of the treatment or the date of birth of a patient? These things can be lost in the data storage without having the proper product management around the data to say in a very clear business context, what does this data mean? And what does it mean to process this data for a particular use case? >>Yeah, it makes sense. It's got the context. If the, if the domains own the data, you, you gotta cut through a lot of the, the, the centralized teams, the technical teams that, that data agnostic, they don't really have that context. All right. Let's send Justin, how does Starburst fit into this modern data stack? Bring us home. >>Yeah. So I think for us, it's really providing our customers with, you know, the flexibility to operate and analyze data that lives in a wide variety of different systems. Ultimately giving them that optionality, you know, and optionality provides the ability to reduce costs, store more in a data lake rather than data warehouse. It provides the ability for the fastest time to insight to access the data directly where it lives. And ultimately with this concept of data products that we've now, you know, incorporated into our offering as well, you can really create and, and curate, you know, data as a product to be shared and consumed. So we're trying to help enable the data mesh, you know, model and make that an appropriate compliment to, you know, the, the, the modern data stack that people have today. >>Excellent. Hey, I wanna thank Justin Theresa and Richard for joining us today. You guys are great. I big believers in the, in the data mesh concept, and I think, you know, we're seeing the future of data architecture. So thank you. Now, remember, all these conversations are gonna be available on the cube.net for on-demand viewing. You can also go to starburst.io. They have some great content on the website and they host some really thought provoking interviews and, and, and they have awesome resources, lots of data mesh conversations over there, and really good stuff in, in the resource section. So check that out. Thanks for watching the data doesn't lie or does it made possible by Starburst data? This is Dave Valante for the cube, and we'll see you next time. >>The explosion of data sources has forced organizations to modernize their systems and architecture and come to terms with one size does not fit all for data management today. Your teams are constantly moving and copying data, which requires time management. And in some cases, double paying for compute resources. Instead, what if you could access all your data anywhere using the BI tools and SQL skills your users already have. 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>>In 2011, early Facebook employee and Cloudera co-founder Jeff Ocker famously said the best minds of my generation are thinking about how to get people to click on ads. And that sucks. Let's face it more than a decade later organizations continue to be frustrated with how difficult it is to get value from data and build a truly agile data-driven enterprise. What does that even mean? You ask? Well, it means that everyone in the organization has the data they need when they need it. In a context that's relevant to advance the mission of an organization. Now that could mean cutting cost could mean increasing profits, driving productivity, saving lives, accelerating drug discovery, making better diagnoses, solving, supply chain problems, predicting weather disasters, simplifying processes, and thousands of other examples where data can completely transform people's lives beyond manipulating internet users to behave a certain way. We've heard the prognostications about the possibilities of data before and in fairness we've made progress, but the hard truth is the original promises of master data management, enterprise data, warehouses, data marts, data hubs, and yes, even data lakes were broken and left us wanting from more welcome to the data doesn't lie, or doesn't a series of conversations produced by the cube and made possible by Starburst data. >>I'm your host, Dave Lanta and joining me today are three industry experts. Justin Borgman is this co-founder and CEO of Starburst. Richard Jarvis is the CTO at EMI health and Theresa tongue is cloud first technologist at Accenture. Today we're gonna have a candid discussion that will expose the unfulfilled and yes, broken promises of a data past we'll expose data lies, big lies, little lies, white lies, and hidden truths. And we'll challenge, age old data conventions and bust some data myths. We're debating questions like is the demise of a single source of truth. Inevitable will the data warehouse ever have featured parody with the data lake or vice versa is the so-called modern data stack, simply centralization in the cloud, AKA the old guards model in new cloud close. How can organizations rethink their data architectures and regimes to realize the true promises of data can and will and open ecosystem deliver on these promises in our lifetimes, we're spanning much of the Western world today. Richard is in the UK. Teresa is on the west coast and Justin is in Massachusetts with me. I'm in the cube studios about 30 miles outside of Boston folks. Welcome to the program. Thanks for coming on. Thanks for having us. Let's get right into it. You're very welcome. Now here's the first lie. The most effective data architecture is one that is centralized with a team of data specialists serving various lines of business. What do you think Justin? >>Yeah, definitely a lie. My first startup was a company called hit adapt, which was an early SQL engine for hit that was acquired by Teradata. And when I got to Teradata, of course, Teradata is the pioneer of that central enterprise data warehouse model. One of the things that I found fascinating was that not one of their customers had actually lived up to that vision of centralizing all of their data into one place. They all had data silos. They all had data in different systems. They had data on prem data in the cloud. You know, those companies were acquiring other companies and inheriting their data architecture. So, you know, despite being the industry leader for 40 years, not one of their customers truly had everything in one place. So I think definitely history has proven that to be a lie. >>So Richard, from a practitioner's point of view, you know, what, what are your thoughts? I mean, there, there's a lot of pressure to cut cost, keep things centralized, you know, serve the business as best as possible from that standpoint. What, what is your experience show? >>Yeah, I mean, I think I would echo Justin's experience really that we, as a business have grown up through acquisition, through storing data in different places sometimes to do information governance in different ways to store data in, in a platform that's close to data experts, people who really understand healthcare data from pharmacies or from, from doctors. And so, although if you were starting from a Greenfield site and you were building something brand new, you might be able to centralize all the data and all of the tooling and teams in one place. The reality is that that businesses just don't grow up like that. And, and it's just really impossible to get that academic perfection of, of storing everything in one place. >>Y you know, Theresa, I feel like Sarbanes Oxley kinda saved the data warehouse, you know, right. You actually did have to have a single version of the truth for certain financial data, but really for those, some of those other use cases, I, I mentioned, I, I do feel like the industry has kinda let us down. What's your take on this? Where does it make sense to have that sort of centralized approach versus where does it make sense to maybe decentralized? >>I, I think you gotta have centralized governance, right? So from the central team, for things like star Oxley, for things like security for certainly very core data sets, having a centralized set of roles, responsibilities to really QA, right. To serve as a design authority for your entire data estate, just like you might with security, but how it's implemented has to be distributed. Otherwise you're not gonna be able to scale. Right? So being able to have different parts of the business really make the right data investments for their needs. And then ultimately you're gonna collaborate with your partners. So partners that are not within the company, right. External partners, we're gonna see a lot more data sharing and model creation. And so you're definitely going to be decentralized. >>So, you know, Justin, you guys last, geez, I think it was about a year ago, had a session on, on data mesh. It was a great program. You invited Jamma, Dani, of course, she's the creator of the data mesh. And her one of our fundamental premises is that you've got this hyper specialized team that you've gotta go through. And if you want anything, but at the same time, these, these individuals actually become a bottleneck, even though they're some of the most talented people in the organization. So I guess question for you, Richard, how do you deal with that? Do you, do you organize so that there are a few sort of rock stars that, that, you know, build cubes and, and the like, and, and, and, or have you had any success in sort of decentralizing with, you know, your, your constituencies, that data model? >>Yeah. So, so we absolutely have got rockstar, data scientists and data guardians. If you like people who understand what it means to use this data, particularly as the data that we use at emos is very private it's healthcare information. And some of the, the rules and regulations around using the data are very complex and, and strict. So we have to have people who understand the usage of the data, then people who understand how to build models, how to process the data effectively. And you can think of them like consultants to the wider business, because a pharmacist might not understand how to structure a SQL query, but they do understand how they want to process medication information to improve patient lives. And so that becomes a, a consulting type experience from a, a set of rock stars to help a, a more decentralized business who needs to, to understand the data and to generate some valuable output. >>Justin, what do you say to a, to a customer or prospect that says, look, Justin, I'm gonna, I got a centralized team and that's the most cost effective way to serve the business. Otherwise I got, I got duplication. What do you say to that? >>Well, I, I would argue it's probably not the most cost effective and, and the reason being really twofold. I think, first of all, when you are deploying a enterprise data warehouse model, the, the data warehouse itself is very expensive, generally speaking. And so you're putting all of your most valuable data in the hands of one vendor who now has tremendous leverage over you, you know, for many, many years to come. I think that's the story at Oracle or Terra data or other proprietary database systems. But the other aspect I think is that the reality is those central data warehouse teams is as much as they are experts in the technology. They don't necessarily understand the data itself. And this is one of the core tenants of data mash that that jam writes about is this idea of the domain owners actually know the data the best. >>And so by, you know, not only acknowledging that data is generally decentralized and to your earlier point about SAR, brain Oxley, maybe saving the data warehouse, I would argue maybe GDPR and data sovereignty will destroy it because data has to be decentralized for, for those laws to be compliant. But I think the reality is, you know, the data mesh model basically says, data's decentralized, and we're gonna turn that into an asset rather than a liability. And we're gonna turn that into an asset by empowering the people that know the data, the best to participate in the process of, you know, curating and creating data products for, for consumption. So I think when you think about it, that way, you're going to get higher quality data and faster time to insight, which is ultimately going to drive more revenue for your business and reduce costs. So I think that that's the way I see the two, the two models comparing and contrasting. >>So do you think the demise of the data warehouse is inevitable? I mean, I mean, you know, there Theresa you work with a lot of clients, they're not just gonna rip and replace their existing infrastructure. Maybe they're gonna build on top of it, but what does that mean? Does that mean the E D w just becomes, you know, less and less valuable over time, or it's maybe just isolated to specific use cases. What's your take on that? >>Listen, I still would love all my data within a data warehouse would love it. Mastered would love it owned by essential team. Right? I think that's still what I would love to have. That's just not the reality, right? The investment to actually migrate and keep that up to date. I would say it's a losing battle. Like we've been trying to do it for a long time. Nobody has the budgets and then data changes, right? There's gonna be a new technology. That's gonna emerge that we're gonna wanna tap into. There's going to be not enough investment to bring all the legacy, but still very useful systems into that centralized view. So you keep the data warehouse. I think it's a very, very valuable, very high performance tool for what it's there for, but you could have this, you know, new mesh layer that still takes advantage of the things. I mentioned, the data products in the systems that are meaningful today and the data products that actually might span a number of systems, maybe either those that either source systems for the domains that know it best, or the consumer based systems and products that need to be packaged in a way that be really meaningful for that end user, right? Each of those are useful for a different part of the business and making sure that the mesh actually allows you to use all of them. >>So, Richard, let me ask you, you take, take Gemma's principles back to those. You got to, you know, domain ownership and, and, and data as product. Okay, great. Sounds good. But it creates what I would argue are two, you know, challenges, self-serve infrastructure let's park that for a second. And then in your industry, the one of the high, most regulated, most sensitive computational governance, how do you automate and ensure federated governance in that mesh model that Theresa was just talking about? >>Well, it absolutely depends on some of the tooling and processes that you put in place around those tools to be, to centralize the security and the governance of the data. And I think, although a data warehouse makes that very simple, cause it's a single tool, it's not impossible with some of the data mesh technologies that are available. And so what we've done at emus is we have a single security layer that sits on top of our data match, which means that no matter which user is accessing, which data source, we go through a well audited well understood security layer. That means that we know exactly who's got access to which data field, which data tables. And then everything that they do is, is audited in a very kind of standard way, regardless of the underlying data storage technology. So for me, although storing the data in one place might not be possible understanding where your source of truth is and securing that in a common way is still a valuable approach and you can do it without having to bring all that data into a single bucket so that it's all in one place. And, and so having done that and investing quite heavily in making that possible has paid dividends in terms of giving wider access to the platform and ensuring that only data that's available under GDPR and other regulations is being used by, by the data users. >>Yeah. So Justin, I mean, Democrat, we always talk about data democratization and you know, up until recently, they really haven't been line of sight as to how to get there. But do you have anything to add to this because you're essentially taking, you know, do an analytic queries and with data that's all dispersed all over the, how are you seeing your customers handle this, this challenge? >>Yeah. I mean, I think data products is a really interesting aspect of the answer to that. It allows you to, again, leverage the data domain owners, people know the data, the best to, to create, you know, data as a product ultimately to be consumed. And we try to represent that in our product as effectively a almost eCommerce like experience where you go and discover and look for the data products that have been created in your organization. And then you can start to consume them as, as you'd like. And so really trying to build on that notion of, you know, data democratization and self-service, and making it very easy to discover and, and start to use with whatever BI tool you, you may like, or even just running, you know, SQL queries yourself, >>Okay. G guys grab a sip of water. After this short break, we'll be back to debate whether proprietary or open platforms are the best path to the future of data excellence, keep it right there. >>Your company has more data than ever, and more people trying to understand it, but there's a problem. Your data is stored across multiple systems. It's hard to access and that delays analytics and ultimately decisions. The old method of moving all of your data into a single source of truth is slow and definitely not built for the volume of data we have today or where we are headed while your data engineers spent over half their time, moving data, your analysts and data scientists are left, waiting, feeling frustrated, unproductive, and unable to move the needle for your business. But what if you could spend less time moving or copying data? What if your data consumers could analyze all your data quickly? >>Starburst helps your teams run fast queries on any data source. We help you create a single point of access to your data, no matter where it's stored. And we support high concurrency, we solve for speed and scale, whether it's fast, SQL queries on your data lake or faster queries across multiple data sets, Starburst helps your teams run analytics anywhere you can't afford to wait for data to be available. Your team has questions that need answers. Now with Starburst, the wait is over. You'll have faster access to data with enterprise level security, easy connectivity, and 24 7 support from experts, organizations like Zolando Comcast and FINRA rely on Starburst to move their businesses forward. Contact our Trino experts to get started. >>We're back with Jess Borgman of Starburst and Richard Jarvis of EVAs health. Okay, we're gonna get to lie. Number two, and that is this an open source based platform cannot give you the performance and control that you can get with a proprietary system. Is that a lie? Justin, the enterprise data warehouse has been pretty dominant and has evolved and matured. Its stack has mature over the years. Why is it not the default platform for data? >>Yeah, well, I think that's become a lie over time. So I, I think, you know, if we go back 10 or 12 years ago with the advent of the first data lake really around Hudu, that probably was true that you couldn't get the performance that you needed to run fast, interactive, SQL queries in a data lake. Now a lot's changed in 10 or 12 years. I remember in the very early days, people would say, you you'll never get performance because you need to be column there. You need to store data in a column format. And then, you know, column formats we're introduced to, to data apes, you have Parque ORC file in aro that were created to ultimately deliver performance out of that. So, okay. We got, you know, largely over the performance hurdle, you know, more recently people will say, well, you don't have the ability to do updates and deletes like a traditional data warehouse. >>And now we've got the creation of new data formats, again like iceberg and Delta and Hodi that do allow for updates and delete. So I think the data lake has continued to mature. And I remember a, a quote from, you know, Kurt Monash many years ago where he said, you know, know it takes six or seven years to build a functional database. I think that's that's right. And now we've had almost a decade go by. So, you know, these technologies have matured to really deliver very, very close to the same level performance and functionality of, of cloud data warehouses. So I think the, the reality is that's become a line and now we have large giant hyperscale internet companies that, you know, don't have the traditional data warehouse at all. They do all of their analytics in a data lake. So I think we've, we've proven that it's very much possible today. >>Thank you for that. And so Richard, talk about your perspective as a practitioner in terms of what open brings you versus, I mean, look closed is it's open as a moving target. I remember Unix used to be open systems and so it's, it is an evolving, you know, spectrum, but, but from your perspective, what does open give you that you can't get from a proprietary system where you are fearful of in a proprietary system? >>I, I suppose for me open buys us the ability to be unsure about the future, because one thing that's always true about technology is it evolves in a, a direction, slightly different to what people expect. And what you don't want to end up is done is backed itself into a corner that then prevents it from innovating. So if you have chosen a technology and you've stored trillions of records in that technology and suddenly a new way of processing or machine learning comes out, you wanna be able to take advantage and your competitive edge might depend upon it. And so I suppose for us, we acknowledge that we don't have perfect vision of what the future might be. And so by backing open storage technologies, we can apply a number of different technologies to the processing of that data. And that gives us the ability to remain relevant, innovate on our data storage. And we have bought our way out of the, any performance concerns because we can use cloud scale infrastructure to scale up and scale down as we need. And so we don't have the concerns that we don't have enough hardware today to process what we want to do, want to achieve. We can just scale up when we need it and scale back down. So open source has really allowed us to maintain the being at the cutting edge. >>So Jess, let me play devil's advocate here a little bit, and I've talked to Shaak about this and you know, obviously her vision is there's an open source that, that the data meshes open source, an open source tooling, and it's not a proprietary, you know, you're not gonna buy a data mesh. You're gonna build it with, with open source toolings and, and vendors like you are gonna support it, but to come back to sort of today, you can get to market with a proprietary solution faster. I'm gonna make that statement. You tell me if it's a lie and then you can say, okay, we support Apache iceberg. We're gonna support open source tooling, take a company like VMware, not really in the data business, but how, the way they embraced Kubernetes and, and you know, every new open source thing that comes along, they say, we do that too. Why can't proprietary systems do that and be as effective? >>Yeah, well, I think at least with the, within the data landscape saying that you can access open data formats like iceberg or, or others is, is a bit dis disingenuous because really what you're selling to your customer is a certain degree of performance, a certain SLA, and you know, those cloud data warehouses that can reach beyond their own proprietary storage drop all the performance that they were able to provide. So it is, it reminds me kind of, of, again, going back 10 or 12 years ago when everybody had a connector to Haddo and that they thought that was the solution, right? But the reality was, you know, a connector was not the same as running workloads in Haddo back then. And I think similarly, you know, being able to connect to an external table that lives in an open data format, you know, you're, you're not going to give it the performance that your customers are accustomed to. And at the end of the day, they're always going to be predisposed. They're always going to be incentivized to get that data ingested into the data warehouse, cuz that's where they have control. And you know, the bottom line is the database industry has really been built around vendor lockin. I mean, from the start, how, how many people love Oracle today, but our customers, nonetheless, I think, you know, lockin is, is, is part of this industry. And I think that's really what we're trying to change with open data formats. >>Well, that's interesting reminded when I, you know, I see the, the gas price, the tees or gas price I, I drive up and then I say, oh, that's the cash price credit card. I gotta pay 20 cents more, but okay. But so the, the argument then, so let me, let me come back to you, Justin. So what's wrong with saying, Hey, we support open data formats, but yeah, you're gonna get better performance if you, if you keep it into our closed system, are you saying that long term that's gonna come back and bite you cuz you're gonna end up, you mentioned Oracle, you mentioned Teradata. Yeah. That's by, by implication, you're saying that's where snowflake customers are headed. >>Yeah, absolutely. I think this is a movie that, you know, we've all seen before. At least those of us who've been in the industry long enough to, to see this movie play over a couple times. So I do think that's the future. And I think, you know, I loved what Richard said. I actually wrote it down. Cause I thought it was an amazing quote. He said, it buys us the ability to be unsure of the future. Th that that pretty much says it all the, the future is unknowable and the reality is using open data formats. You remain interoperable with any technology you want to utilize. If you want to use spark to train a machine learning model and you want to use Starbust to query via sequel, that's totally cool. They can both work off the same exact, you know, data, data sets by contrast, if you're, you know, focused on a proprietary model, then you're kind of locked in again to that model. I think the same applies to data, sharing to data products, to a wide variety of, of aspects of the data landscape that a proprietary approach kind of closes you in and locks you in. >>So I, I would say this Richard, I'd love to get your thoughts on it. Cause I talked to a lot of Oracle customers, not as many te data customers, but, but a lot of Oracle customers and they, you know, they'll admit, yeah, you know, they're jamming us on price and the license cost they give, but we do get value out of it. And so my question to you, Richard, is, is do the, let's call it data warehouse systems or the proprietary systems. Are they gonna deliver a greater ROI sooner? And is that in allure of, of that customers, you know, are attracted to, or can open platforms deliver as fast in ROI? >>I think the answer to that is it can depend a bit. It depends on your businesses skillset. So we are lucky that we have a number of proprietary teams that work in databases that provide our operational data capability. And we have teams of analytics and big data experts who can work with open data sets and open data formats. And so for those different teams, they can get to an ROI more quickly with different technologies for the business though, we can't do better for our operational data stores than proprietary databases. Today we can back off very tight SLAs to them. We can demonstrate reliability from millions of hours of those databases being run at enterprise scale, but for an analytics workload where increasing our business is growing in that direction, we can't do better than open data formats with cloud-based data mesh type technologies. And so it's not a simple answer. That one will always be the right answer for our business. We definitely have times when proprietary databases provide a capability that we couldn't easily represent or replicate with open technologies. >>Yeah. Richard, stay with you. You mentioned, you know, you know, some things before that, that strike me, you know, the data brick snowflake, you know, thing is, oh, is a lot of fun for analysts like me. You've got data bricks coming at it. Richard, you mentioned you have a lot of rockstar, data engineers, data bricks coming at it from a data engineering heritage. You get snowflake coming at it from an analytics heritage. Those two worlds are, are colliding people like PJI Mohan said, you know what? I think it's actually harder to play in the data engineering. So I E it's easier to for data engineering world to go into the analytics world versus the reverse, but thinking about up and coming engineers and developers preparing for this future of data engineering and data analytics, how, how should they be thinking about the future? What, what's your advice to those young people? >>So I think I'd probably fall back on general programming skill sets. So the advice that I saw years ago was if you have open source technologies, the pythons and Javas on your CV, you commander 20% pay, hike over people who can only do proprietary programming languages. And I think that's true of data technologies as well. And from a business point of view, that makes sense. I'd rather spend the money that I save on proprietary licenses on better engineers, because they can provide more value to the business that can innovate us beyond our competitors. So I think I would my advice to people who are starting here or trying to build teams to capitalize on data assets is begin with open license, free capabilities, because they're very cheap to experiment with. And they generate a lot of interest from people who want to join you as a business. And you can make them very successful early, early doors with, with your analytics journey. >>It's interesting. Again, analysts like myself, we do a lot of TCO work and have over the last 20 plus years. And in world of Oracle, you know, normally it's the staff, that's the biggest nut in total cost of ownership, not an Oracle. It's the it's the license cost is by far the biggest component in the, in the blame pie. All right, Justin, help us close out this segment. We've been talking about this sort of data mesh open, closed snowflake data bricks. Where does Starburst sort of as this engine for the data lake data lake house, the data warehouse fit in this, in this world? >>Yeah. So our view on how the future ultimately unfolds is we think that data lakes will be a natural center of gravity for a lot of the reasons that we described open data formats, lowest total cost of ownership, because you get to choose the cheapest storage available to you. Maybe that's S3 or Azure data lake storage, or Google cloud storage, or maybe it's on-prem object storage that you bought at a, at a really good price. So ultimately storing a lot of data in a deal lake makes a lot of sense, but I think what makes our perspective unique is we still don't think you're gonna get everything there either. We think that basically centralization of all your data assets is just an impossible endeavor. And so you wanna be able to access data that lives outside of the lake as well. So we kind of think of the lake as maybe the biggest place by volume in terms of how much data you have, but to, to have comprehensive analytics and to truly understand your business and understand it holistically, you need to be able to go access other data sources as well. And so that's the role that we wanna play is to be a single point of access for our customers, provide the right level of fine grained access controls so that the right people have access to the right data and ultimately make it easy to discover and consume via, you know, the creation of data products as well. >>Great. Okay. Thanks guys. Right after this quick break, we're gonna be back to debate whether the cloud data model that we see emerging and the so-called modern data stack is really modern, or is it the same wine new bottle? When it comes to data architectures, you're watching the cube, the leader in enterprise and emerging tech coverage. >>Your data is capable of producing incredible results, but data consumers are often left in the dark without fast access to the data they need. Starers makes your data visible from wherever it lives. Your company is acquiring more data in more places, more rapidly than ever to rely solely on a data centralization strategy. Whether it's in a lake or a warehouse is unrealistic. A single source of truth approach is no longer viable, but disconnected data silos are often left untapped. We need a new approach. One that embraces distributed data. One that enables fast and secure access to any of your data from anywhere with Starburst, you'll have the fastest query engine for the data lake that allows you to connect and analyze your disparate data sources no matter where they live Starburst provides the foundational technology required for you to build towards the vision of a decentralized data mesh Starburst enterprise and Starburst galaxy offer enterprise ready, connectivity, interoperability, and security features for multiple regions, multiple clouds and everchanging global regulatory requirements. The data is yours. And with Starburst, you can perform analytics anywhere in light of your world. >>Okay. We're back with Justin Boardman. CEO of Starbust Richard Jarvis is the CTO of EMI health and Theresa tongue is the cloud first technologist from Accenture. We're on July number three. And that is the claim that today's modern data stack is actually modern. So I guess that's the lie it's it is it's is that it's not modern. Justin, what do you say? >>Yeah. I mean, I think new isn't modern, right? I think it's the, it's the new data stack. It's the cloud data stack, but that doesn't necessarily mean it's modern. I think a lot of the components actually are exactly the same as what we've had for 40 years, rather than Terra data. You have snowflake rather than Informatica you have five trend. So it's the same general stack, just, you know, a cloud version of it. And I think a lot of the challenges that it plagued us for 40 years still maintain. >>So lemme come back to you just, but okay. But, but there are differences, right? I mean, you can scale, you can throw resources at the problem. You can separate compute from storage. You really, you know, there's a lot of money being thrown at that by venture capitalists and snowflake, you mentioned it's competitors. So that's different. Is it not, is that not at least an aspect of, of modern dial it up, dial it down. So what, what do you say to that? >>Well, it, it is, it's certainly taking, you know, what the cloud offers and taking advantage of that, but it's important to note that the cloud data warehouses out there are really just separating their compute from their storage. So it's allowing them to scale up and down, but your data still stored in a proprietary format. You're still locked in. You still have to ingest the data to get it even prepared for analysis. So a lot of the same sort of structural constraints that exist with the old enterprise data warehouse model OnPrem still exist just yes, a little bit more elastic now because the cloud offers that. >>So Theresa, let me go to you cuz you have cloud first in your, in your, your title. So what's what say you to this conversation? >>Well, even the cloud providers are looking towards more of a cloud continuum, right? So the centralized cloud, as we know it, maybe data lake data warehouse in the central place, that's not even how the cloud providers are looking at it. They have news query services. Every provider has one that really expands those queries to be beyond a single location. And if we look at a lot of where our, the future goes, right, that that's gonna very much fall the same thing. There was gonna be more edge. There's gonna be more on premise because of data sovereignty, data gravity, because you're working with different parts of the business that have already made major cloud investments in different cloud providers. Right? So there's a lot of reasons why the modern, I guess, the next modern generation of the data staff needs to be much more federated. >>Okay. So Richard, how do you deal with this? You you've obviously got, you know, the technical debt, the existing infrastructure it's on the books. You don't wanna just throw it out. A lot of, lot of conversation about modernizing applications, which a lot of times is a, you know, a microservices layer on top of leg legacy apps. How do you think about the modern data stack? >>Well, I think probably the first thing to say is that the stack really has to include the processes and people around the data as well is all well and good changing the technology. But if you don't modernize how people use that technology, then you're not going to be able to, to scale because just cuz you can scale CPU and storage doesn't mean you can get more people to use your data, to generate you more, more value for the business. And so what we've been looking at is really changing in very much aligned to data products and, and data mesh. How do you enable more people to consume the service and have the stack respond in a way that keeps costs low? Because that's important for our customers consuming this data, but also allows people to occasionally run enormous queries and then tick along with smaller ones when required. And it's a good job we did because during COVID all of a sudden we had enormous pressures on our data platform to answer really important life threatening queries. And if we couldn't scale both our data stack and our teams, we wouldn't have been able to answer those as quickly as we had. So I think the stack needs to support a scalable business, not just the technology itself. >>Well thank you for that. So Justin let's, let's try to break down what the critical aspects are of the modern data stack. So you think about the past, you know, five, seven years cloud obviously has given a different pricing model. De-risked experimentation, you know that we talked about the ability to scale up scale down, but it's, I'm, I'm taking away that that's not enough based on what Richard just said. The modern data stack has to serve the business and enable the business to build data products. I, I buy that. I'm a big fan of the data mesh concepts, even though we're early days. So what are the critical aspects if you had to think about, you know, paying, maybe putting some guardrails and definitions around the modern data stack, what does that look like? What are some of the attributes and, and principles there >>Of, of how it should look like or, or how >>It's yeah. What it should be. >>Yeah. Yeah. Well, I think, you know, in, in Theresa mentioned this in, in a previous segment about the data warehouse is not necessarily going to disappear. It just becomes one node, one element of the overall data mesh. And I, I certainly agree with that. So by no means, are we suggesting that, you know, snowflake or Redshift or whatever cloud data warehouse you may be using is going to disappear, but it's, it's not going to become the end all be all. It's not the, the central single source of truth. And I think that's the paradigm shift that needs to occur. And I think it's also worth noting that those who were the early adopters of the modern data stack were primarily digital, native born in the cloud young companies who had the benefit of, of idealism. They had the benefit of it was starting with a clean slate that does not reflect the vast majority of enterprises. >>And even those companies, as they grow up mature out of that ideal state, they go buy a business. Now they've got something on another cloud provider that has a different data stack and they have to deal with that heterogeneity that is just change and change is a part of life. And so I think there is an element here that is almost philosophical. It's like, do you believe in an absolute ideal where I can just fit everything into one place or do I believe in reality? And I think the far more pragmatic approach is really what data mesh represents. So to answer your question directly, I think it's adding, you know, the ability to access data that lives outside of the data warehouse, maybe living in open data formats in a data lake or accessing operational systems as well. Maybe you want to directly access data that lives in an Oracle database or a Mongo database or, or what have you. So creating that flexibility to really Futureproof yourself from the inevitable change that you will, you won't encounter over time. >>So thank you. So there, based on what Justin just said, I, my takeaway there is it's inclusive, whether it's a data Mar data hub, data lake data warehouse, it's a, just a node on the mesh. Okay. I get that. Does that include there on Preem data? O obviously it has to, what are you seeing in terms of the ability to, to take that data mesh concept on Preem? I mean, most implementations I've seen in data mesh, frankly really aren't, you know, adhering to the philosophy. They're maybe, maybe it's data lake and maybe it's using glue. You look at what JPMC is doing. Hello, fresh, a lot of stuff happening on the AWS cloud in that, you know, closed stack, if you will. What's the answer to that Theresa? >>I mean, I, I think it's a killer case for data. Me, the fact that you have valuable data sources, OnPrem, and then yet you still wanna modernize and take the best of cloud cloud is still, like we mentioned, there's a lot of great reasons for it around the economics and the way ability to tap into the innovation that the cloud providers are giving around data and AI architecture. It's an easy button. So the mesh allows you to have the best of both worlds. You can start using the data products on-prem or in the existing systems that are working already. It's meaningful for the business. At the same time, you can modernize the ones that make business sense because it needs better performance. It needs, you know, something that is, is cheaper or, or maybe just tap into better analytics to get better insights, right? So you're gonna be able to stretch and really have the best of both worlds. That, again, going back to Richard's point, that is meaningful by the business. Not everything has to have that one size fits all set a tool. >>Okay. Thank you. So Richard, you know, talking about data as product, wonder if we could give us your perspectives here, what are the advantages of treating data as a product? What, what role do data products have in the modern data stack? We talk about monetizing data. What are your thoughts on data products? >>So for us, one of the most important data products that we've been creating is taking data that is healthcare data across a wide variety of different settings. So information about patients' demographics about their, their treatment, about their medications and so on, and taking that into a standards format that can be utilized by a wide variety of different researchers because misinterpreting that data or having the data not presented in the way that the user is expecting means that you generate the wrong insight. And in any business, that's clearly not a desirable outcome, but when that insight is so critical, as it might be in healthcare or some security settings, you really have to have gone to the trouble of understanding the data, presenting it in a format that everyone can clearly agree on. And then letting people consume in a very structured, managed way, even if that data comes from a variety of different sources in, in, in the first place. And so our data product journey has really begun by standardizing data across a number of different silos through the data mesh. So we can present out both internally and through the right governance externally to, to researchers. >>So that data product through whatever APIs is, is accessible, it's discoverable, but it's obviously gotta be governed as well. You mentioned you, you appropriately provided to internally. Yeah. But also, you know, external folks as well. So the, so you've, you've architected that capability today >>We have, and because the data is standard, it can generate value much more quickly and we can be sure of the security and, and, and value that that's providing because the data product isn't just about formatting the data into the correct tables, it's understanding what it means to redact the data or to remove certain rows from it or to interpret what a date actually means. Is it the start of the contract or the start of the treatment or the date of birth of a patient? These things can be lost in the data storage without having the proper product management around the data to say in a very clear business context, what does this data mean? And what does it mean to process this data for a particular use case? >>Yeah, it makes sense. It's got the context. If the, if the domains own the data, you, you gotta cut through a lot of the, the, the centralized teams, the technical teams that, that data agnostic, they don't really have that context. All right. Let's send Justin, how does Starburst fit into this modern data stack? Bring us home. >>Yeah. So I think for us, it's really providing our customers with, you know, the flexibility to operate and analyze data that lives in a wide variety of different systems. Ultimately giving them that optionality, you know, and optionality provides the ability to reduce costs, store more in a data lake rather than data warehouse. It provides the ability for the fastest time to insight to access the data directly where it lives. And ultimately with this concept of data products that we've now, you know, incorporated into our offering as well, you can really create and, and curate, you know, data as a product to be shared and consumed. So we're trying to help enable the data mesh, you know, model and make that an appropriate compliment to, you know, the, the, the modern data stack that people have today. >>Excellent. Hey, I wanna thank Justin Theresa and Richard for joining us today. You guys are great. I big believers in the, in the data mesh concept, and I think, you know, we're seeing the future of data architecture. So thank you. Now, remember, all these conversations are gonna be available on the cube.net for on-demand viewing. You can also go to starburst.io. They have some great content on the website and they host some really thought provoking interviews and, and, and they have awesome resources, lots of data mesh conversations over there, and really good stuff in, in the resource section. So check that out. Thanks for watching the data doesn't lie or does it made possible by Starburst data? This is Dave Valante for the cube, and we'll see you next time. >>The explosion of data sources has forced organizations to modernize their systems and architecture and come to terms with one size does not fit all for data management today. Your teams are constantly moving and copying data, which requires time management. And in some cases, double paying for compute resources. Instead, what if you could access all your data anywhere using the BI tools and SQL skills your users already have. And what if this also included enterprise security and fast performance with Starburst enterprise, you can provide your data consumers with a single point of secure access to all of your data, no matter where it lives with features like strict, fine grained, access control, end to end data encryption and data masking Starburst meets the security standards of the largest companies. Starburst enterprise can easily be deployed anywhere and managed with insights where data teams holistically view their clusters operation and query execution. So they can reach meaningful business decisions faster, all this with the support of the largest team of Trino experts in the world, delivering fully tested stable releases and available to support you 24 7 to unlock the value in all of your data. You need a solution that easily fits with what you have today and can adapt to your architecture. Tomorrow. 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>>In 2011, early Facebook employee and Cloudera co-founder Jeff Ocker famously said the best minds of my generation are thinking about how to get people to click on ads. And that sucks. Let's face it more than a decade later organizations continue to be frustrated with how difficult it is to get value from data and build a truly agile data driven enterprise. What does that even mean? You ask? Well, it means that everyone in the organization has the data they need when they need it. In a context that's relevant to advance the mission of an organization. Now that could mean cutting costs could mean increasing profits, driving productivity, saving lives, accelerating drug discovery, making better diagnoses, solving, supply chain problems, predicting weather disasters, simplifying processes, and thousands of other examples where data can completely transform people's lives beyond manipulating internet users to behave a certain way. We've heard the prognostications about the possibilities of data before and in fairness we've made progress, but the hard truth is the original promises of master data management, enterprise data, warehouses, data, Mars, data hubs, and yes, even data lakes were broken and left us wanting for more welcome to the data doesn't lie, or does it a series of conversations produced by the cube and made possible by Starburst data. >>I'm your host, Dave Lanta and joining me today are three industry experts. Justin Borgman is this co-founder and CEO of Starburst. Richard Jarvis is the CTO at EMI health and Theresa tongue is cloud first technologist at Accenture. Today we're gonna have a candid discussion that will expose the unfulfilled and yes, broken promises of a data past we'll expose data lies, big lies, little lies, white lies, and hidden truths. And we'll challenge, age old data conventions and bust some data myths. We're debating questions like is the demise of a single source of truth. Inevitable will the data warehouse ever have feature parody with the data lake or vice versa is the so-called modern data stack simply centralization in the cloud, AKA the old guards model in new cloud close. How can organizations rethink their data architectures and regimes to realize the true promises of data can and will and open ecosystem deliver on these promises in our lifetimes, we're spanning much of the Western world today. Richard is in the UK. Teresa is on the west coast and Justin is in Massachusetts with me. I'm in the cube studios about 30 miles outside of Boston folks. Welcome to the program. Thanks for coming on. Thanks for having us. Let's get right into it. You're very welcome. Now here's the first lie. The most effective data architecture is one that is centralized with a team of data specialists serving various lines of business. What do you think Justin? >>Yeah, definitely a lie. My first startup was a company called hit adapt, which was an early SQL engine for IDU that was acquired by Teradata. And when I got to Teradata, of course, Terada is the pioneer of that central enterprise data warehouse model. One of the things that I found fascinating was that not one of their customers had actually lived up to that vision of centralizing all of their data into one place. They all had data silos. They all had data in different systems. They had data on-prem data in the cloud. You know, those companies were acquiring other companies and inheriting their data architecture. So, you know, despite being the industry leader for 40 years, not one of their customers truly had everything in one place. So I think definitely history has proven that to be a lie. >>So Richard, from a practitioner's point of view, you know, what, what are your thoughts? I mean, there, there's a lot of pressure to cut cost, keep things centralized, you know, serve the business as best as possible from that standpoint. What, what is your experience, Joe? >>Yeah, I mean, I think I would echo Justin's experience really that we, as a business have grown up through acquisition, through storing data in different places sometimes to do information governance in different ways to store data in, in a platform that's close to data experts, people who really understand healthcare data from pharmacies or from, from doctors. And so, although if you were starting from a Greenfield site and you were building something brand new, you might be able to centralize all the data and all of the tooling and teams in one place. The reality is that that businesses just don't grow up like that. And, and it's just really impossible to get that academic perfection of, of storing everything in one place. >>Y you know, Theresa, I feel like Sarbanes Oxley kinda saved the data warehouse, you know? Right. But you actually did have to have a single version of the truth for certain financial data, but really for those, some of those other use cases, I, I mentioned, I, I do feel like the industry has kinda let us down. What's your take on this? Where does it make sense to have that sort of centralized approach versus where does it make sense to maybe decentralized? >>I, I think you gotta have centralized governance, right? So from the central team, for things like swans Oxley, for things like security, for certain very core data sets, having a centralized set of roles, responsibilities to really QA, right. To serve as a design authority for your entire data estate, just like you might with security, but how it's implemented has to be distributed. Otherwise you're not gonna be able to scale. Right? So being able to have different parts of the business really make the right data investments for their needs. And then ultimately you're gonna collaborate with your partners. So partners that are not within the company, right. External partners, we're gonna see a lot more data sharing and model creation. And so you're definitely going to be decentralized. >>So, you know, Justin, you guys last, geez, I think it was about a year ago, had a session on, on data mesh. It was a great program. You invited JAK, Dani, of course, she's the creator of the data mesh. And her one of our fundamental premises is that you've got this hyper specialized team that you've gotta go through. And if you want anything, but at the same time, these, these individuals actually become a bottleneck, even though they're some of the most talented people in the organization. So I guess question for you, Richard, how do you deal with that? Do you, do you organize so that there are a few sort of rock stars that, that, you know, build cubes and, and the like, and, and, and, or have you had any success in sort of decentralizing with, you know, your, your constituencies, that data model? >>Yeah. So, so we absolutely have got rockstar, data scientists and data guardians. If you like people who understand what it means to use this data, particularly as the data that we use at emos is very private it's healthcare information. And some of the, the rules and regulations around using the data are very complex and, and strict. So we have to have people who understand the usage of the data, then people who understand how to build models, how to process the data effectively. And you can think of them like consultants to the wider business, because a pharmacist might not understand how to structure a SQL query, but they do understand how they want to process medication information to improve patient lives. And so that becomes a, a consulting type experience from a, a set of rock stars to help a, a more decentralized business who needs to, to understand the data and to generate some valuable output. >>Justin, what do you say to a, to a customer or prospect that says, look, Justin, I'm gonna, I got a centralized team and that's the most cost effective way to serve the business. Otherwise I got, I got duplication. What do you say to that? >>Well, I, I would argue it's probably not the most cost effective and, and the reason being really twofold. I think, first of all, when you are deploying a enterprise data warehouse model, the, the data warehouse itself is very expensive, generally speaking. And so you're putting all of your most valuable data in the hands of one vendor who now has tremendous leverage over you, you know, for many, many years to come, I think that's the story of Oracle or Terra data or other proprietary database systems. But the other aspect I think is that the reality is those central data warehouse teams is as much as they are experts in the technology. They don't necessarily understand the data itself. And this is one of the core tenets of data mash that that jam writes about is this idea of the domain owners actually know the data the best. >>And so by, you know, not only acknowledging that data is generally decentralized and to your earlier point about, so Oxley, maybe saving the data warehouse, I would argue maybe GDPR and data sovereignty will destroy it because data has to be decentralized for, for those laws to be compliant. But I think the reality is, you know, the data mesh model basically says, data's decentralized, and we're gonna turn that into an asset rather than a liability. And we're gonna turn that into an asset by empowering the people that know the data, the best to participate in the process of, you know, curating and creating data products for, for consumption. So I think when you think about it, that way, you're going to get higher quality data and faster time to insight, which is ultimately going to drive more revenue for your business and reduce costs. So I think that that's the way I see the two, the two models comparing and con contrasting. >>So do you think the demise of the data warehouse is inevitable? I mean, I mean, you know, there Theresa you work with a lot of clients, they're not just gonna rip and replace their existing infrastructure. Maybe they're gonna build on top of it, but the, what does that mean? Does that mean the ed w just becomes, you know, less and less valuable over time, or it's maybe just isolated to specific use cases. What's your take on that? >>Listen, I still would love all my data within a data warehouse would love it. Mastered would love it owned by essential team. Right? I think that's still what I would love to have. That's just not the reality, right? The investment to actually migrate and keep that up to date. I would say it's a losing battle. Like we've been trying to do it for a long time. Nobody has the budgets and then data changes, right? There's gonna be a new technology. That's gonna emerge that we're gonna wanna tap into. There's gonna be not enough investment to bring all the legacy, but still very useful systems into that centralized view. So you keep the data warehouse. I think it's a very, very valuable, very high performance tool for what it's there for, but you could have this, you know, new mesh layer that still takes advantage of the things. I mentioned, the data products in the systems that are meaningful today and the data products that actually might span a number of systems. Maybe either those that either source systems, the domains that know it best, or the consumer based systems and products that need to be packaged in a way that be really meaningful for that end user, right? Each of those are useful for a different part of the business and making sure that the mesh actually allows you to lose all of them. >>So, Richard, let me ask you, you take, take Gemma's principles back to those. You got, you know, the domain ownership and, and, and data as product. Okay, great. Sounds good. But it creates what I would argue or two, you know, challenges self-serve infrastructure let's park that for a second. And then in your industry, one of the high, most regulated, most sensitive computational governance, how do you automate and ensure federated governance in that mesh model that Theresa was just talking about? >>Well, it absolutely depends on some of the tooling and processes that you put in place around those tools to be, to centralize the security and the governance of the data. And, and I think, although a data warehouse makes that very simple, cause it's a single tool, it's not impossible with some of the data mesh technologies that are available. And so what we've done at EMI is we have a single security layer that sits on top of our data mesh, which means that no matter which user is accessing, which data source, we go through a well audited well understood security layer. That means that we know exactly who's got access to which data field, which data tables. And then everything that they do is, is audited in a very kind of standard way, regardless of the underlying data storage technology. So for me, although storing the data in one place might not be possible understanding where your source of truth is and securing that in a common way is still a valuable approach and you can do it without having to bring all that data into a single bucket so that it's all in one place. >>And, and so having done that and investing quite heavily in making that possible has paid dividends in terms of giving wider access to the platform and ensuring that only data that's available under GDPR and other regulations is being used by, by the data users. >>Yeah. So Justin mean Democrat, we always talk about data democratization and you know, up until recently, they really haven't been line of sight as to how to get there. But do you have anything to add to this because you're essentially taking, you know, doing analytic queries and with data, that's all dispersed all over the, how are you seeing your customers handle this, this challenge? >>Yeah, I mean, I think data products is a really interesting aspect of the answer to that. It allows you to, again, leverage the data domain owners, people know the data, the best to, to create, you know, data as a product ultimately to be consumed. And we try to represent that in our product as effectively, almost eCommerce, like experience where you go and discover and look for the data products that have been created in your organization. And then you can start to consume them as, as you'd like. And so really trying to build on that notion of, you know, data democratization and self-service, and making it very easy to discover and, and start to use with whatever BI tool you, you may like, or even just running, you know, SQL queries yourself. >>Okay. G guys grab a sip of water. After the short break, we'll be back to debate whether proprietary or open platforms are the best path to the future of data excellence. Keep it right there.

>>Hey, everyone. Welcome to the AWS partner, showcase women in tech. I'm Lisa Martin from the cube. And today we're gonna be looking into the exciting evolution of women in the tech industry. I'm going to be joined by Danielle GShock, the ISP PSA director at AWS. And we have the privilege of speaking with some wicked smart women from Teradata NetApp. JFI a 10th revolution group, company and honeycomb.io. We're gonna look at some of the challenges and biases that women face in the tech industry, especially in leadership roles. We're also gonna be exploring how are these tech companies addressing diversity, equity and inclusion across their organizations? How can we get more young girls into stem earlier in their careers? So many questions. So let's go ahead and get started. This is the AWS partner showcase women in tech. Hey, everyone. Welcome to the AWS partner showcase. This is season one, episode three. And I'm your host, Lisa Martin. I've got two great guests here with me to talk about women in tech. Hillary Ashton joins us the chief product officer at Terry data. And Danielle Greshaw is back with us, the ISV PSA director at AWS ladies. It's great to have you on the program talking through such an important topic, Hillary, let's go ahead and start with you. Give us a little bit of an intro into you, your background, and a little bit about Teradata. >>Yeah, absolutely. So I'm Hillary Ashton. I head up the products organization. So that's our engineering product management office of the CTO team. Um, at Teradata I've been with Terra data for just about three years and really have spent the last several decades. If I can say that in the data and analytics space, um, I spent time, uh, really focused on the value of, of analytics at scale, and I'm super excited to be here at Teradata. I'm also a mom of two teenage boys. And so as we talk about women in tech, I think there's, um, uh, lots of different dimensions and angles of that. Um, at Teradata, we are partnered very deeply with AWS and happy to talk a little bit more about that, um, throughout this discussion as well. >>Excellent. A busy mom of two teen boys. My goodness. I don't know how you do it. Let's now look, Atter data's views of diversity, equity and inclusion. It's a, the, it's a topic that's important to everyone, but give us a snapshot into some of the initiatives that Terra data has there. >>Yeah, I have to say, I am super proud to be working at Teradata. We have gone through, uh, a series of transformations, but I think it starts with culture and we are deeply committed to diversity, equity and inclusion. It's really more than just a statement here. It's just how we live our lives. Um, and we use, uh, data to back that up. Um, in fact, we were named one of the world's most ethical companies for the 13th year in a row. Um, and all of our executive leadership team has taken an oath around D E and I that's available on LinkedIn as well. So, um, in fact, our leadership team reporting into the CEO is just about 50 50, um, men and women, which is the first time I've worked in a company where that has been the case. And I think as individuals, we can probably appreciate what a huge difference that makes in terms of not just being a representative, but truly being on a, on a diverse and equitable, uh, team. And I think it really, uh, improves the behaviors that we can bring, um, to our office. >>There's so much value in that. It's I impressive to see about a 50 50 at the leadership level. That's not something that we see very often. Tell me how you, Hillary, how did you get into tech? Were you an engineering person by computer science, or did you have more of a zigzaggy path to where you are now? >>I'm gonna pick door number two and say more zigzaggy. Um, I started off thinking, um, that I started off as a political science major or a government major. Um, and I was probably destined to go into, um, the law field, but actually took a summer course at Harvard. I did not go to Harvard, but I took a summer course there and learned a lot about multimedia and some programming. And that really set me on a trajectory of how, um, data and analytics can truly provide value and, and outcomes to our customers. Um, and I have been living that life ever since. Um, I graduated from college, so, um, I was very excited and privileged in my early career to, uh, work in a company where I found after my first year that I was managing, um, uh, kids, people who had graduated from Harvard business school and from MIT Sloan school. Um, and that was super crazy, cuz I did not go to either of those schools, but I sort of have always had a natural knack for how do you take technology and, and the really cool things that technology can do, but because I'm not a programmer by training, I'm really focused on the value that I'm able to help, um, organizations really extract value, um, from the technology that we can create, which I think is fantastic. >>I think there's so much value in having a zigzag path into tech. You bring Danielle, you and I have talked about this many times you bring such breadth and such a wide perspective. That really is such a value. Add to teams. Danielle, talk to us from AWS's perspective about what can be done to encourage more young women to get and under and underrepresented groups as well, to get into stem and stay. >>Yeah, and this is definitely a challenge as we're trying to grow our organization and kind of shift the numbers. And the reality is, especially with the more senior folks in our organization, unless you bring folks with a zigzag path, the likelihood is you won't be able to change the numbers that you have. Um, but for me, it's really been about, uh, looking at that, uh, the folks who are just graduating college, maybe in other roles where they are adjacent to technology and to try to spark their interest and show that yes, they can do it because oftentimes it's really about believing in themselves and, and realizing that we need folks with all sorts of different perspectives to kind of come in, to be able to help really, um, provide both products and services and solutions for all types of people inside of technology, which requires all sorts of perspectives. >>Yeah, the diverse perspectives. There's so much value and there's a lot of data that demonstrates how much value revenue impact organizations can make by having diversity, especially at the leadership level. Hillary, let's go back to you. We talked about your career path. You talked about some of the importance of the focus on de and I at Tarana, but what are, what do you think can be done to encourage, to sorry, to recruit more young women and under groups into tech, any, any carrot there that you think are really important that we need to be dangling more of? >>Yeah, absolutely. And I'll build on what Danielle just said. I think the, um, bringing in diverse understandings, um, of, of customer outcomes, I mean, I, the we've really moved from technology for technology's sake and I know AWS and entirety to have had a lot of conversations on how do we drive customer outcomes that are differentiated in the market and really being customer centric and technology is wonderful. You can do wonderful things with it. You can do not so wonderful things with it as well, but unless you're really focused on the outcomes and what customers are seeking, um, technology is not hugely valuable. And so I think bringing in people who understand, um, voice of customer who understand those outcomes, and those are not necessarily the, the, the folks who are PhD in mathematics or statistics, um, those can be people who understand a day in the life of a data scientist or a day in the life of a citizen data scientist. And so really working to bridge the high impact technology with the practical kind of usability, usefulness of data and analytics in our cases, I think is something that we need more of in tech and sort of demystifying tech and freeing technology so that everybody can use it and having a really wide range of people who understand not just the bits and bites and, and how to program, but also the value in outcomes that technology through data and analytics can drive. >>Yeah. You know, we often talk about the hard skills, but this, their soft skills are equally, if not more important that even just being curious, being willing to ask questions, being not afraid to be vulnerable, being able to show those sides of your personality. I think those are important for, for young women and underrepresented groups to understand that those are just as important as some of the harder technical skills that can be taught. >>That's right. >>What do you think about from a bias perspective, Hillary, what have you seen in the tech industry and how do you think we can leverage culture as you talked about to help dial down some of the biases that are going on? >>Yeah. I mean, I think first of all, and, and there's some interesting data out there that says that 90% of the population, which includes a lot of women have some inherent bias in their day, day behaviors when it comes to to women in particular. But I'm sure that that is true across all kinds of, of, um, diverse and underrepresented folks in, in the world. And so I think acknowledging that we have bias and actually really learning how, what that can look like, how that can show up. We might be sitting here and thinking, oh, of course I don't have any bias. And then you realize that, um, as you, as you learn more about, um, different types of bias, that actually you do need to kind of, um, account for that and change behaviors. And so I think learning is sort of a fundamental, um, uh, grounding for all of us to really know what bias looks like, know how it shows up in each of us. >>Um, if we're leaders know how it shows up in our teams and make sure that we are constantly getting better, we're, we're not gonna be perfect anytime soon. But I think being on a path to improvement to overcoming bias, um, is really, is really critical. And part of that is really starting the dialogue, having the conversations, holding ourselves and each other accountable, um, when things aren't going in, in a, in a Coptic way and being able to talk openly about that, that felt, um, like maybe there was some bias in that interaction and how do we, um, how do we make good on that? How do we change our, our behavior? Fundamentally of course, data and analytics can have some bias in it as well. And so I think as we look at the, the technology aspect of bias, um, looking at at ethical AI, I think is a, a really important, uh, additional area. And I'm sure we could spend another 20 minutes talking about that, but I, I would be remiss if I didn't talk more about sort of the bias, um, and the over the opportunity to overcome bias in data and analytics as well. >>Yeah. The opportunity to overcome it is definitely there you bring up a couple of really good points, Hillary. It, it starts with awareness. We need to be aware that there are inherent biases in data in thought. And also to your other point, hold people accountable ourselves, our teammates, that's critical to being able to, to dial that back down, Daniel, I wanna get your perspective on, on your view of women in leadership roles. Do you think that we have good representation or we still have work to do in there? >>I definitely think in both technical and product roles, we definitely have some work to do. And, you know, when I think about, um, our partnership with Teradata, part of the reason why it's so important is, you know, Teradata solution is really the brains of a lot of companies. Um, you know, the what, how, what they differentiate on how they figure out insights into their business. And it's, it's all about the product itself and the data and the same is true at AWS. And, you know, we really could do some work to have some more women in these technical roles, as well as in the product, shaping the products. Uh, just for all the reasons that we just kind of talked about over the last 10 minutes, um, in order to, you know, move bias out of our, um, out of our solutions and also to just build better products and have, uh, better, you know, outcomes for customers. So I think there's a bit of work to do still. >>I agree. There's definitely a bit of work to do, and it's all about delivering those better outcomes for customers at the end of the day, we need to figure out what the right ways are of doing that and working together in a community. Um, we've had obviously a lot had changed in the last couple of years, Hillary, what's your, what have you seen in terms of the impact that the pandemic has had on this status of women in tech? Has it been a pro is silver lining the opposite? What are you seeing? >>Yeah, I mean, certainly there's data out there that tells us factually that it has been, um, very difficult for women during COVID 19. Um, women have, uh, dropped out of the workforce for a wide range of, of reasons. Um, and, and that I think is going to set us back all of us, the, the Royal us or the Royal we back, um, years and years. Um, and, and it's very unfortunate because I think we we're at a time when we're making great progress and now to see COVID, um, setting us back in, in such a powerful way. I think there's work to be done to understand how do we bring people back into the workforce. Um, how do we do that? Understanding work life balance, better understanding virtual and remote, working better. I think in the technology sector, um, we've really embraced, um, hybrid virtual work and are, are empowering people to bring their whole selves to work. >>And I think if anything, these, these zoom calls have, um, both for the men and the women on my team. In fact, I would say much more. So for the men on my team, I'm seeing, I was seeing more kids in the background, more kind of split childcare duties, more ability to start talking about, um, other responsibilities that maybe they had, uh, especially in the early days of COVID where maybe daycares were shut down. And, um, you had, you know, maybe a parent was sick. And so we saw quite a lot of, um, people bringing their whole selves to the office, which I think was, was really wonderful. Um, uh, even our CEO saw some of that. And I think, um, that that really changes the dialogue, right? It changes it to maybe scheduling meetings at a time when, um, people can do it after daycare drop off. >>Um, and really allowing that both for men and for women makes it better for, for women overall. So I would like to think that this hybrid working, um, environment and that this, um, uh, whole view into somebody's life that COVID has really provided for probably for white collar workers, if I'm being honest for, um, people who are in a, at a better point of privilege, they don't necessarily have to go into the office every day. I would like to think that tech can lead the way in, um, you know, coming out of the, the old COVID. I don't know if we have a new COVID coming, but the old COVID and really leading the way for women and for people, um, to transform how we do work, um, leveraging data and analytics, but also, um, overcoming some of the, the disparities that exist for women in particular in the workforce. >>Yeah, I think there's, there's like we say, there's a lot of opportunity there and I like your point of hopefully tech can be that guiding light that shows us this can be done. We're all humans at the end of the day. And ultimately if we're able to have some sort of work life balance, everything benefits, our work or more productive, higher performing teams impacts customers, right? There's so much value that can be gleaned from, from that hybrid model and embracing for humans. We need to be able to, to work when we can, we've learned that you don't have to be, you know, in an office 24, 7 commuting, crazy hours flying all around the world. We can get a lot of things done in a ways that fit people's lives rather than taking command over it. Wanna get your advice, Hillary, if you were to talk to your younger self, what would be some of the key pieces of advice you would say? And Danielle and I have talked about this before, and sometimes we, we would both agree on like, ask more questions. Don't be afraid to raise your hand, but what advice would you give your younger self and that younger generation in terms of being inspired to get into tech >>Oh, inspired and being in tech? You know, I think looking at technology as, in some ways, I feel like we do a disservice to, um, inclusion when we talk about stem, cuz I think stem can be kind of daunting. It can be a little scary for people for younger people. When I, when I go and talk to folks at schools, I think stem is like, oh, all the super smart kids are over there. They're all like maybe they're all men. And so, um, it's, it's a little, uh, intimidating. Um, and stem is actually, you know, especially for, um, people joining the workforce today. It's actually how you've been living your life since you were born. I mean, you know, stem inside and out because you walk around with a phone and you know how to get your internet working and like that is technology right. >>Fundamentally. And so demystifying stem as something that is around how we, um, actually make our, our lives useful and, and, and how we can change outcomes. Um, through technology I think is maybe a different lens to put on it. So, and there's absolutely for, for hard sciences, there's absolutely a, a great place in the world for folks who wanna pursue that and men and women can do that. So I, I don't want to be, um, uh, setting the wrong expectations, but I, I think stem is, is very holistic in, um, in the change that's happening globally for us today across economies, across global warming, across all kinds of impactful issues. And so I think everybody who's interested in, in some of that world change can participate in stem. It just may be through a different, through a different lens than how we classically talk about stem. >>So I think there's great opportunity to demystify stem. I think also, um, what I would tell my younger self is choose your bosses wisely. And that sounds really funny. That sounds like inside out almost, but I think choose the person that you're gonna work for in your first five to seven years. And it might be more than one person, but be, be selective, maybe be a little less selective about the exact company or the exact title. I think picking somebody that, you know, we talk about mentors and we talk about sponsors and those are important. Um, but the person you're gonna spend in your early career, a lot of your day with a lot, who's gonna influence a lot of the outcomes for you. That is the person that you, I think want to be more selective about, um, because that person can set you up for success and give you opportunities and set you on course to be, um, a standout or that person can hold you back. >>And that person can put you in the corner and not invite you to the meetings and not give you those opportunities. And so we're in an economy today where you actually can, um, be a little bit picky about who you go and work for. And I would encourage my younger self. I actually, I just lucked out actually, but I think that, um, my first boss really set me, um, up for success, gave me a lot of feedback and coaching. Um, and some of it was really hard to hear, but it really set me up for, for, um, the, the path that I've been on ever since. So it, that would be my advice. >>I love that advice. I it's brilliant. I didn't think it choose your bosses wisely. Isn't something that we primarily think about. I think a lot of people think about the big name companies that they wanna go after and put on a resume, but you bring up a great point. And Danielle and I have talked about this with other guests about mentors and sponsors. I think that is brilliant advice and also more work to do to demystify stem. But luckily we have great family leaders like the two of you helping us to do that. Ladies, I wanna thank you so much for joining me on the program today and talking through what you're seeing in de and I, what your companies are doing and the opportunities that we have to move the needle. Appreciate your time. >>Thank you so much. Great to see you, Danielle. Thank you Lisa, to see you. >>My pleasure for my guests. I'm Lisa Martin. You're watching the AWS partner showcase season one, episode three. Hey everyone. Welcome to the AWS partner showcase. This is season one, episode three, with a focus on women in tech. I'm your host, Lisa Martin. I've got two guests here with me, Sue Peretti, the EVP of global AWS strategic alliances at Jefferson Frank, a 10th revolution group company, and Danielle brushoff. One of our cube alumni joins us ISV PSA director, ladies. It's great to have you on the program talking about a, a topic that is near and dear to my heart at women in tech. >>Thank you, Lisa. >>So let's go ahead and start with you. Give the audience an understanding of Jefferson Frank, what does the company do and about the partnership with AWS? >>Sure. Um, so let's just start, uh, Jefferson Frank is a 10th revolution group company. And if you look at it, it's really talent as a service. So Jefferson Frank provides talent solutions all over the world for AWS clients, partners and users, et cetera. And we have a sister company called revelent, which is a talent creation company within the AWS ecosystem. So we create talent and put it out in the ecosystem. Usually underrepresented groups over half of them are women. And then we also have, uh, a company called rubra, which is a delivery model around AWS technology. So all three companies fall under the 10th revolution group organization. >>Got it. Danielle, talk to me a little bit about from AWS's perspective and the focus on hiring more women in technology and about the partnership. >>Yes. I mean, this has definitely been a focus ever since I joined eight years ago, but also just especially in the last few years we've grown exponentially and our customer base has changed. You know, we wanna have, uh, an organization interacting with them that reflects our customers, right. And, uh, we know that we need to keep pace with that even with our growth. And so we've very much focused on early career talent, um, bringing more women and underrepresented minorities into the organization, sponsoring those folks, promoting them, uh, giving them paths to growth, to grow inside of the organization. I'm an example of that. Of course I benefit benefited from it, but also I try to bring that into my organization as well. And it's super important. >>Tell me a little bit about how you benefited from that, Danielle. >>Um, I just think that, um, you know, I I've been able to get, you know, a seat at the table. I think that, um, I feel as though I have folks supporting me, uh, very deeply and wanna see me succeed. And also they put me forth as, um, you know, a, represent a representative, uh, to bring more women into the organization as well. And I think, um, they give me a platform, uh, in order to do that, um, like this, um, but also many other, uh, spots as well. Um, and I'm happy to do it because I feel that, you know, if you always wanna feel that you're making a difference in your job, and that is definitely a place where I get that time and space in order to be that representative to, um, bring more, more women into benefiting from having careers in technology, which there's a lot of value there, >>A lot of value. Absolutely. So back over to you, what are some of the trends that you are seeing from a gender diversity perspective in tech? We know the, the numbers of women in technical positions, uh, right. There's so much data out there that shows when girls start dropping up, but what are some of the trends that you are seeing? >>So it's, that's a really interesting question. And, and Lisa, I had a whole bunch of data points that I wanted to share with you, but just two weeks ago, uh, I was in San Francisco with AWS at the, at the summit. And we were talking about this. We were talking about how we can collectively together attract more women, not only to, uh, AWS, not only to technology, but to the AWS ecosystem in particular. And it was fascinating because I was talking about, uh, the challenges that women have and how hard to believe, but about 5% of women who were in the ecosystem have left in the past few years, which was really, really, uh, something that shocked everyone when we, when we were talking about it, because all of the things that we've been asking for, for instance, uh, working from home, um, better pay, uh, more flexibility, uh, better maternity leave seems like those things are happening. >>So we're getting what we want, but people are leaving. And it seemed like the feedback that we got was that a lot of women still felt very underrepresented. The number one thing was that they, they couldn't be, you can't be what you can't see. So because they, we feel collectively women, uh, people who identify as women just don't see enough women in leadership, they don't see enough mentors. Um, I think I've had great mentors, but, but just not enough. I'm lucky enough to have a pres a president of our company, the president of our company, Zoe Morris is a woman and she does lead by example. So I'm very lucky for that. And Jefferson, Frank really quickly, we put out a hiring a salary and hiring guide a career and hiring guide every year and the data points. And that's about 65 pages long. No one else does it. Uh, it gives an abundance of information around, uh, everything about the AWS ecosystem that a hiring manager might need to know. But there is what, what I thought was really unbelievable was that only 7% of the people that responded to it were women. So my goal, uh, being that we have such a very big global platform is to get more women to respond to that survey so we can get as much information and take action. So >>Absolutely 7%. So a long way to go there. Danielle, talk to me about AWS's focus on women in tech. I was watching, um, Sue, I saw that you shared on LinkedIn, the Ted talk that the CEO and founder of girls and co did. And one of the things that she said was that there was a, a survey that HP did some years back that showed that, um, 60%, that, that men will apply for jobs if they only meet 60% of the list of requirements. Whereas with females, it's far, far less, we've all been in that imposter syndrome, um, conundrum before. But Danielle, talk to us about AWS, a specific focus here to get these numbers up. >>I think it speaks to what Susan was talking about, how, you know, I think we're approaching it top and bottom, right? We're looking out at what are the, who are the women who are currently in technical positions and how can we make AWS an attractive place for them to work? And that's all a lot of the changes that we've had around maternity leave and, and those types of things, but then also, um, more flexible working, uh, can, you know, uh, arrangements, but then also, um, early, how can we actually impact early, um, career women and actually women who are still in school. Um, and our training and certification team is doing amazing things to get, um, more girls exposed to AWS, to technology, um, and make it a less intimidating place and have them look at employees from AWS and say like, oh, I can see myself in those people. >>Um, and kind of actually growing the viable pool of candidates. I think, you know, we're, we're limited with the viable pool of candidates, um, when you're talking about mid to late career. Um, but how can we, you know, help retrain women who are coming back into the workplace after, you know, having a child and how can we help with military women who want to, uh, or underrepresented minorities who wanna move into AWS, we have a great military program, but then also just that early high school, uh, career, you know, getting them in, in that trajectory. >>Sue, is that something that Jefferson Frank is also able to help with is, you know, getting those younger girls before they start to feel there's something wrong with me. I don't get this. Talk to us about how Jefferson Frank can help really drive up that in those younger girls. >>Uh, let me tell you one other thing to refer back to that summit that we did, uh, we had breakout sessions and that was one of the topics. What can cuz that's the goal, right? To make sure that, that there are ways to attract them. That's the goal? So some of the things that we talked about was mentoring programs, uh, from a very young age, some people said high school, but then we said even earlier, goes back to you. Can't be what you can't see. So, uh, getting mentoring programs, uh, established, uh, we also talked about some of the great ideas was being careful of how we speak to women using the right language to attract them. And some, there was a teachable moment for, for me there actually, it was really wonderful because, um, an African American woman said to me, Sue and I, I was talking about how you can't be what you can't see. >>And what she said was Sue, it's really different. Um, for me as an African American woman, uh, or she identified, uh, as nonbinary, but she was relating to African American women. She said, your white woman, your journey was very different than my journey. And I thought, this is how we're going to learn. I wasn't offended by her calling me out at all. It was a teachable moment. And I thought I understood that, but those are the things that we need to educate people on those, those moments where we think we're, we're saying and doing the right thing, but we really need to get that bias out there. So here at Jefferson, Frank, we're, we're trying really hard to get that careers and hiring guide out there. It's on our website to get more women, uh, to talk to it, but to make suggestions in partnership with AWS around how we can do this mentoring, we have a mentor me program. We go around the country and do things like this. We, we try to get the education out there in partnership with AWS. Uh, we have a, a women's group, a women's leadership group, uh, so much that, that we do, and we try to do it in partnership with AWS. >>Danielle, can you comment on the impact that AWS has made so far, um, regarding some of the trends and, and gender diversity that Sue was talking about? What's the impact that's been made so far with this partnership? >>Well, I mean, I think just being able to get more of the data and have awareness of leaders, uh, on how <laugh>, you know, it used to be a, a couple years back, I would feel like sometimes the, um, uh, solving to bring more women into the organization was kind of something that folks thought, oh, this is Danielle is gonna solve this. You know? And I think a lot of folks now realize, oh, this is something that we all need to solve for. And a lot of my colleagues who maybe a couple years ago, didn't have any awareness or didn't even have the tools to do what they needed to do in order to improve the statistics on their, or in their organizations. Now actually have those tools and are able to kind of work with, um, work with companies like Susan's work with Jefferson Frank in order to actually get the data and actually make good decisions and feel as though, you know, they, they often, these are not lived experiences for these folks, so they don't know what they don't know. And by providing data and providing awareness and providing tooling and then setting goals, I think all of those things have really turned, uh, things around in a very positive way. >>And so you bring up a great point about from a diversity perspective, what is Jefferson Frank doing to, to get those data points up, to get more women of, of all well, really underrepresented minorities to, to be able to provide that feedback so that you can, can have the data and gleamy insights from it to help companies like AWS on their strategic objectives. >>Right? So as I, when I go back to that higher that, uh, careers in hiring guide, that is my focus today, really because the more data that we have, I mean, the, and the data takes, uh, you know, we need people to participate in order to, to accurately, uh, get a hold of that data. So that's why we're asking, uh, we're taking the initiative to really expand our focus. We are a global organization with a very, very massive database all over the world, but if people don't take action, then we can't get the right. The, the, the data will not be as accurate as we'd like it to be. Therefore take better action. So what we're doing is we're asking people all over the, all over the world to participate on our website, Jefferson frank.com, the se the high, uh, in the survey. So we can learn as much as we can. >>7% is such a, you know, Danielle and I we're, we've got to partner on this just to sort of get that message out there, get more data so we can execute, uh, some of the other things that we're doing. We're, we're partnering in. As I mentioned, more of these events, uh, we're, we're doing around the summits, we're gonna be having more ed and I events and collecting more information from women. Um, like I said, internally, we do practice what we preach and we have our own programs that are, that are out there that are within our own company where the women who are talking to candidates and clients every single day are trying to get that message out there. So if I'm speaking to a client or one of our internal people are speaking to a client or a candidate, they're telling them, listen, you know, we really are trying to get these numbers up. >>We wanna attract as many people as we can. Would you mind going to this, uh, hiring guide and offering your own information? So we've gotta get that 7% up. We've gotta keep talking. We've gotta keep, uh, getting programs out there. One other thing I wanted to Danielle's point, she mentioned, uh, women in leadership, the number that we gathered was only 9% of women in leadership within the AWS ecosystem. We've gotta get that number up, uh, as well because, um, you know, I know for me, when I see people like Danielle or, or her peers, it inspires me. And I feel like, you know, I just wanna give back, make sure I send the elevator back to the first floor and bring more women in to this amazing ecosystem. >>Absolutely. That's not that metaphor I do too, but we, but to your point to get that those numbers up, not just at AWS, but everywhere else we need, it's a help me help use situation. So ladies underrepresented minorities, if you're watching go to the Jefferson Frank website, take the survey, help provide the data so that the woman here that are doing this amazing work, have it to help make decisions and have more of females and leadership roles or underrepresented minorities. So we can be what we can see. Ladies, thank you so much for joining me today and sharing what you guys are doing together to partner on this important. Cause >>Thank you for having me, Leah, Lisa, >>Thank you. My pleasure for my guests. I'm Lisa Martin. You're watching the cubes coverage of the AWS partner showcase. Thanks for your time. Hey everyone. Welcome to the AWS partner showcase season one, episode three women in tech. I'm your host, Lisa Martin. We've got two female rock stars here with me next. Stephanie Curry joins us the worldwide head of sales and go to market strategy for AWS at NetApp and Danielle GShock is back one of our QM ISV PSA director at AWS. Looking forward to a great conversation, ladies, about a great topic, Stephanie, let's go ahead and start with you. Give us an overview of your story, how you got into tech and what inspired you. >>Thanks so much, Lisa and Danielle. It's great to be on this show with you. Um, thank you for that. Uh, my name's Stephanie cur, as Lisa mentioned, I'm the worldwide head of sales for, uh, AWS at NetApp and run a global team of sales people that sell all things AWS, um, going back 25 years now, uh, when I first started my career in tech, it was kind of by accident. Um, I come from a different background. I have a business background and a technical background from school, um, but had been in a different career and I had an opportunity to try something new. Um, I had an ally really that reached out to me and said, Hey, you'd be great for this role. And I thought, I'd take a chance. I was curious. Um, and, uh, it, it turned out to be a 25 year career, um, that I'm really, really excited about and, and, um, really thankful for that person, for introducing me to the, to the industry >>25 years in counting. I'm sure Danielle, we've talked about your background before. So what I wanna focus on with you is the importance of diversity for high performance. I know what a machine AWS is, and Stephanie'll come back to you with the same question, but talk about that, Danielle, from your perspective, that importance, um, for diversity to drive the performance. >>Yeah. Yeah. I truly believe that, you know, in order to have high performing teams, that you have to have people from all different types of backgrounds and experiences. And we do find that oftentimes being, you know, field facing, if we're not reflecting our customers and connecting with them deeply, um, on, on the levels that they're at, we, we end up missing them. And so for us, it's very important to bring people of lots of different technical backgrounds experiences. And of course, both men, women, and underrepresented minorities and put that forth to our customers, um, in order to make that connection and to end up with better outcomes. So >>Definitely it's all about outcomes, Stephanie, your perspective and NetApp's perspective on diversity for creating highly performant teams and organizations. >>I really aligned with Danielle on the comment she made. And in addition to that, you know, just from building teams in my, um, career know, we've had three times as many women on my team since we started a year ago and our results are really showing in that as well. Um, we find the teams are stronger, they're more collaborative and to Danielle's point really reflective, not only our partners, but our customers themselves. So this really creates connections, which are really, really important to scale our businesses and, and really, uh, meet the customer where they're at as well. So huge proponent of that ourselves, and really finding that we have to be intentional in our hiring and intentional in how we attract diversity to our teams. >>So Stephanie let's stay with you. So a three X increase in women on the team in a year, especially the kind of last year that we've had is really incredible. I, I like your, I, your thoughts on there needs to be a, there needs to be focus and, and thought in how teams are hired. Let's talk about attracting and retaining those women now, especially in sales roles, we all know the number, the percentages of women in technical roles, but what are some of the things that, that you do Stephanie, that NetApp does to attract and retain women in those sales roles? >>The, the attracting part's really interesting. And we find that, you know, you, you read the stats and I'd say in my experience, they're also true in the fact that, um, a lot of women would look at a job description and say, I can't do a hundred percent of that, that, so I'm not even going to apply with the women that we've attracted to our team. We've actually intentionally reached out and targeted those people in a good way, um, to say, Hey, we think you've got what it takes. Some of the feedback I've got from those women are, gosh, I didn't think I could ever get this role. I didn't think I had the skills to do that. And they've been hired and they are doing a phenomenal job. In addition to that, I think a lot of the feedback I've got from these hires are, Hey, it's an aggressive sales is aggressive. Sales is competitive. It's not an environment that I think I can be successful in. And what we're showing them is bring those softer skills around collaboration, around connection, around building teams. And they do, they do bring a lot of that to the team. Then they see others like them there and they know they can be successful cuz they see others like them on the team, >>The whole concept of we can't be what we can't see, but we can be what we can't see is so important. You said a couple things, Stephanie, that really stuck with me. And one of them was an interview on the Cub I was doing, I think a couple weeks ago, um, about women in tech. And the stat that we talked about was that women will apply will not apply for a job unless they meet 100% of the skills and the requirements that it's listed, but men will, if they only meet 60. And I, that just shocked me that I thought, you know, I, I can understand that imposter syndrome is real. It's a huge challenge, but the softer skills, as you mentioned, especially in the last two years, plus the ability to communicate, the ability to collaborate are incredibly important to, to drive that performance of any team of any business. >>Absolutely. >>Danielle, talk to me about your perspective and AWS as well for attracting and retaining talent. And, and, and particularly in some of those challenging roles like sales that as Stephanie said, can be known as aggressive. >>Yeah, for sure. I mean, my team is focused on the technical aspect of the field and we definitely have an uphill battle for sure. Um, two things we are focused on first and foremost is looking at early career women and that how we, how can we bring them into this role, whether in they're in support functions, uh, cl like answering the phone for support calls, et cetera, and how, how can we bring them into this organization, which is a bit more strategic, more proactive. Um, and then the other thing that as far as retention goes, you know, sometimes there will be women who they're on a team and there are no other women on that team. And, and for me, it's about building community inside of AWS and being part of, you know, we have women on solution architecture organizations. We have, uh, you know, I just personally connect people as well and to like, oh, you should meet this person. Oh, you should talk to that person. Because again, sometimes they can't see someone on their team like them and they just need to feel anchored, especially as we've all been, you know, kind of stuck at home, um, during the pandemic, just being able to make those connections with women like them has been super important and just being a, a long tenured Amazonian. Um, that's definitely one thing I'm able to, to bring to the table as well. >>That's so important and impactful and spreads across organizations in a good way. Daniel let's stick with you. Let's talk about some of the allies that you've had sponsors, mentors that have really made a difference. And I said that in past tense, but I also mean in present tense, who are some of those folks now that really inspire you? >>Yeah. I mean, I definitely would say that one of my mentors and someone who, uh, ha has been a sponsor of my career has, uh, Matt YK, who is one of our control tower GMs. He has really sponsored my career and definitely been a supporter of mine and pushed me in positive ways, which has been super helpful. And then other of my business partners, you know, Sabina Joseph, who's a cube alum as well. She definitely has been, was a fabulous partner to work with. Um, and you know, between the two of us for a period of time, we definitely felt like we could, you know, conquer the world. It's very great to go in with a, with another strong woman, um, you know, and, and get things done, um, inside of an organization like AWS. >>Absolutely. And S I've, I've agreed here several times. So Stephanie, same question for you. You talked a little bit about your kind of, one of your, uh, original early allies in the tech industry, but talk to me about allies sponsors, mentors who have, and continue to make a difference in your life. >>Yeah. And, you know, I think it's a great differentiation as well, right? Because I think that mentors teach us sponsors show us the way and allies make room for us at the table. And that is really, really key difference. I think also as women leaders, we need to make room for others at the table too, and not forget those softer skills that we bring to the table. Some of the things that Danielle mentioned as well about making those connections for others, right. And making room for them at the table. Um, some of my allies, a lot of them are men. Brian ABI was my first mentor. Uh, he actually is in the distribution, was in distribution, uh, with advent tech data no longer there. Um, Corey Hutchinson, who's now at Hashi Corp. He's also another ally of mine and remains an ally of mine, even though we're not at the same company any longer. Um, so a lot of these people transcend careers and transcend, um, um, different positions that I've held as well and make room for us. And I think that's just really critical when we're looking for allies and when allies are looking for us, >>I love how you described allies, mentors and sponsors Stephanie. And the difference. I didn't understand the difference between a mentor and a sponsor until a couple of years ago. Do you talk with some of those younger females on your team so that when they come into the organization and maybe they're fresh outta college, or maybe they've transitioned into tech so that they can also learn from you and understand the importance and the difference between the allies and the sponsors and the mentors? >>Absolutely. And I think that's really interesting because I do take, uh, an extra, uh, approach an extra time to really reach out to the women that have joined the team. One. I wanna make sure they stay right. I don't want them feeling, Hey, I'm alone here and I need to, I need to go do something else. Um, and they are located around the world, on my team. They're also different age groups, so early in career, as well as more senior people and really reaching out, making sure they know that I'm there. But also as Danielle had mentioned, connecting them to other people in the community that they can reach out to for those same opportunities and making room for them >>Make room at the table. It's so important. And it can, you never know what a massive difference and impact you can make on someone's life. And I, and I bet there's probably a lot of mentors and sponsors and allies of mine that would be surprised to know, uh, the massive influence they've had Daniel back over. Let's talk about some of the techniques that you employ, that AWS employees to make the work environment, a great place for women to really thrive and, and be retained as Stephanie was saying. Of course that's so important. >>Yeah. I mean, definitely I think that the community building, as well as we have a bit more programmatic mentorship, um, we're trying to get to the point of having a more programmatic sponsorship as well. Um, but I think just making sure that, um, you know, both everything from, uh, recruit to onboard to ever boarding that, uh, they they're the women who come into the organization, whether it's they're coming in on the software engineering side or the field side or the sales side that they feel as that they have someone, uh, working with them to help them drive their career. Those are the key things that were, I think from an organizational perspective are happening across the board. Um, for me personally, when I run my organization, I'm really trying to make sure that people feel that they can come to me at any time open door policy, make sure that they're surfacing any times in which they are feeling excluded or anything like that, any challenges, whether it be with a customer, a partner or with a colleague. Um, and then also of course, just making sure that I'm being a good sponsor, uh, to, to people on my team. Um, that is key. You can talk about it, but you have to start with yourself as well. >>That's a great point. You you've got to, to start with yourself and really reflect on that. Mm-hmm <affirmative> and look, am I, am I embodying what it is that I need? And not that I know they need that focused, thoughtful intention on that is so importants, let's talk about some of the techniques that you use that NetApp uses to make the work environment a great place for those women are marginalized, um, communities to really thrive. >>Yeah. And I appreciate it and much like Danielle, uh, and much like AWS, we have some of those more structured programs, right around sponsorship and around mentorship. Um, probably some growth there, opportunities for allies, because I think that's more of a newer concept in really an informal structure around the allies, but something that we're growing into at NetApp, um, on my team personally, I think, um, leading by example's really key. And unfortunately, a lot of the, um, life stuffs still lands on the women, whether we like it or not. Uh, I have a very, uh, active husband in our household, but I still carry when it push comes to shove it's on me. Um, and I wanna make sure that my team knows it's okay to take some time and do the things you need to do with your family. Um, I'm I show up as myself authentically and I encourage them to do the same. >>So it's okay to say, Hey, I need to take a personal day. I need to focus on some stuff that's happening in my personal life this week now, obviously to make sure your job's covered, but just allowing some of that softer vulnerability to come into the team as well, so that others, um, men and women can feel they can do the same thing. And that it's okay to say, I need to balance my life and I need to do some other things alongside. Um, so it's the formal programs, making sure people have awareness on them. Um, I think it's also softly calling people out on biases and saying, Hey, I'm not sure if you know, this landed that way, but I just wanted to make you aware. And usually the feedback is, oh my gosh, I didn't know. And could you coach me on something that I could do better next time? So all of this is driven through our NetApp formal programs, but then it's also how you manifest it on the teams that we're leading. >>Absolutely. And sometimes having that mirror to reflect into can be really eye-opening and, and allow you to, to see things in a completely different light, which is great. Um, you both talked about, um, kind of being what you, uh, can see, and, and I know both companies are upset customer obsessed in a good way. Talk to me a little bit, Danielle, go back over to you about the AWS NetApp partnership. Um, some of that maybe alignment on, on performance on obviously you guys are very well aligned, uh, in terms of that, but also it sounds like you're quite aligned on diversity and inclusion. >>Well, we definitely do. We have the best partnerships with companies in which we have these value alignments. So I think that is a positive thing, of course, but just from a, from a partnership perspective, you know, from my five now plus years of being a part of the APN, this is, you know, one of the most significant years with our launch of FSX for NetApp. Um, with that, uh, key key service, which we're making available natively on AWS. I, I can't think of a better Testament to the, to the, um, partnership than that. And that's doing incredibly well and it really resonates with our customers. And of course it started with customers and their need for NetApp. Uh, so, you know, that is a reflection, I think, of the success that we're having together. >>And Stephanie talk to, uh, about the partnership from your perspective, NetApp, AWS, what you guys are doing together, cultural alignment, but also your alignment on really bringing diversity into drive performance. >>Yeah, I think it's a, a great question. And I have to say it's just been a phenomenal year. Our relationship has, uh, started before our first party service with FSX N but definitely just, um, uh, the trajectory, um, between the two companies since the announcement about nine months ago has just taken off to a, a new level. Um, we feel like an extended part of the family. We worked together seamlessly. A lot of the people in my team often say we feel like Amazonians. Um, and we're really part of this transformation at NetApp from being that storage hardware company into being an ISV and a cloud company. And we could not do this without the partnership with AWS and without the, uh, first party service of Fs XM that we've recently released. Um, I think that those joint values that Danielle referred to are critical to our success, um, starting with customer obsession and always making sure that we are doing the right thing for the customer. >>We coach our team teams all the time on if you are doing the right thing for the customers, you cannot do anything wrong. Just always put the customer at the, in the center of your decisions. And I think that there is, um, a lot of best practice sharing and collaboration as we go through this change. And I think a lot of it is led by the diverse backgrounds that are on the team, um, female, male, um, race and so forth, and just to really, uh, have different perspectives and different experiences about how we approach this change. Um, so we definitely feel like a part of the family. Uh, we are absolutely loving, uh, working with the AWS team and our team knows that we are the right place, the right time with the right people. >>I love that last question for each of you. And I wanna stick with you Stephanie advice to your younger self, think back five years. What advice would you seen what you've accomplished and maybe the thet route that you've taken along the way, what would you advise your youngest Stephanie self. >>Uh, I would say keep being curious, right? Keep being curious, keep asking questions. And sometimes when you get a no, it's not a bad thing, it just means not right now and find out why and, and try to get feedback as to why maybe that wasn't the right opportunity for you. But, you know, just go for what you want. Continue to be curious, continue to ask questions and find a support network of people around you that wanna help you because they are there and they, they wanna see you be successful too. So never be shy about that stuff. >><laugh> absolutely. And I always say failure does not have to be an, a bad F word. A no can be the beginning of something. Amazing. Danielle, same question for you. Thinking back to when you first started in your career, what advice would you give your younger self? >>Yeah, I think the advice I'd give my younger self would be, don't be afraid to put yourself out there. Um, it's certainly, you know, coming from an engineering background, maybe you wanna stay behind the scenes, not, not do a presentation, not do a public speaking event, those types of things, but back to what the community really needs, this thing. Um, you know, I genuinely now, uh, took me a while to realize it, but I realized I needed to put myself out there in order to, um, you know, allow younger women to see what they could be. So that would be the advice I would give. Don't be afraid to put yourself out there. >>Absolutely. That advice that you both gave are, is so fantastic, so important and so applicable to everybody. Um, don't be afraid to put yourself out there, ask questions. Don't be afraid of a, no, that it's all gonna happen at some point or many points along the way. That can also be good. So thank you ladies. You inspired me. I appreciate you sharing what AWS and NetApp are doing together to strengthen diversity, to strengthen performance and the advice that you both shared for your younger selves was brilliant. Thank you. >>Thank you. >>Thank you >>For my guests. I'm Lisa Martin. You're watching the AWS partner showcase. See you next time. Hey everyone. Welcome to the AWS partner showcase season one, episode three women in tech. I'm your host, Lisa Martin. I've got two female rock stars joining me. Next Vero Reynolds is here engineering manager, telemetry at honeycomb, and one of our cube alumni, Danielle Ock ISV PSA director at AWS. Join us as well. Ladies. It's great to have you talking about a very important topic today. >>Thanks for having us. >>Yeah, thanks for having me. Appreciate it. >>Of course, Vera, let's go ahead and start with you. Tell me about your background and tech. You're coming up on your 10th anniversary. Happy anniversary. >>Thank you. That's right. I can't believe it's been 10 years. Um, but yeah, I started in tech in 2012. Um, I was an engineer for most of that time. Uh, and just recently as a March, switched to engineering management here at honeycomb and, um, you know, throughout my career, I was very much interested in all the things, right. And it was a big FOMO as far as trying a few different, um, companies and products. And I've done things from web development to mobile to platforms. Um, it would be apt to call me a generalist. Um, and in the more recent years I was sort of gravitating more towards developer tool space. And for me that, uh, came in the form of cloud Foundry circle CI and now honeycomb. Um, I actually had my eye on honeycomb for a while before joining, I came across a blog post by charity majors. >>Who's one of our founders and she was actually talking about management and how to pursue that and whether or not it's right, uh, for your career. And so I was like, who is this person? I really like her, uh, found the company. They were pretty small at the time. So I was sort of keeping my eye on them. And then when the time came around for me to look again, I did a little bit more digging, uh, found a lot of talks about the product. And on the one hand they really spoke to me as the solution. They talked about developers owning their coding production and answering questions about what is happening, what are your users seeing? And I felt that pain, I got what they were trying to do. And also on the other hand, every talk I saw at the time was from, uh, an amazing woman <laugh>, which I haven't seen before. Uh, so I came across charity majors again, Christine Y our other founder, and then Liz Jones, who's our principal developer advocate. And that really sealed the deal for me as far as wanting to work here. >>Yeah. Honeycomb is interesting. This is a female founded company. You're two leaders. You mentioned that you like the technology, but you were also attracted because you saw females in the leadership position. Talk to me a little bit about what that's like working for a female led organization at honeycomb. >>Yeah. You know, historically, um, we have tried not to over index on that because there was this, uh, maybe fear awareness of, um, it taking away from our legitimacy as an engineering organization, from our success as a company. Um, but I'm seeing that, uh, rhetoric shift recently because we believe that with great responsibility, uh, with great power comes great responsibility, and we're trying to be more intentional as far as using that attribute of our company. Um, so I would say that for me, it was, um, a choice between a few offers, right. And that was a selling point for sure, because again, I've never experienced it and I've really seen how much they walk that walk. Um, even me being here and me moving into management, I think were both, um, ways in which they really put a lot of trust and support in me. And so, um, I it's been a great ride. >>Excellent. Sounds like it. Before we bring Danielle in to talk about the partnership. I do wanna have you there talk to the audience a little bit about honeycomb, what technology it's delivering and what are its differentiators. >>Yeah, absolutely. Um, so honeycomb is an observability tool, uh, that enables engineers to answer questions about the code that runs in production. And, um, we work with a number of various customers. Some of them are Vanguards, slack. Hello, fresh, just to name a couple, if you're not familiar with observability tooling, it's akin to traditional application performance monitoring, but we believe that observability is succeeding APM because, uh, APM tools were built at the time of monoliths and they just weren't designed to help us answer questions about complex distributed systems that we work with today, where things can go wrong anywhere in that chain. And you can't predict what you're gonna need to ask ahead of time. So some of the ways that we are different is our ability to store and query really rich data, which we believe is the key to understanding those complex systems. >>What I mean by rich data is, um, something that has a lot of attributes. So for example, when an error happens, knowing who it happened to, which user ID, which, um, I don't know, region, they were in, um, what, what, what they were doing at the time and what was happening at the rest of your system. And our ingest engine is really fast. You can do it in as little as three seconds and we call data like this. I said, kind of rich data, contextual data. We refer it as having high ality and high dimensionality, which are big words. But at the end of the day, what that means is we can store and we can query the data. We can do it really fast. And to give you an example of how that looks for our customers, let's say you have a developer team who are using comb to understand and observe their system. >>And they get a report that a user is experiencing a slowdown or something's wrong. They can go into comb and figure out that this only happens to users who are using a particular language pack with their app. And they operated their app last week, that it only happens when they are trying to upload a file. And so it's this level of granularity and being able to zoom in and out, um, under your data that allows you to understand what's happening, especially when you have an incident going on, right. Or your really important high profile customer is telling you that something's wrong. And we can do that. Even if everything else in your other tools looks fine, right? All of your dashboards are okay. You're not actually getting paged on it, but your customers are telling you that something's wrong. Uh, and we believe that's where we shine in helping you there. >>Excellent. It sounds like that's where you really shine that real time visibility is so critical these days. Danielle, Danielle, wanna bring you into the conversation. Talk to us a little bit about the honeycomb partnership from the AWS lens. >>Yeah. So excuse me, observability is obviously a very important, uh, segment in the cloud space, very important to AWS, um, because a lot of all of our customers, uh, as they build their systems distributed, they need to be able to see where, where things are happening in the complex systems that they're building. And so honeycomb is a, is an advanced technology partner. Um, they've been working with us for quite some time and they have a, uh, their solution is listed on the marketplace. Um, definitely something that we see a lot of demand with our customers and they have many integrations, uh, which, you know, we've seen is key to success. Um, being able to work seamlessly with the rest of the services inside of the AWS platform. And I know that they've done some, some great things with people who are trying to develop games on top of AWS, uh, things in that area as well. And so, uh, very important partner in the observa observability market that we have >>Back to you, let's kind of unpack the partnership, the significance that honeycomb ha is getting from being partners with an organization as potent and pivotal as AWS. >>Yeah, absolutely. Um, I know this predates me to some extent, but I know for a long time, AWS and honeycomb has really pushed the envelope together. And, um, I think it's a beneficial relationship for both ends. There's kind of two ways of looking at it. On the one side, there is our own infrastructure. So honeycomb runs on AWS and actually one of our critical workloads that supports that fast query engine that I mentioned uses Lambda. And it does so in a pretty Orthodox way. So we've had a longstanding conversation with the AWS team as far as drawing outside those lines and kind of figuring out how to use this technology in a way that works for us and hopefully will work for other customers of theirs as well. Um, that also allows us to ask for early access for certain features when they become available. >>And then that way we can be sort of the Guinea pigs and try things out, um, in a way that migrates our system and optimizes our own performance, but also allows again, other customers of AWS to follow in that path. And then the other side of that partnership is really supporting our customers who are both honeycomb users and AWS users, because it's, as you imagine, quite a big overlap, and there are certain ways in which we can allow our customers to more easily get their data from AWS to honeycomb. So for example, last year we built a tool, um, based on the new Lambda extension capability that allowed our users who run their applications in Lambdas to get that telemetry data out of their applications and into honeycomb. And it man was win, win. >>Excellent. So I'm hearing a lot of synergies from a technology perspective, you're sticking with you, and then Danielle will bring you in, let's talk about how honeycomb supports D and I across its organization. And how is that synergistic with AWS's approach? Yeah, >>Yeah, absolutely. So I sort of alluded to that hesitancy to over index on the women led aspect of ourselves. Um, but again, a lot of things are shifting, we're growing a lot. And so we are recognizing that we need to be more intentional with our DEI initiatives, and we also notice that we can do better and we should do better. And to that, and we're doing a few things differently, um, that are pretty recent initiatives. We are partnering with organizations that help us target specific communities that are underrepresented in tech. Um, some examples would be after tech hu Latinas in tech among, um, a number of others. And another initiative is DEI head start. That's something that is an internal, um, practice that we started that includes reaching out to underrepresented applicants before any new job for honeycomb becomes live. So before we posted to LinkedIn, before it's even live on our job speech, and the idea there is to kind of balance our pipeline of applicants, which the hope is will lead to more diverse hires in the long term. >>That's a great focus there. Danielle, I know we've talked about this before, but for the audience, in terms of the context of the honeycomb partnership, the focus at AWS for D E and I is really significant, unpack that a little bit for us. >>Well, let me just bring it back to just how we think about it, um, with the companies that we work with, but also in, in terms of, you know, what we want to be able to do, excuse me, it's very important for us to, you know, build products that reflect, uh, the customers that we have. And I think, you know, working with, uh, a company like honeycomb that is looking to differentiate in a space, um, by, by bringing in, you know, the experiences of many different types of people I genuinely believe. And I'm sure Vera also believes that by having those diverse perspectives, that we're able to then build better products for our customers. Um, and you know, it's one of, one of our leadership principles, uh, is, is rooted in this. I write a lot, it asks for us to seek out diverse perspectives. Uh, and you can't really do that if everybody kind of looks the same and thinks the same and has the same background. So I think that is where our de and I, um, you know, I thought process is rooted and, you know, companies like honeycomb that give customers choice and differentiate and help them, um, to do what they need to do in their unique, um, environments is super important. So >>The, the importance of thought diversity cannot be underscored enough. It's something that is, can be pivotal to organizations. And it's very nice to hear that that's so fundamental to both companies, Barry, I wanna go back to you for a second. You, I think you mentioned this, the DEI head start program, that's an internal program at honeycomb. Can you shed a little bit of light on that? >>Yeah, that's right. And I actually am in the process of hiring a first engineer for my team. So I'm learning a lot of these things firsthand, um, and how it works is we try to make sure to pre-load our pipeline of applicants for any new job opening we have with diverse candidates to the best of our abilities, and that can involve partnering with the organizations that I mentioned or reaching out to our internal network, um, and make sure that we give those applicants a head start, so to speak. >>Excellent. I like that. Danielle, before we close, I wanna get a little bit of, of your background. We've got various background in tag, she's celebrating her 10th anniversary. Give me a, a short kind of description of the journey that you've navigated through being a female in technology. >>Yeah, thanks so much. I really appreciate, uh, being able to share this. So I started as a software engineer, uh, back actually in the late nineties, uh, during the, the first.com bubble and, uh, have, have spent quite a long time actually as an individual contributor, um, probably working in software engineering teams up through 2014 at a minimum until I joined AWS, uh, as a customer facing solutions architect. Um, I do think spending a lot of time, hands on definitely helped me with some of the imposter syndrome, um, issues that folks suffer from not to say I don't at all, but it, it certainly helped with that. And I've been leading teams at AWS since 2015. Um, so it's really been a great ride. Um, and like I said, I'm very happy to see all of our engineering teams change, uh, as far as their composition. And I'm, I'm grateful to be part of it. >>It's pretty great to be able to witness that composition change for the better last question for each of you. And we're almost out of time and Danielle, I'm gonna stick with you. What's your advice, your recommendations for women who either are thinking about getting into tech or those who may be in tech, maybe they're in individual positions and they're not sure if they should apply for that senior leadership position. What do you advise them to do? >>I mean, definitely for the individual contributors, tech tech is a great career, uh, direction, um, and you will always be able to find women like you, you have to maybe just work a little bit harder, uh, to join, have community, uh, in that. But then as a leader, um, representation is very important and we can bring more women into tech by having more leaders. So that's my, you just have to take the lead, >>Take the lead, love that there. Same question for you. What's your advice and recommendations for those maybe future female leaders in tech? >>Yeah, absolutely. Um, Danielle mentioned imposter syndrome and I think we all struggle with it from time to time, no matter how many years it's been. And I think for me, for me, the advice would be if you're starting out, don't be afraid to ask, uh, questions and don't be afraid to kind of show a little bit of ignorance because we've all been there. And I think it's on all of us to remember what it's like to not know how things work. And on the flip side of that, if you are a more senior IC or, uh, in a leadership role, also being able to model just saying, I don't know how this works and going and figuring out answers together because that was a really powerful shift for me early in my career is just to feel like I can say that I don't know something. >>I totally agree. I've been in that same situation where just ask the question because you I'm guaranteed, there's a million outta people in the room that probably has the, have the same question and because of imposter syndrome, don't wanna admit, I don't understand that. Can we back up, but I agree with you. I think that is, um, one of the best things. Raise your hand, ask a question, ladies. Thank you so much for joining me talking about honeycomb and AWS, what you're doing together from a technology perspective and the focus efforts that each company has on D E and I, we appreciate your insights. Thank you so much for having us great talking to you. My pleasure, likewise for my guests, I'm Lisa Martin. You're watching the AWS partner showcase women in check. Welcome to the AWS partner showcase I'm Lisa Martin, your host. This is season one, episode three, and this is a great episode that focuses on women in tech. I'm pleased to be joined by Danielle Shaw, the ISV PSA director at AWS, and the sponsor of this fantastic program. Danielle, it's great to see you and talk about such an important topic. >>Yes. And I will tell you, all of these interviews have just been a blast for me to do. And I feel like there has been a lot of gold that we can glean from all of the, um, stories that we heard on these interviews and good advice that I myself would not have necessarily thought of. So >>I agree. And we're gonna get to set, cuz advice is one of the, the main things that our audience is gonna hear. We have Hillary Ashton, you'll see from TETA there, Reynolds joins us from honeycomb, Stephanie Curry from NetApp and Sue Paris from Jefferson Frank. And the topics that we dig into are first and foremost, diversity equity and inclusion. That is a topic that is incredibly important to every organization. And some of the things Danielle that our audiences shared were really interesting to me. One of the things that I saw from a thematic perspective over and over was that like D Reynolds was talking about the importance of companies and hiring managers and how they need to be intentional with de and I initiatives. And that intention was a, a, a common thing that we heard. I'm curious what your thoughts are about that, that we heard about being intentional working intentionally to deliver a more holistic pool of candidates where de I is concerned. What are your, what were some of the things that stuck out to you? >>Absolutely. I think each one of us is working inside of organizations where in the last, you know, five to 10 years, there's been a, you know, a strong push in this direction, mostly because we've really seen, um, first and foremost, by being intentional, that you can change the, uh, the way your organization looks. Um, but also just that, you know, without being intentional, um, there was just a lot of, you know, outcomes and situations that maybe weren't great for, um, you know, a healthy, um, and productive environment, uh, working environment. And so, you know, a lot of these companies have made a big investments and put forth big initiatives that I think all of us are involved in. And so we're really excited to get out here and talk about it and talk about, especially as these are all partnerships that we have, how, you know, these align with our values. So >>Yeah, that, that value alignment mm-hmm <affirmative> that you bring up is another thing that we heard consistently with each of the partners, there's a cultural alignment, there's a customer obsession alignment that they have with AWS. There's a D E and I alignment that they have. And I, I think everybody also kind of agreed Stephanie Curry talked about, you know, it's really important, um, for diversity on it, on, on impacting performance, highly performant teams are teams that are more diverse. I think we heard that kind of echoed throughout the women that we talked to in >>This. Absolutely. And I absolutely, and I definitely even feel that, uh, with their studies out there that tell you that you make better products, if you have all of the right input and you're getting all many different perspectives, but not just that, but I can, I can personally see it in the performing teams, not just my team, but also, you know, the teams that I work alongside. Um, arguably some of the other business folks have done a really great job of bringing more women into their organization, bringing more underrepresented minorities. Tech is a little bit behind, but we're trying really hard to bring that forward as well to in technical roles. Um, but you can just see the difference in the outcomes. Uh, at least I personally can just in the adjacent teams of mine. >>That's awesome. We talked also quite a bit during this episode about attracting women and underrepresented, um, groups and retaining them. That retention piece is really key. What were some of the things that stuck out to you that, um, you know, some of the guests talked about in terms of retention? >>Yeah. I think especially, uh, speaking with Hillary and hearing how, uh, Teradata is thinking about different ways to make hybrid work work for everybody. I think that is definitely when I talk to women interested in joining AWS, oftentimes that might be one of the first, uh, concerns that they have. Like, am I going to be able to, you know, go pick my kid up at four o'clock at the bus, or am I going to be able to, you know, be at my kids' conf you know, conference or even just, you know, have enough work life balance that I can, um, you know, do the things that I wanna do outside of work, uh, beyond children and family. So these are all very important, um, and questions that especially women come and ask, but also, um, you know, it kind of is a, is a bellwether for, is this gonna be a company that allows me to bring my whole self to work? And then I'm also gonna be able to have that balance that I need need. So I think that was something that is, uh, changing a lot. And many people are thinking about work a lot differently. >>Absolutely. The pandemic not only changed how we think about work, you know, initially it was, do I work from home or do I live at work? And that was legitimately a challenge that all of us faced for a long time period, but we're seeing the hybrid model. We're seeing more companies be open to embracing that and allowing people to have more of that balance, which at the end of the day, it's so much better for product development for the customers, as you talked about there's, it's a win-win. >>Absolutely. And, you know, definitely the first few months of it was very hard to find that separation to be able to put up boundaries. Um, but I think at least I personally have been able to find the way to do it. And I hope that, you know, everyone is getting that space to be able to put those boundaries up to effectively have a harmonious, you know, work life where you can still be at home most of the time, but also, um, you know, have that cutoff point of the day or at least have that separate space that you can feel that you're able to separate the two. >>Yeah, absolutely. And a lot of that from a work life balance perspective leads into one of the next topics that we covered in detail with, and that's mentors and sponsors the differences between them recommendations from, uh, the women on the panel about how to combat imposter syndrome, but also how to leverage mentors and sponsors throughout your career. One of the things that, that Hillary said that I thought was fantastic, advice were mentors and sponsors are concerned is, is be selective in picking your bosses. We often see people, especially younger folks, not necessarily younger folks. I shouldn't say that that are attracted to a company it's brand maybe, and think more about that than they do the boss or bosses that can help guide them along the way. But I thought that was really poignant advice that Hillary provided something that I'm gonna take into consideration myself. >>Yeah. And I honestly hadn't thought about that, but as I reflect through my own career, I can see how I've had particular managers who have had a major impact on helping me, um, with my career. But, you know, if you don't have the ability to do that, or maybe that's not a luxury that you have, I think even if you're able to, you know, find a mentor for a period of time or, um, you know, just, just enable for you to be able to get from say a point a to point B just for a temporary period. Um, just so you can grow into your next role, have a, have a particular outcome that you wanna drive, have a particular goal in mind find that person who's been there and done that and can really help you get through. If you don't have the luxury of picking your manager mentor, who can help you get to the next step. >>Exactly. That, that I thought that advice was brilliant and something that I hadn't really considered either. We also talked with several of the women about imposter syndrome. You know, that's something that everybody, I think, regardless of gender of your background, everybody feels that at some point. So I think one of the nice things that we do in this episode is sort of identify, yes, imposter syndrome is real. This is, this is how it happened to me. This is I navigated around or got over it. I think there's some great advice there for the audience to glean as well about how to dial down the imposter syndrome that they might be feeling. >>Absolutely. And I think the key there is just acknowledging it. Um, but also just hearing all the different techniques on, on how folks have dealt with it because everybody does, um, you know, even some of the smartest, most confident men I've, I've met in, uh, industry still talk to me about how they have it and I'm shocked by it oftentimes, but, um, it is very common and hopefully we, we talk about some good techniques to, to deal with that. >>I think we do, you know, one of the things that when we were asking the, our audience, our guests about advice, what would they tell their younger selves? What would they tell young women or underrepresented groups in terms of becoming interested in stem and in tech and everybody sort of agreed on me, don't be afraid to raise your hand and ask questions. Um, show vulnerabilities, not just as the employee, but even from a leadership perspective, show that as a leader, I, I don't have all the answers. There are questions that I have. I think that goes a long way to reducing the imposter syndrome that most of us have faced at some point in our lives. And that's just, don't be afraid to ask questions. You never know, oh, how can people have the same question sitting in the room? >>Well, and also, you know, for folks who've been in industry for 20, 25 years, I think we can just say that, you know, it's a, it's a marathon, it's not a sprint and you're always going to, um, have new things to learn and you can spend, you know, back to, we talked about the zing and zagging through careers, um, where, you know, we'll have different experiences. Um, all of that kind of comes through just, you know, being curious and wanting to continue to learn. So yes, asking questions and being vulnerable and being able to say, I don't know all the answers, but I wanna learn is a key thing, uh, especially culturally at AWS, but I'm sure with all of these companies as well, >>Definitely I think it sounded like it was really ingrained in their culture. And another thing too, that we also talked about is the word, no, doesn't always mean a dead end. It can often mean not right now or may, maybe this isn't the right opportunity at this time. I think that's another important thing that the audience is gonna learn is that, you know, failure is not necessarily a bad F word. If you turn it into opportunity, no isn't necessarily the end of the road. It can be an opener to a different door. And I, I thought that was a really positive message that our guests, um, had to share with the, the audience. >>Yeah, totally. I can, I can say I had a, a mentor of mine, um, a very, uh, strong woman who told me, you know, your career is going to have lots of ebbs and flows and that's natural. And you know that when you say that, not right now, um, that's a perfect example of maybe there's an ebb where it might not be the right time for you now, but something to consider in the future. But also don't be afraid to say yes, when you can. <laugh> >>Exactly. Danielle, it's been a pleasure filming this episode with you and the great female leaders that we have on. I'm excited for the audience to be able to learn from Hillary Vera, Stephanie Sue, and you so much valuable content in here. We hope you enjoy this partner showcase season one, episode three, Danielle, thanks so much for helping >>Us with it's been a blast. I really appreciate it >>All audience. We wanna enjoy this. Enjoy the episode.

(upbeat music) >> Hey, guys and girls, welcome back to New York City. Lisa Martin and John Furrier are live with theCUBE at AWS Summit 22, here in The Big Apple. We're excited to be talking about security next. James Arlen joins us, the CISO at Aiven. James, thanks so much for joining us on theCUBE today. >> Absolutely, it's good to be here. >> Tell the audience a little bit about Aiven, what you guys do, what you deliver, and what some of those differentiators are. >> Oh, Aiven. Aiven is a fantastic organization. I'm actually really lucky to work there. It's a database as a service, managed databases, all open source. And we're capital S, serious about open source. So 10 different open source database products delivered as a platform, all managed services, and the game is really about being the most performant, secure, and compliant database as a service on the market, friction free for your developers. You don't need people worrying about how to run databases. You just want to be able to say, here, take care of my data for me. And that's what we do. And that's actually the differentiator. We just take care of it for you. >> Take care of it for you, I like that. >> So they download the open source. They could do it on their own. So all the different projects are out there. >> Yeah, absolutely. >> What do you guys bringing to the table? You said the managed service, can you explain that. >> Yeah, the managed service aspect of it is, really, you could install the software yourself. You can use Postgres or Apache Kafka or any one of the products that we support. Absolutely you can do it yourself. But is that really what you do for a living, or do you develop software, or do you sell a product? So we take and do the hard work of running the systems, running the equipment. We take care of backups, high availability, all the security and compliance things around access and certifications, all of those things that are logging, all of that stuff that's actually difficult to do, well and consistently, that's all we do. >> Talk about the momentum, I see you guys were founded in what? 2016? >> Yes. >> Just in May of '22, raised $210 million in series D funding. >> Yes. >> Talk about the momentum and also from your perspective, all of the massive changes in security. >> It's very interesting to work for a company where you're building more than 100% growth year over year. It's a powers of two thing. Going from one to two, not so scary, two to four, not so scary. 512 to 1024, it's getting scary. (Lisa chuckles) 1024 to 2048, oh crap! I've been with Aiven for just almost two years now, and we are less than 70 when I started, and we're near 500 now. So, explosive growth is very interesting, but it's also that, you're growing within a reasonable burn rate boundary as well. And what that does from a security perspective, is it leaves you in the position that I had. I walked in and I was the first actual CISO. I had a team of four, I now have a team of 40. Because it turns out that like a lot of things in life, as you start unpacking problems, they're kind of fractal. You unpack the problem, you're like oh, well I did deal with that problem, but now I got another problem that I got to deal with. And so there's, it's not turtles all the way down. >> There's a lot of things going on and other authors, survive change. >> And there's fundamental problems that are still not fixed. And yet we treat them like they're fixed. And so we're doing a lot of hard work to make it so that we don't have to do hard work ongoing. >> And that's the value of the managed service. >> Yes. >> Okay, so talk about competition. Obviously, we had ETR on which is Enterprise Research Firm that we trust, we like. And we were looking at the data with the headwinds in the market, looking at the different players like got Amazon has Redshift, Snowflake, and you got Azure Sequence. I think it's called one of those products. The money that's being shifted from on premise data where the old school data warehouse like terra data and whatnot, is going first to Snowflake, then to Azure, then to AWS. Yes, so that points to snowflake being kind of like the bell of the ball if you will, in terms of from a data cloud. >> Absolutely. >> How do you compete with them? What's the pitch 'Cause that seemed to be a knee-jerk reaction from the industry. 'Cause snowflake is hot. They have a good value product. They have a smart team, Databrick is out there too. >> Yeah I mean... >> how do you guys compete against all that. >> So this is that point where you're balancing the value of a specific technology, or a specific technology vendor. And am I going to be stuck with them? So I'm tying my future to their future. With open source, I'm tying my future to the common good right. The internet runs on open source. It doesn't run on anything closed. And so I'm not hitching my wagon to something that I don't control. I'm hitching it to something where, any one of our customers could decide. I'm not getting the value I need from Aiven anymore. I need to go. And we provide you with the tools necessary, to move from our open source managed service to your own. Whether you go on-prem or you run it yourself, on a cloud service provider, move your data to you because it's your data. It's not ours. How can I hold your data? It's like weird extortion ransoming thing. >> Actually speaking, I mean enterprise, it's a big land grab 'cause with cloud you're horizontally scalable. It's a beautiful thing, open source is booming. It's going in Aiven, every day it's just escalating higher and higher. >> Absolutely. >> It is the software business. So open is open. Integration and scale seems to be the competitive advantage. >> Yeah. >> Right. So, how do you guys compete with that? Because now you got open source. How do you offer the same benefits without the lock in, or what's the switching costs? How do you guys maintain that position of not saying the same thing in Snowflake? >> Because all of the biggest data users and consumers tend to give away their data products. LinkedIn gave away their data product. Uber gave away their data product, Facebook gave away their data product. And we now use those as community solutions. So, if the product works for something the scale of LinkedIn, or something the scale of Uber. It will probably work for you too. And scale is just... >> Well Facebook and LinkedIn, they gave away the product to own the data to use against you. >> But it's the product that counts because you need to be able to manipulate data the way they manipulate data, but with yours. >> So low latency needs to work. So horizontally, scalable, fees, machine learning. That's what we're seeing. How do you make that available? Customers want on architecture? What do you recommend? Control plane, data plane, how do you think about that? >> It's interesting. There's architectural reasons to think about it in terms like that. And there's other good architectural reasons to not think about it. There's sort of this dividing line in the cloud, where your cloud service provider, takes over and provides you with the opportunity to say, I don't know. And I don't care >> As long as it's secure >> As long as it's secure absolutely. But there's sort of that water line idea, where if it's below the water line, let somebody else deal. >> What is in the table stakes? 'Cause I like that approach. I think that's a good value proposition. Store it, what boxes have to be checked? Compliance, secure, what are some of the boxes? >> You need to make sure that you've taken care of all of the same basics if you are still running it. Remember you can't absolve yourself of your duty to your customer. You're still on the hook. So, you have to have backups. You have to have access control. You have to understand who's administering it, and how and what they're doing. Good logging, good comprehension there. You have to have anomaly detection, secure operations. You have to have all those compliance check boxes. Especially if you're dealing with regulated data type like PCI data or HIPAA health data or you know what there's other countries besides the United States, there's other kinds of of compliance obligations there. So you have to make sure that you've got all that taken into account. And remember that, like I said, you can't absolve yourself with those things. You can share responsibilities. But you can't walk away from that responsibility. So you still have to make sure that you validate that your vendor knows what they're talking about. >> I wanted to ask you about the cybersecurity skills gap. So I'm kind of giving a little segue here, because you mentioned you've been with Aiven for about two years. >> Almost. >> Almost two years. You've started with a team of four. You've grown at 10X in less than two years. How have you accomplished that, considering we're seeing one of the biggest skills shortages in cyber in history. >> It's amazing, you see this show up in a lot of job Ads, where they ask for 10 years of experience in something that's existed for three years. (John Furrier laughs) And it's like okay, well if I just be logical about this I can hire somebody at less than the skill level that I need today, and bring them up to that skill level. Or I can spend the same amount of time, hoping that I'll find the magical person that has that set of skills that I need. So I can solve the problem of the skills gap by up-skilling the people that I hire. Which is strangely contrary to how this thing works. >> The other thing too, is the market's evolving so fast that, that carry up and pulling someone along, or building and growing your own so to speak is workable. >> It also really helps us with a bunch of sustainability goals. It really helps with anything that has to do with diversity and inclusion, because I can bring forward people who are never given a chance. And say, you know what? You don't have that magical ticket in life, but damn you know what you're talking about? >> It's a classic pedigree. I went to this school, I studied this degree. There's no degree if have to stop a hacker using state of the art malware. (John Furrier laughs) >> Exactly. What I do today as a job, didn't exist when I was in post-secondary at all. >> So when you hire, what do you look for? I mean obviously problem solving. What's your kind of algorithm for hiring? >> Oh, that's a really interesting question. The quickest sort of summary of it is, I'm looking for not a jerk. >> Not a jerk. >> Yeah. >> Okay. >> Because it turns out that the quality that I can't fix in a candidate, is I can't fix whether or not they're a jerk, but I can up-skill them, I can educate them. I can teach them of a part of the world that they've not had any interaction with. But if they're not going to work with the team, if they're going to be, look at me, look at me. If they're going to not have that moment of, I have this great job, and I get to work today. And that's awesome. (Lisa Martin laughs) That's what I'm trying to hire for. >> The essence of this teamwork is fundamental. >> Collaboration. >> Cooperation. >> Curiosity. >> That's the thing yeah, absolutely. >> And everybody? >> Those things, oh absolutely. Those things are really, really hard to interview for. And they're impossible to fix after the fact. So that's where you really want to put the effort. 'Cause I can teach you how to use a computer. I mean it's hard, but it's not that hard. >> Yeah, yeah, yeah. >> Well I love the current state of data management. Good overview, you guys are in the good position. We love open source. Been covering it for, since theCUBE started. It continues to redefine more and more the industry. It is the software industry. Now there's no debate about that. If people want to have that debate, that's kind of waste of time, but there are other ways that are happening. So I have to ask you. As things are going forward with innovation. Okay, if opensource is going to be the software industry. Where's the value? >> That's a fun question wow? >> Is it going to be in the community? Is it the integration? Is it the scale? If you're open and you have low switching costs... >> Yeah so, when you look at Aiven's commitment to open source, a huge part of that is our open source project office, where we contribute back to those core products, whether it's parts of the Apache Foundation, or Postgres, or whatever. We contribute to those, because we have staff who work on those products. They don't work on our stuff. They work on those. And it's like the opposite of a zero sum game. It's more like Nash equilibrium. If you ever watch that movie, "A beautiful mind." That great idea of, you don't have to have winners and losers. You can have everybody loses a little bit but everybody wins a little bit. >> Yeah and that's the open the ethos. >> And that's where it gets tied up. >> Another follow up on that. The other thing I want to get your reaction on is that, now in this modern era of open source, almost all corporations are part of projects. I mean if you're an entrepreneur and you want to get funding it's pretty simple. You start open source project. How many stars you get on GitHub guarantees it's a series C round, pretty much. So open source now has got this new thing going on, where it's not just open source folks who believe in it It's an operating model. What's the dynamic of corporations being part of the system. It used to be, oh what's the balance between corporate and influence, now it's standard. What's your reaction? >> They can do good and they can do harm. And it really comes down to why are you in it? So if you look at the example of open search, which is one of the data products that we operate in the Aiven system. That's a collaboration between Aiven. Hey we're an awesome company, but we're nowhere near the size of AWS. And AWS where we're working together on it. And I just had this conversation with one of the attendees here, where he said, "Well AWS is going to eat your story there. "You're contributing all of this "to the open search platform. "And then AWS is going to go and sell it "and they're going to make more money." And I'm like yep, they are. And I've got staff who work for the organization, who are more fulfilled because they got to deliver something that's used by millions of people. And you think about your jobs. That moment of, (sighs) I did a cool thing today. That's got a lot of value in it. >> And part of something. >> Exactly. >> As a group. >> 100%. >> Exactly. >> And we end up with a product that's used by millions. Some of it we'll capture, because we do a better job running than the AWS does, but everybody ends up winning out of the backend. Again, everybody lost a little, but everybody also won. And that's better than that whole, you have to lose so that I can win. At zero something, that doesn't work. >> I think the silo conversations are coming, what's the balance between siloing something and why that happens. And then what's going to be freely accessible for data. Because the real time information is based upon what you can access. "Hey Siri, what's the weather. "We had a guest on earlier." It says, oh that's a data query. Well, if the weather is, the data weathers stored in a database that's out here and it can't get to the response on the app. Yeah, that's not good, but the data is available. It just didn't get delivered. >> Yeah >> Exactly. >> This is an example of what people are realizing now the consequences of this data, collateral damage or economy value. >> Yeah, and it's understanding how data fits in your environment. And I don't want to get on the accountants too hard, but the accounting organizations, AICPA and ISAE and others, they haven't really done a good job of helping you understand data as an asset, or data as a liability. I hold a lot of customer data. That's a liability to me. It's going to blow up in my face. We don't talk about the income that we get from data, Google. We don't talk about the expense of regenerating that data. We talk about, well what happens if you lose it? I don't know. And we're circling the drain around fiduciary responsibility, and we know how to do this. If you own a manufacturing plant, or if you own a fleet of vehicles you understand the fiduciary duty of managing your asset. But because we can't touch it, we don't do a good job of it. >> How far do you think are people getting into the point where they actually see that asset? Because I think it's out of sight out of mind. Now there's consequences, there's now it's public companies might have to do filings. It's not like sustainability and data. Like, wait a minute, I got to deal with these things. >> It's interesting, we got this great benefit of the move to cloud computing, and the move to utility style computing. But we took away that. I got to walk around and pet my computers. Like oh! This is my good database. I'm very proud of you. Like we're missing that piece now. And when you think about the size of data centers, we become detached from that, you don't really think about, Aiven operates tens of thousands of machines. It would take entire buildings to hold them all. You don't think about it. So how do you recreate that visceral connection to your data? Well, you need to start actually thinking about it. And you need to do some of that tokenization. When was the last time you printed something out, like you get a report and happens to me all the time with security reports. Look at a security report and it's like 150 page PDF. Scroll, scroll, scroll, scroll. Print it out, stump it on the table in front of you. Oh, there's gravitas here. There's something here. Start thinking about those records, count them up, and then try to compare that to something in the real world. My wife is a school teacher, kindergarten to grade three, and tokenizing math is how they teach math to little kids. You want to count something? Here's 10 things, count them. Well, you've got 60,000 customer records, or you have 2 billion data points in your IOT database, tokenize that, what does 2 billion look like? What does $1 million look like in the form of $100 dollars bills on a pallet? >> Wow. >> Right. Tokenize that data, create that visceral connection with it, and then talk about it. >> So when you say tokenized, you mean like token as in decentralization token? >> No, I mean create like a totem or an icon of it. >> Okay, got it. >> A thing you can hold holy. If you're a token company. >> Not token as in Token economics and Crypto. >> If you're a mortgage company, take that customer record for one of your customers, print it out and hold the file. Like in a Manila folder, like it's 1963. Hold that file, and then say yes. And you're explaining to somebody and say yes, and we have 3 million of these. If we printed them all out, it would take up a room this size. >> It shows the scale. >> Right. >> Right. >> Exactly, create that connection back to the human level of interaction with data. How do you interact with a terabyte of data, but you do. >> Right. >> But once she hits upgrade from Google drive. (team laughs) >> What's a terabyte right? We don't hold that anymore. >> Right, right. >> Great conversation. >> Recreate that connection. Talk about data that way. >> The visceral connection with data. >> Follow up after this event. We'd love to dig more and love the approach. Love open source, love what you're doing there. That's a very unique approach. And it's also an alternative to some of the other vast growing plus your valuations are very high too. So you're not like a... You're not too far away from these big valuations. So congratulations. >> Absolutely. >> Yeah excellent, I'm sure there's lots of work to do, lots of strategic work to do with that round of funding. But also lots of opportunity, that it's going to open up, and we know you don't hire jerks. >> I don't >> You have a whole team of non jerks. That's pretty awesome. Especially 40 of 'em. That's impressive James.| >> It is. >> Congratulations to you on what you've accomplished in the course of the team. And thank you for sharing your insights with John and me today, we appreciate it. >> Awesome. >> Thanks very much, it's been great. >> Awesome, for John furrier, I'm Lisa Martin and you're watching theCube, live in New York city at AWS Summit NYC 22, John and I will be right back with our next segment, stick around. (upbeat music)

ladies and gentlemen this is your captain speaking we will soon be taking off on our way to altitude please keep your seatbelts fastened and remain in your seats we will be experiencing turbulence until we are above the clouds ladies and gentlemen we are now cruising at altitude sit back and enjoy the ride [Music] altitude is a community of thought leaders and pioneers cloud architects and enlightened network engineers who have individually and are now collectively leading their own IT teams and the industry on a path to lift cloud networking above the clouds empowering Enterprise IT to architect design and control their own cloud network regardless of the turbulent clouds beneath them it's time to gain altitude ladies and gentlemen Steve Mulaney president and CEO of aviatrix the leader of multi cloud networking [Music] [Applause] all right good morning everybody here in Santa Clara as well as to the what millions of people watching the livestream worldwide welcome to altitude 2020 alright so we've got a fantastic event today really excited about the speakers that we have today and the experts that we have and really excited to get started so one of the things I wanted to just share was this is not a one-time event this is not a one-time thing that we're gonna do sorry for the aviation analogy but you know sherry way aviatrix means female pilot so everything we do as an aviation theme this is a take-off for a movement this isn't an event this is a take-off of a movement a multi-cloud networking movement and community that we're inviting all of you to become part of and-and-and why we're doing that is we want to enable enterprises to rise above the clouds so to speak and build their network architecture regardless of which public cloud they're using whether it's one or more of these public clouds so the good news for today there's lots of good news but this is one good news is we don't have any powerpoint presentations no marketing speak we know that marketing people have their own language we're not using any of that in those sales pitches right so instead what are we doing we're going to have expert panels we've got Simone Rashard Gartner here we've got 10 different network architects cloud architects real practitioners they're going to share their best practices and there are real-world experiences on their journey to the multi cloud so before we start and everybody know what today is in the u.s. it's Super Tuesday I'm not gonna get political but Super Tuesday there was a bigger Super Tuesday that happened 18 months ago and maybe eight six employees know what I'm talking about 18 months ago on a Tuesday every enterprise said I'm gonna go to the cloud and so what that was was the Cambrian explosion for cloud for the price so Frank kibrit you know what a Cambrian explosion is he had to look it up on Google 500 million years ago what happened there was an explosion of life where it went from very simple single-cell organisms to very complex multi-celled organisms guess what happened 18 months ago on a Tuesday I don't really know why but every enterprise like I said all woke up that day and said now I'm really gonna go to cloud and that Cambrian explosion of cloud went meant that I'm moving from very simple single cloud single use case simple environment to a very complex multi cloud complex use case environment and what we're here today is we're gonna go and dress that and how do you handle those those those complexities and when you look at what's happening with customers right now this is a business transformation right people like to talk about transitions this is a transformation and it's actually not just the technology transformation it's a business transformation it started from the CEO and the boards of enterprise customers where they said I have an existential threat to the survival of my company if you look at every industry who they're worried about is not the other 30 year old enterprise what they're worried about is the three year old enterprise that's leveraging cloud that's leveraging AI and that's where they fear that they're going to actually get wiped out right and so because of this existential threat this is CEO lead this is board led this is not technology led it is mandated in the organization's we are going to digitally transform our enterprise because of this existential threat and the movement to cloud is going to enable us to go do that and so IT is now put back in charge if you think back just a few years ago in cloud it was led by DevOps it was led by the applications and it was like I said before their Cambrian explosion is very simple now with this Cambrian explosion and enterprises getting very serious and mission critical they care about visibility they care about control they care about compliance conformance everything governance IT is in charge and and and that's why we're here today to discuss that so what we're going to do today is much of things but we're gonna validate this journey with customers did they see the same thing we're gonna validate the requirements for multi-cloud because honestly I've never met an enterprise that is not going to be multi-cloud many are one cloud today but they all say I need to architect my network for multiple clouds because that's just what the network is there to support the applications and the applications will run and whatever cloud it runs best in and you have to be prepared for that the second thing is is architecture again with IT in charge you architecture matters whether it's your career whether it's how you build your house it doesn't matter horrible architecture your life is horrible forever good architecture your life is pretty good so we're gonna talk about architecture and how the most fundamental and critical part of that architecture and that basic infrastructure is the network if you don't get that right nothing works right way more important and compute way more important than storm dense storage network is the foundational element of your infrastructure then we're going to talk about day 2 operations what does that mean well day 1 is one day of your life that's who you wire things up they do and beyond I tell everyone in networking and IT it's every day of your life and if you don't get that right your life is bad forever and so things like operations visibility security things like that how do I get my operations team to be able to handle this in an automated way because it's not just about configuring it in the cloud it's actually about how do I operationalize it and that's a huge benefit that we bring as aviatrix and then the last thing we're going to talk and it's the last panel we have I always say you can't forget about the humans right so all this technology all these things that we're doing it's always enabled by the humans at the end of the day if the humans fight it it won't get deployed and we have a massive skills gap in cloud and we also have a massive skill shortage you have everyone in the world trying to hire cloud network architects right there's just not enough of them going around so at aviatrix we as leaders do we're gonna help address that issue and try to create more people we created a program and we call the ACE program again an aviation theme it stands for aviatrix certified engineer very similar to what Cisco did with CCI ease where Cisco taught you about IP networking a little bit of Cisco we're doing the same thing we're gonna teach network architects about multi-cloud networking and architecture and yeah you'll get a little bit of aviatrix training in there but this is the missing element for people's careers and also within their organization so we're gonna we're gonna go talk about that so great great event great show when to try to keep it moving I'd next want to introduce my my host he's the best in the business you guys have probably seen him multiple million times he's the co CEO and co-founder of tube Jon Fourier okay awesome great great speech they're awesome I'd totally agree with everything you said about the explosion happening and I'm excited here at the heart of Silicon Valley to have this event it's a special digital event with the cube and aviatrix were we live streaming to millions of people as you said maybe not a million maybe not really take this program to the world this is a little special for me because multi-cloud is the hottest wave and cloud and cloud native networking is fast becoming the key engine of the innovation so we got an hour and a half of action-packed programming we have a customer panel two customer panels before that Gartner is going to come on talk about the industry we have a global system integrators we talk about how they're advising and building these networks and cloud native networking and then finally the Aces the aviatrix certified engineer is gonna talk more about their certifications and the expertise needed so let's jump right in and let's ask someone rashard to come on stage from Gartner check it all up [Applause] okay so kicking things off sitting started gartner the industry experts on cloud really kind of more to your background talk about your background before you got the gardener yeah before because gardener was a chief network architect of a fortune five companies with thousands of sites over the world and I've been doing everything and IT from a C programmer in a 92 a security architect to a network engineer to finally becoming a network analyst so you rode the wave now you're covering at the marketplace with hybrid cloud and now moving quickly to multi cloud is really was talking about cloud natives been discussed but the networking piece is super important how do you see that evolving well the way we see Enterprise adapt in cloud first thing you do about networking the initial phases they either go in a very ad hoc way is usually led by non non IT like a shadow I to your application people are some kind of DevOps team and it's it just goes as it's completely unplanned decreed VP sees left and right with different account and they create mesh to manage them and their direct connect or Express route to any of them so that's what that's a first approach and on the other side again it within our first approach you see what I call the lift and shift way we see like enterprise IT trying to basically replicate what they have in a data center in the cloud so they spend a lot of time planning doing Direct Connect putting Cisco routers and f5 and Citrix and any checkpoint Palo Alto divides that the audinate that are sent removing that to that cloud and I ask you the aha moments gonna come up a lot of our panels is where people realize that it's a multi cloud world I mean they either inherit clouds certainly they're using public cloud and on-premises is now more relevant than ever when's that aha moment that you're seeing where people go well I got to get my act together and get on this well the first but even before multi-cloud so these two approach the first one like the ad hoc way doesn't scale at some point idea has to save them because they don't think about the two they don't think about operations they have a bunch of VPC and multiple clouds the other way that if you do the left and shift wake they cannot take any advantages of the cloud they lose elasticity auto-scaling pay by the drink these feature of agility features so they both realize okay neither of these ways are good so I have to optimize that so I have to have a mix of what I call the cloud native services within each cloud so they start adapting like other AWS constructor is your construct or Google construct then that's what I call the optimal phase but even that they realize after that they are very different all these approaches different the cloud are different identities is completely difficult to manage across clouds I mean for example AWS has accounts there's subscription and in adarand GCP their projects it's a real mess so they realize well I can't really like concentrate use the cloud the cloud product and every cloud that doesn't work so I have I'm doing multi cloud I like to abstract all of that I still wanna manage the cloud from an API to interview I don't necessarily want to bring my incumbent data center products but I have to do that in a more API driven cloud they're not they're not scaling piece and you were mentioning that's because there's too many different clouds yes that's the piece there so what are they doing whether they really building different development teams as its software what's the solution well this the solution is to start architecting the cloud that's the third phase I call that the multi cloud architect phase where they have to think about abstraction that works across cloud fact even across one cloud it might not scale as well if you start having like 10,000 security group in AWS that doesn't scale you have to manage that if you have multiple VPC it doesn't scale you need a third party identity provider so it barely scales within one cloud if you go multiple cloud it gets worse and worse see way in here what's your thoughts I thought we said this wasn't gonna be a sales pitch for aviatrix you just said exactly what we do so anyway I'm just a joke what do you see in terms of where people are in that multi-cloud so a lot of people you know everyone I talked to started in one cloud right but then they look and they say okay but I'm now gonna move to adjourn I'm gonna move do you see a similar thing well yes they are moving but they're not there's not a lot of application that use a tree cloud at once they move one app in deserve one app in individuals one get happen Google that's what we see so far okay yeah I mean one of the mistakes that people think is they think multi-cloud no one is ever gonna go multi-cloud for arbitrage they're not gonna go and say well today I might go into Azure because I got a better rate of my instance that's never do you agree with that's never going to happen what I've seen with enterprise is I'm gonna put the workload in the app the app decides where it runs best that may be a sure maybe Google and for different reasons and they're gonna stick there and they're not gonna move let me ask you infrastructure has to be able to support from a networking team be able to do that do you agree with that yes I agree and one thing is also very important is connecting to that cloud is kind of the easiest thing so though while their network part of the cloud connectivity to the cloud is kind of simple I agree IPSec VP and I reckon Express that's a simple part what's difficult and even a provisioning part is easy you can use terraform and create v pieces and v nets across which free cloud providers right what's difficult is the day-to-day operations so it's what to find a to operations what is that what does that actually mean this is the day-to-day operations after you know the natural let's add an app let's add a server let's troubleshoot a problem so so your life something changes how would he do so what's the big concerns I want to just get back to this cloud native networking because everyone kind of knows with cloud native apps are that's been a hot trend what is cloud native networking how do you how do you guys define that because that seems to be the oddest part of the multi cloud wave that's coming as cloud native networking well there's no you know official garner definition but I can create one on and if another spot is do it I just want to leverage the cloud construct and a cloud epi I don't want to have to install like like for example the first version was let's put a virtual router that doesn't even understand and then the cloud environment right if I have if I have to install a virtual machine it has to be cloud aware it has to understand the security group if it's a router it has to be programmable to the cloud API and and understand the cloud environment you know one things I hear a lot from either see Saussure CIOs or CXOs in general is this idea of I'm definitely on going API so it's been an API economy so API is key on that point but then they say okay I need to essentially have the right relationship with my suppliers aka clouds you call it above the clouds so the question is what do i do from an architecture standpoint do I just hire more developers and have different teams because you mentioned that's a scale point how do you solve this this problem of okay I got AWS I got GCP or Azure or whatever do I just have different teams or just expose api's where is that optimization where's the focus well I take what you need from an android point of view is a way a control plane across the three clouds and be able to use the api of the cloud to build networks but also to troubleshoot them and do they to operation so you need a view across a three cloud that takes care of routing connectivity that's you know that's the aviatrix plug of you right there so so how do you see so again your Gartner you you you you see the industry you've been a network architect how do you see this this plane out what are the what are the legacy incumbent client-server on-prem networking people gonna do well these versus people like aviatrix well how do you see that plane out well obviously all the incumbent like Arista cisco juniper NSX right they want to basically do the lift and ship or they want to bring and you know VM I want to bring in a section that cloud they call that NSX everywhere and cisco monks bring you star and the cloud recall that each guy anywhere right so everyone what and and then there's cloud vision for my red star and contrail is in the cloud so they just want to bring the management plane in the cloud but it's still based most of them it's still based on putting a VM them in controlling them right you you extend your management console to the cloud that's not truly cloud native right cloud native you almost have to build it from scratch we like to call that cloud naive clown that so close one letter yeah so that was a big con surgeon reinvent take the tea out of cloud native it's cloud naive that went super viral you guys got t-shirts now I know you love but yeah but that really ultimately is kind of double edged sword you got to be you can be naive on the on the architecture side and rolling out but also suppliers are can be naive so how would you define who's naive and who's not well in fact they're evolving as well so for example in Cisco you it's a little bit more native than other ones because they're really scr in the cloud you can't you you really like configure API so the cloud and NSX is going that way and so is Arista but they're incumbent they have their own tools is difficult for them they're moving slowly so it's much easier to start from scratch Avenue like and you know a network happiness started a few years ago there's only really two aviatrix was the first one they've been there for at least three or four years and there's other ones like al kira for example that just started now that doing more connectivity but they wanna create an overlay network across the cloud and start doing policies and trying abstracting all the clouds within one platform so I gotta ask you I interviewed an executive at VMware Sanjay Pune and he said to me at RSA last week oh the only b2 networking vendors left Cisco and VMware what's your respect what's your response to that obviously I mean when you have these waves as new brands that emerge like aviation others though I think there'll be a lot of startups coming out of the woodwork how do you respond to that comment well there's still a data center there's still like a lot of action on campus and there's the one but from the cloud provisioning and clown networking in general I mean they're behind I think you know in fact you don't even need them to start to it you can if you're small enough you can just keep if you're in AWS you can user it with us construct they have to insert themselves I mean they're running behind they're all certainly incumbents I love the term Andy Jesse's that Amazon Web Services uses old guard new guard to talk about the industry what does the new guard have to do the new and new brands that emerge in is it be more DevOps oriented neck Nets a cops is that net ops is the programmability these are some of the key discussions we've been having what's your view on how you this programmability their most important part is they have to make the network's simple for the dev teams and from you cannot have that you cannot make a phone call and get every line in two weeks anymore so if you move to that cloud you have to make the cloud construct as simple enough so that for example a dev team could say okay I'm going to create this VP see but this VP see automatically being associate to your account you cannot go out on the internet you have to go to the transit VP see so there's a lot of action in terms of the I am part and you have to put the control around them too so to make it as simple as possible you guys both I mean you're the COC aviatrix but also you guys a lot of experience going back to networking going back to I call the OSI mace which for us old folks know what that means but you guys know what this means I want to ask you the question as you look at the future of networking here a couple of objectives oh the cloud guys they got networking we're all set with them how do you respond to the fact that networking is changing and the cloud guys have their own networking what some of the pain points that's going on premises and these enterprises so are they good with the clouds what needs what are the key things that's going on in networking that makes it more than just the cloud networking what's your take on well as I said earlier that once you you could easily provision in the cloud you can easily connect to that cloud is when you start troubleshooting application in the cloud and try to scale so this that's where the problem occurs see what you're taking on it and you'll hear from the from the customers that that we have on stage and I think what happens is all the cloud the clouds by definition designed to the 80/20 rule which means they'll design 80% of the basic functionality and they'll lead to 20% extra functionality that of course every Enterprise needs they'll leave that to ISVs like aviatrix because why because they have to make money they have a service and they can't have huge instances for functionality that not everybody needs so they have to design to the common and that's they all do it right they have to and then the extra the problem is that Cambrian explosion that I talked about with enterprises that's holy that's what they need that they're the ones who need that extra 20% so that's that's what I see is is there's always gonna be that extra functionality the in in an automated and simple way that you talked about but yet powerful with up with the visible in control that they expect of on prep that that's that kind of combination that yin and the yang that people like us are providing some I want to ask you were gonna ask some of the cloud architect customer panels it's the same question this pioneers doing some work here and there's also the laggers who come in behind the early adopters what's gonna be the tipping point what are some of those conversations that the cloud architects are having out there or what's the signs that they need to be on this multi cloud or cloud native networking trend what are some the signals that are going on in their environment what are some of the thresholds or things that are going on that there can pay attention to well well once they have application and multiple cloud and they have they get wake up at 2:00 in the morning to troubleshoot them they don't know it's important so I think that's the that's where the robber will hit the road but as I said it's easier to prove it it's ok it's 80s it's easy use a transit gateway put a few V PCs and you're done and use create some presents like equinox and do Direct Connect and Express route with Azure that looks simple is the operations that's when they'll realize ok now I need to understand our car networking works I also need a tool that give me visibility and control not button tell me that I need to understand the basic underneath it as well what are some of the day in the life scenarios that you envision happening with multi Bob because you think about what's happening it kind of has that same vibe of interoperability choice multi-vendor because you have multi clouds essentially multi vendor these are kind of old paradigms that we've lived through the client server and internet working wave what are some of those scenarios of success and that might be possible it would be possible with multi cloud and cloud native networking well I think once you have good enough visibility to satisfy your customers you know not only like to keep the service running an application running but to be able to provision fast enough I think that's what you want to achieve small final question advice for folks watching on the live stream if they're sitting there as a cloud architect or a CXO what's your advice to them right now in this more because honestly public cloud check hybrid cloud they're working on that that gets on-premise is done now multi clouds right behind it what's your advice the first thing they should do is really try to understand cloud networking for each of their cloud providers and then understand the limitation and is what there's cloud service provider offers enough or you need to look to a third party but you don't look at a third party to start with especially an incumbent one so it's tempting to say on and I have a bunch of f5 experts nothing against that five I'm going to bring my five in the cloud when you can use a needle be that automatically understand Easy's and auto scaling and so on and you understand that's much simpler but sometimes you need you have five because you have requirements you have like AI rules and that kind of stuff that you use for years you cannot do it's okay I have requirement and that met I'm going to use legacy stuff and then you have to start thinking okay what about visibility control about the tree cloud but before you do that you have to understand the limitation of the existing cloud providers so first try to be as native as possible until things don't work after that you can start taking multi-cloud great insight somewhat thank you for coming someone in charge with Gardner thanks for sharing informatica is known as the leading enterprise cloud data management company we are known for being the top in our industry in at least five different products over the last few years especially we've been transforming into a cloud model which allows us to work better with the trends of our customers in order to see agile and effective in the business you need to make sure that your products and your offerings are just as relevant in all these different clouds than what you're used to and what you're comfortable with one of the most difficult challenges we've always had is that because we're a data company we're talking about data that a customer owns some of that data may be in the cloud some of that data may be on Prem some of that data may be actually in their data center in another region or even another country and having that data connect back to our systems that are located in the cloud has always been a challenge when we first started our engagement with aviatrix we only had one plan that was Amazon it wasn't till later that a jerk came up and all of a sudden we found hey the solution we already had in place for her aviatrix already working in Amazon and now works in Missouri as well before we knew what GCP came up but it really wasn't a big deal for us because we already had the same solution in Amazon and integer now just working in GCP by having a multi cloud approach we have access to all three of them but more commonly it's not just one it's actually integrations between multiple we have some data and ensure that we want to integrate with Amazon we have some data in GCP that we want to bring over to a data Lake assure one of the nice things about aviatrix is that it gives a very simple interface that my staff can understand and use and manage literally hundreds of VPNs around the world and while talking to and working with our customers who are literally around the world now that we've been using aviatrix for a couple years we're actually finding that even problems that we didn't realize we had were actually solved even before we came across the problem and it just worked cloud companies as a whole are based on reputation we need to be able to protect our reputation and part of that reputation is being able to protect our customers and being able to protect more importantly our customers data aviatrix has been helpful for us in that we only have one system that can manage this whole huge system in a simple easy direct model aviatrix is directly responsible for helping us secure and manage our customers not only across the world but across multiple clouds users don't have to be VPN or networking experts in order to be able to use the system all the members on my team can manage it all the members regardless of their experience can do different levels of it one of the unexpected advantages of aviatrix is that I don't have to sell it to my management the fact that we're not in the news at 3 o'clock in the morning or that we don't have to get calls in the middle of the night no news is good news especially in networking things that used to take weeks to build or done in hours I think the most important thing about a matrix is it provides me a Beatrix gives me a consistent model that I can use across multiple regions multiple clouds multiple customers okay welcome back to altitude 2020 for the folks on the livestream I'm John for Steve Mulaney with CEO of aviatrix for our first of two customer panels on cloud with cloud network architects we got Bobby Willoughby they gone Luis Castillo of National Instruments David should Nick with fact set guys welcome to the stage for this digital event come on up [Applause] [Music] hey good to see you thank you okay okay customer panelist is my favorite part we get to hear the real scoop gets a gardener given this the industry overview certainly multi clouds very relevant and cloud native networking is the hot trend with a live stream out there and the digital event so guys let's get into it the journey is you guys are pioneering this journey of multi cloud and cloud native networking and is soon gonna be a lot more coming so we want to get into the journey what's it been like is it real you got a lot of scar tissue and what are some of the learnings yeah absolutely so multi cloud is whether or not we we accepted as a network engineers is is a reality like Steve said about two years ago companies really decided to to just to just bite the bullet and and and move there whether or not whether or not we we accept that fact we need to now create a consistent architecture across across multiple clouds and that that is challenging without orchestration layers as you start managing different different tool sets and different languages across different clouds so that's it's really important that to start thinking about that guys on the other panelists here there's different phases of this journey some come at it from a networking perspective some come in from a problem troubleshooting which what's your experiences yeah so from a networking perspective it's been incredibly exciting it's kind of a once-in-a-generation 'el opportunity to look at how you're building out your network you can start to embrace things like infrastructure as code that maybe your peers on the systems teams have been doing for years but it just never really worked on bram so it's really it's really exciting to look at all the opportunities that we have and then all the interesting challenges that come up that you that you get to tackle an effect said you guys are mostly AWS right yep right now though we're we are looking at multiple clouds we have production workloads running in multiple clouds today but a lot of the initial work has been with Amazon and you've seen it from a networking perspective that's where you guys are coming at it from yep we evolved more from a customer requirement perspective started out primarily as AWS but as the customer needed more resources from Azure like HPC you know as your ad things like that even recently Google Google Analytics our journey has evolved into more of a multi cloud environment Steve weigh in on the architecture because this has been the big conversation I want you to lead this second yeah so I mean I think you guys agree the journey you know it seems like the journey started a couple years ago got real serious the need for multi cloud whether you're there today of course it's gonna be there in the future so that's really important I think the next thing is just architecture I'd love to hear what you you know had some comments about architecture matters it all starts I mean every Enterprise I talk to maybe talk about architecture and the importance of architecture maybe Bobby it's a fun architecture perspective we sorted a journey five years ago Wow okay and we're just now starting our fourth evolution of our network marketer and we call it networking security net SEC yeah versus Justice Network yeah and that fourth generation architectures be based primarily upon Palo Alto Networks an aviatrix I have Atrix doing the orchestration piece of it but that journey came because of the need for simplicity ok the need for a multi cloud orchestration without us having to go and do reprogramming efforts across every cloud as it comes along right I guess the other question I also had around architectures also Louis maybe just talk about I know we've talked a little bit about you know scripting right and some of your thoughts on that yeah absolutely so so for us we started we started creating the network constructs with cloud formation and we've we've stuck with that for the most part what's interesting about that is today on premise we have a lot of a lot of automation around around how we provision networks but cloud formation has become a little bit like the new manual for us so we we're now having issues with having the to automate that component and making it consistent with our on premise architecture making it consistent with Azure architecture and Google cloud so it's really interesting to see to see companies now bring that layer of abstraction that SEO and brought to the to the web side now it's going up into into the into the cloud networking architecture so on the fourth generation of you mentioned you're in the fourth gen architecture what do you guys what have you learned is there any lessons scar tissue what to avoid what worked what was some of the that's probably the biggest list and there is that when you think you finally figured it out you have it right Amazon will change something as you or change something you know transit gateways a game changer so in listening to the business requirements is probably the biggest thing we need to do up front but I think from a simplicity perspective we like I said we don't want to do things four times we want to do things one time we won't be able to write to an API which aviatrix has and have them do the orchestration for us so that we don't have to do it four times how important is architecture in the progression is it you guys get thrown in the deep end to solve these problems or you guys zooming out and looking at it it's that I mean how are you guys looking at the architecture I mean you can't get off the ground if you don't have the network there so all of those that we've gone through similar evolutions we're on our fourth or fifth evolution I think about what we started off with Amazon without a direct connect gate without a trans a gateway without a lot of the things that are available today kind of the 80/20 that Steve was talking about just because it wasn't there doesn't mean we didn't need it so we needed to figure out a way to do it we couldn't say oh you need to come back to the network team in a year and maybe Amazon will have a solution for it right you need to do it now and in evolve later and maybe optimize or change the way you're doing things in the future but don't sit around and wait you can't I'd love to have you guys each individually answer this question for the live stream because it comes up a lot a lot of cloud architects out in the community what should they be thinking about the folks that are coming into this proactively and/or realizing the business benefits are there what advice would you guys give them an architecture what should be they be thinking about and what are some guiding principles you could share so I would start with looking at an architecture model that that can that can spread and and give consistency they're different to different cloud vendors that you will absolutely have to support cloud vendors tend to want to pull you into using their native toolset and that's good if only it was realistic to talk about only one cloud but because it doesn't it's it's it's super important to talk about and have a conversation with the business and with your technology teams about a consistent model how do I do my day one work so that I'm not you know spending 80 percent of my time troubleshooting or managing my network because I'm doing that then I'm missing out on ways that I can make improvements or embrace new technologies so it's really important early on to figure out how do I make this as low maintenance as possible so that I can focus on the things that the team really should be focusing on Bobby your advice the architect I don't know what else I can do that simplicity operations is key right all right so the holistic view of j2 operation you mentioned let's can jump in day one is your your your getting stuff set up day two is your life after all right this is kind of what you're getting at David so what does that look like what are you envisioning as you look at that 20 mile stare at post multi-cloud world what are some of the things that you want in a day to operations yeah infrastructure is code is really important to us so how do we how do we design it so that we can fit start making network changes and fitting them into like a release pipeline and start looking at it like that rather than somebody logging into a router seoi and troubleshooting things on in an ad hoc nature so moving more towards the DevOps model yes anything on that day - yeah I would love to add something so in terms of day 2 operations you can you can either sort of ignore the day 2 operations for a little while where you get well you get your feet wet or you can start approaching it from the beginning the fact is that the the cloud native tools don't have a lot of maturity in that space and when you run into an issue you're gonna end up having a bad day going through millions and millions of logs just to try to understand what's going on so that's something that that the industry just now is beginning to realize it's it's such as such a big gap I think that's key because for us we're moving to more of an event-driven operations in the past monitoring got the job done it's impossible to modern monitor something there's nothing there when the event happens all right so the event-driven application and then detection is important yeah I think Gardiner was all about the cloud native wave coming into networking that's going to be here thing I want to get your guys perspectives I know you have different views of how you came on into the journey and how you're executing and I always say the beauties in the eye of the beholder and that kind of applies the network's laid out so Bobby you guys do a lot of high-performance encryption both on AWS and Azure that's kind of a unique thing for you how are you seeing that impact with multi cloud yeah and that's a new requirement for us to where we we have a requirement to encrypt and they never get the question should I encryption or not encrypt the answer is always yes you should encrypt when you can encrypt for our perspective we we need to migrate a bunch of data from our data centers we have some huge data centers and then getting that data to the cloud is the timely expense in some cases so we have been mandated that we have to encrypt everything leave from the data center so we're looking at using the aviatrix insane mode appliances to be able to encrypt you know 10 20 gigabits of data as it moves to the cloud itself David you're using terraform you got fire Ned you've got a lot of complexity in your network what do you guys look at the future for yours environment yeah so something exciting that or yeah now is fire net so for our security team they obviously have a lot of a lot of knowledge base around Palo Alto and with our commitments to our clients you know it's it's it's not very easy to shift your security model to a specific cloud vendor right so there's a lot of stuck to compliance of things like that where being able to take some of what you've you know you've worked on for years on Bram and put it in the cloud and have the same type of assurance that things are gonna work and be secured in the same way that they are on prem helps make that journey into the cloud a lot easier and Louis you guys got scripting and get a lot of things going on what's your what's your unique angle on this yeah no absolutely so full disclosure I'm not a not not an aviatrix customer yet it's okay we want to hear the truth that's good Ellis what are you thinking about what's on your mind no really when you when you talk about implementing the tool like this it's really just really important to talk about automation and focus on on value so when you talk about things like encryption and things like so you're encrypting tunnels and crypting the path and those things are it should it should should be second nature really when you when you look at building those back ends and managing them with your team it becomes really painful so tools like a Beatrix that that add a lot of automation it's out of out of sight out of mind you can focus on the value and you don't have to focus on so I gotta ask you guys I'll see aviatrix is here they're their supplier to this sector but you guys are customers everyone's pitching you stuff people are not going to buy my stuff how do you guys have that conversation with the suppliers like the cloud vendors and other folks what's that what's it like we're API all the way you got to support this what are some of the what are some of your requirements how do you talk to and evaluate people that walk in and want to knock on your door and pitch you something what's the conversation like it's definitely it's definitely API driven we we definitely look at the at the PAP i structure of the vendors provide before we select anything that that is always first in mind and also what a problem are we really trying to solve usually people try to sell or try to give us something that isn't really valuable like implementing a solution on the on the on the cloud isn't really it doesn't really add a lot of value that's where we go David what's your conversation like with suppliers you have a certain new way to do things as as becomes more agile and essentially the networking and more dynamic what are some of the conversation is with the either incumbents or new new vendors that you're having what do what do you require yeah so ease of use is definitely definitely high up there we've had some vendors come in and say you know hey you know when you go to set this up we're gonna want to send somebody on site and they're gonna sit with you for your day to configure it and that's kind of a red flag what wait a minute you know do we really if one of my really talented engineers can't figure it out on his own what's going on there and why is that so I you know having having some ease-of-use and the team being comfortable with it and understanding it is really important Bobby how about you I mean the old days was do a bake-off and you know the winner takes all I mean is it like that anymore but what's the Volvic a bake-off last year for us do you win so but that's different now because now when you when you get the product you can install the product and they double your energy or have it in a matter of minutes and so the key is is they can you be operational you know within hours or days instead of weeks but but do we also have the flexibility to customize it to meet your needs could you want to be you want to be put into a box with the other customers when you have needs that your pastor cut their needs yeah almost see the challenge that you guys are living where you've got the cloud immediate value depending how you can roll up any solutions but then you have might have other needs so you got to be careful not to buy into stuff that's not shipping so you're trying to be proactive at the same time deal with what you got I mean how do you guys see that evolving because multi-cloud to me is definitely relevant but it's not yet clear how to implement across how do you guys look at this baked versus you know future solutions coming how do you balance that so again so right now we we're we're taking the the ad hoc approach and experimenting with the different concepts of cloud and and really leveraging the the native constructs of each cloud but but there's a there's a breaking point for sure you don't you don't get to scale this like Alexa mom said and you have to focus on being able to deliver a developer they're their sandbox or they're their play area for the for the things that they're trying to build quickly and the only way to do that is with the with with some sort of consistent orchestration layer that allows you to so use a lot more stuff to be coming pretty quickly hides area I do expect things to start to start maturing quite quite quickly this year and you guys see similar trend new stuff coming fast yeah part of the biggest challenge we've got now is being able to segment within the network being able to provide segmentation between production on production workloads even businesses because we support many businesses worldwide and and isolation between those is a key criteria there so the ability to identify and quickly isolate those workloads is key so the CIOs that are watching or that are saying hey take that he'll do multi cloud and then you know the bottoms-up organization Nick pops you're kind of like off a little bit it's not how it works I mean what is the reality in terms of implementing you know in as fast as possible because the business benefits are but it's not always clear in the technology how to move that fast yeah what are some of the barriers one of the blockers what are the enablers I think the reality is is that you may not think you're multi-cloud but your business is right so I think the biggest barriers there is understanding what the requirements are and how best to meet those requirements and then secure manner because you need to make sure that things are working from a latency perspective that things work the way they did and get out of the mind shift that you know it was a cheery application in the data center it doesn't have to be a Tier three application in the cloud so lift and shift is is not the way to go yeah scale is a big part of what I see is the competitive advantage to a lot these clouds and needs to be proprietary network stacks in the old days and then open systems came that was a good thing but as clouds become bigger there's kind of an inherent lock in there with the scale how do you guys keep the choice open how're you guys thinking about interoperability what are some of the conversations and you guys are having around those key concepts well when we look at when we look at the upfront from a networking perspective it it's really key for you to just enable enable all the all the clouds to be to be able to communicate between them developers will will find a way to use the cloud that best suits their their business need and and like like you said it's whether whether you're in denial or not of the multi cloud fact that then your company is in already that's it becomes really important for you to move quickly yeah and I a lot of it also hinges on how well is the provider embracing what that specific cloud is doing so are they are they swimming with Amazon or Azure and just helping facilitate things they're doing the you know the heavy lifting API work for you or are they swimming upstream and they're trying to hack it all together in a messy way and so that helps you you know stay out of the lock-in because they're you know if they're doing if they're using Amazon native tools to help you get where you need to be it's not like Amazon's gonna release something in the future that completely you know makes you have designed yourself into a corner so the closer they're more than cloud native they are the more the easier it is to to deploy but you also need to be aligned in such a way that you can take advantage of those cloud native technologies will it make sense tgw is a game changer in terms of cost and performance right so to completely ignore that would be wrong but you know if you needed to have encryption you know teach Adobe's not encrypted so you need to have some type of a gateway to do the VPN encryption you know so the aviatrix tool give you the beauty of both worlds you can use tgw with a gateway Wow real quick in the last minute we have I want to just get a quick feedback from you guys I hear a lot of people say to me hey the I picked the best cloud for the workload you got and then figure out multi cloud behind the scenes so that seems to be do you guys agree with that I mean is it do I go Mull one cloud across the whole company or this workload works great on AWS that work was great on this from a cloud standpoint do you agree with that premise and then witness multi-cloud stitch them all together yeah from from an application perspective it it can be per workload but it can also be an economical decision certain enterprise contracts will will pull you in one direction that value but the the network problem is still the same doesn't go away yeah yeah yeah I mean you don't want to be trying to fit a square into a round Hall right so if it works better on that cloud provider then it's our job to make sure that that service is there and people can use it agree you just need to stay ahead of the game make sure that the network infrastructure is there secure is available and is multi cloud capable yeah I'm at the end of the day you guys just validating that it's the networking game now cloud storage compute check networking is where the action is awesome thanks for your insights guys appreciate you coming on the panel appreciate it thanks thank you [Applause] [Music] [Applause] okay welcome back on the live feed I'm John fritz T Blaney my co-host with aviatrix I'm with the cube for the special digital event our next customer panel got great another set of cloud network architects Justin Smith was aura Justin broadly with Ellie Mae and Amit Oh tree job with Koopa welcome to stage [Applause] all right thank you thank you okay he's got all the the cliff notes from the last session welcome back rinse and repeat yeah yeah we're going to go under the hood a little bit I think I think they nailed the what we've been reporting and we've been having this conversation around networking is where the action is because that's the end of the day you got a move a pack from A to B and you get workloads exchanging data so it's really killer so let's get started Amit what are you seeing as the journey of multi cloud as you go under the hood and say okay I got to implement this I have to engineer the network make it enabling make it programmable make it interoperable across clouds and that's like I mean almost sounds impossible to me what's your take yeah I mean it it seems impossible but if you are running an organization which is running infrastructure as a cordon all right it is easily doable like you can use tools out there that's available today you can use third-party products that can do a better job but but put your architecture first don't wait architecture may not be perfect put the best architecture that's available today and be agile to iterate and make improvements over the time we get to Justin's over here so I have to be careful when I point a question in Justin they both have the answer but okay journeys what's the journey been like I mean is there phases we heard that from Gartner people come in to multi cloud and cloud native networking from different perspectives what's your take on the journey Justin yeah I mean from our perspective we started out very much focused on one cloud and as we started doing errands we started doing new products the market the need for multi cloud comes very apparent very quickly for us and so you know having an architecture that we can plug in play into and be able to add and change things as it changes is super important for what we're doing in the space just in your journey yes for us we were very ad hoc oriented and the idea is that we were reinventing all the time trying to move into these new things and coming up with great new ideas and so rather than it being some iterative approach with our deployments that became a number of different deployments and so we shifted that tore in the network has been a real enabler of this is that it there's one network and it touches whatever cloud we want it to touch and it touches the data centers that we need it to touch and it touches the customers that we need it to touch our job is to make sure that the services that are available and one of those locations are available in all of the locations so the idea is not that we need to come up with this new solution every time it's that we're just iterating on what we've already decided to do before we get the architecture section I want to ask you guys a question I'm a big fan of you know let the app developers have infrastructure as code so check but having the right cloud run that workload I'm a big fan of that if it works great but we just heard from the other panel you can't change the network so I want to get your thoughts what is cloud native networking and is that the engine really that's the enabler for this multi cloud trend but you guys taken we'll start with Amit what do you think about that yeah so you are gonna have workloads running in different clouds and the workloads would have affinity to one cloud over other but how you expose that it matter of how you are going to build your networks how we are gonna run security how we are going to do egress ingress out of it so it's a big problem how do you split says what's the solution what's the end the key pain points and problem statement I mean the key pain point for most companies is how do you take your traditionally on-premise network and then blow that out to the cloud in a way that makes sense you know IP conflicts you have IP space you pub public eye peas and premise as well as in the cloud and how do you kind of make a sense of all of that and I think that's where tools like a v8 ryx make a lot of sense in that space from our site it's it's really simple its latency its bandwidth and availability these don't change whether we're talking about cloud or data center or even corporate IT networking so our job when when these all of these things are simplified into like s3 for instance and our developers want to use those we have to be able to deliver that and for a particular group or another group that wants to use just just GCP resources these aren't we have to support these requirements and these wants as opposed to saying hey that's not a good idea our job is to enable them not to disable them do you think you guys think infrastructure is code which I love that I think it's that's the future it is we saw that with DevOps but I do start getting the networking is it getting down to the network portion where it's network is code because storage and compute working really well is seeing all kubernetes and service master and network as code reality is it there is got work to do it's absolutely there I mean you mentioned net DevOps and it's it's very real I mean in Cooper we build our networks through terraform and on not only just out of fun build an API so that we can consistently build V nets and VPC all across in the same unit yeah and even security groups and then on top an aviatrix comes in we can peer the networks bridge bridge all the different regions through code same with you guys but yeah everything we deploy is done with automation and then we also run things like lambda on top to make changes in real time we don't make manual changes on our network in the data center funny enough it's still manual but the cloud has enabled us to move into this automation mindset and and all my guys that's what they focus on is bringing what now what they're doing in the cloud into the data center which is kind of opposite of what it should be that's full or what it used to be it's full DevOps then yes yeah I mean for us was similar on-premise still somewhat very manual although we're moving more Norton ninja and terraform concepts but everything in the production environment is colored Confirmation terraform code and now coming into the datacenter same I just wanted to jump in on a Justin Smith one of the comment that you made because it's something that we always talk about a lot is that the center of gravity of architecture used to be an on-prem and now it's shifted in the cloud and once you have your strategic architecture what you--what do you do you push that everywhere so what you used to see at the beginning of cloud was pushing the architecture on prem into cloud now I want to pick up on what you said to you others agree that the center of architect of gravity is here I'm now pushing what I do in the cloud back into on pram and and then so first that and then also in the journey where are you at from 0 to 100 of actually in the journey to cloud DUI you 50% there are you 10% yes I mean are you evacuating data centers next year I mean were you guys at yeah so there's there's two types of gravity that you typically are dealing with no migration first is data gravity and your data set and where that data lives and then the second is the network platform that interrupts all that together right in our case the data gravity sold mostly on Prem but our network is now extending out to the app tier that's going to be in cloud right eventually that data gravity will also move to cloud as we start getting more sophisticated but you know in our journey we're about halfway there about halfway through the process we're taking a handle of you know lift and shift and when did that start and we started about three years ago okay okay go by it's a very different story it started from a garage and one hundred percent on the clock it's a business spend management platform as a software-as-a-service one hundred percent on the cloud it was like ten years ago right yes yeah you guys are riding the wave love that architecture Justin I want to ask user you guys mentioned DevOps I mean obviously we saw the huge observability wave which is essentially network management for the cloud in my opinion right yeah it's more dynamic but this isn't about visibility we heard from the last panel you don't know what's being turned on or turned off from a services standpoint at any given time how is all this playing out when you start getting into the DevOps down well this this is the big challenge for all of us as visibility when you talk transport within a cloud you know we very interesting we we have moved from having a backbone that we bought that we own that would be data center connectivity we now I work for as or as a subscription billing company so we want to support the subscription mindset so rather than going and buying circuits and having to wait three months to install and then coming up with some way to get things connected and resiliency and redundancy I my backbone is in the cloud I use the cloud providers interconnections between regions to transport data across and and so if you do that with their native solutions you you do lose visibility there are areas in that that you don't get which is why controlling you know controllers and having some type of management plane is a requirement for us to do what we're supposed to do and provide consistency while doing it a great conversation I loved when you said earlier latency bandwidth I think availability with your sim pop3 things guys SLA I mean you just do ping times between clouds it's like you don't know what you're getting for round-trip times this becomes a huge kind of risk management black hole whatever you want to call blind spot how are you guys looking at the interconnects between clouds because you know I can see that working from you know ground to cloud I'm per cloud but when you start doing with multi clouds workload I mean SL leis will be all over the map won't they just inherently but how do you guys view that yeah I think we talked about workload and we know that the workloads are going to be different in different clouds but they are going to be calling each other so it's very important to have that visibility that you can see how data is flowing at what latency and what our ability is hour is there and our authority needs to operate on that so it's solely use the software dashboard look at the times and look at the latency in the old days strong so on open so on you try to figure it out and then your day is you have to figure out just and what's your answer to that because you're in the middle of it yeah I mean I think the the key thing there is that we have to plan for that failure we have to plan for that latency and our applications it's starting start tracking in your SLI something you start planning for and you loosely couple these services and a much more micro services approach so you actually can handle that kind of failure or that type of unknown latency and unfortunately the cloud has made us much better at handling exceptions a much better way you guys are all great examples of cloud native from day one and you guys had when did you have the tipping point moment or the Epiphany of saying a multi clouds real I can't ignore it I got to factor it into all my design design principles and and everything you're doing what's it was there a moment or was it was it from day one now there are two divisions one was the business so in business there was some affinity to not be in one cloud or to be in one cloud and that drove from the business side so it has a cloud architect our responsibility was to support that business and other is the technology some things are really running better in like if you are running dot network load or you are going to run machine learning or AI so that you have you would have that preference of one cloud over other so it was the bill that we got from AWS I mean that's that's what drives a lot of these conversations is the financial viability of what you're building on top of it which is so we this failure domain idea which is which is fairly interesting is how do I solve or guarantee against a failure domain you have methodologies with you know back-end direct connects or interconnect with GCP all of these ideas are something that you have to take into account but that transport layer should not matter to whoever we're building this for our job is to deliver the frames in the packets what that flows across how you get there we want to make that seamless and so whether it's a public internet API call or it's a back-end connectivity through Direct Connect it doesn't matter it just has to meet a contract that you signed with your application folks yeah that's the availability piece just on your thoughts on that I think any comment on that so actually multi clouds become something much more recent in the last six to eight months I'd say we always kind of had a very much an attitude of like moving to Amazon from our private cloud is hard enough why complicate it further but the realities of the business and as we start seeing you know improvements in Google and Asia and different technology spaces the need for multi cloud becomes much more important as well as those are acquisition strategies I matured we're seeing that companies that used to be on premise that we typically acquire are now very much already on a cloud and if they're on a cloud I need to plug them into our ecosystem and so that's really change our multi cloud story in a big way I'd love to get your thoughts on the clouds versus the clouds because you know you compare them Amazon's got more features they're rich with features I see the bills are haiku people using them but Google's got a great Network Google's networks pretty damn good and then you got a sure what's the difference between the clouds who where they've evolved something whether they peak in certain areas better than others what what are the characteristics which makes one cloud better do they have a unique feature that makes Azure better than Google and vice versa what do you guys think about the different clouds yeah to my experience I think there is the approach is different in many places Google has a different approach very devops friendly and you can run your workload like your network can spend regions time I mean but our application ready to accept that MS one is evolving I mean I remember ten years back Amazon's network was a flat network we will be launching servers and 10.0.0.0 mode multi-account came out so they are evolving as you are at a late start but because they have a late start they saw the pattern and they they have some mature set up on the I mean I think they're all trying to say they're equal in their own ways I think they all have very specific design philosophies that allow them to be successful in different ways and you have to kind of that in mine is your architectural and solution for example Amazon has a very much a very regional affinity they don't like to go cross region in their architecture whereas Google is very much it's a global network we're gonna think about as a global solution I think Google also has advantages there to market and so it has seen what asier did wrong it's seen what AWS did wrong and it's made those improvements and I think that's one of their big advantage at great scale to Justin thoughts on the cloud so yeah Amazon built from the system up and Google built from the network down so their ideas and approaches are from a global versus or regional I agree with you completely that that is the big number one thing but the if you look at it from the outset interestingly the the inability or the ability for Amazon to limit layer 2 broadcasting and and what that really means from a VPC perspective changed all the routing protocols you can use all the things that we have built inside of a data center to provide resiliency and and and make things seamless to users all of that disappeared and so because we had to accept that at the VPC level now we have to accept it at the LAN level Google's done a better job of being able to overcome those things and provide those traditional Network facilities to us it's just great panel can go all day here's awesome so I heard we could we'll get to the cloud native naive question so kind of think about what's not even what's cloud is that next but I got to ask you had a conversation with a friend he's like when is the new land so if you think about what the land was at a data center when is the new link you get talking about the cloud impact so that means st when the old st was kind of changing into the new land how do you guys look at that because if you think about it what lands were for inside a premises was all about networking high speed but now when you take the win and make essentially a land do you agree with that and how do you view this trend and is it good or bad or is it ugly and what's what you guys take on this yeah I think it's the it's a thing that you have to work with your application architect so if you are managing networks and if you're a sorry engineer you need to work with them to expose the unreliability that would bring in so the application has to hand a lot of this the difference in the Layton sees and and the reliability has to be worked through the application there land when same concept as it be yesterday I think we've been talking about for a long time the erosion of the edge and so is this is just a continuation of that journey we've been on for the last several years as we get more and more cloud native when we start about API is the ability to lock my data in place and not be able to access it really goes away and so I think this is just continuation that thing I think it has challenges we start talking about weighing scale versus land scale the tooling doesn't work the same the scale of that tooling is much larger and the need to automation is much much higher in a way than it was in a land that's what we're seeing so much infrastructure as code yeah yeah so for me I'll go back again to this its bandwidth and its latency right that bet define those two land versus win but the other thing that's comes up more and more with cloud deployments is where is our security boundary and where can I extend this secure aware appliance or set of rules to protect what's inside of it so for us we're able to deliver VRS or route forwarding tables for different segments wherever we're at in the world and so they're they're trusted to talk to each other but if they're gonna go to someplace that's outside of their their network then they have to cross a security boundary and where we enforce policy very heavily so for me there's it's not just land when it's it's how does environment get to environment more importantly that's a great point and security we haven't talked to yet but that's got to be baked in from the beginning that's architecture thoughts on security are you guys are dealing with it yeah start from the base have app to have security built in have TLS have encryption on the data I transit data at rest but as you bring the application to the cloud and they are going to go multi-cloud talking to over the Internet in some places well have apt web security I mean I mean our principals day Security's day zero every day and so we we always build it into our design we load entire architecture into our applications it's encrypt everything it's TLS everywhere it's make sure that that data is secured at all times yeah one of the cool trends at RSA just as a side note was the data in use encryption piece which is a homomorphic stuff was interesting all right guys final question you know we heard on the earlier panel was also trending at reinvent we take the tea out of cloud native it spells cloud naive okay they got shirts now he being sure he's gonna got this trend going what does that mean to be naive so if you're to your peers out there watching a live stream and also the suppliers that are trying to you know supply you guys with technology and services what's naive look like and what's native look like when is someone naive about implementing all this stuff so for me it's because we are in hundred-percent cloud for us its main thing is ready for the change and you will you will find new building blocks coming in and the network design will evolve and change so don't be naive and think that it's static you wall with the change I think the big naivety that people have is that well I've been doing it this way for twenty years and been successful it's going to be successful in cloud the reality is that's not the case you have to think some of the stuff a little bit differently and you need to think about it early enough so that you can become cloud native and really enable your business on cloud yeah for me it's it's being open minded right the the our industry the network industry as a whole has been very much I am smarter than everybody else and we're gonna tell everybody how it's going to be done and we have we fell into a lull when it came to producing infrastructure and and and so embracing this idea that we can deploy a new solution or a new environment in minutes as opposed to hours or weeks or four months in some cases is really important and and so you know it's are you being closed-minded native being open-minded exactly and and it took a for me it was that was a transformative kind of where I was looking to solve problems in a cloud way as opposed to looking to solve problems in this traditional old-school way all right I know we're out of time but I ask one more question so you guys so good it could be a quick answer what's the BS language when you the BS meter goes off when people talk to you about solutions what's the kind of jargon that you hear that's the BS meter going off what are people talking about that in your opinion you here you go that's total B yes what what triggers use it so that I have two lines out of movies that are really I can if the if I say them without actually thinking them it's like 1.21 jigowatts how you're out of your mind from Back to the Future right somebody's gonna be a bank and then and then Martin ball and and Michael Keaton and mr. mom when he goes to 22 21 whatever it takes yeah those two right there if those go off in my mind somebody's talking to me I know they're full of baloney so a lot of speeds would be a lot of speeds and feeds a lot of data did it instead of talking about what you're actually doing and solutioning for you're talking about well I does this this this and okay 220 221 anytime I start seeing the cloud vendor start benchmarking against each other it's your workload is your workload you need to benchmark yourself don't don't listen to the marketing on that that's that's all I'm a what triggers you and the bsp I think if somebody explains you a not simple they cannot explain you in simplicity then that's a good one all right guys thanks for the great insight great panel how about a round of applause practitioners DX easy solutions integrating company than we service customers from all industry verticals and we're helping them to move to the digital world so as a solutions integrator we interface with many many customers that have many different types of needs and they're on their IT journey to modernize their applications into the cloud so we encounter many different scenarios many different reasons for those migrations all of them seeking to optimize their IT solutions to better enable their business we have our CPS organization it's cloud platform services we support AWS does your Google Alibaba corkle will help move those workloads to wherever it's most appropriate no one buys the house for the plumbing equally no one buys the solution for the networking but if the plumbing doesn't work no one likes the house and if this network doesn't work no one likes a solution so network is ubiquitous it is a key component of every solution we do the network connectivity is the lifeblood of any architecture without network connectivity nothing works properly planning and building a scalable robust network that's gonna be able to adapt with the application needs its when encountering some network design and talking about speed the deployment aviatrix came up in discussion and we then further pursued an area DHT products that incorporated aviatrix is part of a new offering that we are in the process of developing that really enhances our ability to provide cloud connectivity for the lance cloud connectivity there's a new line of networking services that we're getting into as our clients move into hybrid cloud networking it is much different than our traditional based services an aviatrix provides a key component in that service before we found aviatrix we were using just native peering connections but there wasn't a way to visualize all those peering connections and with multiple accounts multiple contacts for security with a v8 church we were able to visualize those different peering connections of security groups it helped a lot especially in areas of early deployment scenarios were quickly able to then take those deployment scenarios and turn them into scripts that we can then deploy repeatedly their solutions were designed for work with the cloud native capabilities first and where those cloud native capabilities fall short they then have solution sets that augment those capabilities I was pleasantly surprised number one with the aviatrix team as a whole in their level of engagement with us you know we weren't only buying the product we were buying a team that came on board to help us implement and solution that was really good to work together to learn both what aviatrix had to offer as well as enhancements that we had to bring that aviatrix was able to put into their product and meet our needs even better aviatrix was a joy to find because they really provided us the technology that we needed in order to provide multi cloud connectivity that really added to the functionality that you can't get from the basic law providing services we're taking our customers on a journey to simplify and optimize their IT infrastructure aviatrix certainly has made my job much easier okay welcome back to altitude 2020 for the digital event for the live feed welcome back I'm John Ford with the cube with Steve Mulaney CEO aviatrix for the next panel from global system integrators the folks who are building and working with folks on their journey to multi cloud and cloud native networking we've got a great panel George Buckman with dxc and Derek Monahan with wwt welcome to the stage [Applause] [Music] okay you guys are the ones out there advising building and getting down and dirty with multi cloud and cloud native networking we heard from the customer panel you can see the diversity of where people come into the journey of cloud it kind of depends upon where you are but the trends are all clear cloud native networking DevOps up and down the stack this has been the main engine what's your guys take of the disk journey to multi cloud what do you guys seeing yeah it's it's critical I mean we're seeing all of our enterprise customers enter into this they've been through the migrations of the easy stuff you know now they're trying to optimize and get more improvement so now the tough stuffs coming on right and you know they need their data processing near where their data is so that's driving them to a multi cloud environment okay we heard some of the edge stuff I mean you guys are exactly you've seen this movie before but now it's a whole new ballgame what's your take yeah so I'll give you a hint so our practice it's not called the cloud practice it's the multi cloud practice and so if that gives you a hint of how we approach things it's very consultative and so when we look at what the trends are let's look a little year ago about a year ago we were having conversations with customers let's build a data center in the cloud let's put some VP C's let's throw some firewalls with some DNS and other infrastructure out there and let's hope it works this isn't a science project so what we're trying we're starting to see is customers are starting to have more of a vision and we're helping with that consultative nature but it's totally based on the business and you got to start understanding how the lines of business are using the apps and then we evolved into that next journey which is a foundational approach to what are some of the problem statement customers are solving when they come to you what are the top things that are on their my house or the ease of use of jelly all that stuff but what specifically they did digging into yeah some complexity I think when you look at multi cloud approach in my view is network requirements are complex you know I think they are but I think the approach can be let's simplify that so one thing that we try to do and this is how we talk to customers is let's just like you simplify an aviatrix simplifies the automation orchestration of cloud networking we're trying to simplify the design the planning implementation of infrastructure across multiple workloads across multiple platforms and so the way we do it is we sit down we look at not just use cases and not just the questions in common we anticipate we actually build out based on the business and function requirements we build out a strategy and then create a set of documents and guess what we actually build in the lab and that lab that we platform we built proves out this reference architecture actually works absolutely we implement similar concepts I mean we they're proven practices they work great so well George you mentioned that the hard part is now upon us are you referring to networking what is specifically were you getting at Tara so the easy parts done now so for the enterprises themselves migrating their more critical apps or more difficult apps into the environments you know they've just we've just scratched the surface I believe on what enterprises that are doing to move into the cloud to optimize their environments to take advantage of the scale and speed to deployment and to be able to better enable their businesses so they're just now really starting the >> so do you get you guys see what I talked about them in terms of their Cambrian explosion I mean you're both monster system integrators with you know top fortune enterprise customers you know really rely on you for for guidance and consulting and so forth and boy they're networks is that something that you you've seen I mean does that resonate did you notice a year and a half ago and all of a sudden the importance of cloud for enterprise shoot up yeah I mean we're seeing it okay in our internal environment as yeah you know we're a huge company or right customer zero or an IT so we're experiencing that internal okay and every one of our other customers so I have another question oh I don't know the answer to this and the lawyer never asks a question that you don't know the answer to but I'm gonna ask it anyway d XE @ wwt massive system integrators why aviatrix yep so great question Steve so I think the way we approach things I think we have a similar vision a similar strategy how you approach things how we approach things that it worldwide technology number one we want to simplify the complexity and so that's your number one priorities let's take the networking but simplify it and I think part of the other point I'm making is we have we see this automation piece as not just an afterthought anymore if you look at what customers care about visibility and automation is probably the at the top three maybe the third on the list and I think that's where we see the value and I think the partnership that we're building and what I what I get excited about is not just putting yours in our lab and showing customers how it works it's Co developing a solution with you figuring out hey how can we make this better right mr. piller is a huge thing Jenna insecurity alone Network everything's around visibility what automation do you see happening in terms of progression order of operations if you will it's the low-hanging fruit what are people working on now and what are what are some of the aspirational goals around when you start thinking about multi cloud and automation yep so I wanted to get back to answer that question I want to answer your question you know what led us there and why aviatrix you know in working some large internal IT projects and and looking at how we were going to integrate those solutions you know we like to build everything with recipes where Network is probably playing catch-up in the DevOps world but with a DevOps mindset looking to speed to deploy support all those things so when you start building your recipes you take a little of this a little of that and you mix it all together well when you look around you say wow look there's this big bag of a VHS let me plop that in that solves a big part of my problems that I have to speed to integrate speed to deploy and the operational views that I need to run this so that was 11 years about reference architectures yeah absolutely so you know they came with a full slate of reference architectures already the out there and ready to go that fit our needs so it's very very easy for us to integrate those into our recipes what do you guys think about all the multi vendor interoperability conversations that have been going on choice has been a big part of multi cloud in terms of you know customers want choice didn't you know they'll put a workload in the cloud that works but this notion of choice and interoperability is become a big conversation it is and I think our approach and that's why we talk to customers is let's let's speed and be risk of that decision making process and how do we do that because the interoperability is key you're not just putting it's not just a single vendor we're talking you know many many vendors I mean think about the average number of cloud applications a customer uses a business and enterprise business today you know it's it's above 30 it's it's skyrocketing and so what we do and we look at it from an Billy approaches how do things interoperate we test it out we validate it we build a reference architecture it says these are the critical design elements now let's build one with aviatrix and show how this works with aviatrix and I think the the important part there though is the automation piece that we add to it invisibility so I think the visibility is what's what I see lacking across the industry today and the cloud needed that's been a big topic yep okay in terms of aviatrix that you guys see them coming in there one of the ones that are emerging and the new brands emerging with multi cloud you still got the old guard incumbents with huge footprints how our customers dealing with that that kind of component in dealing with both of them yeah I mean where we have customers that are ingrained with a particular vendor and you know we have partnerships with many vendors so our objective is to provide the solution that meets that client and you they all want multi vendor they all want interoperability correct all right so I got to ask you guys a question while we were defining de to operations what does that mean I mean you guys are looking at the big business and technical components of architecture what does de two operations mean what's the definition of that yeah so I think from our perspective my experience we you know de to operations whether it's it's not just the you know the orchestration piece and setting up and let it a lot of automate and have some you know change control you're looking at this from a data perspective how do I support this ongoing and make it easy to make changes as we evolve that the the cloud is very dynamic the the nature of how that fast is expanding the number of features is astonishing trying to keep up to date with a number of just networking capabilities and services that are added so I think day to operation starts with a fundable understanding of you know building out supporting a customer's environments and making it the automation piece easy from from you know a distance I think yeah and you know taking that to the next level of being able to enable customers to have catalog items that they can pick and choose hey I need this network connectivity from this cloud location back to this on pram and being able to have that automated and provisioned just simply by ordering it for the folks watching out there guys take a minute to explain as you guys are in the trenches doing a lot of good work what are some of the engagement that you guys get into how does that progress what is that what's what happens there they call you up and say hey I need multi-cloud or you're already in there I mean take us through why how someone can engage to use a global si to come in and make this thing happen what's looks like typical engagement look like yeah so from our perspective we typically have a series of workshops in a methodology that we kind of go along the journey number one we have a foundational approach and I don't mean foundation meaning the network foundation that's a very critical element we got a factor in security we got a factor in automation so we think about foundation we do a workshop that starts with education a lot of times we'll go in and we'll just educate the customer what does VPC sharing you know what is a private link and Azure how does that impact your business you know customers I want to share services out in an ecosystem with other customers and partners well there's many ways to accomplish that so our goal is to you know understand those requirements and then build that strategy with them thoughts George oh yeah I mean I'm one of the guys that's down in the weeds making things happen so I'm not the guy on the front line interfacing with the customers every day but we have a similar approach you know we have a consulting practice that will go out and and apply their practices to see what those and when do you parachute in yeah when I then is I'm on the back end working with our offering development leads for the networking so we understand or seeing what customers are asking for and we're on the back end developing the solutions that integrate with our own offerings as well as enable other customers to just deploy quickly to meet their connectivity needs it so the patterns are similar great final question for you guys I want to ask you to paint a picture of what success looks like and you know for name customers you don't forget in reveal of kind of who they are but what does success look like in multi-cloud as you as you paint a picture for the folks here and watching on the live stream it's if someone says hey I want to be multi-cloud I got to have my operations agile I want full DevOps I want programmability security built in from day zero what does success look like yeah I think success looks like this so when you're building out a network the network is a harder thing to change than some other aspects of cloud so what we think is even if you're thinking about that second cloud which we have most of our customers are on to public clouds today they might be dabbling in that is you build that network foundation an architecture that takes in consideration where you're going and so once we start building that reference architecture out that shows this is how to sit from a multi-cloud perspective not a single cloud and let's not forget our branches let's not forget our data centers let's not forget how all this connects together because that's how we define multi-cloud it's not just in the cloud it's on Prem and it's off Prem and so collectively I think the key is also is that we provide them an hld you got to start with in a high-level design that can be tweaked as you go through the journey but you got to give a solid structural foundation and that networking which we think most customers think as not not the network engineers but as an afterthought we want to make that the most critical element before you start the journey Jorge from your seed had a success look for you so you know it starts out on these journeys often start out people not even thinking about what is gonna happen what what their network needs are when they start their migration journey to the cloud so I want this success to me looks like them being able to end up not worrying about what's happening in the network when they move to the cloud good guys great insight thanks for coming on share and pen I've got a round of applause the global system integrators [Applause] [Music] okay welcome back from the live feed I'm shuffle with the cube Steve Eleni CEO of aviatrix my co-host our next panel is the aviatrix certified engineers also known as aces this is the folks that are certified their engineering they're building these new solutions please welcome Toby Foster min from Attica Stacy linear from Terra data and Jennifer Reid with Victor Davis to the stage I was just gonna I was just gonna rip you guys and say where's your jackets and Jen's got the jacket on okay good love the aviatrix aces pile of gear there above the clouds soaring to new heights that's right so guys aviatrix aces love the name I think it's great certified this is all about getting things engineered so there's a level of certification I want to get into that but first take us through the day in the life of an ace and just to point out Stacey's a squad leader so he's like a squadron leader Roger and leader yeah squadron leader so he's got a bunch of aces underneath him but share your perspective day-in-the-life Jeff we'll start with you sure so I have actually a whole team that works for me both in the in the North America both in the US and in Mexico and so I'm eagerly working to get them certified as well so I can become a squad leader myself but it's important because one of the the critical gaps that we've found is people having the networking background because they're you graduate from college and you have a lot of computer science background you can program you've got Python but networking in packets they just don't get and so just taking them through all the processes that it's really necessary to understand when you're troubleshooting is really critical mm-hmm and because you're gonna get an issue where you need to figure out where exactly is that happening on the network you know is my my issue just in the V PCs and on the instant side is a security group or is it going on print and this is something actually embedded within Amazon itself I mean I should troubleshot an issue for about six months going back and forth with Amazon and it was the vgw VPN because they were auto-scaling on two sides and we ended up having to pull out the Cisco's and put in aviatrix so I could just say okay it's fixed and actually actually helped the application teams get to that and get it solved yeah but I'm taking a lot of junior people and getting them through that certification process so they can understand and see the network the way I see the network I mean look I've been doing this such for 25 years but I got out when I went in the Marine Corps that's what I did and coming out the network is still the network but people don't get the same training they get they got in the 90s it's just so easy just write some software and they work takes care of itself yes I'll be will get I'll come back to that I want to come back to that that problem solved with Amazon but Toby I think the only thing I have to add to that is that it's always the network fault as long as I've been in network have always been the network's fault and I'm even to this day you know it's still the network's fault and part of being a network guy is that you need to prove when it is and when it's not your fault and that means you need to know a little bit about a hundred different things to make that and now you got a full stack DevOps you gotta know a lot more times another hundred and these times are changing yeah they say you're a squadron leader I get that right what is what does a squadron leader first can you describe what it is I think probably just leading all the network components of it but not they from my perspective when to think about what you asked them was it's about no issues and no escalation soft my day is a good that's a good day yes it's a good day Jennifer you mentioned the Amazon thing this brings up a good point you know when you have these new waves come in you have a lot of new things newly use cases a lot of the finger-pointing it's that guy's problem that girl's problem so what is how do you solve that and how do you get the young guns up to speed is there training is that this is where the certification comes in well is where the certification is really going to come in I know when we we got together at reinvent one of the the questions that that we had with Stephen the team was what what should our certification look like you know she would just be teaching about what aviatrix troubleshooting brings to bear but what should that be like and I think Toby and I were like no no no that's going a little too high we need to get really low because the the better someone can get at actually understanding what actually happening in the network and and where to actually troubleshoot the problem how to step back each of those processes because without that it's just a big black box and they don't know you know because everything is abstracted in Amazon Internet and Azure and Google is substracted and they have these virtual gateways they have VPNs that you just don't have the logs on it's you just don't know and so then what tools can you put in front of them of where they can look because there are full logs well as long as we turned on the flow logs when they built it you know and there's like each one of those little things that well if they had decided to do that when they built it it's there but if you can come in later to really supplement that with training to actual troubleshoot and do a packet capture here as it's going through then teaching them how to read that even yeah Toby we were talking before we came on up on stage about your career you've been networking all your time and then you know you're now entering a lot of younger people how is that going because the people who come in fresh they don't have all the old war stories they don't know you talk about you know that's dimmer fault I walk in bare feet in the snow when I was your age I mean it's so easy now right they say what's your take on how you train the young P so I've noticed two things one is that they are up to speed a lot faster in generalities of networking they can tell you what a network is in high school level now where I didn't learn that too midway through my career and they're learning it faster but they don't necessarily understand why it's that way or you know everybody thinks that it's always slash 24 for a subnet and they don't understand why you can break it down smaller why it's really necessary so the the ramp up speed is much faster for these guys that are coming in but they don't understand why and they need some of that background knowledge to see where it's coming from and why is it important and old guys that's where we thrive Jennifer you mentioned you you got in from the Marines health spa when you got into networking how what was it like then and compared it now almost like we heard earlier static versus dynamic don't be static cuz then you just set the network you got a perimeter yeah no there was no such thing ya know so back in the day I mean I mean we had banyan vines for email and you know we had token ring and I had to set up token ring networks and figure out why that didn't work because how many of things were actually sharing it but then actually just cutting fiber and running fiber cables and dropping them over you know shelters to plug them in and oh crap they swung it too hard and shattered it now I gotta be great polished this thing and actually shoot like to see if it works I mean that was the network crimped five cat5 cables to run an Ethernet you know and then from that just said network switches dumb switches like those were the most common ones you had then actually configuring routers and you know logging into a Cisco router and actually knowing how to configure that and it was funny because I had gone all the way up and was a software product manager for a while so I've gone all the way up the stack and then two and a half three years ago I came across to to work with entity group that it became Victor Davis but we went to help one of our customers Davis and it was like okay so we need to fix the network okay I haven't done this in 20 years but all right let's get to it you know because it really fundamentally does not change it's still the network I mean I've had people tell me well you know when we go to containers we will not have to worry about the network and I'm like yeah you don't I do and then with this were the program abilities it really interesting so I think this brings up the certification what are some of the new things that people should be aware of that come in with the aviatrix ace certification what are some of the highlights can you guys share some of the some of the highlights around the certifications I think some of the importance is that it's it doesn't need to be vendor specific for network generality or basic networking knowledge and instead of learning how Cisco does something or how Palo Alto does something we need to understand how and why it works as a basic model and then understand how each vendor has gone about that problem and solved it in a general that's true in multi cloud as well you can't learn how cloud networking works without understanding how a double u.s. senator and GCP are all slightly the same but slightly different and some things work and some things don't I think that's probably the number one take I think having a certification across clouds is really valuable cuz we heard the global si help the business issues what does it mean to do that is it code is that networking is it configuration is that aviatrix what is the I mean op C aviatrix is the ASA certification but what is it about the multi cloud that makes it multi networking and multi vendor easy answer is yes so you got to be a generalist getting your hands and all you have to be right it takes experience because it's every every cloud vendor has their own certification whether that's hops and advanced networking and advanced security or whatever it might be yeah they can take the test but they have no idea how to figure out what's wrong with that system and the same thing with any certification but it's really getting your hands in there and actually having to troubleshoot the problems you know actually work the problem you know and calm down it's going to be okay I mean because I don't know how many calls I've been on or even had aviatrix join me on it's like okay so everyone calm down let's figure out what's happening it's like we've looked at that screen three times looking at it again it's not gonna solve that problem right but at the same time you know remaining calm but knowing that it really is I'm getting a packet from here to go over here it's not working so what could be the problem you know and actually stepping them through with those scenarios but that's like you only get that by having to do it you know and seeing it and going through it and then I have a question so we you know I just see it we started this program maybe months ago we're seeing a huge amount of interest I mean we're oversubscribed on all the training sessions we've got people flying from around the country even with coronavirus flying to go to Seattle to go to these events were oversubscribed good is that watching leader would put there yeah is that something that you see in your organization's are you recommending that to people do you see I mean I'm just I guess I'm surprised I'm not surprised but I'm really surprised by the demand if you would of this multi cloud network certification because it really isn't anything like that is that something you guys can comment on or do you see the same things in your organization's I say from my side because we operate in the multi cloud environment so it really helps and it's beneficial for us yeah I think I would add that uh networking guys have always needed to use certifications to prove that they know what they know right it's not good enough to say yeah I know IP addresses or I know how a network works and a couple little check marks or a little letters buying helps give you validity um so even in our team we can say hey you know we're using these certifications to know that you know enough of the basics and enough of the understandings that you have the tools necessary right so I guess my final question for you guys is why an eighth certification is relevant and then second part is share what the livestream folks who aren't yet a certified or might want to jump in to be AVH or certified engineers why is it important so why is it relevant and why shouldn't someone want to be an ace-certified I'm uses the right engineer I think my views a little different I think certification comes from proving that you have the knowledge not proving that you get a certification to get no I mean they're backwards so when you've got the training and the understanding and the you use that to prove and you can like grow your certification list with it versus studying for a test to get a certification and have no understanding of ok so that who is the right person that look at this is saying I'm qualified is it a network engineer is it a DevOps person what's your view you know is it a certain you know I think cloud is really the answer it's the as we talked like the edge is getting eroded so is the network definitions eating eroded we're getting more and more of some network some DevOps some security lots and lots of security because network is so involved in so many of them that's just the next progression there I would say I expand that to more automation engineers because we have those now probably extended as well well I think that the training classes themselves are helpful especially the entry-level ones for people who may be quote-unquote cloud architects but I've never done anything and networking for them to understand why we need those things to really work whether or not they go through to eventually get a certification is something different but I really think fundamentally understanding how these things work it makes them a better architect makes them better application developer but even more so as you deploy more of your applications into the cloud really getting an understanding even from our people who have tradition down on Prem networking they can understand how that's going to work in the cloud - well I know we've got just under 30 seconds left I want to get one more question than just one more for the folks watching that are maybe younger that don't have that networking training from your experiences each of you can answer why is it should they know about networking what's the benefit what's in it for them motivate them share some insights and why they should go a little bit deeper in networking Stacey we'll start with you we'll go down I'd say it's probably fundamental right if you don't deliver solutions networking use the very top I would say if you fundamental of an operating system running on a machine how those machines talk together as a fundamental change is something that starts from the base and work your way up right well I think it's a challenge because you you've come from top down now you're gonna start looking from bottom up and you want those different systems to cross communicate and say you built something and you're overlapping IP space not that that doesn't happen but how can I actually make that still operate without having to reappear e-platform it's like those challenges like those younger developers or sis engineers can really start to get their hands around and understand those complexities and bring that forward in their career they got to know the how the pipes are working and because know what's going some plumbing that's right and the works a how to code it that's right awesome thank you guys for great insights ace certified engineers also known as aces give a round of applause thank you okay all right that concludes my portion thank you Steve thanks for have Don thank you very much that was fantastic everybody round of applause for John Currier yeah so great event great event I'm not going to take long we've got we've got lunch outside for that for the people here just a couple of things just call to action right so we saw the Aces you know for those of you out on the stream here become a certified right it's great for your career it's great for knowledge is is fantastic it's not just an aviatrix thing it's gonna teach you about cloud networking multi-cloud networking with a little bit of aviatrix exactly what the Cisco CCIE program was for IP network that type of the thing that's number one second thing is is is is learn right so so there's a there's a link up there for the four to join the community again like I started this this is a community this is the kickoff to this community and it's a movement so go to what a v8 community bh6 comm starting a community at multi cloud so you know get get trained learn I'd say the next thing is we're doing over a hundred seminars in across the United States and also starting into Europe soon will come out and will actually spend a couple hours and talk about architecture and talk about those beginning things for those of you on the you know on the livestream in here as well you know we're coming to a city near you go to one of those events it's a great way to network with other people that are in the industry as well as to start to learn and get on that multi-cloud journey and then I'd say the last thing is you know we haven't talked a lot about what aviatrix does here and that's intentional we want you you know leaving with wanting to know more and schedule get with us in schedule a multi our architecture workshop session so we we sit out with customers and we talk about where they're at in that journey and more importantly where they're going in that in-state architecture from networking compute storage everything and everything you heard today every panel kept talking about architecture talking about operations those are the types of things that we saw we help you cook define that canonical architecture that system architecture that's yours so for so many of our customers they have three by five plotted lucid charts architecture drawings and it's the customer name slash aviatrix arc network architecture and they put it on their whiteboard that's what what we and that's the most valuable thing they get from us so this becomes their twenty-year network architecture drawing that they don't do anything without talking to us and look at that architecture that's what we do in these multi hour workshop sessions with customers and that's super super powerful so if you're interested definitely call us and let's schedule that with our team so anyway I just want to thank everybody on the livestream thank everybody here hopefully it was it was very useful I think it was and joined the movement and for those of you here join us for lunch and thank you very much [Applause] [Music]

hi I'm Peter Burroughs welcome to a wiki bond action item quick take Neal Raiden Terry data announced earnings this week what does it tell us about Terry data and the overall market for analytics well tear date announced their first quarter earnings and they beat estimates for both earnings than revenues but they but lo they announced lower guidance for the fiscal year which I guess you know failed to impress Wall Street but recurring quarter one revenue was up 11% nearly a year to three hundred and two million dollars but perpetual revenue was down 23% from quarter one seventeen consulting was up to 135 million for the quarter you know not not altogether shabby for a company in transition but I think what it shows is that Teradata is executing this transitional program and there are some pluses and minuses but they're making progress jury's out but I think overall I'd consider it a good quarter what does it tell us about the market anything we can glean from their daters results about the market overall Neal it's hard to say there's a lot of you know at the ATW conference last week I listened to the keynote from Mike Ferguson I've known Mike for years and I think I always think that Mike's the real deal because he spends all of his time doing consulting and when he speaks he's there to tell us what's happening it he gave a great presentation about datawarehouse versus data Lake and if if he's correct there is still a market for a company like Terra data so you know we'll just have to see excellent Neil Raiden thanks very much this has been a wiki bond critique or actually it's been a wiki bond action item quick-take talk to you again