>>From the Cube Studios in Palo Alto in Boston, bringing you data-driven insights from the cube and E T R. This is breaking analysis with Dave Valante. >>Making technology predictions in 2022 was tricky business, especially if you were projecting the performance of markets or identifying I P O prospects and making binary forecast on data AI and the macro spending climate and other related topics in enterprise tech 2022, of course was characterized by a seesaw economy where central banks were restructuring their balance sheets. The war on Ukraine fueled inflation supply chains were a mess. And the unintended consequences of of forced march to digital and the acceleration still being sorted out. Hello and welcome to this week's weekly on Cube Insights powered by E T R. In this breaking analysis, we continue our annual tradition of transparently grading last year's enterprise tech predictions. And you may or may not agree with our self grading system, but look, we're gonna give you the data and you can draw your own conclusions and tell you what, tell us what you think. >>All right, let's get right to it. So our first prediction was tech spending increases by 8% in 2022. And as we exited 2021 CIOs, they were optimistic about their digital transformation plans. You know, they rushed to make changes to their business and were eager to sharpen their focus and continue to iterate on their digital business models and plug the holes that they, the, in the learnings that they had. And so we predicted that 8% rise in enterprise tech spending, which looked pretty good until Ukraine and the Fed decided that, you know, had to rush and make up for lost time. We kind of nailed the momentum in the energy sector, but we can't give ourselves too much credit for that layup. And as of October, Gartner had it spending growing at just over 5%. I think it was 5.1%. So we're gonna take a C plus on this one and, and move on. >>Our next prediction was basically kind of a slow ground ball. The second base, if I have to be honest, but we felt it was important to highlight that security would remain front and center as the number one priority for organizations in 2022. As is our tradition, you know, we try to up the degree of difficulty by specifically identifying companies that are gonna benefit from these trends. So we highlighted some possible I P O candidates, which of course didn't pan out. S NQ was on our radar. The company had just had to do another raise and they recently took a valuation hit and it was a down round. They raised 196 million. So good chunk of cash, but, but not the i p O that we had predicted Aqua Securities focus on containers and cloud native. That was a trendy call and we thought maybe an M SS P or multiple managed security service providers like Arctic Wolf would I p o, but no way that was happening in the crummy market. >>Nonetheless, we think these types of companies, they're still faring well as the talent shortage in security remains really acute, particularly in the sort of mid-size and small businesses that often don't have a sock Lacework laid off 20% of its workforce in 2022. And CO C e o Dave Hatfield left the company. So that I p o didn't, didn't happen. It was probably too early for Lacework. Anyway, meanwhile you got Netscope, which we've cited as strong in the E T R data as particularly in the emerging technology survey. And then, you know, I lumia holding its own, you know, we never liked that 7 billion price tag that Okta paid for auth zero, but we loved the TAM expansion strategy to target developers beyond sort of Okta's enterprise strength. But we gotta take some points off of the failure thus far of, of Okta to really nail the integration and the go to market model with azero and build, you know, bring that into the, the, the core Okta. >>So the focus on endpoint security that was a winner in 2022 is CrowdStrike led that charge with others holding their own, not the least of which was Palo Alto Networks as it continued to expand beyond its core network security and firewall business, you know, through acquisition. So overall we're gonna give ourselves an A minus for this relatively easy call, but again, we had some specifics associated with it to make it a little tougher. And of course we're watching ve very closely this this coming year in 2023. The vendor consolidation trend. You know, according to a recent Palo Alto network survey with 1300 SecOps pros on average organizations have more than 30 tools to manage security tools. So this is a logical way to optimize cost consolidating vendors and consolidating redundant vendors. The E T R data shows that's clearly a trend that's on the upswing. >>Now moving on, a big theme of 2020 and 2021 of course was remote work and hybrid work and new ways to work and return to work. So we predicted in 2022 that hybrid work models would become the dominant protocol, which clearly is the case. We predicted that about 33% of the workforce would come back to the office in 2022 in September. The E T R data showed that figure was at 29%, but organizations expected that 32% would be in the office, you know, pretty much full-time by year end. That hasn't quite happened, but we were pretty close with the projection, so we're gonna take an A minus on this one. Now, supply chain disruption was another big theme that we felt would carry through 2022. And sure that sounds like another easy one, but as is our tradition, again we try to put some binary metrics around our predictions to put some meat in the bone, so to speak, and and allow us than you to say, okay, did it come true or not? >>So we had some data that we presented last year and supply chain issues impacting hardware spend. We said at the time, you can see this on the left hand side of this chart, the PC laptop demand would remain above pre covid levels, which would reverse a decade of year on year declines, which I think started in around 2011, 2012. Now, while demand is down this year pretty substantially relative to 2021, I D C has worldwide unit shipments for PCs at just over 300 million for 22. If you go back to 2019 and you're looking at around let's say 260 million units shipped globally, you know, roughly, so, you know, pretty good call there. Definitely much higher than pre covid levels. But so what you might be asking why the B, well, we projected that 30% of customers would replace security appliances with cloud-based services and that more than a third would replace their internal data center server and storage hardware with cloud services like 30 and 40% respectively. >>And we don't have explicit survey data on exactly these metrics, but anecdotally we see this happening in earnest. And we do have some data that we're showing here on cloud adoption from ET R'S October survey where the midpoint of workloads running in the cloud is around 34% and forecast, as you can see, to grow steadily over the next three years. So this, well look, this is not, we understand it's not a one-to-one correlation with our prediction, but it's a pretty good bet that we were right, but we gotta take some points off, we think for the lack of unequivocal proof. Cause again, we always strive to make our predictions in ways that can be measured as accurate or not. Is it binary? Did it happen, did it not? Kind of like an O K R and you know, we strive to provide data as proof and in this case it's a bit fuzzy. >>We have to admit that although we're pretty comfortable that the prediction was accurate. And look, when you make an hard forecast, sometimes you gotta pay the price. All right, next, we said in 2022 that the big four cloud players would generate 167 billion in IS and PaaS revenue combining for 38% market growth. And our current forecasts are shown here with a comparison to our January, 2022 figures. So coming into this year now where we are today, so currently we expect 162 billion in total revenue and a 33% growth rate. Still very healthy, but not on our mark. So we think a w s is gonna miss our predictions by about a billion dollars, not, you know, not bad for an 80 billion company. So they're not gonna hit that expectation though of getting really close to a hundred billion run rate. We thought they'd exit the year, you know, closer to, you know, 25 billion a quarter and we don't think they're gonna get there. >>Look, we pretty much nailed Azure even though our prediction W was was correct about g Google Cloud platform surpassing Alibaba, Alibaba, we way overestimated the performance of both of those companies. So we're gonna give ourselves a C plus here and we think, yeah, you might think it's a little bit harsh, we could argue for a B minus to the professor, but the misses on GCP and Alibaba we think warrant a a self penalty on this one. All right, let's move on to our prediction about Supercloud. We said it becomes a thing in 2022 and we think by many accounts it has, despite the naysayers, we're seeing clear evidence that the concept of a layer of value add that sits above and across clouds is taking shape. And on this slide we showed just some of the pickup in the industry. I mean one of the most interesting is CloudFlare, the biggest supercloud antagonist. >>Charles Fitzgerald even predicted that no vendor would ever use the term in their marketing. And that would be proof if that happened that Supercloud was a thing and he said it would never happen. Well CloudFlare has, and they launched their version of Supercloud at their developer week. Chris Miller of the register put out a Supercloud block diagram, something else that Charles Fitzgerald was, it was was pushing us for, which is rightly so, it was a good call on his part. And Chris Miller actually came up with one that's pretty good at David Linthicum also has produced a a a A block diagram, kind of similar, David uses the term metacloud and he uses the term supercloud kind of interchangeably to describe that trend. And so we we're aligned on that front. Brian Gracely has covered the concept on the popular cloud podcast. Berkeley launched the Sky computing initiative. >>You read through that white paper and many of the concepts highlighted in the Supercloud 3.0 community developed definition align with that. Walmart launched a platform with many of the supercloud salient attributes. So did Goldman Sachs, so did Capital One, so did nasdaq. So you know, sorry you can hate the term, but very clearly the evidence is gathering for the super cloud storm. We're gonna take an a plus on this one. Sorry, haters. Alright, let's talk about data mesh in our 21 predictions posts. We said that in the 2020s, 75% of large organizations are gonna re-architect their big data platforms. So kind of a decade long prediction. We don't like to do that always, but sometimes it's warranted. And because it was a longer term prediction, we, at the time in, in coming into 22 when we were evaluating our 21 predictions, we took a grade of incomplete because the sort of decade long or majority of the decade better part of the decade prediction. >>So last year, earlier this year, we said our number seven prediction was data mesh gains momentum in 22. But it's largely confined and narrow data problems with limited scope as you can see here with some of the key bullets. So there's a lot of discussion in the data community about data mesh and while there are an increasing number of examples, JP Morgan Chase, Intuit, H S P C, HelloFresh, and others that are completely rearchitecting parts of their data platform completely rearchitecting entire data platforms is non-trivial. There are organizational challenges, there're data, data ownership, debates, technical considerations, and in particular two of the four fundamental data mesh principles that the, the need for a self-service infrastructure and federated computational governance are challenging. Look, democratizing data and facilitating data sharing creates conflicts with regulatory requirements around data privacy. As such many organizations are being really selective with their data mesh implementations and hence our prediction of narrowing the scope of data mesh initiatives. >>I think that was right on J P M C is a good example of this, where you got a single group within a, within a division narrowly implementing the data mesh architecture. They're using a w s, they're using data lakes, they're using Amazon Glue, creating a catalog and a variety of other techniques to meet their objectives. They kind of automating data quality and it was pretty well thought out and interesting approach and I think it's gonna be made easier by some of the announcements that Amazon made at the recent, you know, reinvent, particularly trying to eliminate ET t l, better connections between Aurora and Redshift and, and, and better data sharing the data clean room. So a lot of that is gonna help. Of course, snowflake has been on this for a while now. Many other companies are facing, you know, limitations as we said here and this slide with their Hadoop data platforms. They need to do new, some new thinking around that to scale. HelloFresh is a really good example of this. Look, the bottom line is that organizations want to get more value from data and having a centralized, highly specialized teams that own the data problem, it's been a barrier and a blocker to success. The data mesh starts with organizational considerations as described in great detail by Ash Nair of Warner Brothers. So take a listen to this clip. >>Yeah, so when people think of Warner Brothers, you always think of like the movie studio, but we're more than that, right? I mean, you think of H B O, you think of t n t, you think of C N N. We have 30 plus brands in our portfolio and each have their own needs. So the, the idea of a data mesh really helps us because what we can do is we can federate access across the company so that, you know, CNN can work at their own pace. You know, when there's election season, they can ingest their own data and they don't have to, you know, bump up against, as an example, HBO if Game of Thrones is going on. >>So it's often the case that data mesh is in the eyes of the implementer. And while a company's implementation may not strictly adhere to Jamma Dani's vision of data mesh, and that's okay, the goal is to use data more effectively. And despite Gartner's attempts to deposition data mesh in favor of the somewhat confusing or frankly far more confusing data fabric concept that they stole from NetApp data mesh is taking hold in organizations globally today. So we're gonna take a B on this one. The prediction is shaping up the way we envision, but as we previously reported, it's gonna take some time. The better part of a decade in our view, new standards have to emerge to make this vision become reality and they'll come in the form of both open and de facto approaches. Okay, our eighth prediction last year focused on the face off between Snowflake and Databricks. >>And we realized this popular topic, and maybe one that's getting a little overplayed, but these are two companies that initially, you know, looked like they were shaping up as partners and they, by the way, they are still partnering in the field. But you go back a couple years ago, the idea of using an AW w s infrastructure, Databricks machine intelligence and applying that on top of Snowflake as a facile data warehouse, still very viable. But both of these companies, they have much larger ambitions. They got big total available markets to chase and large valuations that they have to justify. So what's happening is, as we've previously reported, each of these companies is moving toward the other firm's core domain and they're building out an ecosystem that'll be critical for their future. So as part of that effort, we said each is gonna become aggressive investors and maybe start doing some m and a and they have in various companies. >>And on this chart that we produced last year, we studied some of the companies that were targets and we've added some recent investments of both Snowflake and Databricks. As you can see, they've both, for example, invested in elation snowflake's, put money into Lacework, the Secur security firm, ThoughtSpot, which is trying to democratize data with ai. Collibra is a governance platform and you can see Databricks investments in data transformation with D B T labs, Matillion doing simplified business intelligence hunters. So that's, you know, they're security investment and so forth. So other than our thought that we'd see Databricks I p o last year, this prediction been pretty spot on. So we'll give ourselves an A on that one. Now observability has been a hot topic and we've been covering it for a while with our friends at E T R, particularly Eric Bradley. Our number nine prediction last year was basically that if you're not cloud native and observability, you are gonna be in big trouble. >>So everything guys gotta go cloud native. And that's clearly been the case. Splunk, the big player in the space has been transitioning to the cloud, hasn't always been pretty, as we reported, Datadog real momentum, the elk stack, that's open source model. You got new entrants that we've cited before, like observe, honeycomb, chaos search and others that we've, we've reported on, they're all born in the cloud. So we're gonna take another a on this one, admittedly, yeah, it's a re reasonably easy call, but you gotta have a few of those in the mix. Okay, our last prediction, our number 10 was around events. Something the cube knows a little bit about. We said that a new category of events would emerge as hybrid and that for the most part is happened. So that's gonna be the mainstay is what we said. That pure play virtual events are gonna give way to hi hybrid. >>And the narrative is that virtual only events are, you know, they're good for quick hits, but lousy replacements for in-person events. And you know that said, organizations of all shapes and sizes, they learn how to create better virtual content and support remote audiences during the pandemic. So when we set at pure play is gonna give way to hybrid, we said we, we i we implied or specific or specified that the physical event that v i p experience is going defined. That overall experience and those v i p events would create a little fomo, fear of, of missing out in a virtual component would overlay that serves an audience 10 x the size of the physical. We saw that really two really good examples. Red Hat Summit in Boston, small event, couple thousand people served tens of thousands, you know, online. Second was Google Cloud next v i p event in, in New York City. >>Everything else was, was, was, was virtual. You know, even examples of our prediction of metaverse like immersion have popped up and, and and, and you know, other companies are doing roadshow as we predicted like a lot of companies are doing it. You're seeing that as a major trend where organizations are going with their sales teams out into the regions and doing a little belly to belly action as opposed to the big giant event. That's a definitely a, a trend that we're seeing. So in reviewing this prediction, the grade we gave ourselves is, you know, maybe a bit unfair, it should be, you could argue for a higher grade, but the, but the organization still haven't figured it out. They have hybrid experiences but they generally do a really poor job of leveraging the afterglow and of event of an event. It still tends to be one and done, let's move on to the next event or the next city. >>Let the sales team pick up the pieces if they were paying attention. So because of that, we're only taking a B plus on this one. Okay, so that's the review of last year's predictions. You know, overall if you average out our grade on the 10 predictions that come out to a b plus, I dunno why we can't seem to get that elusive a, but we're gonna keep trying our friends at E T R and we are starting to look at the data for 2023 from the surveys and all the work that we've done on the cube and our, our analysis and we're gonna put together our predictions. We've had literally hundreds of inbounds from PR pros pitching us. We've got this huge thick folder that we've started to review with our yellow highlighter. And our plan is to review it this month, take a look at all the data, get some ideas from the inbounds and then the e t R of January surveys in the field. >>It's probably got a little over a thousand responses right now. You know, they'll get up to, you know, 1400 or so. And once we've digested all that, we're gonna go back and publish our predictions for 2023 sometime in January. So stay tuned for that. All right, we're gonna leave it there for today. You wanna thank Alex Myerson who's on production and he manages the podcast, Ken Schiffman as well out of our, our Boston studio. I gotta really heartfelt thank you to Kristen Martin and Cheryl Knight and their team. They helped get the word out on social and in our newsletters. Rob Ho is our editor in chief over at Silicon Angle who does some great editing for us. Thank you all. Remember all these podcasts are available or all these episodes are available is podcasts. Wherever you listen, just all you do Search Breaking analysis podcast, really getting some great traction there. Appreciate you guys subscribing. I published each week on wikibon.com, silicon angle.com or you can email me directly at david dot valante silicon angle.com or dm me Dante, or you can comment on my LinkedIn post. And please check out ETR AI for the very best survey data in the enterprise tech business. Some awesome stuff in there. This is Dante for the Cube Insights powered by etr. Thanks for watching and we'll see you next time on breaking analysis.

(upbeat music) >> From theCube Studios in Palo Alto in Boston, bringing you data driven insights from theCube and ETR. This is Breaking Analysis with Dave Vellante. >> While by no means a safe haven, the cybersecurity sector has outpaced the broader tech market by a meaningful margin, that is up until very recently. Cybersecurity remains the number one technology priority for the C-suite, but as we've previously reported the CISO's budget has constraints just like other technology investments. Recent trends show that economic headwinds have elongated sales cycles, pushed deals into future quarters, and just like other tech initiatives, are pacing cybersecurity investments and breaking them into smaller chunks. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this Breaking Analysis we explain how cybersecurity trends are reverting to the mean and tracking more closely with other technology investments. We'll make a couple of valuation comparisons to show the magnitude of the challenge and which cyber firms are feeling the heat, which aren't. There are some exceptions. We'll then show the latest survey data from ETR to quantify the contraction in spending momentum and close with a glimpse of the landscape of emerging cybersecurity companies, the private companies that could be ripe for acquisition, consolidation, or disruptive to the broader market. First, let's take a look at the recent patterns for cyber stocks relative to the broader tech market as a benchmark, as an indicator. Here's a year to date comparison of the bug ETF, which comprises a basket of cyber security names, and we compare that with the tech heavy NASDAQ composite. Notice that on April 13th of this year the cyber ETF was actually in positive territory while the NAS was down nearly 14%. Now by August 16th, the green turned red for cyber stocks but they still meaningfully outpaced the broader tech market by more than 950 basis points as of December 2nd that Delta had contracted. As you can see, the cyber ETF is now down nearly 25%, year to date, while the NASDAQ is down 27% and change. Now take a look at just how far a few of the high profile cybersecurity names have fallen. Here are six security firms that we've been tracking closely since before the pandemic. We've been, you know, tracking dozens but let's just take a look at this data and the subset. We show for comparison the S&P 500 and the NASDAQ, again, just for reference, they're both up since right before the pandemic. They're up relative to right before the pandemic, and then during the pandemic the S&P shot up more than 40%, relative to its pre pandemic level, around February is what we're using for the pre pandemic level, and the NASDAQ peaked at around 65% higher than that February level. They're now down 85% and 71% of their previous. So they're at 85% and 71% respectively from their pandemic highs. You compare that to these six companies, Splunk, which was and still is working through a transition is well below its pre pandemic market value and 44, it's 44% of its pre pandemic high as of last Friday. Palo Alto Networks is the most interesting here, in that it had been facing challenges prior to the pandemic related to a pivot to the Cloud which we reported on at the time. But as we said at that time we believe the company would sort out its Cloud transition, and its go to market challenges, and sales compensation issues, which it did as you can see. And its valuation jumped from 24 billion prior to Covid to 56 billion, and it's holding 93% of its peak value. Its revenue run rate is now over 6 billion with a healthy growth rate of 24% expected for the next quarter. Similarly, Fortinet has done relatively well holding 71% of its peak Covid value, with a healthy 34% revenue guide for the coming quarter. Now, Okta has been the biggest disappointment, a darling of the pandemic Okta's communication snafu, with what was actually a pretty benign hack combined with difficulty absorbing its 7 billion off zero acquisition, knocked the company off track. Its valuation has dropped by 35 billion since its peak during the pandemic, and that's after a nice beat and bounce back quarter just announced by Okta. Now, in our view Okta remains a viable long-term leader in identity. However, its recent fiscal 24 revenue guide was exceedingly conservative at around 16% growth. So either the company is sandbagging, or has such poor visibility that it wants to be like super cautious or maybe it's actually seeing a dramatic slowdown in its business momentum. After all, this is a company that not long ago was putting up 50% plus revenue growth rates. So it's one that bears close watching. CrowdStrike is another big name that we've been talking about on Breaking Analysis for quite some time. It like Okta has led the industry in a key ETR performance indicator that measures customer spending momentum. Just last week, CrowdStrike announced revenue increased more than 50% but new ARR was soft and the company guided conservatively. Not surprisingly, the stock got absolutely crushed as CrowdStrike blamed tepid demand from smaller and midsize firms. Many analysts believe that competition from Microsoft was one factor along with cautious spending amongst those midsize and smaller customers. Notably, large customers remain active. So we'll see if this is a longer term trend or an anomaly. Zscaler is another company in the space that we've reported having great customer spending momentum from the ETR data. But even though the company beat expectations for its recent quarter, like other companies its Outlook was conservative. So other than Palo Alto, and to a lesser extent Fortinet, these companies and others that we're not showing here are feeling the economic pinch and it shows in the compression of value. CrowdStrike, for example, had a 70 billion valuation at one point during the pandemic Zscaler top 50 billion, Okta 45 billion. Now, having said that Palo Alto Networks, Fortinet, CrowdStrike, and Zscaler are all still trading well above their pre pandemic levels that we tracked back in February of 2020. All right, let's go now back to ETR'S January survey and take a look at how much things have changed since the beginning of the year. Remember, this is obviously pre Ukraine, and pre all the concerns about the economic headwinds but here's an X Y graph that shows a net score, or spending momentum on the y-axis, and market presence on the x-axis. The red dotted line at 40% on the vertical indicates a highly elevated net score. Anything above that we think is, you know, super elevated. Now, we filtered the data here to show only those companies with more than 50 responses in the ETR survey. Still really crowded. Note that there were around 20 companies above that red 40% mark, which is a very, you know, high number. It's a, it's a crowded market, but lots of companies with, you know, positive momentum. Now let's jump ahead to the most recent October survey and take a look at what, what's happening. Same graphic plotting, spending momentum, and market presence, and look at the number of companies above that red line and how it's been squashed. It's really compressing, it's still a crowded market, it's still, you know, plenty of green, but the number of companies above 40% that, that key mark has gone from around 20 firms down to about five or six. And it speaks to that compression and IT spending, and of course the elongated sales cycles pushing deals out, taking them in smaller chunks. I can't tell you how many conversations with customers I had, at last week at Reinvent underscoring this exact same trend. The buyers are getting pressure from their CFOs to slow things down, do more with less and, and, and prioritize projects to those that absolutely are critical to driving revenue or cutting costs. And that's rippling through all sectors, including cyber. Now, let's do a bit more playing around with the ETR data and take a look at those companies with more than a hundred citations in the survey this quarter. So N, greater than or equal to a hundred. Now remember the followers of Breaking Analysis know that each quarter we take a look at those, what we call four star security firms. That is, those are the, that are in, that hit the top 10 for both spending momentum, net score, and the N, the mentions in the survey, the presence, the pervasiveness in the survey, and that's what we show here. The left most chart is sorted by spending momentum or net score, and the right hand chart by shared N, or the number of mentions in the survey, that pervasiveness metric. that solid red line denotes the cutoff point at the top 10. And you'll note we've actually cut it off at 11 to account for Auth 0, which is now part of Okta, and is going through a go to market transition, you know, with the company, they're kind of restructuring sales so they can take advantage of that. So starting on the left with spending momentum, again, net score, Microsoft leads all vendors, typical Microsoft, very prominent, although it hadn't always done so, it, for a while, CrowdStrike and Okta were, were taking the top spot, now it's Microsoft. CrowdStrike, still always near the top, but note that CyberArk and Cloudflare have cracked the top five in Okta, which as I just said was consistently at the top, has dropped well off its previous highs. You'll notice that Palo Alto Network Palo Alto Networks with a 38% net score, just below that magic 40% number, is healthy, especially as you look over to the right hand chart. Take a look at Palo Alto with an N of 395. It is the largest of the independent pure play security firms, and has a very healthy net score, although one caution is that net score has dropped considerably since the beginning of the year, which is the case for most of the top 10 names. The only exception is Fortinet, they're the only ones that saw an increase since January in spending momentum as ETR measures it. Now this brings us to the four star security firms, that is those that hit the top 10 in both net score on the left hand side and market presence on the right hand side. So it's Microsoft, Palo Alto, CrowdStrike, Okta, still there even not accounting for a Auth 0, just Okta on its own. If you put in Auth 0, it's, it's even stronger. Adding then in Fortinet and Zscaler. So Microsoft, Palo Alto, CrowdStrike, Okta, Fortinet, and Zscaler. And as we've mentioned since January, only Fortinet has shown an increase in net score since, since that time, again, since the January survey. Now again, this talks to the compression in spending. Now one of the big themes we hear constantly in cybersecurity is the market is overcrowded. Everybody talks about that, me included. The implication there, is there's a lot of room for consolidation and that consolidation can come in the form of M&A, or it can come in the form of people consolidating onto a single platform, and retiring some other vendors, and getting rid of duplicate vendors. We're hearing that as a big theme as well. Now, as we saw in the previous, previous chart, this is a very crowded market and we've seen lots of consolidation in 2022, in the form of M&A. Literally hundreds of M&A deals, with some of the largest companies going private. SailPoint, KnowBe4, Barracuda, Mandiant, Fedora, these are multi billion dollar acquisitions, or at least billion dollars and up, and many of them multi-billion, for these companies, and hundreds more acquisitions in the cyberspace, now less you think the pond is overfished, here's a chart from ETR of emerging tech companies in the cyber security industry. This data comes from ETR's Emerging Technologies Survey, ETS, which is this diamond in a rough that I found a couple quarters ago, and it's ripe with companies that are candidates for M&A. Many would've liked, many of these companies would've liked to, gotten to the public markets during the pandemic, but they, you know, couldn't get there. They weren't ready. So the graph, you know, similar to the previous one, but different, it shows net sentiment on the vertical axis and that's a measurement of, of, of intent to adopt against a mind share on the X axis, which measures, measures the awareness of the vendor in the community. So this is specifically a survey that ETR goes out and, and, and fields only to track those emerging tech companies that are private companies. Now, some of the standouts in Mindshare, are OneTrust, BeyondTrust, Tanium and Endpoint, Net Scope, which we've talked about in previous Breaking Analysis. 1Password, which has been acquisitive on its own. In identity, the managed security service provider, Arctic Wolf Network, a company we've also covered, we've had their CEO on. We've talked about MSSPs as a real trend, particularly in small and medium sized business, we'll come back to that, Sneek, you know, kind of high flyer in both app security and containers, and you can just see the number of companies in the space this huge and it just keeps growing. Now, just to make it a bit easier on the eyes we filtered the data on these companies with with those, and isolated on those with more than a hundred responses only within the survey. And that's what we show here. Some of the names that we just mentioned are a bit easier to see, but these are the ones that really stand out in ERT, ETS, survey of private companies, OneTrust, BeyondTrust, Taniam, Netscope, which is in Cloud, 1Password, Arctic Wolf, Sneek, BitSight, SecurityScorecard, HackerOne, Code42, and Exabeam, and Sim. All of these hit the ETS survey with more than a hundred responses by, by the IT practitioners. Okay, so these firms, you know, maybe they do some M&A on their own. We've seen that with Sneek, as I said, with 1Password has been inquisitive, as have others. Now these companies with the larger footprint, these private companies, will likely be candidate for both buying companies and eventually going public when the markets settle down a bit. So again, no shortage of players to affect consolidation, both buyers and sellers. Okay, so let's finish with some key questions that we're watching. CrowdStrike in particular on its earnings calls cited softness from smaller buyers. Is that because these smaller buyers have stopped adopting? If so, are they more at risk, or are they tactically moving toward the easy button, aka, Microsoft's good enough approach. What does that mean for the market if smaller company cohorts continue to soften? How about MSSPs? Will companies continue to outsource, or pause on on that, as well as try to free up, to try to free up some budget? Adam Celiski at Reinvent last week said, "If you want to save money the Cloud's the best place to do it." Is the cloud the best place to save money in cyber? Well, it would seem that way from the standpoint of controlling budgets with lots of, lots of optionality. You could dial up and dial down services, you know, or does the Cloud add another layer of complexity that has to be understood and managed by Devs, for example? Now, consolidation should favor the likes of Palo Alto and CrowdStrike, cause they're platform players, and some of the larger players as well, like Cisco, how about IBM and of course Microsoft. Will that happen? And how will economic uncertainty impact the risk equation, a particular concern is increase of tax on vulnerable sectors of the population, like the elderly. How will companies and governments protect them from scams? And finally, how many cybersecurity companies can actually remain independent in the slingshot economy? In so many ways the market is still strong, it's just that expectations got ahead of themselves, and now as earnings forecast come, come, come down and come down to earth, it's going to basically come down to who can execute, generate cash, and keep enough runway to get through the knothole. And the one certainty is nobody really knows how tight that knothole really is. All right, let's call it a wrap. Next week we dive deeper into Palo Alto Networks, and take a look at how and why that company has held up so well and what to expect at Ignite, Palo Alto's big user conference coming up later this month in Las Vegas. We'll be there with theCube. Okay, many thanks to Alex Myerson on production and manages the podcast, Ken Schiffman as well, as our newest edition to our Boston studio. Great to have you Ken. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our EIC over at Silicon Angle. He does some great editing for us. Thank you to all. Remember these episodes are all available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibond.com and siliconangle.com, or you can email me directly David.vellante@siliconangle.com or DM me @DVellante, or comment on our LinkedIn posts. Please do checkout etr.ai, they got the best survey data in the enterprise tech business. This is Dave Vellante for theCube Insights powered by ETR. Thanks for watching, and we'll see you next time on Breaking Analysis. (upbeat music)

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

(contemplative upbeat music) >> Hello and welcome to this CUBE Conversation. I'm John Furrier, your host of theCUBE, here in Palo Alto, California. Got a great topic on expanding capabilities for urgent computing. Dan Stanzione, he's Executive Director of TACC, the Texas Advanced Computing Center, and Rajesh Pohani, VP of PowerEdge, HPC Core Compute at Dell Technologies. Gentlemen, welcome to this CUBE Conversation. >> Thanks, John. >> Thanks, John, good to be here. >> Rajesh, you got a lot of computing in PowerEdge, HPC, Core Computing. I mean, I get a sense that you love compute, so we'll jump right into it. And of course, I got to love TACC, Texas Advanced Computing Center. I can imagine a lot of stuff going on there. Let's start with TACC. What is the Texas Advanced Computing Center? Tell us a little bit about that. >> Yeah, we're part of the University of Texas at Austin here, and we build large-scale supercomputers, data systems, AI systems, to support open science research. And we're mainly funded by the National Science Foundation, so we support research projects in all fields of science, all around the country and around the world. Actually, several thousand projects at the moment. >> But tied to the university, got a lot of gear, got a lot of compute, got a lot of cool stuff going on. What's the coolest thing you got going on right now? >> Well, for me, it's always the next machine, but I think science-wise, it's the machines we have. We just finished deploying Lonestar6, which is our latest supercomputer, in conjunction with Dell. A little over 600 nodes of those PowerEdge servers that Rajesh builds for us. Which makes more than 20,000 that we've had here over the years, of those boxes. But that one just went into production. We're designing new systems for a few years from now, where we'll be even larger. Our Frontera system was top five in the world two years ago, just fell out of the top 10. So we've got to fix that and build the new top-10 system sometime soon. We always have a ton going on in large-scale computing. >> Well, I want to get to the Lonestar6 in a minute, on the next talk track, but... What are some of the areas that you guys are working on that are making an impact? Take us through, and we talked before we came on camera about, obviously, the academic affiliation, but also there's a real societal impact of the work you're doing. What are some of the key areas that the TACC is making an impact? >> So there's really a huge range from new microprocessors, new materials design, photovoltaics, climate modeling, basic science and astrophysics, and quantum mechanics, and things like that. But I think the nearest-term impacts that people see are what we call urgent computing, which is one of the drivers around Lonestar and some other recent expansions that we've done. And that's things like, there's a hurricane coming, exactly where is it going to land? Can we refine the area where there's going to be either high winds or storm surge? Can we assess the damage from digital imagery afterwards? Can we direct first responders in the optimal routes? Similarly for earthquakes, and a lot recently, as you might imagine, around COVID. In 2020, we moved almost a third of our resources to doing COVID work, full-time. >> Rajesh, I want to get your thoughts on this, because Dave Vellante and I have been talking about this on theCUBE recently, a lot. Obviously, people see what cloud's, going on with the cloud technology, but compute and on-premises, private cloud's been growing. If you look at the hyperscale on-premises and the edge, if you include that in, you're seeing a lot more user consumption on-premises, and now, with 5G, you got edge, you mentioned first responders, Dan. This is now pointing to a new architectural shift. As the VP of PowerEdge and HPC and Core Compute, you got to look at this and go, "Hmm." If Compute's going to be everywhere, and in locations, you got to have that compute. How does that all work together? And how do you do advanced computing, when you have these urgent needs, as well as real-time in a new architecture? >> Yeah, John, I mean, it's a pretty interesting time when you think about some of the changing dynamics and how customers are utilizing Compute in the compute needs in the industry. Seeing a couple of big trends. One, the distribution of Compute outside of the data center, 5G is really accelerating that, and then you're generating so much data, whether what you do with it, the insights that come out of it, that we're seeing more and more push to AI, ML, inside the data center. Dan mentioned what he's doing at TACC with computational analysis and some of the work that they're doing. So what you're seeing is, now, this push that data in the data center and what you do with it, while data is being created out at the edge. And it's actually this interesting dichotomy that we're beginning to see. Dan mentioned some of the work that they're doing in medical and on COVID research. Even at Dell, we're making cycles available for COVID research using our Zenith cluster, that's located in our HPC and AI Innovation Lab. And we continue to partner with organizations like TACC and others on research activities to continue to learn about the virus, how it mutates, and then how you treat it. So if you think about all the things, and data that's getting created, you're seeing that distribution and it's really leading to some really cool innovations going forward. >> Yeah, I want to get to that COVID research, but first, you mentioned a few words I want to get out there. You mentioned Lonestar6. Okay, so first, what is Lonestar6, then we'll get into the system aspect of it. Take us through what that definition is, what is Lonestar6? >> Well, as Dan mentioned, Lonestar6 is a Dell technology system that we developed with TACC, it's located at the University of Texas at Austin. It consists of more than 800 Dell PowerEdge 6525 servers that are powered with 3rd Generation AMD EPYC processors. And just to give you an example of the scale of this cluster, it could perform roughly three quadrillion operations per second. That's three petaFLOPS, and to match what Lonestar6 can compute in one second, a person would have to do one calculation every second for a hundred million years. So it's quite a good-size system, and quite a powerful one as well. >> Dan, what's the role that the system plays, you've got petaFLOPS, what, three petaFLOPS, you mentioned? That's a lot of FLOPS! So obviously urgent computing, what's cranking through the system there? Take us through, what's it like? >> Sure, well, there there's a mix of workloads on it, and on all our systems. So there's the urgent computing work, right? Fast turnaround, near real-time, whether it's COVID research, or doing... Project now where we bring in MRI data and are doing sort of patient-specific dosing for radiation treatments and chemotherapy, tailored to your tumor, instead of just the sort of general for people your size. That all requires sort of real-time turnaround. There's a lot AI research going on now, we're incorporating AI in traditional science and engineering research. And that uses an awful lot of data, but also consumes a huge amount of cycles in training those models. And then there's all of our traditional, simulation-based workloads and materials and digital twins for aircraft and aircraft design, and more efficient combustion in more efficient photovoltaic materials, or photovoltaic materials without using as much lead, and things like that. And I'm sure I'm missing dozens of other topics, 'cause, like I said, that one really runs every field of science. We've really focused the Lonestar line of systems, and this is obviously the sixth one we built, around our sort of Texas-centric users. It's the UT Austin users, and then with contributions from Texas A&M , and Texas Tech and the University of Texas system, MD Anderson Healthcare Center, the University of North Texas. So users all around the state, and every research problem that you might imagine, those are into. We're just ramping up a project in disaster information systems, that's looking at the probabilities of flooding in coastal Texas and doing... Can we make building code changes to mitigate impact? Do we have to change the standard foundation heights for new construction, to mitigate the increasing storm surges from these sort of slow storms that sit there and rain, like hurricanes didn't used to, but seem to be doing more and more. All those problems will run on Lonestar, and on all the systems to come, yeah. >> It's interesting, you mentioned urgent computing, I love that term because it could be an event, it could be some slow kind of brewing event like that rain example you mentioned. It could also be, obviously, with the healthcare, and you mentioned COVID earlier. These are urgent, societal challenges, and having that available, the processing capability, the compute, the data. You mentioned digital twins. I can imagine all this new goodness coming from that. Compare that, where we were 10 years ago. I mean, just from a mind-blowing standpoint, you have, have come so far, take us through, try to give a context to the level of where we are now, to do this kind of work, and where we were years ago. Can you give us a feel for that? >> Sure, there's a lot of ways to look at that, and how the technology's changed, how we operate around those things, and then sort of what our capabilities are. I think one of the big, first, urgent computing things for us, where we sort of realized we had to adapt to this model of computing was about 15 years ago with the big BP Gulf Oil spill. And suddenly, we were dumping thousands of processors of load to figure out where that oil spill was going to go, and how to do mitigation, and what the potential impacts were, and where you need to put your containment, and things like that. And it was, well, at that point we thought of it as sort of a rare event. There was another one, that I think was the first real urgent computing one, where the space shuttle was in orbit, and they knew something had hit it during takeoff. And we were modeling, along with NASA and a bunch of supercomputers around the world, the heat shield and could they make reentry safely? You have until they come back to get that problem done, you don't have months or years to really investigate that. And so, what we've sort of learned through some of those, the Japanese tsunami was another one, there have been so many over the years, is that one, these sort of disasters are all the time, right? One thing or another, right? If we're not doing hurricanes, we're doing wildfires and drought threat, if it's not COVID. We got good and ready for COVID through SARS and through the swine flu and through HIV work, and things like that. So it's that we can do the computing very fast, but you need to know how to do the work, right? So we've spent a lot of time, not only being able to deliver the computing quickly, but having the data in place, and having the code in place, and having people who know the methods who know how to use big computers, right? That's been a lot of what the COVID Consortium, the White House COVID Consortium, has been about over the last few years. And we're actually trying to modify that nationally into a strategic computing reserve, where we're ready to go after these problems, where we've run drills, right? And if there's a, there's a train that derails, and there's a chemical spill, and it's near a major city, we have the tools and the data in place to do wind modeling, and we have the terrain ready to go. And all those sorts of things that you need to have to be ready. So we've really sort of changed our sort of preparedness and operational model around urgent computing in the last 10 years. Also, just the way we scheduled the system, the ability to sort of segregate between these long-running workflows for things that are really important, like we displaced a lot of cancer research to do COVID research. And cancer's still important, but it's less likely that we're going to make an impact in the next two months, right? So we have to shuffle how we operate things and then just, having all that additional capacity. And I think one of the things that's really changed in the models is our ability to use AI, to sort of adroitly steer our simulations, or prune the space when we're searching parameters for simulations. So we have the operational changes, the system changes, and then things like adding AI on the scientific side, since we have the capacity to do that kind of things now, all feed into our sort of preparedness for this kind of stuff. >> Dan, you got me sold, I want to come work with you. Come on, can I join the team over there? It sounds exciting. >> Come on down! We always need good folks around here, so. (laughs) >> Rajesh, when I- >> Almost 200 now, and we're always growing. >> Rajesh, when I hear the stories about kind of the evolution, kind of where the state of the art is, you almost see the innovation trajectory, right? The growth and the learning, adding machine learning only extends out more capabilities. But also, Dan's kind of pointing out this kind of response, rapid compute engine, that they could actually deploy with learnings, and then software, so is this a model where anyone can call up and get some cycles to, say, power an autonomous vehicle, or, hey, I want to point the machinery and the cycles at something? Is the service, do you guys see this going that direction, or... Because this sounds really, really good. >> Yeah, I mean, one thing that Dan talked about was, it's not just the compute, it's also having the right algorithms, the software, the code, right? The ability to learn. So I think when those are set up, yeah. I mean, the ability to digitally simulate in any number of industries and areas, advances the pace of innovation, reduces the time to market of whatever a customer is trying to do or research, or even vaccines or other healthcare things. If you can reduce that time through the leverage of compute on doing digital simulations, it just makes things better for society or for whatever it is that we're trying to do, in a particular industry. >> I think the idea of instrumenting stuff is here forever, and also simulations, whether it's digital twins, and doing these kinds of real-time models. Isn't really much of a guess, so I think this is a huge, historic moment. But you guys are pushing the envelope here, at University of Texas and at TACC. It's not just research, you guys got real examples. So where do you guys see this going next? I see space, big compute areas that might need some data to be cranked out. You got cybersecurity, you got healthcare, you mentioned oil spill, you got oil and gas, I mean, you got industry, you got climate change. I mean, there's so much to tackle. What's next? >> Absolutely, and I think, the appetite for computing cycles isn't going anywhere, right? And it's only going to, it's going to grow without bound, essentially. And AI, while in some ways it reduces the amount of computing we do, it's also brought this whole new domain of modeling to a bunch of fields that weren't traditionally computational, right? We used to just do engineering, physics, chemistry, were all super computational, but then we got into genome sequencers and imaging and a whole bunch of data, and that made biology computational. And with AI, now we're making things like the behavior of human society and things, computational problems, right? So there's this sort of growing amount of workload that is, in one way or another, computational, and getting bigger and bigger. So that's going to keep on growing. I think the trick is not only going to be growing the computation, but growing the software and the people along with it, because we have amazing capabilities that we can bring to bear. We don't have enough people to hit all of them at once. And so, that's probably going to be the next frontier in growing out both our AI and simulation capability, is the human element of it. >> It's interesting, when you think about society, right? If the things become too predictable, what does a democracy even look like? If you know the election's going to be over two years from now in the United States, or you look at these major, major waves >> Human companies don't know. >> of innovation, you say, "Hmm." So it's democracy, AI, maybe there's an algorithm for checking up on the AI 'cause biases... So, again, there's so many use cases that just come out of this. It's incredible. >> Yeah, and bias in AI is something that we worry about and we work on, and on task forces where we're working on that particular problem, because the AI is going to take... Is based on... Especially when you look at a deep learning model, it's 100% a product of the data you show it, right? So if you show it a biased data set, it's going to have biased results. And it's not anything intrinsic about the computer or the personality, the AI, it's just data mining, right? In essence, right, it's learning from data. And if you show it all images of one particular outcome, it's going to assume that's always the outcome, right? It just has no choice, but to see that. So how we deal with bias, how do we deal with confirmation, right? I mean, in addition, you have to recognize, if you haven't, if it gets data it's never seen before, how do you know it's not wrong, right? So there's about data quality and quality assurance and quality checking around AI. And that's where, especially in scientific research, we use what's starting to be called things like physics-informed or physics-constrained AI, where the neural net that you're using to design an aircraft still has to follow basic physical laws in its output, right? Or if you're doing some materials or astrophysics, you still have to obey conservation of mass, right? So I can't say, well, if you just apply negative mass on this other side and positive mass on this side, everything works out right for stable flight. 'Cause we can't do negative mass, right? So you have to constrain it in the real world. So this notion of how we bring in the laws of physics and constrain your AI to what's possible is also a big part of the sort of AI research going forward. >> You know, Dan, you just, to me just encapsulate the science that's still out there, that's needed. Computer science, social science, material science, kind of all converging right now. >> Yeah, engineering, yeah, >> Engineering, science, >> slipstreams, >> it's all there, >> physics, yeah, mmhmm. >> it's not just code. And, Rajesh, data. You mentioned data, the more data you have, the better the AI. We have a world what's going from silos to open control planes. We have to get to a world. This is a cultural shift we're seeing, what's your thoughts? >> Well, it is, in that, the ability to drive predictive analysis based on the data is going to drive different behaviors, right? Different social behaviors for cultural impacts. But I think the point that Dan made about bias, right, it's only as good as the code that's written and the way that the data is actually brought into the system. So making sure that that is done in a way that generates the right kind of outcome, that allows you to use that in a predictive manner, becomes critically important. If it is biased, you're going to lose credibility in a lot of that analysis that comes out of it. So I think that becomes critically important, but overall, I mean, if you think about the way compute is, it's becoming pervasive. It's not just in selected industries as damage, and it's now applying to everything that you do, right? Whether it is getting you more tailored recommendations for your purchasing, right? You have better options that way. You don't have to sift through a lot of different ideas that, as you scroll online. It's tailoring now to some of your habits and what you're looking for. So that becomes an incredible time-saver for people to be able to get what they want in a way that they want it. And then you look at the way it impacts other industries and development innovation, and it just continues to scale and scale and scale. >> Well, I think the work that you guys are doing together is scratching the surface of the future, which is digital business. It's about data, it's about out all these new things. It's about advanced computing meets the right algorithms for the right purpose. And it's a really amazing operation you guys got over there. Dan, great to hear the stories. It's very provocative, very enticing to just want to jump in and hang out. But I got to do theCUBE day job here, but congratulations on success. Rajesh, great to see you and thanks for coming on theCUBE. >> Thanks for having us, John. >> Okay. >> Thanks very much. >> Great conversation around urgent computing, as computing becomes so much more important, bigger problems and opportunities are around the corner. And this is theCUBE, we're documenting it all here. I'm John Furrier, your host. Thanks for watching. (contemplative music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> The pandemic has changed the way we think about and predict the future. As we enter the third year of a global pandemic, we see the significant impact that it's had on technology strategy, spending patterns, and company fortunes Much has changed. And while many of these changes were forced reactions to a new abnormal, the trends that we've seen over the past 24 months have become more entrenched, and point to the way that's coming ahead in the technology business. Hello and welcome to this week's Wikibon CUBE Insights powered by ETR. In this Breaking Analysis, we welcome our partner and colleague and business friend, Erik Porter Bradley, as we deliver what's becoming an annual tradition for Erik and me, our predictions for Enterprise Technology in 2022 and beyond Erik, welcome. Thanks for taking some time out. >> Thank you, Dave. Luckily we did pretty well last year, so we were able to do this again. So hopefully we can keep that momentum going. >> Yeah, you know, I want to mention that, you know, we get a lot of inbound predictions from companies and PR firms that help shape our thinking. But one of the main objectives that we have is we try to make predictions that can be measured. That's why we use a lot of data. Now not all will necessarily fit that parameter, but if you've seen the grading of our 2021 predictions that Erik and I did, you'll see we do a pretty good job of trying to put forth prognostications that can be declared correct or not, you know, as black and white as possible. Now let's get right into it. Our first prediction, we're going to go run into spending, something that ETR surveys for quarterly. And we've reported extensively on this. We're calling for tech spending to increase somewhere around 8% in 2022, we can see there on the slide, Erik, we predicted spending last year would increase by 4% IDC. Last check was came in at five and a half percent. Gardner was somewhat higher, but in general, you know, not too bad, but looking ahead, we're seeing an acceleration from the ETR September surveys, as you can see in the yellow versus the blue bar in this chart, many of the SMBs that were hard hit by the pandemic are picking up spending again. And the ETR data is showing acceleration above the mean for industries like energy, utilities, retail, and services, and also, notably, in the Forbes largest 225 private companies. These are companies like Mars or Koch industries. They're predicting well above average spending for 2022. So Erik, please weigh in here. >> Yeah, a lot to bring up on this one, I'm going to be quick. So 1200 respondents on this, over a third of which were at the C-suite level. So really good data that we brought in, the usual bucket of, you know, fortune 500, global 2000 make up the meat of that median, but it's 8.3% and rising with momentum as we see. What's really interesting right now is that energy and utilities. This is usually like, you know, an orphan stock dividend type of play. You don't see them at the highest point of tech spending. And the reason why right now is really because this state of tech infrastructure in our energy infrastructure needs help. And it's obvious, remember the Florida municipality break reach last year? When they took over the water systems or they had the ability to? And this is a real issue, you know, there's bad nation state actors out there, and I'm no alarmist, but the energy and utility has to spend this money to keep up. It's really important. And then you also hit on the retail consumer. Obviously what's happened, the work from home shift created a shop from home shift, and the trends that are happening right now in retail. If you don't spend and keep up, you're not going to be around much longer. So I think the really two interesting things here to call out are energy utilities, usually a laggard in IT spend and it's leading, and also retail consumer, a lot of changes happening. >> Yeah. Great stuff. I mean, I recall when we entered the pandemic, really ETR was the first to emphasize the impact that work from home was going to have, so I really put a lot of weight on this data. Okay. Our next prediction is we're going to get into security, it's one of our favorite topics. And that is that the number one priority that needs to be addressed by organizations in 2022 is security and you can see, in this slide, the degree to which security is top of mind, relative to some other pretty important areas like cloud, productivity, data, and automation, and some others. Now people may say, "Oh, this is obvious." But I'm going to add some context here, Erik, and then bring you in. First, organizations, they don't have unlimited budgets. And there are a lot of competing priorities for dollars, especially with the digital transformation mandate. And depending on the size of the company, this data will vary. For example, while security is still number one at the largest public companies, and those are of course of the biggest spenders, it's not nearly as pronounced as it is on average, or in, for example, mid-sized companies and government agencies. And this is because midsized companies or smaller companies, they don't have the resources that larger companies do. Larger companies have done a better job of securing their infrastructure. So these mid-size firms are playing catch up and the data suggests cyber is even a bigger priority there, gaps that they have to fill, you know, going forward. And that's why we think there's going to be more demand for MSSPs, managed security service providers. And we may even see some IPO action there. And then of course, Erik, you and I have talked about events like the SolarWinds Hack, there's more ransomware attacks, other vulnerabilities. Just recently, like Log4j in December. All of this has heightened concerns. Now I want to talk a little bit more about how we measure this, you know, relatively, okay, it's an obvious prediction, but let's stick our necks out a little bit. And so in addition to the rise of managed security services, we're calling for M&A and/or IPOs, we've specified some names here on this chart, and we're also pointing to the digital supply chain as an area of emphasis. Again, Log4j really shone that under a light. And this is going to help the likes of Auth0, which is now Okta, SailPoint, which is called out on this chart, and some others. We're calling some winners in end point security. Erik, you're going to talk about sort of that lifecycle, that transformation that we're seeing, that migration to new endpoint technologies that are going to benefit from this reset refresh cycle. So Erik, weigh in here, let's talk about some of the elements of this prediction and some of the names on that chart. >> Yeah, certainly. I'm going to start right with Log4j top of mind. And the reason why is because we're seeing a real paradigm shift here where things are no longer being attacked at the network layer, they're being attacked at the application layer, and in the application stack itself. And that is a huge shift left. And that's taking in DevSecOps now as a real priority in 2022. That's a real paradigm shift over the last 20 years. That's not where attacks used to come from. And this is going to have a lot of changes. You called out a bunch of names in there that are, they're either going to work. I would add to that list Wiz. I would add Orca Security. Two names in our emerging technology study, in addition to the ones you added that are involved in cloud security and container security. These names are either going to get gobbled up. So the traditional legacy names are going to have to start writing checks and, you know, legacy is not fair, but they're in the data center, right? They're, on-prem, they're not cloud native. So these are the names that money is going to be flowing to. So they're either going to get gobbled up, or we're going to see some IPO's. And on the other thing I want to talk about too, is what you mentioned. We have CrowdStrike on that list, We have SentinalOne on the list. Everyone knows them. Our data was so strong on Tanium that we actually went positive for the first time just today, just this morning, where that was released. The trifecta of these are so important because of what you mentioned, under resourcing. We can't have security just tell us when something happens, it has to automate, and it has to respond. So in this next generation of EDR and XDR, an automated response has to happen because people are under-resourced, salaries are really high, there's a skill shortage out there. Security has to become responsive. It can't just monitor anymore. >> Yeah. Great. And we should call out too. So we named some names, Snyk, Aqua, Arctic Wolf, Lacework, Netskope, Illumio. These are all sort of IPO, or possibly even M&A candidates. All right. Our next prediction goes right to the way we work. Again, something that ETR has been on for awhile. We're calling for a major rethink in remote work for 2022. We had predicted last year that by the end of 2021, there'd be a larger return to the office with the norm being around a third of workers permanently remote. And of course the variants changed that equation and, you know, gave more time for people to think about this idea of hybrid work and that's really come in to focus. So we're predicting that is going to overtake fully remote as the dominant work model with only about a third of the workers back in the office full-time. And Erik, we expect a somewhat lower percentage to be fully remote. It's now sort of dipped under 30%, at around 29%, but it's still significantly higher than the historical average of around 15 to 16%. So still a major change, but this idea of hybrid and getting hybrid right, has really come into focus. Hasn't it? >> Yeah. It's here to stay. There's no doubt about it. We started this in March of 2020, as soon as the virus hit. This is the 10th iteration of the survey. No one, no one ever thought we'd see a number where only 34% of people were going to be in office permanently. That's a permanent number. They're expecting only a third of the workers to ever come back fully in office. And against that, there's 63% that are saying their permanent workforce is going to be either fully remote or hybrid. And this, I can't really explain how big of a paradigm shift this is. Since the start of the industrial revolution, people leave their house and go to work. Now they're saying that's not going to happen. The economic impact here is so broad, on so many different areas And, you know, the reason is like, why not? Right? The productivity increase is real. We're seeing the productivity increase. Enterprises are spending on collaboration tools, productivity tools, We're seeing an increased perception in productivity of their workforce. And the CFOs can cut down an expense item. I just don't see a reason why this would end, you know, I think it's going to continue. And I also want to point out these results, as high as they are, were before the Omicron wave hit us. I can only imagine what these results would have been if we had sent the survey out just two or three weeks later. >> Yeah. That's a great point. Okay. Next prediction, we're going to look at the supply chain, specifically in how it's affecting some of the hardware spending and cloud strategies in the future. So in this chart, ETRS buyers, have you experienced problems procuring hardware as a result of supply chain issues? And, you know, despite the fact that some companies are, you know, I would call out Dell, for example, doing really well in terms of delivering, you can see that in the numbers, it's pretty clear, there's been an impact. And that's not not an across the board, you know, thing where vendors are able to deliver, especially acute in PCs, but also pronounced in networking, also in firewall servers and storage. And what's interesting is how companies are responding and reacting. So first, you know, I'm going to call the laptop and PC demand staying well above pre-COVID norms. It had peaked in 2012. Pre-pandemic it kept dropping and dropping and dropping, in terms of, you know, unit volume, where the market was contracting. And we think can continue to grow this year in double digits in 2022. But what's interesting, Erik, is when you survey customers, is despite the difficulty they're having in procuring network hardware, there's as much of a migration away from existing networks to the cloud. You could probably comment on that. Their networks are more fossilized, but when it comes to firewalls and servers and storage, there's a much higher propensity to move to the cloud. 30% of customers that ETR surveyed will replace security appliances with cloud services and 41% and 34% respectively will move to cloud compute and storage in 2022. So cloud's relentless march on traditional on-prem models continues. Erik, what do you make of this data? Please weigh in on this prediction. >> As if we needed another reason to go to the cloud. Right here, here it is yet again. So this was added to the survey by client demand. They were asking about the procurement difficulties, the supply chain issues, and how it was impacting our community. So this is the first time we ran it. And it really was interesting to see, you know, the move there. And storage particularly I found interesting because it correlated with a huge jump that we saw on one of our vendor names, which was Rubrik, had the highest net score that it's ever had. So clearly we're seeing some correlation with some of these names that are there, you know, really well positioned to take storage, to take data into the cloud. So again, you didn't need another reason to, you know, hasten this digital transformation, but here we are, we have it yet again, and I don't see it slowing down anytime soon. >> You know, that's a really good point. I mean, it's not necessarily bad news for the... I mean, obviously you wish that it had no change, would be great, but things, you know, always going to change. So we'll talk about this a little bit later when we get into the Supercloud conversation, but this is an opportunity for people who embrace the cloud. So we'll come back to that. And I want to hang on cloud a bit and share some recent projections that we've made. The next prediction is the big four cloud players are going to surpass 167 billion, an IaaS and PaaS revenue in 2022. We track this. Observers of this program know that we try to create an apples to apples comparison between AWS, Azure, GCP and Alibaba in IaaS and PaaS. So we're calling for 38% revenue growth in 2022, which is astounding for such a massive market. You know, AWS is probably not going to hit a hundred billion dollar run rate, but they're going to be close this year. And we're going to get there by 2023, you know they're going to surpass that. Azure continues to close the gap. Now they're about two thirds of the size of AWS and Google, we think is going to surpass Alibaba and take the number three spot. Erik, anything you'd like to add here? >> Yeah, first of all, just on a sector level, we saw our sector, new survey net score on cloud jumped another 10%. It was already really high at 48. Went up to 53. This train is not slowing down anytime soon. And we even added an edge compute type of player, like CloudFlare into our cloud bucket this year. And it debuted with a net score of almost 60. So this is really an area that's expanding, not just the big three, but everywhere. We even saw Oracle and IBM jump up. So even they're having success, taking some of their on-prem customers and then selling them to their cloud services. This is a massive opportunity and it's not changing anytime soon, it's going to continue. >> And I think the operative word there is opportunity. So, you know, the next prediction is something that we've been having fun with and that's this Supercloud becomes a thing. Now, the reason I say we've been having fun is we put this concept of Supercloud out and it's become a bit of a controversy. First, you know, what the heck's the Supercloud right? It's sort of a buzz-wordy term, but there really is, we believe, a thing here. We think there needs to be a rethinking or at least an evolution of the term multi-cloud. And what we mean is that in our view, you know, multicloud from a vendor perspective was really cloud compatibility. It wasn't marketed that way, but that's what it was. Either a vendor would containerize its legacy stack, shove it into the cloud, or a company, you know, they'd do the work, they'd build a cloud native service on one of the big clouds and they did do it for AWS, and then Azure, and then Google. But there really wasn't much, if any, leverage across clouds. Now from a buyer perspective, we've always said multicloud was a symptom of multi-vendor, meaning I got different workloads, running in different clouds, or I bought a company and they run on Azure, and I do a lot of work on AWS, but generally it wasn't necessarily a prescribed strategy to build value on top of hyperscale infrastructure. There certainly was somewhat of a, you know, reducing lock-in and hedging the risk. But we're talking about something more here. We're talking about building value on top of the hyperscale gift of hundreds of billions of dollars in CapEx. So in addition, we're not just talking about transforming IT, which is what the last 10 years of cloud have been like. And, you know, doing work in the cloud because it's cheaper or simpler or more agile, all of those things. So that's beginning to change. And this chart shows some of the technology vendors that are leaning toward this Supercloud vision, in our view, building on top of the hyperscalers that are highlighted in red. Now, Jerry Chan at Greylock, they wrote a piece called Castles in the Cloud. It got our thinking going, and he and the team at Greylock, they're building out a database of all the cloud services and all the sub-markets in cloud. And that got us thinking that there's a higher level of abstraction coalescing in the market, where there's tight integration of services across clouds, but the underlying complexity is hidden, and there's an identical experience across clouds, and even, in my dreams, on-prem for some platforms, so what's new or new-ish and evolving are things like location independence, you've got to include the edge on that, metadata services to optimize locality of reference and data source awareness, governance, privacy, you know, application independent and dependent, actually, recovery across clouds. So we're seeing this evolve. And in our view, the two biggest things that are new are the technology is evolving, where you're seeing services truly integrate cross-cloud. And the other big change is digital transformation, where there's this new innovation curve developing, and it's not just about making your IT better. It's about SaaS-ifying and automating your entire company workflows. So Supercloud, it's not just a vendor thing to us. It's the evolution of, you know, the, the Marc Andreessen quote, "Every company will be a SaaS company." Every company will deliver capabilities that can be consumed as cloud services. So Erik, the chart shows spending momentum on the y-axis and net score, or presence in the ETR data center, or market share on the x-axis. We've talked about snowflake as the poster child for this concept where the vision is you're in their cloud and sharing data in that safe place. Maybe you could make some comments, you know, what do you think of this Supercloud concept and this change that we're sensing in the market? >> Well, I think you did a great job describing the concept. So maybe I'll support it a little bit on the vendor level and then kind of give examples of the ones that are doing it. You stole the lead there with Snowflake, right? There is no better example than what we've seen with what Snowflake can do. Cross-portability in the cloud, the ability to be able to be, you know, completely agnostic, but then build those services on top. They're better than anything they could offer. And it's not just there. I mean, you mentioned edge compute, that's a whole nother layer where this is coming in. And CloudFlare, the momentum there is out of control. I mean, this is a company that started off just doing CDN and trying to compete with Okta Mite. And now they're giving you a full soup to nuts with security and actual edge compute layer, but it's a fantastic company. What they're doing, it's another great example of what you're seeing here. I'm going to call out HashiCorp as well. They're more of an infrastructure services, a little bit more of an open-source freemium model, but what they're doing as well is completely cloud agnostic. It's dynamic. It doesn't care if you're in a container, it doesn't matter where you are. They recently IPO'd and they're down 25%, but their data looks so good across both of our emerging technology and TISA survey. It's certainly another name that's playing on this. And another one that we mentioned as well is Rubrik. If you need storage, compute, and in the cloud layer and you need to be agnostic to it, they're another one that's really playing in this space. So I think it's a great concept you're bringing up. I think it's one that's here to stay and there's certainly a lot of vendors that fit into what you're describing. >> Excellent. Thank you. All right, let's shift to data. The next prediction, it might be a little tough to measure. Before I said we're trying to be a little black and white here, but it relates to Data Mesh, which is, the ideas behind that term were created by Zhamak Dehghani of ThoughtWorks. And we see Data Mesh is really gaining momentum in 2022, but it's largely going to be, we think, confined to a more narrow scope. Now, the impetus for change in data architecture in many companies really stems from the fact that their Hadoop infrastructure really didn't solve their data problems and they struggle to get more value out of their data investments. Data Mesh prescribes a shift to a decentralized architecture in domain ownership of data and a shift to data product thinking, beyond data for analytics, but data products and services that can be monetized. Now this a very powerful in our view, but they're difficult for organizations to get their heads around and further decentralization creates the need for a self-service platform and federated data governance that can be automated. And not a lot of standards around this. So it's going to take some time. At our power panel a couple of weeks ago on data management, Tony Baer predicted a backlash on Data Mesh. And I don't think it's going to be so much of a backlash, but rather the adoption will be more limited. Most implementations we think are going to use a starting point of AWS and they'll enable domains to access and control their own data lakes. And while that is a very small slice of the Data Mesh vision, I think it's going to be a starting point. And the last thing I'll say is, this is going to take a decade to evolve, but I think it's the right direction. And whether it's a data lake or a data warehouse or a data hub or an S3 bucket, these are really, the concept is, they'll eventually just become nodes on the data mesh that are discoverable and access is governed. And so the idea is that the stranglehold that the data pipeline and process and hyper-specialized roles that they have on data agility is going to evolve. And decentralized architectures and the democratization of data will eventually become a norm for a lot of different use cases. And Erik, I wonder if you'd add anything to this. >> Yeah. There's a lot to add there. The first thing that jumped out to me was that that mention of the word backlash you said, and you said it's not really a backlash, but what it could be is these are new words trying to solve an old problem. And I do think sometimes the industry will notice that right away and maybe that'll be a little pushback. And the problems are what you already mentioned, right? We're trying to get to an area where we can have more assets in our data site, more deliverable, and more usable and relevant to the business. And you mentioned that as self-service with governance laid on top. And that's really what we're trying to get to. Now, there's a lot of ways you can get there. Data fabric is really the technical aspect and data mesh is really more about the people, the process, and the governance, but the two of those need to meet, in order to make that happen. And as far as tools, you know, there's even cataloging names like Informatica that play in this, right? Istio plays in this, Snowflake plays in this. So there's a lot of different tools that will support it. But I think you're right in calling out AWS, right? They have AWS Lake, they have AWS Glue. They have so much that's trying to drive this. But I think the really important thing to keep here is what you said. It's going to be a decade long journey. And by the way, we're on the shoulders of giants a decade ago that have even gotten us to this point to talk about these new words because this has been an ongoing type of issue, but ultimately, no matter which vendors you use, this is going to come down to your data governance plan and the data literacy in your business. This is really about workflows and people as much as it is tools. So, you know, the new term of data mesh is wonderful, but you still have to have the people and the governance and the processes in place to get there. >> Great, thank you for that, Erik. Some great points. All right, for the next prediction, we're going to shine the spotlight on two of our favorite topics, Snowflake and Databricks, and the prediction here is that, of course, Databricks is going to IPO this year, as expected. Everybody sort of expects that. And while, but the prediction really is, well, while these two companies are facing off already in the market, they're also going to compete with each other for M&A, especially as Databricks, you know, after the IPO, you're going to have, you know, more prominence and a war chest. So first, these companies, they're both looking pretty good, the same XY graph with spending velocity and presence and market share on the horizontal axis. And both Snowflake and Databricks are well above that magic 40% red dotted line, the elevated line, to us. And for context, we've included a few other firms. So you can see kind of what a good position these two companies are really in, especially, I mean, Snowflake, wow, it just keeps moving to the right on this horizontal picture, but maintaining the next net score in the Y axis. Amazing. So, but here's the thing, Databricks is using the term Lakehouse implying that it has the best of data lakes and data warehouses. And Snowflake has the vision of the data cloud and data sharing. And Snowflake, they've nailed analytics, and now they're moving into data science in the domain of Databricks. Databricks, on the other hand, has nailed data science and is moving into the domain of Snowflake, in the data warehouse and analytics space. But to really make this seamless, there has to be a semantic layer between these two worlds and they're either going to build it or buy it or both. And there are other areas like data clean rooms and privacy and data prep and governance and machine learning tooling and AI, all that stuff. So the prediction is they'll not only compete in the market, but they'll step up and in their competition for M&A, especially after the Databricks IPO. We've listed some target names here, like Atscale, you know, Iguazio, Infosum, Habu, Immuta, and I'm sure there are many, many others. Erik, you care to comment? >> Yeah. I remember a year ago when we were talking Snowflake when they first came out and you, and I said, "I'm shocked if they don't use this war chest of money" "and start going after more" "because we know Slootman, we have so much respect for him." "We've seen his playbook." And I'm actually a little bit surprised that here we are, at 12 months later, and he hasn't spent that money yet. So I think this prediction's just spot on. To talk a little bit about the data side, Snowflake is in rarefied air. It's all by itself. It is the number one net score in our entire TISA universe. It is absolutely incredible. There's almost no negative intentions. Global 2000 organizations are increasing their spend on it. We maintain our positive outlook. It's really just, you know, stands alone. Databricks, however, also has one of the highest overall net sentiments in the entire universe, not just its area. And this is the first time we're coming up positive on this name as well. It looks like it's not slowing down. Really interesting comment you made though that we normally hear from our end-user commentary in our panels and our interviews. Databricks is really more used for the data science side. The MLAI is where it's best positioned in our survey. So it might still have some catching up to do to really have that caliber of usability that you know Snowflake is seeing right now. That's snowflake having its own marketplace. There's just a lot more to Snowflake right now than there is Databricks. But I do think you're right. These two massive vendors are sort of heading towards a collision course, and it'll be very interesting to see how they deploy their cash. I think Snowflake, with their incredible management and leadership, probably will make the first move. >> Well, I think you're right on that. And by the way, I'll just add, you know, Databricks has basically said, hey, it's going to be easier for us to come from data lakes into data warehouse. I'm not sure I buy that. I think, again, that semantic layer is a missing ingredient. So it's going to be really interesting to see how this plays out. And to your point, you know, Snowflake's got the war chest, they got the momentum, they've got the public presence now since November, 2020. And so, you know, they're probably going to start making some aggressive moves. Anyway, next prediction is something, Erik, that you and I have talked about many, many times, and that is observability. I know it's one of your favorite topics. And we see this world screaming for more consolidation it's going all in on cloud native. These legacy stacks, they're fighting to stay relevant, but the direction is pretty clear. And the same XY graph lays out the players in the field, with some of the new entrants that we've also highlighted, like Observe and Honeycomb and ChaosSearch that we've talked about. Erik, we put a big red target around Splunk because everyone wants their gold. So please give us your thoughts. >> Oh man, I feel like I've been saying negative things about Splunk for too long. I've got a bad rap on this name. The Splunk shareholders come after me all the time. Listen, it really comes down to this. They're a fantastic company that was designed to do logging and monitoring and had some great tool sets around what you could do with it. But they were designed for the data center. They were designed for prem. The world we're in now is so dynamic. Everything I hear from our end user community is that all net new workloads will be going to cloud native players. It's that simple. So Splunk has entrenched. It's going to continue doing what it's doing and it does it really, really well. But if you're doing something new, the new workloads are going to be in a dynamic environment and that's going to go to the cloud native players. And in our data, it is extremely clear that that means Datadog and Elastic. They are by far number one and two in net score, increase rates, adoption rates. It's not even close. Even New Relic actually is starting to, you know, entrench itself really well. We saw New Relic's adoption's going up, which is super important because they went to that freemium model, you know, to try to get their little bit of an entrenched customer base and that's working as well. And then you made a great list here, of all the new entrants, but it goes beyond this. There's so many more. In our emerging technology survey, we're seeing Century, Catchpoint, Securonix, Lucid Works. There are so many options in this space. And let's not forget, the biggest data that we're seeing is with Grafana. And Grafana labs as yet to turn on their enterprise. Elastic did it, why can't Grafana labs do it? They have an enterprise stack. So when you look at how crowded this space is, there has to be consolidation. I recently hosted a panel and every single guy on that panel said, "Please give me a consolidation." Because they're the end users trying to actually deploy these and it's getting a little bit confusing. >> Great. Thank you for that. Okay. Last prediction. Erik, might be a little out of your wheelhouse, but you know, you might have some thoughts on it. And that's a hybrid events become the new digital model and a new category in 2022. You got these pure play digital or virtual events. They're going to take a back seat to in-person hybrids. The virtual experience will eventually give way to metaverse experiences and that's going to take some time, but the physical hybrid is going to drive it. And metaverse is ultimately going to define the virtual experience because the virtual experience today is not great. Nobody likes virtual. And hybrid is going to become the business model. Today's pure virtual experience has to evolve, you know, theCUBE first delivered hybrid mid last decade, but nobody really wanted it. We did Mobile World Congress last summer in Barcelona in an amazing hybrid model, which we're showing in some of the pictures here. Alex, if you don't mind bringing that back up. And every physical event that we're we're doing now has a hybrid and virtual component, including the pre-records. You can see in our studios, you see that the green screen. I don't know. Erik, what do you think about, you know, the Zoom fatigue and all this. I know you host regular events with your round tables, but what are your thoughts? >> Well, first of all, I think you and your company here have just done an amazing job on this. So that's really your expertise. I spent 20 years of my career hosting intimate wall street idea dinners. So I'm better at navigating a wine list than I am navigating a conference floor. But I will say that, you know, the trend just goes along with what we saw. If 35% are going to be fully remote. If 70% are going to be hybrid, then our events are going to be as well. I used to host round table dinners on, you know, one or two nights a week. Now those have gone virtual. They're now panels. They're now one-on-one interviews. You know, we do chats. We do submitted questions. We do what we can, but there's no reason that this is going to change anytime soon. I think you're spot on here. >> Yeah. Great. All right. So there you have it, Erik and I, Listen, we always love the feedback. Love to know what you think. Thank you, Erik, for your partnership, your collaboration, and love doing these predictions with you. >> Yeah. I always enjoy them too. And I'm actually happy. Last year you made us do a baker's dozen, so thanks for keeping it to 10 this year. >> (laughs) We've got a lot to say. I know, you know, we cut out. We didn't do much on crypto. We didn't really talk about SaaS. I mean, I got some thoughts there. We didn't really do much on containers and AI. >> You want to keep going? I've got another 10 for you. >> RPA...All right, we'll have you back and then let's do that. All right. All right. Don't forget, these episodes are all available as podcasts, wherever you listen, all you can do is search Breaking Analysis podcast. Check out ETR's website at etr.plus, they've got a new website out. It's the best data in the industry, and we publish a full report every week on wikibon.com and siliconangle.com. You can always reach out on email, David.Vellante@siliconangle.com I'm @DVellante on Twitter. Comment on our LinkedIn posts. This is Dave Vellante for the Cube Insights powered by ETR. Have a great week, stay safe, be well. And we'll see you next time. (mellow music)

(upbeat music) >> Welcome everyone to this CUBE coverage of AWS re:Invent 2021. We have a lot going on at this year's re:Invent with over 100 guests on the program, and I'm excited to welcome two of those guests here with me right now. We are joined by Ralph Munsen, the Chief Information Officer at Warner Music Group and Atif Khan, the CTO of Alkira and founder of Alkira as well. Gentlemen, welcome to the program. >> Thank you so much, Lisa. So glad to be here with you. >> Good to be here. >> Yeah. Good old fashioned Zoom is become our best friend in the last 22 months or so I'm losing count. Atif, I'd like to start with you. I know Alkira has been on the key before, but it's been a while and you guys are a relatively young company. Give the audience an overview of Alkira and what it is that you deliver. >> Absolutely, Lisa. So we started back in may of 2018, and the Cloud networking space, multicloud networking. And we came out of stealth mode back in April of 2020, and launched the company. In fact, one of our first events coming out of stealth mode was a Cuban interview back in April of 2020. So here at Telecare, what we are doing is we are building a Cloud platform, which allows customers to build a common network across multiple Clouds with built-in network and security services, with the policy and management layer on top full end to end visibility and governance capabilities. And all of this is delivered as a service and consumed as a service as well. And I'm very glad to be here with Ralph, who is from Warner Music Group and is one of our marquee customers. So I'll let Ralph introduce himself, and tell us a bit more about Alkira and WMTS Cloud journey. >> That sounds great. Ralph, why don't you start by giving the audience? I'm sure everyone knows Warner Music Group, but in case there's anyone out there that might not. Give us a little bit of a background. >> Yeah, so the Warner Music Group has been around since 1950 and 1940 even it had its roots at Hollywood and out of Warner Brothers Pictures, Today, say global company in 79 countries we operated. If the 100 employees and we have two major divisions, we have our era recorded music division, which has the labels people commonly turn to Atlantic records, Warner brothers records, and so forth. And then we have our publishing division, which is more a chapel, which is where our songwriters live. And of course we have some singer songwriters that are on both sides of our business. But now currently people may know our artists. We have ed Sheeran, Bruno Mars, Coldplay, Cardi B, Blake Shelton and I could go on and on. But exciting, great year, we're having one of our best years ever. And I'm so glad to be here and partnering with an Alkira. >> Excellent. I love all of those artists that you mentioned. Fantastic. So let's talk a little bit now Ralph about the backstory. Talk to me about the IT infrastructure at Warner Music Group, what you had there and some of the challenges that you had that you came to Alkira to solve. >> Yeah, well initially when I took over about five years ago now, we were very much a data center based business with traditional networking and IT functions. Additionally with our foreign affiliates, IT was sort of decentralized in the sense that a lot of the networking and data center components were left to regions. And so while we operated globally, we didn't really operate globally, at Warner among our affiliates. So one of the challenges was how do we get out of the data center? Cloud was new. One of the big things that were coming with big data, which is absolutely right for moving, going straight to the Cloud, especially if you don't have anything on-prem and how do we rationalize all of these different locations and conduct all the M&A work we've been doing? So it was quite a challenge, really. At the end, we wanted to have one view of the network, and Alkira. I looked at many a company and Alkira seemed the best to provide that to us. So. >> Well, talk to me a little bit more about why Alkira, because as Atif was saying, they're very young. What came out of stealth mode during the pandemic Warner Music Group, being around since the 40s and 50s, the legacy institution, a great brand. What made you take a risk on such an early stage startup? >> Quite frankly, there was nothing in the space (chuckles) at the time you loved, there were companies that had components of it, of what Alkira does, which is basically network orchestration allowing us to use existing components. And nobody has the whole package, especially incorporating security. So, we figured why not take, take a chance? There's no, it won't hurt you no harm. And if anything is successful, it will give us a great ability to manage our network, much more efficiently taking things that took days down to hours and being able to do it much more efficiently with much fewer staff, as opposed to hiring a lot more because when you orchestrate all the components that are underneath, obviously it requires more bodies, more resources. >> Right. That efficiency and cost optimization is key there. Atif I have to ask you, talk to me about, this is only a few years ago, the gap in the market that you and your brothers saw a few years ago, when you founded the company, because as Rob was saying, there was nobody else in the market at the time that could do what you're doing. >> Yeah, absolutely. So Lisa, as you know, myself and Amir, we were also a part of the founding team of Viptela, which was the SD-WAN Company. So back in the day when we did SD-WAN, the requirement was to connect sites together. So if you go back like 5, 10, 5, 7, 10 years ago, networking was done to connect sites together, which could be remote sites, data centers, sites to data centers, all of that together. But fast forward, a few more years with the adoption of Cloud, requirements changed from the networking perspective. So now your network is not just connecting sites together, but most of the traffic now is from sites or users, which could be sitting anywhere. If you look at, what's going on? in the pandemic people are working from all across the globe. They are not just sitting in campuses or sites. So traffic patterns are from sites or users mostly to the Cloud or SaaS applications. So now networks also need to evolve and they need to be built inside the Cloud rather than from outside or connecting into the Cloud. So Cloud access is one capability, but building a network inside the Cloud becomes a requirement. And secondly, now it's not just only about connectivity because security becomes even more important because your security perimeter is changing as well. So securing all these Cloud networks becomes very, very complicated. And now as Ralph can tell you, majority of the enterprises have a multicloud strategy and each Cloud is done differently. So the moment you bring in multiple Clouds, multiple regions across the globe, it becomes so complicated for enterprises to build and manage. They need something, or a platform which makes it easy, gives them one way of doing networking, building a common network across whether you're connecting multiple Clouds or Clouds to your on-prem locations or Clouds to internet or sites to internet. So that's where we saw this gap and we decided to build Alkira to tackle this problem. >> Got it. So Rob, let's talk now about what you've implemented as a team was saying we live in this, in this work from anywhere hybrid multicloud world. Talk to us about Warner, what you implemented and maybe a little bit about your multicloud strategy, if you've got one. >> Ralph: Yeah. So over the last five years, Warner has migrated entirely into Cloud. And to this point before it's multicloud, we're mainly in AWS, but we do have some pleasure and some Google Cloud. And with that, I was telling Atif and Amir. It was interesting and they built a Cloud on site. They totally forgot about the networking aspect. So (laughs), you have ease of use for services and servers inside (indistinct) cloud, but networking is not really present, not to mention when it was built out, it wasn't made to go to competing Clouds. So most companies are facing this problem. How do you treat these environments as a single holistic environment? How do you turn things up, turn things down? How do you secure it, When every single one is different habits, selling unique ways of doing things? So that really was, how we ended up looking for an out Alkira, because I just kept looking at the costs and the profit print grow and grow and grow. And the complexity to a (indistinct) before is growing exponential. One change in one thing would lead to two changes to another. If you add another Cloud or you add another point on the network, you've got exponential growth and complexity, complexity, you have to deal with. So one stop shop. (chuckles) >> One stop shop and reducing that complexity. Talk to me about reducing complexity, and what you're accomplishing there. Especially, in the last year and a half as things have been so dynamic, shall we say? (chuckles) >> Yeah, well, I will say this. It was turnkey for the most part. It took a matter of months as opposed to years, because out of the box, there was a lot of integrations with the major network of players. So as of right now, you can buy firewalls, routing, VPC, things like this, they all exist, but they're not orchestrated together. Right? And then you have policies and security, again not orchestrating a different set of tools. So it really only took us two to three months to get it up and running, I acts, I just had a conversation (chuckles) with them when we were going to finish. So I think we'll be finishing this up completely in January and sometime. So, I was pretty sure. >> LISA: That's fantastic. So really, >> Yeah. >> Sorry Relaph fast time to market there with getting things implemented. Talk to me about from a business outcome perspective, you are CIO, what are some of the outcomes? That this technology is enabling you to deliver back to the business? >> Yeah, it really, the number 1, 2 big ones come to mind. One being able to provide them a secure enterprise. I know when there is the change it's made uniforms for our network without, some of older something's being forgotten about. So that's number one, security is big. You can imagine a company like more ever marquee brands, all brands, any company of marquee brands are targets today. That's number one. Number two is our time to market for eminent. So when we buy a company the time it takes us to get them to be completely part of Warner and therefore start realizing the business case and benefits sort of reasonably bought. Bought the company to begin with. So, we're buying a lot more and we're turning them up and turning those business cases up faster. But usually those cases would say things like six months to a year to integrate with us, and then we can unlock the set of benefits. Now it's more like, two to three months and you start to be able to lock the benefits sooner. And of course, those are different than a case by case basis, but that's. >> Sure, but significantly faster there, you're looking at a two to three X multiplier there, as you talked about. >> Ralph: right. >> Now, you mentioned multicloud Ralph. So here we are at re:Invent. I imagine part of your AWS as part of your Cloud infrastructure and they're a technology partner of ALkira's. >> Ralph: Correct. Yeah. So AWS is actually our biggest Cloud provider of the three, and yeah (laugh) they're their partner without cure. So Good. >> And Atif then you, Alkira's technology partner of AWS, correct? >> Yeas. Alkira is a technology partner of AWS, we are also available on AWS marketplace. So customers can consume, AlKira's platform from AWS marketplace as well. >> But given the fact that so many businesses in every industry are multicloud, I assume that you work with all the Cloud vendors. Atif Yeah? >> Absolutely. So our platform runs inside of the Cloud and runs in AWS is a Cloud as well. And from there it connects to multiple Clouds. So if customers need to connect to Azure or AWS from there or Oracle Cloud or any other Cloud, for that matter, they can connect from our platform and our platform is it scales horizontally. So as customers needs scale, it scales as well. And one of the key advantages is, it's consumed as a service. So there's no software to download or hardware to run for or to acquire for any of the customers. It's a software solution and it's consumed as a service. >> Got it. Ralph one on one more question for you before we wrap things up here, want to get your recommendations for IT Executives, CEOs, who might be in a similar situation to you, whether or not they are with a legacy organization, what are some of your recommendations that you say you need to be looking at a, B and C? >> Yeah, I would primarily say really need to be looking at some of these newer technologies that can help speed up, people, especially in this case to transition to the Cloud and that planning ahead of time, especially goal-setting, I find to be it's any of these places, providers is absolutely Paramount, because you can, if you don't make your own (indistinct) take that step forward and you can end up with shelter. So I make sure that it's very important that when you commit to that, you commit fully, you plan it out and you make sure you actually use it to get the benefits. One of my tech key is software. So. (chuckles) (Lisa Laughing) I'm a bit of it so. >> Well, you've been there and It costs a lot of money and it doesn't do any good. It doesn't move the business forward. And in this day and age, there is a competitor right behind the rear view mirror who might be smaller, more nimble, and more agile, who can take your place easily. >> Absolutely. >> If the organization isn't willing to take the risks and commit, as you said, Atif last question over for you, where are the customers go to learn more? I know you are at re:Invent your booth 1628, but what do you recommend folks go attendees of the event, as well as just other prospects to go to learn more about what you guys are delivering for companies like Warner Music Group. >> So if you're at re:Invent, please stop by our booth. And one of our Cloud specialists will give you a demo as well. So it's a very quick demo and you'll see, how we are reinventing networking for the Cloud narrow. You can also go to our website and you'll find a lot of information on our website. You can request a demo there as well. So look forward to seeing most of you at our booth and those who are not attending in person, please go visit our website. >> Lisa: Reinventing Networking. I like your play on words. They are Atif very appropriate. Gentlemen, thank you for joining me today talking about Alkira, Warner Music Group, what you guys are doing together and how this new early stage technology is really quite transformative. We appreciate your insights. >> Thank you. >> Thank you so much. >> For Ralph Munsen and Atif Khan, I'm Lisa Martin, and you're watching theCUBE's continuous coverage of AWS re:Invent 2021. Thanks for watching. (soft techno music)

(upbeat music) >> Welcome everyone to this CUBE coverage of AWS re:Invent 2021. We have a lot going on at this year's re:Invent with over 100 guests on the program, and I'm excited to welcome two of those guests here with me right now. We are joined by Ralph Munsen, the Chief Information Officer at Warner Music Group and Atif Khan, the CTO of Alkira and founder of Alkira as well. Gentlemen, welcome to the program. >> Thank you so much, Lisa. So glad to be here with you. >> Good to be here. >> Yeah. Good old fashioned Zoom is become our best friend in the last 22 months or so I'm losing count. Atif, I'd like to start with you. I know Alkira has been on the key before, but it's been a while and you guys are a relatively young company. Give the audience an overview of Alkira and what it is that you deliver. >> Absolutely, Lisa. So we started back in may of 2018, and the Cloud networking space, multicloud networking. And we came out of stealth mode back in April of 2020, and launched the company. In fact, one of our first events coming out of stealth mode was a Cuban interview back in April of 2020. So here at Telecare, what we are doing is we are building a Cloud platform, which allows customers to build a common network across multiple Clouds with built-in network and security services, with the policy and management layer on top full end to end visibility and governance capabilities. And all of this is delivered as a service and consumed as a service as well. And I'm very glad to be here with Ralph, who is from Warner Music Group and is one of our marquee customers. So I'll let Ralph introduce himself, and tell us a bit more about Alkira and WMTS Cloud journey. >> That sounds great. Ralph, why don't you start by giving the audience? I'm sure everyone knows Warner Music Group, but in case there's anyone out there that might not. Give us a little bit of a background. >> Yeah, so the Warner Music Group has been around since 1950 and 1940 even it had its roots at Hollywood and out of Warner Brothers Pictures, Today, say global company in 79 countries we operated. If the 100 employees and we have two major divisions, we have our era recorded music division, which has the labels people commonly turn to Atlantic records, Warner brothers records, and so forth. And then we have our publishing division, which is more a chapel, which is where our songwriters live. And of course we have some singer songwriters that are on both sides of our business. But now currently people may know our artists. We have ed Sheeran, Bruno Mars, Coldplay, Cardi B, Blake Shelton and I could go on and on. But exciting, great year, we're having one of our best years ever. And I'm so glad to be here and partnering with an Alkira. >> Excellent. I love all of those artists that you mentioned. Fantastic. So let's talk a little bit now Ralph about the backstory. Talk to me about the IT infrastructure at Warner Music Group, what you had there and some of the challenges that you had that you came to Alkira to solve. >> Yeah, well initially when I took over about five years ago now, we were very much a data center based business with traditional networking and IT functions. Additionally with our foreign affiliates, IT was sort of decentralized in the sense that a lot of the networking and data center components were left to regions. And so while we operated globally, we didn't really operate globally, at Warner among our affiliates. So one of the challenges was how do we get out of the data center? Cloud was new. One of the big things that were coming with big data, which is absolutely right for moving, going straight to the Cloud, especially if you don't have anything on-prem and how do we rationalize all of these different locations and conduct all the M&A work we've been doing? So it was quite a challenge, really. At the end, we wanted to have one view of the network, and now Alkira. I looked at many of companies and I'm curious in the best to provide that to us. So. >> Well, talk to me a little bit more about why Alkira, because as Atif was saying, they're very young. What came out of stealth mode during the pandemic Warner Music Group, being around since the 40s and 50s, the legacy institution, a great brand. What made you take a risk on such an early stage startup? >> Quite frankly, there was nothing in the space (chuckles) at the time you loved, there were companies that had components of it, of what Alkira does, which is basically network orchestration allowing us to use existing components. And nobody has the whole package, especially incorporating security. So, we figured why not take, take a chance? There's no, it won't hurt you no harm. And if anything is successful, it will give us a great ability to manage our network, much more efficiently taking things that took days down to hours and being able to do it much more efficiently with much fewer staff, as opposed to hiring a lot more because when you orchestrate all the components that are underneath, obviously it requires more bodies, more resources. >> Right. That efficiency and cost optimization is key there. Atif I have to ask you, talk to me about, this is only a few years ago, the gap in the market that you and your brothers saw a few years ago, when you founded the company, because as Rob was saying, there was nobody else in the market at the time that could do what you're doing. >> Yeah, absolutely. So Lisa, as you know, myself and Amir, we were also a part of the founding team of Viptela, which was the SD-WAN Company. So back in the day when we did SD-WAN, the requirement was to connect sites together. So if you go back like 5, 10, 5, 7, 10 years ago, networking was done to connect sites together, which could be remote sites, data centers, sites to data centers, all of that together. But fast forward, a few more years with the adoption of Cloud, requirements changed from the networking perspective. So now your network is not just connecting sites together, but most of the traffic now is from sites or users, which could be sitting anywhere. If you look at, what's going on? in the pandemic people are working from all across the globe. They are not just sitting in campuses or sites. So traffic patterns are from sites or users mostly to the Cloud or SaaS applications. So now networks also need to evolve and they need to be built inside the Cloud rather than from outside or connecting into the Cloud. So Cloud access is one capability, but building a network inside the Cloud becomes a requirement. And secondly, now it's not just only about connectivity because security becomes even more important because your security perimeter is changing as well. So securing all these Cloud networks becomes very, very complicated. And now as Ralph can tell you, majority of the enterprises have a multicloud strategy and each Cloud is done differently. So the moment you bring in multiple Clouds, multiple regions across the globe, it becomes so complicated for enterprises to build and manage. They need something, or a platform which makes it easy, gives them one way of doing networking, building a common network across whether you're connecting multiple Clouds or Clouds to your on-prem locations or Clouds to internet or sites to internet. So that's where we saw this gap and we decided to build Alkira to tackle this problem. >> Got it. So Rob, let's talk now about what you've implemented as a team was saying we live in this, in this work from anywhere hybrid multicloud world. Talk to us about Warner, what you implemented and maybe a little bit about your multicloud strategy, if you've got one. >> Ralph: Yeah. So over the last five years, Warner has migrated entirely into Cloud. And to this point before it's multicloud, we're mainly in AWS, but we do have some pleasure and some Google Cloud. And with that, I was telling Atif and Amir. It was interesting and they built a Cloud on site. They totally forgot about the networking aspect. So (laughs), you have ease of use for services and servers inside (indistinct) cloud, but networking is not really present, not to mention when it was built out, it wasn't made to go to competing Clouds. So most companies are facing this problem. How do you treat these environments as a single holistic environment? How do you turn things up, turn things down? How do you secure it, When every single one is different habits, selling unique ways of doing things? So that really was, how we ended up looking for an out Alkira, because I just kept looking at the costs and the profit print grow and grow and grow. And the complexity to a (indistinct) before is growing exponential. One change in one thing would lead to two changes to another. If you add another Cloud or you add another point on the network, you've got exponential growth and complexity, complexity, you have to deal with. So one stop shop. (chuckles) >> One stop shop and reducing that complexity. Talk to me about reducing complexity, and what you're accomplishing there. Especially, in the last year and a half as things have been so dynamic, shall we say? (chuckles) >> Yeah, well, I will say this. It was turnkey for the most part. It took a matter of months as opposed to years, because out of the box, there was a lot of integrations with the major network of players. So as of right now, you can buy firewalls, routing, VPC, things like this, they all exist, but they're not orchestrated together. Right? And then you have policies and security, again not orchestrating a different set of tools. So it really only took us two to three months to get it up and running, I acts, I just had a conversation (chuckles) with them when we were going to finish. So I think we'll be finishing this up completely in January and sometime. So, I was pretty sure. >> LISA: That's fantastic. So really, >> Yeah. >> Sorry Relaph fast time to market there with getting things implemented. Talk to me about from a business outcome perspective, you are CIO, what are some of the outcomes? That this technology is enabling you to deliver back to the business? >> Yeah, it really, the number 1, 2 big ones come to mind. One being able to provide them a secure enterprise. I know when there is the change it's made uniforms for our network without, some of older something's being forgotten about. So that's number one, security is big. You can imagine a company like more ever marquee brands, all brands, any company of marquee brands are targets today. That's number one. Number two is our time to market for eminent. So when we buy a company the time it takes us to get them to be completely part of Warner and therefore start realizing the business case and benefits sort of reasonably bought. Bought the company to begin with. So, we're buying a lot more and we're turning them up and turning those business cases up faster. But usually those cases would say things like six months to a year to integrate with us, and then we can unlock the set of benefits. Now it's more like, two to three months and you start to be able to lock the benefits sooner. And of course, those are different than a case by case basis, but that's. >> Sure, but significantly faster there, you're looking at a two to three X multiplier there, as you talked about. >> Ralph: right. >> Now, you mentioned multicloud Ralph. So here we are at re:Invent. I imagine part of your AWS as part of your Cloud infrastructure and they're a technology partner of ALkira's. >> Ralph: Correct. Yeah. So AWS is actually our biggest Cloud provider of the three, and yeah (laugh) they're their partner without cure. So Good. >> And Atif then you, Alkira's technology partner of AWS, correct? >> Yeas. Alkira is a technology partner of AWS, we are also available on AWS marketplace. So customers can consume, AlKira's platform from AWS marketplace as well. >> But given the fact that so many businesses in every industry are multicloud, I assume that you work with all the Cloud vendors. Atif Yeah? >> Absolutely. So our platform runs inside of the Cloud and runs in AWS is a Cloud as well. And from there it connects to multiple Clouds. So if customers need to connect to Azure or AWS from there or Oracle Cloud or any other Cloud, for that matter, they can connect from our platform and our platform is it scales horizontally. So as customers needs scale, it scales as well. And one of the key advantages is, it's consumed as a service. So there's no software to download or hardware to run for or to acquire for any of the customers. It's a software solution and it's consumed as a service. >> Got it. Ralph one on one more question for you before we wrap things up here, want to get your recommendations for IT Executives, CEOs, who might be in a similar situation to you, whether or not they are with a legacy organization, what are some of your recommendations that you say you need to be looking at a, B and C? >> Yeah, I would primarily say really need to be looking at some of these newer technologies that can help speed up, people, especially in this case to transition to the Cloud and that planning ahead of time, especially goal-setting, I find to be it's any of these places, providers is absolutely Paramount, because you can, if you don't make your own (indistinct) take that step forward and you can end up with shelter. So I make sure that it's very important that when you commit to that, you commit fully, you plan it out and you make sure you actually use it to get the benefits. One of my tech key is software. So. (chuckles) (Lisa Laughing) I'm a bit of it so. >> Well, you've been there and It costs a lot of money and it doesn't do any good. It doesn't move the business forward. And in this day and age, there is a competitor right behind the rear view mirror who might be smaller, more nimble, and more agile, who can take your place easily. >> Absolutely. >> If the organization isn't willing to take the risks and commit, as you said, Atif last question over for you, where are the customers go to learn more? I know you are at re:Invent your booth 1628, but what do you recommend folks go attendees of the event, as well as just other prospects to go to learn more about what you guys are delivering for companies like Warner Music Group. >> So if you're at re:Invent, please stop by our booth. And one of our Cloud specialists will give you a demo as well. So it's a very quick demo and you'll see, how we are reinventing networking for the Cloud narrow. You can also go to our website and you'll find a lot of information on our website. You can request a demo there as well. So look forward to seeing most of you at our booth and those who are not attending in person, please go visit our website. >> Lisa: Reinventing Networking. I like your play on words. They are Atif very appropriate. Gentlemen, thank you for joining me today talking about Alkira, Warner Music Group, what you guys are doing together and how this new early stage technology is really quite transformative. We appreciate your insights. >> Thank you. >> Thank you so much. >> For Ralph Munsen and Atif Khan, I'm Lisa Martin, and you're watching theCUBE's continuous coverage of AWS re:Invent 2021. Thanks for watching. (soft techno music)

>>Yeah. >>Hello. Welcome to the Special Cube conversation here in Palo Alto, California. I'm John for a host of the Cube. We have a conversation around a I for the enterprise. What this means I got two great guests. John Finelli, Vice President, virtual GPU at NVIDIA and Maurizio D V D C T o University of Pisa in Italy. Uh, Practitioner, customer partner, um, got VM world coming up. A lot of action happening in the enterprise. John. Great to see you. Nice to meet you. Remotely coming in from Italy for this remote. >>John. Thanks for having us on again. >>Yeah. Nice to meet >>you. I wish we could be in person face to face, but that's coming soon. Hopefully, John, you were talking. We were just talking about before we came on camera about AI for the enterprise. And the last time I saw you in person was in Cuba interview. We were talking about some of the work you guys were doing in AI. It's gotten so much stronger and broader and the execution of an video, the success you're having set the table for us. What is the ai for the enterprise conversation frame? >>Sure. So, um, we, uh we've been working with enterprises today on how they can deliver a I or explore AI or get involved in a I, um uh, in a standard way in the way that they're used to managing and operating their data centre. Um, writing on top of you know, they're Dell servers with B M or V sphere. Um, so that AI feels like a standard workload that night organisation can deliver to their engineers and data scientists. And then the flip side of that, of course, is ensuring that engineers and data scientists get the workloads position to them or have access to them in the way that they need them. So it's no longer a trouble ticket that you have to submit to, I t and you know, count the hours or days or weeks until you you can get new hardware, right By being able to pull it into the mainstream data centre. I can enable self service provisioning for those folks. So we actually we make a I more consumable or easier to manage for I t administrators and then for the engineers and the data scientists, etcetera. We make it easy for them to get access to those resources so they can get to their work right away. >>Quite progress in the past two years. Congratulations on that and looking. It's only the beginning is Day one Mercy. I want to ask you about what's going on as the CTO University piece of what's happening down there. Tell us a little bit about what's going on. You have the centre of excellence there. What does that mean? What does that include? >>Uh, you know, uh, University of Peace. Are you one of one of the biggest and oldest in Italy? Uh, if you have to give you some numbers is around 50 K students and 3000 staff between, uh, professors resurgence and that cabinet receive staff. So I we are looking into data operation of the centres and especially supports for scientific computing. And, uh, this is our our daily work. Let's say this, uh, taking us a lot of times, but, you know, we are able to, uh, reserve a merchant percentage of our time, Uh, for r and D, And this is where the centre of excellence is, Uh, is coming out. Uh, so we are always looking into new kinds of technologies that we can put together to build new solutions to do next generation computing gas. We always say we are looking for the right partners to do things together. And at the end of the day is the work that is good for us is good for our partners and typically, uh, ends in a production system for our university. So is the evolution of the scientific computing environment that we have. >>Yeah. And you guys have a great track record and reputation of, you know, R and D, testing software, hardware combinations and sharing those best practises, you know, with covid impact in the world. Certainly we see it on the supply chain side. Uh, and John, we heard Jensen, your CEO and video talk multiple keynotes. Now about software, uh, and video being a software company. Dell, you mentioned Dale and VM Ware. You know, Covid has brought this virtualisation world back. And now hybrid. Those are words that we used basically in the text industry. Now it's you're hearing hybrid and virtualisation kicked around in real world. So it's ironic that vm ware and El, uh, and the Cube eventually all of us together doing more virtual stuff. So with covid impacting the world, how does that change you guys? Because software is more important. You gotta leverage the hardware you got, Whether it's Dell or in the cloud, this is a huge change. >>Yeah. So, uh, as you mentioned organisations and enterprises, you know, they're looking at things differently now, Um, you know, the idea of hybrid. You know, when you talk to tech folks and we think about hybrid, we always think about you know, how the different technology works. Um, what we're hearing from customers is hybrid, you know, effectively translates into, you know, two days in the office, three days remote, you know, in the future when they actually start going back to the office. So hybrid work is actually driving the need for hybrid I t. Or or the ability to share resources more effectively. Um, And to think about having resources wherever you are, whether you're working from home or you're in the office that day, you need to have access to the same resources. And that's where you know the the ability to virtualize those resources and provide that access makes that hybrid part seamless >>mercy What's your world has really changed. You have students and faculty. You know, Things used to be easy in the old days. Physical in this network. That network now virtual there. You must really be having him having impact. >>Yeah, we have. We have. Of course. As you can imagine, a big impact, Uh, in any kind of the i t offering, uh, from, uh, design new networking technologies, deploying new networking technologies, uh, new kind of operation we find. We found it at them. We were not able anymore to do burr metal operations directly, but, uh, from the i t point of view, uh, we were how can I say prepared in the sense that, uh, we ran from three or four years parallel, uh, environment. We have bare metal and virtual. So as you can imagine, traditional bare metal HPC cluster D g d g X machines, uh, multi GPU s and so on. But in parallel, we have developed, uh, visual environment that at the beginning was, as you can imagine, used, uh, for traditional enterprise application, or VD. I, uh, we have a significant significant arise on a farm with the grid for remote desktop remote pull station that we are using for, for example, uh, developing a virtual classroom or visual go stations. And so this is was typical the typical operation that we did the individual world. But in the same infrastructure, we were able to develop first HPC individual borders of utilisation of the HPC resources for our researchers and, uh, at the end, ai ai offering and ai, uh, software for our for our researchers, you can imagine our vehicle infrastructure as a sort of white board where we are able to design new solution, uh, in a fast way without losing too much performance. And in the case of the AI, we will see that we the performance are almost the same at the bare metal. But with all the flexibility that we needed in the covid 19 world and in the future world, too. >>So a couple things that I want to get John's thoughts as well performance you mentioned you mentioned hybrid virtual. How does VM Ware and NVIDIA fit into all this as you put this together, okay, because you bring up performance. That's now table stakes. He's leading scale and performance are really on the table. everyone's looking at it. How does VM ware an NVIDIA John fit in with the university's work? >>Sure. So, um, I think you're right when it comes to, uh, you know, enterprises or mainstream enterprises beginning their initial foray into into a I, um there are, of course, as performance in scale and also kind of ease of use and familiarity are all kind of things that come into play in terms of when an enterprise starts to think about it. And, um, we have a history with VM Ware working on this technology. So in 2019, we introduced our virtual compute server with VM Ware, which allowed us to effectively virtual is the Cuda Compute driver at last year's VM World in 2020 the CEOs of both companies got together and made an announcement that we were going to bring a I R entire video AI platform to the Enterprise on top of the sphere. And we did that, Um, starting in March this year, we we we finalise that with the introduction of GM wears V, Sphere seven, update two and the early access at the time of NVIDIA ai Enterprise. And, um, we have now gone to production with both of those products. And so customers, Um, like the University of Pisa are now using our production capabilities. And, um, whenever you virtualize in particular and in something like a I where performances is really important. Um, the first question that comes up is, uh doesn't work and And how quickly does it work Or or, you know, from an I t audience? A lot of times you get the How much did it slow down? And and and so we We've worked really closely from an NVIDIA software perspective and a bm wear perspective. And we really talk about in media enterprise with these fair seven as optimist, certified and supported. And the net of that is, we've been able to run the standard industry benchmarks for single node as well as multi note performance, with about maybe potentially a 2% degradation in performance, depending on the workload. Of course, it's very different, but but effectively being able to trade that performance for the accessibility, the ease of use, um, and even using things like we realise, automation for self service for the data scientists, Um and so that's kind of how we've been pulling it together for the market. >>Great stuff. Well, I got to ask you. I mean, people have that reaction of about the performance. I think you're being polite. Um, around how you said that shows the expectation. It's kind of sceptical, uh, and so I got to ask you, the impact of this is pretty significant. What is it now that customers can do that? They couldn't or couldn't feel they had before? Because if the expectations as well as it worked well, I mean, there's a fast means. It works, but like performance is always concerned. What's different now? What what's the bottom line impact on what country do now that they couldn't do before. >>So the bottom line impact is that AI is now accessible for the enterprise across there. Called their mainstream data centre, enterprises typically use consistent building blocks like the Dell VX rail products, right where they have to use servers that are common standard across the data centre. And now, with NVIDIA Enterprise and B M R V sphere, they're able to manage their AI in the same way that they're used to managing their data centre today. So there's no retraining. There's no separate clusters. There isn't like a shadow I t. So this really allows an enterprise to efficiently deploy um, and cost effectively Deploy it, uh, it without because there's no performance degradation without compromising what their their their data scientists and researchers are looking for. And then the flip side is for the data science and researcher, um, using some of the self service automation that I spoke about earlier, they're able to get a virtual machine today that maybe as a half a GPU as their models grow, they do more exploring. They might get a full GPU or or to GPS in a virtual machine. And their environment doesn't change because it's all connected to the back end storage. And so for the for the developer and the researcher, um, it makes it seamless. So it's really kind of a win for both Nike and for the user. And again, University of Pisa is doing some amazing things in terms of the workloads that they're doing, Um, and, uh and, uh, and are validating that performance. >>Weigh in on this. Share your opinion on or your reaction to that, What you can do now that you couldn't do before. Could you share your experience? >>Our experience is, uh, of course, if you if you go to your, uh, data scientists or researchers, the idea of, uh, sacrificing four months to flexibility at the beginning is not so well accepted. It's okay for, uh, for the Eid management, As John was saying, you have people that is know how to deal with the virtual infrastructure, so nothing changed for them. But at the end of the day, we were able to, uh, uh, test with our data. Scientists are researchers veteran The performance of us almost similar around really 95% of the performance for the internal developer developer to our work clothes. So we are not dealing with benchmarks. We have some, uh, work clothes that are internally developed and apply to healthcare music generator or some other strange project that we have inside and were able to show that the performance on the beautiful and their metal world were almost the same. We, the addition that individual world, you are much more flexible. You are able to reconfigure every finger very fast. You are able to design solution for your researcher, uh, in a more flexible way. An effective way we are. We were able to use the latest technologies from Dell Technologies and Vidia. You can imagine from the latest power edge the latest cuts from NVIDIA. The latest network cards from NVIDIA, like the blue Field to the latest, uh, switches to set up an infrastructure that at the end of the day is our winning platform for our that aside, >>a great collaboration. Congratulations. Exciting. Um, get the latest and greatest and and get the new benchmarks out their new playbooks. New best practises. I do have to ask you marriage, if you don't mind me asking why Look at virtualizing ai workloads. What's the motivation? Why did you look at virtualizing ai work clothes? >>Oh, for the sake of flexibility Because, you know, uh, in the latest couple of years, the ai resources are never enough. So we are. If you go after the bare metal, uh, installation, you are going into, uh, a world that is developing very fastly. But of course, you can afford all the bare metal, uh, infrastructure that your data scientists are asking for. So, uh, we decided to integrate our view. Dual infrastructure with AI, uh, resources in order to be able to, uh, use in different ways in a more flexible way. Of course. Uh, we have a We have a two parallels world. We still have a bare metal infrastructure. We are growing the bare metal infrastructure. But at the same time, we are growing our vehicle infrastructure because it's flexible, because we because our our stuff, people are happy about how the platform behaviour and they know how to deal them so they don't have to learn anything new. So it's a sort of comfort zone for everybody. >>I mean, no one ever got hurt virtualizing things that makes it makes things go better faster building on on that workloads. John, I gotta ask you, you're on the end video side. You You see this real up close than video? Why do people look at virtualizing ai workloads is the unification benefit. I mean, ai implies a lot of things, implies you have access to data. It implies that silos don't exist. I mean, that doesn't mean that's hard. I mean, is this real people actually looking at this? How is it working? >>Yeah. So? So again, um you know for all the benefits and activity today AI brings a I can be pretty complex, right? It's complex software to set up and to manage. And, um, within the day I enterprise, we're really focusing in on ensuring that it's easier for organisations to use. For example Um, you know, I mentioned you know, we we had introduced a virtual compute server bcs, um uh, two years ago and and that that has seen some some really interesting adoption. Some, uh, enterprise use cases. But what we found is that at the driver level, um, it still wasn't accessible for the majority of enterprises. And so what we've done is we've built upon that with NVIDIA Enterprise and we're bringing in pre built containers that remove some of the complexities. You know, AI has a lot of open source components and trying to ensure that all the open source dependencies are resolved so you can get the AI developers and researchers and data scientists. Actually doing their work can be complex. And so what we've done is we've brought these pre built containers that allow you to do everything from your initial data preparation data science, using things like video rapids, um, to do your training, using pytorch and tensorflow to optimise those models using tensor rt and then to deploy them using what we call in video Triton Server Inference in server. Really helping that ai loop become accessible, that ai workflow as something that an enterprise can manage as part of their common core infrastructure >>having the performance and the tools available? It's just a huge godsend people love. That only makes them more productive and again scales of existing stuff. Okay, great stuff. Great insight. I have to ask, What's next one's collaboration? This is one of those better together situations. It's working. Um, Mauricio, what's next for your collaboration with Dell VM Ware and video? >>We will not be for sure. We will not stop here. Uh, we are just starting working on new things, looking for new development, uh, looking for the next beast. Come, uh, you know, the digital world is something that is moving very fast. Uh, and we are We will not We will not stop here because because they, um the outcome of this work has been a very big for for our research group. And what John was saying This the fact that all the software stock for AI are simplified is something that has been, uh, accepted. Very well, of course you can imagine researching is developing new things. But for people that needs, uh, integrated workflow. The work that NVIDIA has done in the development of software package in developing containers, that gives the end user, uh, the capabilities of running their workloads is really something that some years ago it was unbelievable. Now, everything is really is really easy to manage. >>John mentioned open source, obviously a big part of this. What are you going to? Quick, Quick follow if you don't mind. Are you going to share your results so people can can look at this so they can have an easier path to AI? >>Oh, yes, of course. All the all the work, The work that is done at an ideal level from University of Visa is here to be shared. So we we as, uh, as much as we have time to write down we are. We are trying to find a way to share the results of the work that we're doing with our partner, Dell and NVIDIA. So for sure will be shared >>well, except we'll get that link in the comments, John, your thoughts. Final thoughts on the on the on the collaboration, uh, with the University of Pisa and Delvian, where in the video is is all go next? >>Sure. So So with University of Pisa, We're you know, we're absolutely, uh, you know, grateful to Morocco and his team for the work they're doing and the feedback they're sharing with us. Um, we're learning a lot from them in terms of things we can do better and things that we can add to the product. So that's a fantastic collaboration. Um, I believe that Mauricio has a session at the M World. So if you want to actually learn about some of the workloads, um, you know, they're doing, like, music generation. They're doing, you know, covid 19 research. They're doing deep, multi level, uh, deep learning training. So there's some really interesting work there, and so we want to continue that partnership. University of Pisa, um, again, across all four of us, uh, university, NVIDIA, Dell and VM Ware. And then on the tech side, you know, for our enterprise customers, um, you know, one of the things that we actually didn't speak much about was, um I mentioned that the product is optimised certified and supported, and I think that support cannot be understated. Right? So as enterprises start to move into these new areas, they want to know that they can pick up the phone and call in video or VM ware. Adele, and they're going to get support for these new workloads as they're running them. Um, we were also continuing, uh, you know, to to think about we spent a lot of time today on, like, the developer side of things and developing ai. But the flip side of that, of course, is that when those ai apps are available or ai enhanced apps, right, Pretty much every enterprise app today is adding a I capabilities all of our partners in the enterprise software space and so you can think of a beady eye enterprises having a runtime component so that as you deploy your applications into the data centre, they're going to be automatically take advantage of the GPS that you have there. And so we're seeing this, uh, future as you're talking about the collaboration going forward, where the standard data centre building block still maintains and is going to be something like a VX rail two U server. But instead of just being CPU storage and RAM, they're all going to go with CPU, GPU, storage and RAM. And that's going to be the norm. And every enterprise application is going to be infused with AI and be able to take advantage of GPS in that scenario. >>Great stuff, ai for the enterprise. This is a great QB conversation. Just the beginning. We'll be having more of these virtualizing ai workloads is real impacts data scientists impacts that compute the edge, all aspects of the new environment we're all living in. John. Great to see you, Maurizio here to meet you and all the way in Italy looking for the meeting in person and good luck in your session. I just got a note here on the session. It's at VM World. Uh, it's session 22 63 I believe, um And so if anyone's watching, Want to check that out? Um, love to hear more. Thanks for coming on. Appreciate it. >>Thanks for having us. Thanks to >>its acute conversation. I'm John for your host. Thanks for watching. We'll talk to you soon. Yeah,

>>Yeah. Hello and welcome back to the cubes coverage of AWS public sector summit here in Washington D. C. We're live on the ground for two days. Face to face conference and expo hall and everything here but keith brooks who is the director and head of technical business development for a dress government Govcloud selling brains 10th birthday. Congratulations. Welcome to the cube. Thank you john happy to be E. C. 2 15 S three is 9.5 or no, that maybe they're 10 because that's the same day as sqs So Govcloud. 10 years, 20 years. What time >>flies? 10 years? >>Big milestone. Congratulations. A lot of history involved in Govcloud. Yes. Take us through what's the current situation? >>Yeah. So um let's start with what it is just for the viewers that may not be familiar. So AWS Govcloud is isolated. AWS cloud infrastructure and services that were purposely built for our U. S. Government customers that had highly sensitive data or highly regulated data or applications and workloads that they wanted to move to the cloud. So we gave customers the ability to do that with AWS Govcloud. It is subject to the fed ramp I and D O D S R G I L four L five baselines. It gives customers the ability to address ITAR requirements as well as Seaga's N'est ce MMC and Phipps requirements and gives customers a multi region architecture that allows them to also designed for disaster recovery and high availability in terms of why we built it. It starts with our customers. It was pretty clear from the government that they needed a highly secure and highly compliant cloud infrastructure to innovate ahead of demand and that's what we delivered. So back in august of 2011 we launched AWS GovCloud which gave customers the best of breed in terms of high technology, high security, high compliance in the cloud to allow them to innovate for their mission critical workloads. Who >>was some of the early customers when you guys launched after the C. I. A deal intelligence community is a big one but some of the early customers. >>So the Department of Health and Human Services, the Department of Veterans Affairs, the Department of Justice and the Department of Defense were all early users of AWS GovCloud. But one of our earliest lighthouse customers was the Nasa jet propulsion laboratory and Nasa Jpl used AWS GovCloud to procure Procure resources ahead of demand which allowed them to save money and also take advantage of being efficient and only paying for what they needed. But they went beyond just I. T. Operations. They also looked at how do they use the cloud and specifically GovCloud for their mission programs. So if you think back to all the way to 2012 with the mars curiosity rover, Nasa Jpl actually streamed and processed and stored that data from the curiosity rover on AWS Govcloud They actually streamed over 150 terabytes of data responded to over 80,000 requests per second and took it beyond just imagery. They actually did high performance compute and data analytics on the data as well. That led to additional efficiencies for future. Over there >>were entire kicking they were actually >>hard core missing into it. Mission critical workloads that also adhere to itar compliance which is why they used AWS GovCloud. >>All these compliance. So there's also these levels. I remember when I was working on the jetty uh stories that were out there was always like level for those different classifications. What does all that mean like? And then this highly available data and highly high availability all these words mean something in these top secret clouds. Can you take us through kind of meetings >>of those? Yeah absolutely. So it starts with the federal compliance program and the two most popular programs are Fed ramp and Dodi srg fed ramp is more general for federal government agencies. There are three levels low moderate and high in the short and skinny of those levels is how they align to the fisma requirements of the government. So there's fisma low fisma moderate fisma high depending on the sensitivity of the government data you will have to align to those levels of Fed ramp to use workloads and store data in the cloud. Similar story for D. O. D. With srg impact levels to 45 and six uh impacts levels to four and five are all for unclassified data. Level two is for less sensitive public defense data levels. Four and five cover more sensitive defense data to include mission critical national security systems and impact level six is for classified information. So those form the basis of security and compliance, luckily with AWS GovCloud celebrating our 10th anniversary, we address Fed ramp high for our customers that require that and D. O. D impact levels to four and five for a sensitive defense guy. >>And that was a real nuanced point and a lot of the competition can't do that. That's real people don't understand, you know, this company, which is that company and all the lobbying and all the mudslinging that goes on. We've seen that in the industry. It's unfortunate, but it happens. Um, I do want to ask you about the Fed ramp because what I'm seeing on the commercial side in the cloud ecosystem, a lot of companies that aren't quote targeting public sector are coming in on the Fed ramp. So there's some good traction there. You guys have done a lot of work to accelerate that. Any new, any new information to share their. >>Yes. So we've been committed to supporting the federal government compliance requirements effectively since the launch of GovCloud. And we've demonstrated our commitment to Fed ramp over the last number of years and GovCloud specifically, we've taken dozens of services through Fed ramp high and we're 100% committed to it because we have great relationships with the Fed ramp, Jabor the joint authorization board. We work with individual government agencies to secure agency A. T. O. S. And in fact we actually have more agency A. T. O. S. With AWS GovCloud than any other cloud provider. And the short and skinny is that represents the baseline for cloud security to address sensitive government workloads and sensitive government data. And what we're seeing from industry and specifically highly regulated industries is the standard that the U. S. Government set means that they have the assurance to run control and classified information or other levels of highly sensitive data on the cloud as well. So Fed ramp set that standard. It's interesting >>that the cloud, this is the ecosystem within an ecosystem again within crossover section. So for instance um the impact of not getting Fed ramp certified is basically money. Right. If you're a supplier vendor uh software developer or whatever used to being a miracle, no one no one would know right bed ramp. I'm gonna have to hire a whole department right now. You guys have a really easy, this is a key value proposition, isn't it? >>Correct. And you see it with a number of I. S. V. S. And software as the service providers. If you visit the federal marketplace website, you'll see dozens of providers that have Fed ramp authorized third party SAAS products running on GovCloud industry leading SAAS companies like Salesforce dot com driven technology Splunk essay PNS to effectively they're bringing their best of breed capabilities, building on top of AWS GovCloud and offering those highly compliant fed ramp, moderate fed ramp high capabilities to customers both in government and private industry that need that level of compliance. >>Just as an aside, I saw they've got a nice tweet from Teresa Carlson now it's plunk Govcloud yesterday. That was a nice little positive gesture uh, for you guys at GovCloud, what other areas are you guys moving the needle on because architecturally this is a big deal. What are some areas that you're moving the needle on for the GovCloud? >>Well, when I look back across the last 10 years, there were some pretty important developments that stand out. The first is us launching the second Govcloud infrastructure region in 2018 And that gave customers that use GovCloud specifically customers that have highly sensitive data and high levels of compliance. The ability to build fault tolerant, highly available and mission critical workloads in the cloud in a region that also gives them an additional three availability zones. So the launch of GovCloud East, which is named AWS GovCloud Us East gave customers to regions a total of six availability zones that allowed them accelerate and build more scalable solutions in the cloud. More recently, there is an emergence of another D O D program called the cybersecurity maturity model, C M M C and C M M C is something where we looked around the corner and said we need to Innovate to help our customers, particularly defense customers and the defense industrial based customers address see MMC requirements in the cloud. So with Govcloud back in December of 2020, we actually launched the AWS compliant framework for federal defense workloads, which gives customers a turnkey capability and tooling and resources to spin up environments that are configured to meet see MMC controls and D. O. D. Srg control. So those things represent some of the >>evolution keith. I'm interested also in your thoughts on how you see the progression of Govcloud outside the United States. Tactical Edge get wavelength coming on board. How does how do you guys look at that? Obviously us is global, it's not just the jet, I think it's more of in general. Edge deployments, sovereignty is also going to be world's flat, Right? I mean, so how does that >>work? So it starts back with customer requirements and I tie it back to the first question effectively we built Govcloud to respond to our U. S. Government customers and are highly regulated industry customers that had highly sensitive data and a high bar to meet in terms of regulatory compliance and that's the foundation of it. So as we look to other customers to include those outside of the US. It starts with those requirements. You mentioned things like edge and hybrid and a good example of how we marry the two is when we launched a W. S. Outpost in Govcloud last year. So outpost brings the power of the AWS cloud to on premises environments of our customers, whether it's their data centers or Coehlo environments by bringing AWS services, a. P. I. S and service and points to the customer's on premises facilities >>even outside the United States. >>Well, for Govcloud is focused on us right now. Outside of the U. S. Customers also have availability to use outpost. It's just for us customers, it's focused on outpost availability, geography >>right now us. Right. But other governments gonna want their Govcloud too. Right, Right, that's what you're getting at, >>Right? And it starts with the data. Right? So we we we spent a lot of time working with government agencies across the globe to understand their regulations and their requirements and we use that to drive our decisions. And again, just like we started with govcloud 10 years ago, it starts with our customer requirements and we innovate from there. Well, >>I've been, I love the D. O. D. S vision on this. I know jet I didn't come through and kind of went scuttled, got thrown under the bus or whatever however you want to call it. But that whole idea of a tactical edge, it was pretty brilliant idea. Um so I'm looking forward to seeing more of that. That's where I was supposed to come in, get snowball, snowmobile, little snow snow products as well, how are they doing? And because they're all part of the family to, >>they are and they're available in Govcloud and they're also authorized that fed ramp and Gov srg levels and it's really, it's really fascinating to see D. O. D innovate with the cloud. Right. So you mentioned tactical edge. So whether it's snowball devices or using outposts in the future, I think the D. O. D. And our defense customers are going to continue to innovate. And quite frankly for us, it represents our commitment to the space we want to make sure our defense customers and the defense industrial base defense contractors have access to the best debris capabilities like those edge devices and edge capable. I >>think about the impact of certification, which is good because I just thought of a clean crows. We've got aerospace coming in now you've got D O. D, a little bit of a cross colonization if you will. So nice to have that flexibility. I got to ask you about just how you view just in general, the intelligence community a lot of uptake since the CIA deal with amazon Just overall good health for eight of his gum cloud. >>Absolutely. And again, it starts with our commitment to our customers. We want to make sure that our national security customers are defense customers and all of the customers and the federal government that have a responsibility for securing the country have access to the best of breed capability. So whether it's the intelligence community, the Department of Defense are the federal agencies and quite frankly we see them innovating and driving things forward to include with their sensitive workloads that run in Govcloud, >>what's your strategy for partnerships as you work on the ecosystem? You do a lot with strategy. Go to market partnerships. Um, it's got its public sector pretty much people all know each other. Our new firms popping up new brands. What's the, what's the ecosystem looks like? >>Yeah, it's pretty diverse. So for Govcloud specifically, if you look at partners in the defense community, we work with aerospace companies like Lockheed martin and Raytheon Technologies to help them build I tar compliant E. R. P. Application, software development environments etcetera. We work with software companies I mentioned salesforce dot com. Splunk and S. A. P. And S. To uh and then even at the state and local government level, there's a company called Pay It that actually worked with the state of Kansas to develop the Icann app, which is pretty fascinating. It's a app that is the official app of the state of Kansas that allow citizens to interact with citizens services. That's all through a partner. So we continue to work with our partner uh broad the AWS partner network to bring those type of people >>You got a lot of MST is that are doing good work here. I saw someone out here uh 10 years. Congratulations. What's the coolest thing uh you've done or seen. >>Oh wow, it's hard to name anything in particular. I just think for us it's just seeing the customers and the federal government innovate right? And, and tie that innovation to mission critical workloads that are highly important. Again, it reflects our commitment to give these government customers and the government contractors the best of breed capabilities and some of the innovation we just see coming from the federal government leveraging the count now. It's just super cool. So hard to pinpoint one specific thing. But I love the innovation and it's hard to pick a favorite >>Child that we always say. It's kind of a trick question I do have to ask you about just in general, the just in 10 years. Just look at the agility. Yeah, I mean if you told me 10 years ago the government would be moving at any, any agile anything. They were a glacier in terms of change, right? Procure Man, you name it. It's just like, it's a racket. It's a racket. So, so, but they weren't, they were slow and money now. Pandemic hits this year. Last year, everything's up for grabs. The script has been flipped >>exactly. And you know what, what's interesting is there were actually a few federal government agencies that really paved the way for what you're seeing today. I'll give you some examples. So the Department of Veterans Affairs, they were an early Govcloud user and way back in 2015 they launched vets dot gov on gov cloud, which is an online platform that gave veterans the ability to apply for manage and track their benefits. Those type of initiatives paved the way for what you're seeing today, even as soon as last year with the U. S. Census, right? They brought the decennial count online for the first time in history last year, during 2020 during the pandemic and the Census Bureau was able to use Govcloud to launch and run 2020 census dot gov in the cloud at scale to secure that data. So those are examples of federal agencies that really kind of paved the way and leading to what you're saying is it's kind >>of an awakening. It is and I think one of the things that no one's reporting is kind of a cultural revolution is the talent underneath that way, the younger people like finally like and so it's cooler. It is when you go fast and you can make things change, skeptics turned into naysayers turned into like out of a job or they don't transform so like that whole blocker mentality gets exposed just like shelf where software you don't know what it does until the cloud is not performing, its not good. Right, right. >>Right. Into that point. That's why we spend a lot of time focused on education programs and up skilling the workforce to, because we want to ensure that as our customers mature and as they innovate, we're providing the right training and resources to help them along their journey, >>keith brooks great conversation, great insight and historian to taking us to the early days of Govcloud. Thanks for coming on the cube. Thanks thanks for having me cubes coverage here and address public sector summit. We'll be back with more coverage after this short break. Mhm. Mhm mm.

>> From theCUBE studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE in ETR. This is breaking analysis with Dave Vellante. >> ServiceNow is a company that investors love to love, but there's caution in the investor community right now is confusion about transitory inflation and higher interest rates looms. ServiceNow also suffers from a perfection syndrome of sorts. The company has seen that the slightest misstep can cause many freak outs from the investor community. So what it's done is it's architected a financial and communications model that allows it to beat expectations and raise its outlook on a consistent basis. Regardless, ServiceNow appears to be on track to vie for what its CEO Bill McDermott refers to as the next great enterprise software company. Wait, I thought Marc Benioff had his hands on that steering wheel. Hello everyone, and welcome to this week's Wikibon CUBE insights powered by ETR. In this breaking analysis, we'll dig into one of the companies we began following almost 10 years ago and provide some thoughts on ServiceNow's March to 15 billion by 2026, which we think is a highly probable achievement. In 2020, despite the contraction in IT spending, SeviceNow outperformed both the S&P 500 and the NASDAQ, but here's a view of 2021. And you can see while the stock has done well since it saw a softness in May and again in early June, and it bounced off that double bottom, it's performance is well below those other benchmarks. This is not a big surprise given the fact that this is a high growth stock and we all know that those names with high multiples get hurt in an inflationary environment, but still the gaps are notable. This is especially true given the performance of the company. It's not often that you see a company with four to $5 billion in revenue growing at a 30% clip, throwing off billions of dollars in free cash flow and increasing operating margins at 100 basis points a year and promising to do that over the next several years. In fact, I don't think we've ever seen that before. I remember years ago, when the trade press was criticizing SeviceNow for its lofty valuation, despite the fact that it was losing money, then CEO, Frank Slootman said to me, "Dave, we can be highly profitable tomorrow if we want it to be, but this is a marathon and we're planning to go big." So essentially Slootman was telling me that this company was going to be an ATM machine that prints money. And that seems to be how it's shaping up. I happened to be at SeviceNow headquarters in 2017, literally the first day on the job for John Donahoe, the CEO replaced Slootman, and I remember while I was there thinking Donahoe was certainly capable, but why the heck I said, would the board let Frank Slootman get away? You know what? It turned great for Slootman, he's at snowflake. Donahoe, I always felt was a consumer guy anyway, and not long for SeviceNow. And now you have this guy, new CEO, Bill McDermott at the helm. He's not a more qualified CEO for the company in my view. About two months ago, McDermott led a virtual investor day. We've had McDermott on theCUBE a couple of times back when he was CEO of SAP and this individual is very compelling. He's got JFK like looks and charisma, but more than that, he's passionate and convincing. And he obviously knows enterprise software. And with conviction, he laid the groundwork for how SeviceNow will get to $10 billion in revenue by 2024 on its way to 15 billion two years thereafter. And one of the big things McDermott's stressed was they're going to get there without any big M&A moves. And that's important because previously the door was left open for that possibility. And now the company is assuring investors that it can get there organically, even with slower growth. So this chart implies no big M&A, and you can see Slootman handed over the reigns at that year one tick on the horizontal axis. This was not a turnaround story. It was a rocket ship at the time. And look at the logos on this chart. This is a revenue view and SeviceNow is aiming to be the fastest to get to 10 billion in software industry history. SeviceNow is valuation just to sort of shift gears here for a minute blew by workdays years ago. Its sites are now set on SAP which is currently valued at 170 billion. And then there's Oracle and Salesforce. They're at around 250 billion and 225 billion in valuation respectively. And these lines back to revenue show the trajectory that these companies took to get to 10 billion. And you can see how SeviceNow plans to get there with those dotted lines. And this is why I call this a collision course with Salesforce, because I think Marc Benioff might say, "Hey, we are ready." Are the next great enterprise software company. We have no plans to give up that post, that mantle anytime soon. I want to share a clip from four years ago. something we've been saying for a long, long time. Roll the clip. >> As they say their goal now is to be four billion by 2020. It feels like, you know, when we first covered SeviceNow knowledge, we said, wow, this company reminds us a lot of the early days of Salesforce. They've got this platform you can develop on this platform, you know, call it paths or, you know, whatever you want to call it, but we at the time said, they're on a collision course with Salesforce. Now there's plenty of room for both of those companies in the marketplace. Salesforce obviously focused predominantly on Salesforce automation, SeviceNow really on workflow automation, but you can see those sort of two markets coming together. >> Now you may be thinking isn't Salesforce's revenue like 5X that of SeviceNow? And yes it is. But I would say a couple of things. One is that Salesforce has gotten to where it is with a lot of M&A, more than 60 acquisitions. At some high profile wants to like slack and Tableau as well as MuleSoft and Heroku back in the day and many others. So we'll see how far McDermott can get before he reverts to his inquisitive self that we saw at SAP. But the second thing I'll say is serviceNow positions itself as the platform of platforms. And the thing is it runs its own cloud. And when it does acquisitions, it replatforms the acquiree into the now platform so that it can drive integrations more seamlessly. That's fundamentally part of its value proposition, a big part of its value proposition. And that means it's somewhat limited on the acquisitions it can make, it has to be pretty selective. Otherwise it's got to do a heavy lift to get it the now platform. It's the power of the models, especially if customers can get to a single CMDB, that configuration database management system, which by the way, a lot of customers never get to that kind of skirt that, but remember SeviceNow is like the ERP for IT. So the more you can get to a single data model, the more effective you're going to be, especially in this data era where you got to put data at the core of your organization, something we've talked about a lot. And the third thing I'll mention the SeviceNow wants to use this platform to attack what it sees as a very large TAM as shown here. Now, a couple of things I want to point out. One is when SeviceNow IPO in 2012, a lot of the analysts said that they were way overvalued because they were in a market. It was help desk and writing tickets was a $2 billion business that was in decline and BMC remedy. Wasn't really that big of a base to attack. In 2013, the Wikibon team took a stab at sizing the TAM. I dug back into the old Wiki. We had well over 30 billion at the time and we expected the company to move deeper into IT and then beyond IT into lines of business and line of business management. Yeah, we felt we were being conservative. We thought the number could be as big as 100 billion, but we felt like putting that number out there, was too aggressive but, you know, it turns out from SeviceNow standpoint, it sees these new software opportunities coming together. And SeviceNow in a way they can double dip both in and beyond their current markets. What I mean by that is it can partner with, for instance, HCM vendors and then at the same time offer employee workflows. They can partner or even purchase RPA tools from specialists like UI path or automation anywhere. And it can go acquire a company which it did like Intel a bot and integrate what I would consider lighter-weight RPA into its platform. So it can manage workflows for best of breed and pick off functionality throughout the software stack. Now what's interesting in this chart is first, the size of the TAM that SeviceNow sees 175 billion, but also how it's now reorganizing its business around workflows, which you see in the left-hand side. This was done of course, to simplify the many, many, many things that you can buy from SeviceNow. But there's also speculation that SeviceNow is leveraging its orchestration and service catalog capabilities, which are meaningful from a revenue standpoint and using them to power these workflows because the way it was organized was both confusing and not as effective as it could be. Now, it's well known that SeviceNow has ITSM this comprises the biggest piece of its revenue pie, probably a couple billion. And it's adding to that with ITSM pro and ITSM enterprise going deeper, deeper into the ITSM space. And it's ITAM business is also doing well against the likes of Datadog and Elastic and Splunk and others and its acquisition of LightStep. It's going to push it further into this space, which is both crowded is morphing into observability as we've been reporting. What's unclear though is how well, for instance, HR and the CSM businesses are doing as sort of standalone businesses, you might remember they used to be standalone businesses with standalone GMs. They've sort of changed that up a little bit. So this is potentially not only a way to simplify, but also shuffle the deck chairs a bit and maybe prop up the non IT workflows, which then allows SeviceNow to show this chart, which essentially says to the street, see, we have this huge TAM and our TAM expansion strategy is working as the overall business is growing nicely yet the mix is shifting toward customer, employee and creator workflows. See how awesome our business is and see how smart we are. So this is possibly a way to hide some of the warts and accentuate the growth. Look, there's not a lot to criticize SeviceNow about, but they've been pretty good at featuring what some perceive as weaknesses. Like for instance, the way it marketed it's a multi-instance and turned that into an advantage as a better model. Even though the whole cloud world was going multitenant and within a ServiceNow you got to really plan new releases, which they drop every six months, although CJ decide. So he's SeviceNows head of products. He did say at the investor meeting, that event that they held last May, that they do certain releases now bi-monthly and even some bi-weekly. So, yeah, maybe a little bit of nitpicking here, but I always liked to question when such changes are made to the reporting structures to the street. And if workflows are the new black, so to speak, I wonder will SeviceNow start pricing by workflows versus what really has been a legacy of, you know, what's your ticket volume and how many agents need access to the model and we'll charge you accordingly? Now, I'm not a service pricing expert and they don't make it easy to figure out that pricing. So let's dig a little bit more on that and keep an eye on it. Now I want to turn to the customers survey data from ETR on ServiceNow. First, here's the latest update on IT spending from ETR, something that we've been tracking for quite some time. We've been consistently saying to expect this year a seven to 8% growth for 2021 IT spend off of last year's contraction. And the latest ETR survey data puts it right at 8%. So we really liked that number. You know, could even be higher push 10% this year. Now, let's look at the spending profile within the ETR dataset. Of the 1100 plus respondents to this quarter, there were 377 SeviceNow customers, and this chart shows the breakdown of net score or spending velocity among those respondents. Remember, net score is a measure of that spending momentum. What it does is it takes the lime green bar, which is adopting new, that says 11% of that 377 customers are adopting ServiceNow for the first time. It takes that lime green and it adds the forest green bar that's growth in spending of 6% or more this half relative to the first half. That's 43% of the customers that have been surveyed here. And then it subtracts out the reds, which is that pinkish is spending less, that's 3%, small number of spending less. And then the bright red is we're leaving the platform. That's a minuscule 1% of the respondents. And you can see the rest in that gray area is flat spending, which is ignored. And so what this does is it calculates out, you'd take the greens minus the reds. It calculates out to a net score 50% for SeviceNow, which is well above that magic 40% elevated mark that we'd like to see. It's rare for a company of this size, except for the hyperscalers. You see AWS and Microsoft and Google are up that high and oh, there's another great enterprise software company at the 45% net score level. Guess who that is, salesforce.com. But anyway, it's rare to see that large of a company have that much spending momentum in the ETR surveys. Now let's take a look at the time series data for ServiceNow. This chart shows the net score granularity over time. So you see the bars, that time series, the blue line is net score. And you can see that it was dragged down during last year's lockdown. As, even though SeviceNow did pretty well last year and it's now spiking back to pre-COVID levels, which is a very positive sign for the company. That red call-out that ETR makes it shows market share. That's an indicator of pervasiveness in the dataset. I'm not overlyconcern there that downturn. I don't think it's a meaningful indicator because ServiceNow revenue is skewed towards a big spender accounts and this is an account unit indicator, if you will not spending level metric. And okay, and here's another reason and why I'm not concerned about SeviceNow is a so-called market share number in the ETR dataset as ETR defines it. This is an X, Y Z view chart that we'd like to show here. We've got net score on the vertical axis and market share in the horizontal plane. This is focusing on enterprise software. So remember that 40% red line is the magic level, anything above that is really indicative of momentum. Oh look, there's Salesforce and ServiceNow on that little collision course that I talked about. Now, CEO McDermott, I would say as by the way, would his predecessors, look, we're a platform of platforms and we partner with other companies, we'll meet at the customer level and sure we'll integrate functions where we think it can add value to customers. But we also understand we have to work with the vendors that our customers are using. So it's all good, plenty of room for growth for all of us, which by the way is true. But I would say this, anyone who's ever been in the enterprise software industry knows that enterprise software execs and their salespeople believe that every dollar spent on software should go to them. And if it's a good market with momentum and growth, they believe they can either organically write software to deliver customer function and value, or they can acquire to fill gaps. So, well, what McDermott would say is true. The likes of Oracle, Microsoft, SAP, Salesforce, Infor, et cetera, they all want as big of a budget piece as possible in the enterprise software space. That's just the way it is. Now, we're going to close with some anecdotal comments from ETR insights, formerly called VENN, which is a round table discussion with CXOs. You can read the summaries when we post on Wikibon and SiliconANGLE but let me summarize. This first comment comes from an assistant VP in retail who says SeviceNow is a key part of their digital transformation. They moved off of BMC remedy two years ago for the global ticketing system. And this person is saying that while the platform is extremely powerful, you got to buy into specific modules to just get one feature that you want. You may not need a lot of the other features, so it starts to get expensive. The other thing this individual is saying is initially, it's a very services heavy project. And so I'll tell you, when you look at the SeviceNow ecosystem the big SIs, the big names, they have big appetites. They love to eat at the trough as I sometimes say, and they want big clients with big budgets. So if you're not one of those top 500 or 700 customers, the big name SIs, you know, they might not be for you. They're not going to pay attention to you. They're going after the big prizes. So what I would suggest is you call up someone like Jason Wojahn of third era, he's the CEO over there and he's got a lot of experience in this space or some more specialized SeviceNow consultancy like them because you're going to get better value for the money. And you're going to get short-term ROI faster with a long-term sustainable ROI as a measurable objective. And I think this last comment sums it up nice, let me to skip over the second one and go just jump to the third one. This basically says the platform is integrated. It's like a mesh. It's not a bunch of stovepipes and cul-de-sacs. Yes it's expensive, but people love it. And like the iPhone, it just works. And their feature pace is accelerating. So pretty strong testimonials, but I want to keep an eye on price transparency any possible backlash there and how the ecosystem evolves. It's something that we called out early on. It's an indicator and SeviceNow needs to continue to invest in that partner network is especially as it builds out its vertical industry practices and expands internationally. Okay, we'll leave it there for now. Remember I publish each week on wikibon.com and siliconangle.com. These episodes they're all available as podcasts. All you got to do is search for breaking analysis podcast. You can always connect with me on Twitter @DVellante or email me @david.vellantesiliconangle.com. Appreciate the comments on LinkedIn. And don't forget to check out etr.plus for all the survey data. This is Dave Vellante for theCUBE insights powered by ETR. Be well, and we'll see you next time. (upbeat music)

>>Hello everyone. Thank you, add appreciating the studio. We're here at the cube here in cloud city telco DRS Cloud city. I'm Jeffrey Day Volonte. We're here for the next three days. Wall to wall live coverage. It's a physical event with a virtual program. It's hybrid. We're here with Daniel Royston, the Ceo of telco D. R. And the acting Ceo Toby, which is announced today. Great >>to see you. It's awesome to see you guys. >>Awesome to see how you doing, how you >>Feeling? I'm feeling congratulations. Right. 101 days ago, I didn't even think this doesn't exist. Right. And we got in contact with you guys and we said we knew there was always going to be a big virtual component and we invited you guys and here we are together. It's insane. >>Well we did the preview videos, but we're kind of walking through and document in the early stages. It all came together beautifully spectacular For the folks watching behind us is the most spectacular build out clouds. It's an ecosystem open concept. It feels like the Apple store meets paradise. Of course. We got the cube here in the set and we got the studio with all the command and control of adam there. So I gotta ask you with the connected keynotes going on right now. The connected world. Yeah. It's connected. We all know that everyone knows that what's, what's different now real quick before we get into the program, what's going on? >>Yeah. I think a big part of my messages and advocating it's more than just the network, Right? And I think telcos forever have relied on. That's all it is. That's what it's about. And I'm like, nope, you guys got to start focusing on your subscribers, right? And so the over the top players keep coming in and siphoning away their revenue and it's time for them to start focusing on us, right and making experience great. And I think that's what this is all about. >>So we're gonna get the news but I want to toss it to Katie. The roving reporter is going to give it a detail on how it all came together. So Katie take it away. >>Mhm We're here in Barcelona and so excited to be back in this beautiful city over at the convention center. The team is working hard putting the finishing touches to tell Cody are amazing cloud city booth at MwC Barcelona 2021. I'm sure you know the story of how this all came together as one of the biggest vendors Erickson pulled out of M. W. C. With just over 100 days until the start of the event. When this happened last year, it kicked off a tidal wave of departures and MwC was called off this year. We all wondered if MWC was going to be cancelled again and that's when Daniel Royston Ceo of Telco D. R. And Tito G swooped in and took over the booth all 6000 square meters of it. The plan turn the booth into cloud city, the epicenter of public cloud innovation at MWC crews have been working around the clock. Over 100 and 50 people have been on this construction site for over three weeks with covid testing every day to prevent outbreaks during the build and in 100 days, it's become just that Cloud city has over 30 vendors presenting over 70 demos with 24 private meeting areas. Cloud City Live is a virtual showcase and live broadcast studio featuring 50 guests from cloud Thought leaders around the world. They have telepresence robots for a more personalized experience and the Cloud city quest game with a chance to win more than $100,000 to gain access to live streams of our nightly concerts with rosario flores and rock legend Jon bon Jovi. And don't forget to visit cloud city dot telco D R dot com to join in on the fun Daniel Royston and Nacho Gomez, founder and Ceo of one of the key vendors in the construction of the booth gave us a behind the scenes tour of the booth. >>Nacho. We did it. Yeah, we did. It can't even touch because of Covid. Yeah, but look what we did. But right, 100 days ago I called and I said I'm taking over the Ericsson booth. What did you think? I know you were crazy but just a little bit crazy, realized that you were mortgages than I thought. So at the very, at the very beginning I thought, yeah, she's crazy. But then I couldn't sleep that night. But the next uh then I realized that it was a very good it's a great idea. Yeah super smart. So yeah we're gonna show everyone toward the booth. Yeah let's go. Let's go. Okay So how do we build such an amazing, beautiful building now? So this is we've made building inside a book. So it was very hard to find a glassful of facade. The roof is around 24 tones. Yeah so it's crazy crazy but we made it work and it's totally amazing. Yeah. Do you want to go to tragedy life? Do let's go. Okay so here we are Cloud city live. I know we're producing a whole live streaming tv show. We always knew because of covid that not everyone will be able to come to Mwc as we wanted to make sure that people can learn about the public cloud. So over here we have the keynote stage, we're gonna have awesome speakers talking all throughout M. W. C. People from AWS Microsoft, google vendors companies. So really really great content. And then over there we have the cube interviewing people again 15 minute segments, live streaming but also available on demand. And you can find all of this content on cloud city. Tell Cody are calm and it's available for anyone to you. Well, a lot of content. And what about the roberts? I never get them out. Come on. We remember 100 days ago we were locked down. So we came up with the idea of having robots for the people who cannot attend in person. I know right. We always knew that there was gonna be a big virtual component to MWC this year. So we bought 100 telepresence robots. It's a great way to have a more personal experience inside the boot. Just sign up for one on cloud city dot telco D r dot com and you can control it yourself. Right? So today we have Nikki with us, who's dialing in from the Philippines in Manila? Hello, Nicky. Hi there, how are you? I were great. Can you show us a twirl all gaining on us? Super cool. Yeah, it is. What an experience. So Nikki robots are not the only cool thing we have in cloud city. We also have super awesome concert. We have rosario flores on monday. Who's a latin grammy award winner. We have Jon bon Jovi, Jon bon Jovi on Tuesday, can't be changing telephone that a little bit of rock n roll and that's Tuesday. And on Wednesday we have DJ official, it's going to be a super party. Now if you play our cloud city quest on cloud city telco D R dot com you can participate in a live streaming concert and so I know a lot of people out there have been a lockdown. Haven't been able to be going to concerts. Things from austin texas, which is the live music capital of the world, How to have music. It would be so exciting is gonna be great. I'm getting hungry. Why don't we go to the restaurant? Let's go eat. Let's go. Yeah, Here is our awesome restaurant. I know it's called Cloud nine. Right? It's a place to come and sit down and relax now. Barcelona is known for its great food and I'm a foodie. So we had to have a restaurant. Should we go check out my secret bar? Let's go. Mhm. Yeah, here >>thanks to a R. And thank you Nacho if you're watching this at home, I'm so sorry you can't join us in person. However, let's not forget this is a hybrid event meaning we're bringing all the public cloud action right to you wherever in the world you might be. This includes the Pact cloud city live program. We've partnered with the cube Silicon angle Media's live streaming video studio to make sure that all of the keynotes, panel discussions, demos, case studies interviews and way more are available on demand so you can watch them whenever and wherever you want or you can live stream and enjoy all things cloud city as and when they happen. So for those of you not able to join us in, Barcelona, be sure to log in to cloud city live and catch all the action and don't miss the awesome concert Tuesday night with Jon bon Jovi available for free. If you participate in our cloud city quest game, I'll be here throughout MWc bringing you reports and updates. Stay >>tuned. Yeah. >>Mhm. Okay, we're back here on the cube on the floor at mobile world congress in cloud city telco DRS clouds. They were here with D. R. Of telco, D R. Danielle Rice and great to see you back, we're back. So the keynotes going on connected world, the big news here, I'll see the open shift that's happening is going open. Open ran, it's been a big thing. Open ran alliance. You're starting to see the industry come together around this clear mandate that applications are gonna be cloud native and the public cloud is just coming in like a big wave and people are gonna be driftwood or they'll be surfing the wave. Yeah, this is what's happening. >>Yeah, I think public cloud is an unstoppable megatrend. It's hit every other industry regulated industries like banking, right? Top secret industries like government. They all use the public cloud tells us the last, you know, standing old school industry and it's coming and I don't think we could have had an MWc without talking about open man. That's the other major shift. And so we're bringing both of those ideas here together in cloud city. So >>the big theme is telco transformation. Maybe we could start with the basics like paint a picture of what the telco infrastructure looks like, particularly the data center stuff because they all have big data centers >>because that's >>those are the candidates to go into the cloud explained to the audience. >>Well, do you have a time machine? I think if any of us were in tech in the late 90s and early 2000s, that's what telcos like today. Right. So for people outside of the industry don't know right there mostly still managing their own data centers, they're just sort of adopting virtualization. Some of the more advanced telcos are mostly virtualized public cloud. Is this idea that like this advanced thought and so yeah, I mean things are on premise, things are in silom, things don't use a P. I. S there all integrated with custom code. And so the transformation, we can all see it because we've lived it in other industries. And I'm bringing that to telco and say come along for the ride. It totally works and it's gonna be amazing. >>So it's hardened purpose built infrastructure. Okay. That ultimately parts of that need to go to the public cloud. Right. What parts do you see going first? >>I think all of it. Really. Yeah. And I think when you look at like dish in the W. S. Which was an announcement that came out about two months ago. Right. I mean dish was doing all these are FPs. Everyone knew about it. They were looking for a cloud native software and no one knew what they were. They knew a big part was open man. But their coupling open ran with AWS and deploying their parts of their network onto the public cloud and the whole industry is like wait we thought this was years away, right? Or number two, you're crazy. And I'm saying this is what I've been talking about guys. This is exactly what you can do, leverage the Capex over. Let's see. I think Amazon did $100 billion 2020 right, leverage that Capex for yourself. Get that infinite scalability right? It's going to, well we >>have, we have a saying here in the queue, we just made this up called D. R. That's your initial tucker. The digital revolution and the three Rs reset re platform and re factor. I think the observation we're seeing is that you're coming in with the narrative what everyone's kind of like they're waking up because they have to reset and then re platform with the cloud. But the opportunity is gonna be the re factoring, You're seeing the public cloud, do that already with the Enterprise Enterprises. Already re factoring has done that. Already done that now. Telcos the last area to be innovated by the cloud. >>Yeah, I think there's old school big, we're kind of on a hollowed ground here in the Ericsson booth that I took over, right? They bailed and I kind of made fun of them. I was like, they don't have anything to say, right, They're not going to go to the show. I'm like, this is this is a revolution that's happening in telco and I don't think the big guys are really interested in rewriting their software that frankly makes them billions and billions of dollars of revenue. And I'm like to use the public cloud. All of the software needs to be rewritten needs to be re factored and you've got to start training your teams on how to use it. They don't have any capability. The telcos, in terms of those skills hire the right people, retrain your teams, move your applications, rewrite them. And I think that's what we're talking, this is not a short journey, this is a 10 year journey. So >>let's fast forward to the future a little bit because when I look around cloud city, I see ecosystem everywhere. So as you well know, the telcos have generally done a poor job of attacking adjacent seas. So my question is can they go beyond should they go beyond connectivity or is that going to be the role of the ecosystem? >>Yeah, I think it's time that the telco starts to focus on their subscriber, right? It's been really easy for them to rely on the oligopoly of the network, Right? The network, we live in the United States, we see the 18 T Verizon T mobile five G network, five G network. Like what about us? Right. And it's really easy for the over the top players right, that come in and they're always, telcos are always complaining about being coming dumb pipes and I'm like, you don't focus on the customer, we would rather buy from an Apple and amazon if they provided a mobile service because the customer experience will be better. Right? They need to start focusing on us. They have great businesses but they want to make them better. They need to start focusing on the subscriber, so >>it's a partnership with the ecosystem then for them to go beyond just straight connectivity because you're right, those are the brands that we want to do business >>with. You know, there was a great survey, Peter Atherton who will be talking as a speaker I think um I can't remember when he's talking but he was talking about how there was a survey done, where would you rather get your mobile service from? And it had a couple of big names in telco and then of course the obvious, you know, consumer brands, the ones that we all know and it was like overwhelmingly would rather buy from an amazon or an apple. And I'm like, this is like if you guys don't change, right, if telco doesn't change they keep rolling out 60 and blah blah blah. It's about the network and I don't start making about the subscriber right? Those revenues are going to continue to erode and they just sit there and complain about the O. T. T. Players. Like it's time to fight back. Yeah, I own the subscriber >>relationship. It's a digital revolution and I think This event really encapsulates in my mind this hybrid world here because it's physical events back. It's been since 2019 winter that this event actually happened. >>Well no it was even longer than, well I guess winter it was February of 19, right? And so like you look at ericsson and some of the big names that dropped out of the show, the time they come back, three years will have passed three years, right? This is how you feel your sales funnel is how you connect with your customers right? Tokyo is a very global, you know experience and so you gotta, you gotta get in front of people and you got to talk a >>lot of change to its happened, look at just what public clouds done in 2.5 years. You imagine three years being just >>gone, right? And I think a lot of people back to edition A. W. S. I think the industry was a little bit surprised by that announcement. So I've been telling executives if you were surprised by that, if you think that's, you know, if you don't know how that's gonna work, you need to come to cloud cities, you start meeting all the vendors are here. We have over 30 vendors, 70 demos, right? People who are pushing the technology forward, you need to learn what's going on here. We have several dish vendors here. Come learn about open rand, come learn about public cloud. So >>we're tight on time today, but we're going to have you back and we want to get into the tech, Get it to open, ran a little bit, get into what 5G and beyond and how we're going to take advantage of that and monetize it and what that all means. >>And also we want to hear what's going on the hallways. I know you got a lot of your key noting, you're gonna be a lot of events, the yacht. You've got a lot of briefings, >>yep. Yeah, I've already had two meetings this morning. I shot a video. Um, I met with one of the world's largest groups and I met with a tiny little super app company. Right? So running the gamut, doing everything reporter >>now, we could be like our roaming >>reporter. You know, I love, I love talking to execs and telco getting their perspective on what is public cloud and where are they going, what are they thinking about? And you talked to people who really, really get it and you get people who are just nascent and everywhere in between and I love mwc it's going great. >>Daniel Rose and you are a digital revolution telco DDR. There's amazing. Davis has been fantastic. Again for the folks watching, this is a hybrid events, there's an online component and we're reaching out with our remote interviews to get people brought in and we're shipping this content out to the masses all over the world. It's gonna be really amazing cube coverages here. It's gonna be rocking you guys are doing great. I just want to give you a compliment that you guys just did an amazing job. And of course we've got adam in the studio with the team. So adam, I'm gonna pass it off back to you in the studio

>>from the cube studios in Palo alto in boston connecting with thought leaders all around the world. >>This is a cute conversation. Welcome to the cubes coverage of HP discover 2021 I'm lisa martin. I've got three guests with me here. They're going to be talking about the partnership between HP and AMG. Please welcome George hope worldwide Head of partner sales at HP terry, Richardson north american channel chief for AMG and Peter chan, the director of media channel sales at AMG Gentlemen, it's great to have you on the cube. >>Well, thanks for having us lisa. >>All right, >>we're excited to talk to you. We want to start by talking about this partnership terry. Let's go ahead and start with you. H P E and M D have been partners for a very long time, very long history of collaboration. Talk to us about the partnership >>HB named, He do have a rich history of collaboration spinning back to the days of chapter on and then when A M. D brought the first generation AMG equity process department back in 2017, HP was a foundational partner providing valuable engineering and customer insights from day one AmY has a long history of innovation that created a high performance CP roadmap for value partners like HP to leverage in their workload optimized product portfolios, maximizing the synergies between the two companies. We've kicked off initiatives to grow the chain of business together with workload focused solutions and together we define the future. >>Thanks terry George, let's get your perspective as worldwide had a partner sales at HP. Talked to me about H P S perspective of that AMG partnership. >>Yeah, they say it's uh the introduction of the third generation AMG Epic processors, we've we've doubled our A. M. D. Based Pro Lion portfolio. We've even extended it to our follow systems. And with this we have achieved a number of world records across a variety of workloads and are seeing real world results. The third generation am the epic processor delivers strong performance, expand ability and the security our customers need as they continue their digital transformation, We can deliver better outcomes and lay a strong foundation for profitable apartment growth. And we're incorporating unmatched workload optimization and intelligent automation with 360° security. And of course, uh with that as a service experience. >>But as a service experience becoming even more critical as is the security as we've seen some of the groundbreaking numbers and data breaches in 2020 alone. Peter I want to jump over to you now. One of the things that we see H P E and M. D. Talking about our solutions and workloads that are key areas of focus for both companies. Can you explain some of those key solutions and the value that they deliver for your customers? >>Absolutely. It's from computing to HPC to the cloud and everything in between and the young HB have been focused on delivering not just servers but meaningful solutions that can solve customer challenges. For example, we've seen here in India, the DL- 325 has been really powerful for customers that want to deploy video. Hp nmD have worked together with icy partners in the industry to tune the performance and ensure that the user experience is exceptional. Um This just one example of many of course, for instance, the 3 45 with database 3 65 for dense deployments, it's key the 35 That has led the way in big data analytics. Um the Apollo 60 500 breaking new path in terms of AI and Machine learning, quite a trending topic and m D H p are always in the news when it comes to groundbreaking HPC solutions and oh by the way, we're able to do this due to an unyielding commitment to the data center and long term laser focused execution on the M the road map. >>Excellent. Thanks. Peter. Let's talk about the channel expansion a little bit more terry with you. You know, you and the team here. Channel Chief focused on the channel. What is A. M. D. Doing specifically to expand your channel capabilities and support all of the Channel partners that work with Andy >>great question lisa Campbell is investing in so many areas around the channel. Let's start with digital transformation. Our Channel partners consistently provided feedback that customers need to do more with less between A and B and H P. E. We have solutions that increase capabilities and deliver faster time to value for the customer looking to do more with less. We have a tool on our website called the and metrics server virtualization, Tco estimation tool and those who have visually see the savings. We also have lots of other resources such as technical documentation, A and E arena for training and general CPU's departments can take advantage of aside from solution examples, AMG is investing in headcount internally and at our channel part race. I'm actually an example of the investment MD is making to build out the channel. One more thing that I'll mention is the investment that are, you know, lisa su and Andy are making to build out the ecosystem from head Count to code development and is investing to have a more powerful user experience with our software partners in the ecosystem. From my discussions with our channel partners, they're glad to see A and d expanding our our channel through the many initiatives and really bringing that ecosystem. >>Here's another question for you as channel chief. I'm just curious in the last year, speaking and you talked about digital transformation. We've seen so much acceleration of the adoption of that since the last 15 months has presented such challenges. Talk to me a little bit about some of the feedback from your channel partners about what you am, D N H B are doing together to help those customers needed to deliver that fast time to value, >>you know, so really it's all about close collaboration. Um we we work very closely with our counterparts at H P. E just to make sure we understand partner and customer requirements and then we work to craft solutions together from engaging, technically to collaborating on on, you know, when products will be shipped and delivered and also just what are we doing to uh to identify the next key workloads and projects that are going to be engaged in together? So it's it's really brought the companies I think even closer together, >>that's excellent as a covid catalyst. As I say, there's a lot of silver linings that we've seen and it sounds like the collaboration terry that you mentioned has become even stronger George. I want to go to you. Let's HP has been around for a long time. My first job in tech was Hewlett Packard by the way, many years ago. I won't mention how long but talk to me about the partnership with AMG from H P s perspective, is this part of H P S D N A? >>Absolutely. Partnering is our D N A. We've had 80 years of collaboration with an ever expanding ecosystem of partners that that all play a key role in our go to market strategy. We actually design and test our strategic initiatives in close collaboration with our partners so that we can meet their most pressing needs. We do that through like farmer advisory boards and things of that nature. Um but we have we have one of the most profitable partner programs in the industry, 2-3 times higher rebates than most of our competitors. And we continue to invest in the partner experience in creating that expertise so partners can stand out in a highly competitive market. Uh And Andy is in direct alignment with that strategy. We have strong synergies and a common focus between the two companies. >>And I also imagine George one question and one question to that there's tremendous value in it for your end user customers, especially those that have had to everyone pivot so many times in the last year and have talked to me a little bit about George What you're saying from the customer's perspective. >>Well as Antonio Neri said a couple of years back, the world is going to be hybrid and uh, he was right. We continue uh we continue to see that evolution and we continue to deliver solutions around a hybrid digital world with, with Green Lake and the new wave of digital transformation that we refer to now as the age of insight customers want a cloud experience everywhere. And 70% of today's workloads can easily be re factored for the public cloud or they need to stay physically close to the data and other apps at the emerging edge or in polos are in the data centers. So as a result, most organizations are forced to deal with the complexity of having two divergent operating models and they're paying higher cost to maintain them both with Green Lake, we provide one consistent operating model with visibility and control across public clouds and on prem environments. And that applies to all workloads, you know, whether it's cloud native or non cloud native applications. Um we also have other benefits like no cloud block in or no data. Egress charges, so you have to pay a steep price just to move workloads out of the public cloud. And then we're expanding collaboration opportunities within for our partner ecosystem so that we can bring that cloud experience to a faster growing number of customers worldwide. So we've launched new initiatives uh in support of the core strategy as we accelerate our as a service vision and then work with partners to unlock better customer outcomes with Green Lake and of course, hb compute of which I am d is part of is, is the underlying value added technology. >>Can you expand on some of those customer outcomes as we look at, as I mentioned before, this very dynamic market in which we live. It's all about customer outcomes. What are some of those that from a hybrid cloud environment perspective with Green like that you're helping customers achieve? >>Well, at least Greenland has come out with with about 30 different different offerings that package up some solutions. So you're not just buying infrastructure as a service. We have offerings like HPC as a service. We have offerings like uh, V D I as a service, ml, ops as a service. So we're packaging in technology, some are are some are not ours, but into completing some solutions. So that creates the outcome that the customers are looking for. >>Excellent. Thanks, George and Peter, last question to you again with the hybrid cloud environment being something that we're seeing more and more of the benefits that Green Lake is delivering through the channel. What's your perspective from a. M decide? >>Absolutely lisa. So, so I mean I think it's clear with a MD based systems, customers get the benefit of performance, security and fast time to value whether deployed on prem and cloud on a hybrid model. So please come try out our HP system based on name the processors and see how we can accelerate and protect your applications. Thank you lisa. >>Excellent, Peter George terry, thank you for joining me today. I'm sure there's a lot more that folks are going to be able to learn about what AM D and H. P. Are doing together on the virtual show floor. We appreciate your time. Thank you. Yeah, for my guests, I'm lisa martin. You're watching the cubes coverage of HP discover 2021 Yeah.

>>from around the globe it's the >>cube >>presenting >>Future Cloud one event. A >>world of >>opportunities >>brought to you by Cisco. We're here with Dejoy Pandey a VP of emerging tech and incubation at Cisco. V. Joy. Good to see you welcome. >>Good to see you as well. Thank you Dave and pleasure to be here. >>So in 2020 we kind of had to redefine the notion of agility when it came to digital business or you know organizations, they had to rethink their concept of agility and business resilience. What are you seeing in terms of how companies are thinking about their operations in this sort of new abnormal context? >>Yeah I think that's a great question I think what what we're seeing is that pretty much the application is the center of the universe and if you think about it the application is actually driving brand recognition and the brand experience and the brand value. So the example I like to give is think about a banking app uh recovered that did everything that you would expect it to do. But if you wanted to withdraw cash from your bank you would actually have to go to the ATM and punch in some numbers and then look at your screen and go through a process and then finally withdraw cash. Think about what that would have, what that would do in a post pandemic era where people are trying to go contact less. And so in a situation like this the digitization efforts that all of these companies are going through and the modernization of the automation is what is driving brand recognition, brand trust and brand experience. >>Yeah. So I was gonna ask you when I heard you say that, I was gonna say well but hasn't it always been about the application? But it's different now, isn't it? So I wonder if you talk more about how the application is experience is changing? Yes. As a result of this new digital mandate. But how should organizations think about optimizing those experiences in this new world? >>Absolutely. And I think, yes, it's always been about the application, but it's becoming the center of the universe right now because all interactions with customers and consumers and even businesses are happening through that application. So if the application is unreliable or if the application is not available is untrusted insecure, uh, there's a problem. There's a problem with the brand with the company and the trust that consumers and customers have with our company. So if you think about an application developer, the weight he or she is carrying on their shoulders is tremendous because you're thinking about rolling features quickly to be competitive. That's the only way to be competitive in this world. You need to think about availability and resiliency, like you pointed out and experience, you need to think about security and trust. Am I as a customer or consumer willing to put my data in that application? So velocity availability, security and trust and all of that depends on the developer. So the experience, the security, the trust, the feature velocity is what is driving the brand experience now. >>So are those two tensions that say agility and trust, you know, zero trust used to be a buzzword now, it's a mandate. But are those two vectors counter posed? Can they be merged into one and not affect each other? Does the question makes sense? Right? Security usually handcuffs my speed. But how do you address that? >>Yeah, that's a great question. And I think if you think about it today, that's the way things are. And if you think about this developer, all they want to do is run fast because they want to build those features out and they're going to pick and choose a purpose and services that matter to them and build up their app and they want the complexities of the infrastructure and security and trust to be handled by somebody else is not that they don't care about it, but they want that abstraction so that is handled by somebody else. And typically within an organization we've seen in the past where there's friction between Netapp, Succop cited hopes and the cloud platform teams and the developer on one side and these these frictions and these meetings and toil actually take a toll on the developer and that's why companies and apps and developers are not as agile as they would like to be. So I think, but it doesn't have to be that way. So I think if there was something that would allow a developer to pick and choose, discover the apis that they would like to use, connect those api is in a very simple manner and then be able to scale them out and be able to secure them and in fact not just secure them during the run time when it's deployed, we're right off the back when the fire up that I'd and start developing the application, wouldn't that be nice? And as you do that, there is a smooth transition between that discovery connectivity and ease of consumption and security with the idea cops, netapp psych ops teams and see source to ensure that they are not doing something that the organization won't allow them to do in a very seamless manner. >>I want to go back and talk about security but I want to add another complexity before we do that. So for a lot of organizations in the public cloud became a staple of keeping the lights on during the pandemic. But it brings new complexities and differences in terms of latency security, which I want to come back to deployment models etcetera. So what are some of the specific networking challenges that you've seen with the cloud? Native architecture is how are you addressing those? >>Yeah. In fact, if you think about cloud, to me that is a that is a different way of seeing a distributed system. And if you think about a distributed system, what is at the center of the distributed system is the network. So my my favorite comment here is that the network is the wrong time for all distribute systems and modern applications. And that is true because if you think about where things are today, like you said, there's there's cloud assets that a developer might use in the banking example that I gave earlier. I mean if you want to build a contact less app so that you get verified, a customer gets verified on the app. They walk over to the ATM and they were broadcast without touching that ATM. In that kind of an example, you're touching the mobile Rus, let's say, Ohio escapees, you're touching Cloud API is where the back end might sit, you're touching on primary purpose, maybe it's an oracle database or a mainframe even where transactional data exists, you're touching branch pipes were the team actually exists and the need for consistency when you withdraw cash and you're carrying all of this and in fact there might be customer data sitting in Salesforce somewhere. So it's cloud API is a song premise branch, it's ass is mobile and you need to bring all of these things together and over time you will see more and more of these API is coming from various as providers. So it's not just cloud providers but saAS providers that the developer has to use. And so this complexity is very very real and this complexity is across the wide open internet. So the application is built across this wide open internet. So the problems of discovery ability, the problems of being able to simply connect these apis and manage the data flow across these apis. The problems of consistency of policy and consumption because all of these areas have their own nuances and what they mean, what the arguments mean and what the A. P. I. Actually means. How do you make it consistent and easy for the developer? That is the networking problem. And that is a problem of building out this network, making traffic engineering easy making policy easy, making scale out, scale down easy, all of that our networking problems. And so we are solving those problems. Uh Francisco >>Yeah the internet is the new private network but it's not so private. So I want to go back to security. I often say that the security model of building a moat, you dig the moat, you get the hardened castle that's just outdated now that the queen is left her castle. I always say it's dangerous out there. And the point is you touched on this? It's it's a huge decentralized system and with distributed apps and data, that notion of perimeter security, it's just no longer valid. So I wonder if you could talk more about how you're thinking about this problem and you definitely address some of that in your earlier comments. But what are you specifically doing to address this? And how do you see it evolving? >>Yeah, I mean that that's that's a very important point. I mean I think if you think about again the wide open internet being the wrong time for all modern applications, what is perimeter security in this uh in this new world? I mean it's to me it boils down to securing an API because again, going with that running example of this contact lists cash withdrawal feature for a bank. The FBI wherever it sits on tram branch sas cloud, IOS android doesn't matter that FBI is your new security perimeter and the data object that is trying to access is also the new security perimeter. So if you can secure ap to ap communication and P two data object communication, you should be good. So that is the new frontier. But guess what? Software is buggy? Everybody's software not saying Cisco software, everybody's Softwares buggy. Uh software is buggy, humans are not reliable and so things mature, Things change, Things evolve over time. So there needs to be defense in depth. So you need to secure at the API layer had the data object layer, but you also need to secure at every layer below it so that you have good defense and depth if any layer in between is not working out properly. So for us that means ensuring ap to ap communication, not just during long time when the app has been deployed and is running, but during deployment and also during the development life cycle. So as soon as the developer launches an ID, they should be able to figure out that this API is security uses reputable. It has compliant, it is compliant to my my organization's needs because it is hosted, let's say from Germany and my organization wants a P is to be used only if they are being hosted out of Germany. So compliance needs and and security needs and reputation. Is it available all the time? Is it secure and being able to provide that feedback all the time between the security teams and the developer teams in a very seamless real time manner? Yes, again, that's something that we're trying to solve through some of the services that we're trying to produce in SAN Francisco. >>Yeah, I mean those that layered approach that you're talking about is critical because every layer has, you know, some vulnerability and so you you've got to protect that with some depth in terms of thinking about security, how should we think about where where Cisco's primary value add is, I mean it's parts of the interview has a great security business. Is growing business. Is it your intention to to to to add value across the entire value chain? I mean obviously you can't do everything so you've got a partner but so has the we think about Cisco's role over the next I'm thinking longer term over the over the next decade. >>Yeah, I mean I think so. We do come in with good strength from the runtime side of the house. So if you think about the security aspects that we haven't played today, uh there's a significant set of assets that we have around user security around around uh with with do and password less. We have significant assets in random security. I mean the entire portfolio that Cisco brings to the table is I don't run time security. The security checks aspects around posture and policy that will bring to the table. And as you see, Cisco evolve over time, you will see us shifting left. I mean I know it's an overused term, but that is where security is moving towards. And so that is where api security and data security are moving towards. So learning what we have during runtime. Because again, runtime is where you learn what's available and that's where you can apply all of the M. L. And I models to figure out what works what doesn't taking those learnings, Taking those catalogs, taking that reputation database and moving it into the deployment and development life cycle and making sure that that's part of that entire they have to deploy to runtime chain is what you will see Cisco do overtime. >>That's fantastic phenomenal perspective video. Thanks for coming on the cube. Great to have you and look forward to having you again. >>Absolutely. Thank you. Pleasure to be here. >>This is Dave Volonte for the cube. Thank you for watching. Mhm. >>Mhm mm.

>>Hello and welcome back to the cubes coverage of dr khan 2021. I'm john for your host of the cube. Great guests here cube alumni Stephen Chin, vice president of developer relations for jay frog Stephen, great to see you again this remote this time this last time was in person. Our last physical event. We had you in the queue but great to see you. Thanks for coming in remotely. >>No, no, I'm very glad to be here. And also it was, it was awesome to be in person at our s a conference when we last talked and the last year has been super exciting with a whole bunch of crazy things like the I. P. O. And doing virtual events. So we've, we're transitioning to the new normal. We're looking forward to things getting to be hybrid. >>Great success with jay frog. We've been documenting the history of this company, very developer focused the successful I. P. O. And just the continuation that you guys have transitioned beautifully to virtual because you know, developer company, it runs virtual, but also you guys have been all about simplicity for developers and and we've been talking for many, many years with you guys on this. This is the theme that dr khan again, this is a developer conference, not so much an operator conference, but more of a deva deV developer focused. You guys have been there from the beginning, um nationally reported on it. But talk about jay Frog and the Doctor partnership and why is this event so important for you? >>Yeah. So I think um like like you said, jay Frog has and always is a developer focused company. So we we build tools and things which which focus on developer use cases, how you get your code to production and streamlining the entire devoPS pipeline. And one of the things which which we believe very strongly in and I think we're very aligned with with doctor on this is having secure clean upstream dependencies for your Docker images for other package and language dependencies and um you know, with the announcement of dr khan and dr Hubbs model changing, we wanted to make sure that we have the best integration with doctor and also the best support for our customers on with Docker hub. So one of the things we did strategically is um, we um combined our platforms so um you can get the best in class developer tools for managing images from Docker. Um everyone uses their um desktop tools for for building and managing your containers and then you can push them right to the best container registry for managing Docker Images, which is the jay frog platform. And just like Docker has free tools available for developers to use. We have a free tier which integrates nicely what their offerings and one of the things which we collaborate with them on is for anybody using our free tier in the cloud. Um there's there's no limits on the Docker images. You can pull no rate limiting, no throttling. So it just makes a clean seamless developer experience to to manage your cloud native projects and applications. >>What's the role of the container registry in cloud NATO? You brought that up? But can you just expand on that point? >>Yeah. So I think when you when you're doing deployments to production, you want to make sure both that you have the best security so that you're making sure that you're scanning and checking for vulnerabilities in your application and also that you have a complete um traceability. Basically you need a database in a log of everything you're pushing out to production. So what container registries allow you to do is um they keep all of the um releases all of the Docker images which are pushing out. You can go back and roll back to a previous version. You can see exactly what's included in those Docker images. And we jay frog, we have a product called X ray which does deep scanning of container images. So it'll go into the Docker Image, it'll go into any packages installed, it'll go into application libraries and it does kind of this onion peel apart of your entire document image to figure out exactly what you're using. Are there any vulnerabilities? And the funny thing about about Docker Images is um because of the number of libraries and packages and installed things which you haven't given Docker Image. If you just take your released Docker Image and let it sit on the shelf for a month, you have thousands of vulnerabilities, just just buy it um, by accruing from different reported zero day vulnerabilities over time. So it's extremely important that you, you know what those are, you can evaluate the risk to your organization and then mitigated as quickly as possible. If there is anything which could impact your customers, >>you bring up a great point right there and that is ultimately a developer thing that's been, that's generational, you know what generation you come from and that's always the problem getting the patches in the old days, getting a new code updated now when you have cloud native, that's more important than ever. And I also want to get your thoughts on this because you guys have been early on shift left two years ago, shift left was not it was not a new thing for you guys ever. So you got shift left building security at the point of coding, but you're bringing up a whole another thing which is okay automation. How do you make it? So the developments nothing stop what they're doing and then get back and say, okay, what's out there and my containers. So so how do you simplify that role? Because that's where the partnership, I think really people are looking to you guys and Dakar on is how do you make my life easier? Bottom line, what's it, what's it, what's it about? >>Yeah. So I I think when you when you're looking at trying to manage um large applications which are deployed to big kubernetes clusters and and how you have kind of this, this um all this infrastructure behind it. One of the one of the challenges is how do you know what you have that in production? Um So what, how do you know exactly what's released and what dependencies are out there and how easily can you trace those back? Um And one of the things which we're gonna be talking about at um swamp up next week is managing the overall devops lifecycle from code all the way through to production. Um And we we have a great platform for doing package management for doing vulnerability scanning, for doing um ci cd but you you need a bunch of other tools too. So you need um integrations like docker so you can get trusted packages into your system. You need integrations with observe ability tools like data, dog, elastic and you need it some tools for doing incident management like Patriot duty. And what we've, what we've built out um is we built out an ecosystem of partner integrations which with the J frog platform at the center lets you manage your entire and and life cycle of um devops infrastructure. And this this addresses security. It addresses the need to do quick patches and fixes and production and it kind of stitches together all the tools which all of the successful companies are using to manage their fast moving continuous release cycle, um and puts all that information together with seamless integration with even developer tools which um which folks are using on a day to day basis, like slack jeer A and M. S. Teams. >>So the bottom line then for the developer is you take the best of breed stuff and put it, make it all work together easily. That right? >>Yeah. I mean it's like it's seamless from you. You've got an incidents, you click a button, it sticks Ajira ticket in for you to resolve. Um you can tie that with the code, commits what you're doing and then directly to the security vulnerability which is reported by X ray. So it stitches all these different tools and technologies together for a for a seamless developer experience. And I think the great relationship we have with Docker um offers developers again, this this best in class container management um and trusted images combined with the world's best container registry. >>Awesome. Well let's get into that container issue products. I think that's the fascinating and super important thing that you guys solve a big problem for. So I gotta ask you, what are the security risks of using unverified and outdated Docker containers? Could you share your thoughts on what people should pay attention to because if they got unverified and outdated Docker containers, you mentioned vulnerabilities. What are those specific risks to them? >>Yeah, so I there's there's a lot of um different instances where you can see in the news or even some of the new government mandates coming out that um if you're not taking the right measures to secure your production applications and to patch critical vulnerabilities and libraries you're using, um you end up with um supply chain vulnerability risks like what happened to solar winds and what's been fueling the recent government mandates. So I think there's a there's a whole class of of different vulnerabilities which um bad actors can exploit. It can actually go quite deep with um folks um exploiting application software. Neither your your company or in other people's systems with with the move to cloud native, we also have heavily interconnected systems with a lot of different attack points from the container to the application level to the operating system level. So there's multiple different attack vectors for people to get into your software. And the best defense is an organization against security. Vulnerabilities is to know about them quickly and to mitigate them and fix them in production as quickly as possible. And this requires having a fast continuous deployment strategy for how you can update your code quickly, very quick identification of vulnerabilities with tools like X ray and other security scanning tools, um and just just good um integration with tools developers are using because at the end of the day it's the developers who both are picking the libraries and dependencies which are gonna be pushed into production and also they're the ones who have to react and and fix it when there's a uh production incident, >>you know, machine learning and automation. And it's always, I love that tech because it's always kind of cool because it's it's devops in action, but you know, it's it's not like a silver bullet, your machine, your machine learning is only as good as your your data and the code is written on staying with automation. You're not automating the right things or or wrong things. It's all it's all subjective based on what you're doing and you know Beauty's in the eye of the beholder when you do things like that. So I wanna hear your thoughts on on automation because that's really been a big part of the story here, both on simplicity and making the load lighter for developers. So when you have to go out and look at modifying code updates and looking at say um unverified containers or one that gets a little bit of a hair on it with with with more updates that are needed as we say, what do you what's the role of automation? How do you guys view that and how do you talk to the developers out there when posturing for a strategy on and a playbook for automation? >>Yeah, I think you're you're touching on one of the most critical parts of of any good devops um platform is from end to end. Everything should be automated with the right quality gates inserted at different points so that if there's a um test failure, if you have a build failure, if you have a security vulnerability, the the automatic um points in there will be triggered so that your release process will be stopped um that you have automated rollbacks in production um so that you can make sure that their issues which affect your customers, you can quickly roll back and once you get into production um having the right tools for observe ability so that you can actually sift through what is a essentially a big data problem. So with large systems you get so much data coming back from your application, from the production systems, from all these different sources that even an easy way to sift through and identify what are the messages coming back telling you that there's a problem that there's a real issue that you need to address versus what's just background noise about different different processes or different application alerts, which really don't affect the security of the functionality of your applications. So I think this this end to end automation gives you the visibility and the single pane of glass to to know how to manage and diagnose your devops infrastructure. >>You know, steve you bring up a great point. I love this conversation because it always highlights to me why I love uh Coop Con and Cloud Native con part of the C N C F and dr khan, because to me it's like a microcosm of two worlds that are living together. Right? You got I think Coop khan has proven its more operated but not like operator operator, developer operators. And you got dr khan almost pure software development, but now becoming operators. So you've got that almost those two worlds are fusing together where they are running together. You have operating concerns like well the Parachute open, will it work? And how do I roll back these roll back? These are like operating questions that now developers got to think about. So I think we're seeing this kind of confluence of true devops next level where you can't you can be just a developer and have a little bit of opposite you and not be a problem. Right? Or or get down under the under the hood and be an operator whenever you want. So they're seeing a flex. What's your thoughts on this is just more about my observation kind of real time here? >>Yeah, so um I think it's an interesting, obviously observation on the industry and I think you know, I've been doing DEVOPS for for a long time now and um I started as a developer who needed to push to production, needed to have the ability to to manage releases and packages and be able to automate everything. Um and this naturally leads you on a path of doing more operations, being able to manage your production, being able to have fewer incidents and issues. Um I think DEVOPS has evolved to become a very complicated um set of tools and problems which it solves and even kubernetes as an example. Um It's not easy to set up like setting up a kubernetes cluster and managing, it is a full time job now that said, I think what you're seeing now is more and more companies are shifting back to developers as a focus because teams and developers are the kingmakers ends with the rise of cloud computing, you don't need a full operations team, you don't need a huge infrastructure stack, you can you can easily get set up in the cloud on on amazon google or as your and start deploying today to production from from a small team straight from code to production. And I think as we evolve and as we get better tools, simpler ways of managing your deployments of managing your packages, this makes it possible for um development teams to do that entire site lifecycle from code through to production with good quality checks with um good security and also with the ability to manage simple production incidents all by themselves. So I think that's that's coming where devoPS is shifting back to development teams. >>It's great to have your leadership and your experience. All right there. That's a great call out, great observation, nice gym there. I think that's right on. I think to get your thoughts if you don't mind going next level because you're, you're nailing what I see is the successful companies having these teams that could be and and workflows and have a mix of a team. I was talking about Dana Lawson who was the VP of engineering get up and she and I were riffing on this idea that you don't have to have a monolithic team because you've got you no longer have a monolithic environment. So you have this microservices and now you can have these, I'm gonna call micro teams, but you're starting to see an SRE on the team, that's the developer. Right? So this idea of having an SRE department maybe for big companies, that could be cool if you're hyper scalar, but these development teams are having certain formations. What's your observation to your customer base in terms of how your customers are organizing? Because I think you nailed the success form of how teams are executing because it's so much more agile, you get the reliability, you need to have security baked in, you want end to end visibility because you got services starting and stopping. How are teams? How are you seeing developers? What's the state of the art in your mind for formation? >>Yeah, so I think um we we work with a lot of the biggest companies who were really at the bleeding edge of innovation and devoPS and continuous delivery. And when you look at those teams, they have, they have very, very small teams, um supporting thousands of developers teams um building and deploying applications. So um when you think of of SRE and deVOPS focus there is actually a very small number of those folks who typically support humongous organizations and I think what we're hearing from them is their increasingly getting requirements from the teams who want to be self service, right? They want to be able to take their applications, have simple platforms to deploy it themselves to manage things. Um They don't they don't want to go through heavy way processes, they wanted to be automated and lightweight and I think this is this is putting pressure on deVOPS teams to to evolve and to adopt more platforms and services which allow developers to to do things themselves. And I think over time um this doesn't this doesn't get rid of the need for for devops and for SRE roles and organizations but it it changes because now they become the enablers of success and good development teams. It's it's kind of like um like how I. T. Organizations they support you with automated rollouts with all these tools rather than in person as much as they can do with automation. Um That helps the entire organization. I think devops is becoming the same thing where they're now simplifying and automating how developers can be self service and organizations. >>And I think it's a great evolution to because that makes total sense because it is kind of like what the I. T. Used to do in the old days but its the scale is different, the services are different, the deVOPS tools are different and so they really are enabling not just the cost center there really driving value. Um and this brings up the whole next threat. I'd love to get your thoughts because you guys are, have been doing this for developers for a while. Tools versus platform because you know, this whole platform where we're a platform were control plane, there's still a need for tooling for developers. How do we thread the needle between? What's, what's good for a tool? What's good for a platform? >>Yeah, So I I think that um, you know, there's always a lot of focus and it's, it's easier if you can take an end to end platform, which solves a bunch of different use cases together. But um, I I think a lot of folks, um, when you're looking at what you need and how you want to apply, um, devops practices to your organization, you ideally you want to be able to use best in breed tools to be able to solve exactly what your use cases. And this is one of the reasons why as a company with jay frog, we we try to be as open as possible to integrations with the entire vendor ecosystem. So um, it doesn't matter what ci cd tool you're using, you could be using Jenkins circle, ci spinnaker checked on, it doesn't matter what observe ability platform you're using in production, it doesn't matter what um tools you're using for collaboration. We, we support that whole ecosystem and we make it possible for you to select the the best of breed tools and technologies that you need to be successful as an organization. And I think the risk is if, if you, if you kind of accept vendor lock in on a single platform or or a single cloud platform even um then you're, you're not getting the best in breed tools and technologies which you need to stay ahead of the curve and devops is a very, very fast moving um, um, discipline along with all the cloud native technologies which you use for application development and for production. So if you're, if you're not staying at the bleeding edge and kind of pushing things forward, then you're then you're behind and if you're behind, you're not be able to keep up with the releases, the deployments, you need to be secure. So I think what you see is the leading organizations are pushing the envelope on on security, on deployment and they're they're using the best tools in the industry to make that happen. >>Stephen great to have you on the cube. I want to just get your thoughts on jay frog and the doctor partnership to wrap this up. Could you take them in to explain what's the most important thing that developers should pay attention to when it comes to security for Docker images? >>Yeah. So I think when you're when you're developer and you're looking at your your security strategy, um you want tools that help you that come to you and that help you. So you want things which are going to give you alerts in your I. D. With things which are going to trigger your in your Ci cd and your build process. And we should make it easy for you to identify mitigate and release um things which will help you do that. So we we provide a lot of those tools with jay frog and our doctor partnership. And I think if you if you look at our push towards helping developers to become more productive, build better applications and more secure applications, this is something the entire industry needs for us to address. What's increasingly a risk to software development, which is a higher profile vulnerabilities, which are affecting the entire industry. >>Great stuff. Big fan of jay frog watching you guys be so successful, you know, making things easy for developers is uh, and simpler and reducing the steps it takes to do things as a, I say, is the classic magic formula for any company, Make it easier, reduce the steps it takes to do something and make it simple. Um, good success formula. Great stuff. Great to have you on um for a minute or two, take a minute to plug what's going on in jay frog and share what's the latest increase with the company, what you guys are doing? Obviously public company. Great place to work, getting awards for that. Give the update on jay frog, put a plug in. >>Yeah. And also dr Frog, I've been having a lot of fun working at J frog, it's very, very fast growing. We have a lot of awesome announcements at swamp up. Um like the partnerships were doing um secure release bundles for deployments and just just a range of advances. I think the number of new features and innovation we put into the product in the past six months since I. P. O. Is astounding. So we're really trying to push the edge on devops um and we're also gonna be announcing and talking about stuff that dr khan as well and continue to invest in the cloud native and the devops ecosystem with our support of the continuous delivery foundation and the C. N C F, which I'm also heavily involved in. So it's it's exciting time to be in the devoPS industry and I think you can see that we're really helping software developers to improve their art to become better, better at release. Again, managing production applications >>and the ecosystem is just flourishing. It's only the beginning and again Making bring the craft back in Agile, which is a super big theme this year. Stephen. Great, great to see you. Thanks for dropping those gems and insights here on the Cube here at Dr. 2021 virtual. Thanks for coming on. >>Yeah. Thank you john. >>Okay. Dr. 2020 coverage virtual. I'm John for your host of the Cube. Thanks for watching. Mhm. Mhm. Yeah.

>>Individuals create developers, translate ideas to code, to create great applications and great applications. Touch everyone. A Docker. We know that collaboration is key to your innovation sharing ideas, working together. Launching the most secure applications. Docker is with you wherever your team innovates, whether it be robots or autonomous cars, we're doing research to save lives during a pandemic, revolutionizing, how to buy and sell goods online, or even going into the unknown frontiers of space. Docker is launching innovation everywhere. Join us on the journey to build, share, run the future. >>Hello and welcome to Docker con 2021. We're incredibly excited to have more than 80,000 of you join us today from all over the world. As it was last year, this year at DockerCon is 100% virtual and 100% free. So as to enable as many community members as possible to join us now, 100%. Virtual is also an acknowledgement of the continuing global pandemic in particular, the ongoing tragedies in India and Brazil, the Docker community is a global one. And on behalf of all Dr. Khan attendees, we are donating $10,000 to UNICEF support efforts to fight the virus in those countries. Now, even in those regions of the world where the pandemic is being brought under control, virtual first is the new normal. It's been a challenging transition. This includes our team here at Docker. And we know from talking with many of you that you and your developer teams are challenged by this as well. So to help application development teams better collaborate and ship faster, we've been working on some powerful new features and we thought it would be fun to start off with a demo of those. How about it? Want to have a look? All right. Then no further delay. I'd like to introduce Youi Cal and Ben, gosh, over to you and Ben >>Morning, Ben, thanks for jumping on real quick. >>Have you seen the email from Scott? The one about updates and the docs landing page Smith, the doc combat and more prominence. >>Yeah. I've got something working on my local machine. I haven't committed anything yet. I was thinking we could try, um, that new Docker dev environments feature. >>Yeah, that's cool. So if you hit the share button, what I should do is it will take all of your code and the dependencies and the image you're basing it on and wrap that up as one image for me. And I can then just monitor all my machines that have been one click, like, and then have it side by side, along with the changes I've been looking at as well, because I was also having a bit of a look and then I can really see how it differs to what I'm doing. Maybe I can combine it to do the best of both worlds. >>Sounds good. Uh, let me get that over to you, >>Wilson. Yeah. If you pay with the image name, I'll get that started up. >>All right. Sen send it over >>Cheesy. Okay, great. Let's have a quick look at what you he was doing then. So I've been messing around similar to do with the batter. I've got movie at the top here and I think it looks pretty cool. Let's just grab that image from you. Pick out that started on a dev environment. What this is doing. It's just going to grab the image down, which you can take all of the code, the dependencies only get brunches working on and I'll get that opened up in my idea. Ready to use. It's a here close. We can see our environment as my Molly image, just coming down there and I've got my new idea. >>We'll load this up and it'll just connect to my dev environment. There we go. It's connected to the container. So we're working all in the container here and now give it a moment. What we'll do is we'll see what changes you've been making as well on the code. So it's like she's been working on a landing page as well, and it looks like she's been changing the banner as well. So let's get this running. Let's see what she's actually doing and how it looks. We'll set up our checklist and then we'll see how that works. >>Great. So that's now rolling. So let's just have a look at what you use doing what changes she had made. Compare those to mine just jumped back into my dev container UI, see that I've got both of those running side by side with my changes and news changes. Okay. So she's put Molly up there rather than mobi or somebody had the same idea. So I think in a way I can make us both happy. So if we just jumped back into what we'll do, just add Molly and Moby and here I'll save that. And what we can see is, cause I'm just working within the container rather than having to do sort of rebuild of everything or serve, or just reload my content. No, that's straight the page. So what I can then do is I can come up with my browser here. Once that's all refreshed, refresh the page once hopefully, maybe twice, we should then be able to see your refresh it or should be able to see that we get Malia mobi come up. So there we go, got Molly mobi. So what we'll do now is we'll describe that state. It sends us our image and then we'll just create one of those to share with URI or share. And we'll get a link for that. I guess we'll send that back over to you. >>So I've had a look at what you were doing and I'm actually going to change. I think that might work for both of us. I wondered if you could take a look at it. If I send it over. >>Sounds good. Let me grab the link. >>Yeah, it's a dev environment link again. So if you just open that back in the doc dashboard, it should be able to open up the code that I've changed and then just run it in the same way you normally do. And that shouldn't interrupt what you're already working on because there'll be able to run side by side with your other brunch. You already got, >>Got it. Got it. Loading here. Well, that's great. It's Molly and movie together. I love it. I think we should ship it. >>Awesome. I guess it's chip it and get on with the rest of.com. Wasn't that cool. Thank you Joey. Thanks Ben. Everyone we'll have more of this later in the keynote. So stay tuned. Let's say earlier, we've all been challenged by this past year, whether the COVID pandemic, the complete evaporation of customer demand in many industries, unemployment or business bankruptcies, we all been touched in some way. And yet, even to miss these tragedies last year, we saw multiple sources of hope and inspiration. For example, in response to COVID we saw global communities, including the tech community rapidly innovate solutions for analyzing the spread of the virus, sequencing its genes and visualizing infection rates. In fact, if all in teams collaborating on solutions for COVID have created more than 1,400 publicly shareable images on Docker hub. As another example, we all witnessed the historic landing and exploration of Mars by the perseverance Rover and its ingenuity drone. >>Now what's common in these examples, these innovative and ambitious accomplishments were made possible not by any single individual, but by teams of individuals collaborating together. The power of teams is why we've made development teams central to Docker's mission to build tools and content development teams love to help them get their ideas from code to cloud as quickly as possible. One of the frictions we've seen that can slow down to them in teams is that the path from code to cloud can be a confusing one, riddle with multiple point products, tools, and images that need to be integrated and maintained an automated pipeline in order for teams to be productive. That's why a year and a half ago we refocused Docker on helping development teams make sense of all this specifically, our goal is to provide development teams with the trusted content, the sharing capabilities and the pipeline integrations with best of breed third-party tools to help teams ship faster in short, to provide a collaborative application development platform. >>Everything a team needs to build. Sharon run create applications. Now, as I noted earlier, it's been a challenging year for everyone on our planet and has been similar for us here at Docker. Our team had to adapt to working from home local lockdowns caused by the pandemic and other challenges. And despite all this together with our community and ecosystem partners, we accomplished many exciting milestones. For example, in open source together with the community and our partners, we open sourced or made major contributions to many projects, including OCI distribution and the composed plugins building on these open source projects. We had powerful new capabilities to the Docker product, both free and subscription. For example, support for WSL two and apple, Silicon and Docker, desktop and vulnerability scanning audit logs and image management and Docker hub. >>And finally delivering an easy to use well-integrated development experience with best of breed tools and content is only possible through close collaboration with our ecosystem partners. For example, this last year we had over 100 commercialized fees, join our Docker verified publisher program and over 200 open source projects, join our Docker sponsored open source program. As a result of these efforts, we've seen some exciting growth in the Docker community in the 12 months since last year's Docker con for example, the number of registered developers grew 80% to over 8 million. These developers created many new images increasing the total by 56% to almost 11 million. And the images in all these repositories were pulled by more than 13 million monthly active IP addresses totaling 13 billion pulls a month. Now while the growth is exciting by Docker, we're even more excited about the stories we hear from you and your development teams about how you're using Docker and its impact on your businesses. For example, cancer researchers and their bioinformatics development team at the Washington university school of medicine needed a way to quickly analyze their clinical trial results and then share the models, the data and the analysis with other researchers they use Docker because it gives them the ease of use choice of pipeline tools and speed of sharing so critical to their research. And most importantly to the lives of their patients stay tuned for another powerful customer story later in the keynote from Matt fall, VP of engineering at Oracle insights. >>So with this last year behind us, what's next for Docker, but challenge you this last year of force changes in how development teams work, but we felt for years to come. And what we've learned in our discussions with you will have long lasting impact on our product roadmap. One of the biggest takeaways from those discussions that you and your development team want to be quicker to adapt, to changes in your environment so you can ship faster. So what is DACA doing to help with this first trusted content to own the teams that can focus their energies on what is unique to their businesses and spend as little time as possible on undifferentiated work are able to adapt more quickly and ship faster in order to do so. They need to be able to trust other components that make up their app together with our partners. >>Docker is doubling down and providing development teams with trusted content and the tools they need to use it in their applications. Second, remote collaboration on a development team, asking a coworker to take a look at your code used to be as easy as swiveling their chair around, but given what's happened in the last year, that's no longer the case. So as you even been hinted in the demo at the beginning, you'll see us deliver more capabilities for remote collaboration within a development team. And we're enabling development team to quickly adapt to any team configuration all on prem hybrid, all work from home, helping them remain productive and focused on shipping third ecosystem integrations, those development teams that can quickly take advantage of innovations throughout the ecosystem. Instead of getting locked into a single monolithic pipeline, there'll be the ones able to deliver amps, which impact their businesses faster. >>So together with our ecosystem partners, we are investing in more integrations with best of breed tools, right? Integrated automated app pipelines. Furthermore, we'll be writing more public API APIs and SDKs to enable ecosystem partners and development teams to roll their own integrations. We'll be sharing more details about remote collaboration and ecosystem integrations. Later in the keynote, I'd like to take a moment to share with Docker and our partners are doing for trusted content, providing development teams, access to content. They can trust, allows them to focus their coding efforts on what's unique and differentiated to that end Docker and our partners are bringing more and more trusted content to Docker hub Docker official images are 160 images of popular upstream open source projects that serve as foundational building blocks for any application. These include operating systems, programming, languages, databases, and more. Furthermore, these are updated patch scan and certified frequently. So I said, no image is older than 30 days. >>Docker verified publisher images are published by more than 100 commercialized feeds. The image Rebos are explicitly designated verify. So the developers searching for components for their app know that the ISV is actively maintaining the image. Docker sponsored open source projects announced late last year features images for more than 200 open source communities. Docker sponsors these communities through providing free storage and networking resources and offering their community members unrestricted access repos for businesses allow businesses to update and share their apps privately within their organizations using role-based access control and user authentication. No, and finally, public repos for communities enable community projects to be freely shared with anonymous and authenticated users alike. >>And for all these different types of content, we provide services for both development teams and ISP, for example, vulnerability scanning and digital signing for enhanced security search and filtering for discoverability packaging and updating services and analytics about how these products are being used. All this trusted content, we make available to develop teams for them directly to discover poll and integrate into their applications. Our goal is to meet development teams where they live. So for those organizations that prefer to manage their internal distribution of trusted content, we've collaborated with leading container registry partners. We announced our partnership with J frog late last year. And today we're very pleased to announce our partnerships with Amazon and Miranda's for providing an integrated seamless experience for joint for our joint customers. Lastly, the container images themselves and this end to end flow are built on open industry standards, which provided all the teams with flexibility and choice trusted content enables development teams to rapidly build. >>As I let them focus on their unique differentiated features and use trusted building blocks for the rest. We'll be talking more about trusted content as well as remote collaboration and ecosystem integrations later in the keynote. Now ecosystem partners are not only integral to the Docker experience for development teams. They're also integral to a great DockerCon experience, but please join me in thanking our Dr. Kent on sponsors and checking out their talks throughout the day. I also want to thank some others first up Docker team. Like all of you this last year has been extremely challenging for us, but the Docker team rose to the challenge and worked together to continue shipping great product, the Docker community of captains, community leaders, and contributors with your welcoming newcomers, enthusiasm for Docker and open exchanges of best practices and ideas talker, wouldn't be Docker without you. And finally, our development team customers. >>You trust us to help you build apps. Your businesses rely on. We don't take that trust for granted. Thank you. In closing, we often hear about the tenant's developer capable of great individual feeds that can transform project. But I wonder if we, as an industry have perhaps gotten this wrong by putting so much emphasis on weight, on the individual as discussed at the beginning, great accomplishments like innovative responses to COVID-19 like landing on Mars are more often the results of individuals collaborating together as a team, which is why our mission here at Docker is delivered tools and content developers love to help their team succeed and become 10 X teams. Thanks again for joining us, we look forward to having a great DockerCon with you today, as well as a great year ahead of us. Thanks and be well. >>Hi, I'm Dana Lawson, VP of engineering here at get hub. And my job is to enable this rich interconnected community of builders and makers to build even more and hopefully have a great time doing it in order to enable the best platform for developers, which I know is something we are all passionate about. We need to partner across the ecosystem to ensure that developers can have a great experience across get hub and all the tools that they want to use. No matter what they are. My team works to build the tools and relationships to make that possible. I am so excited to join Scott on this virtual stage to talk about increasing developer velocity. So let's dive in now, I know this may be hard for some of you to believe, but as a former CIS admin, some 21 years ago, working on sense spark workstations, we've come such a long way for random scripts and desperate systems that we've stitched together to this whole inclusive developer workflow experience being a CIS admin. >>Then you were just one piece of the siloed experience, but I didn't want to just push code to production. So I created scripts that did it for me. I taught myself how to code. I was the model lazy CIS admin that got dangerous and having pushed a little too far. I realized that working in production and building features is really a team sport that we had the opportunity, all of us to be customer obsessed today. As developers, we can go beyond the traditional dev ops mindset. We can really focus on adding value to the customer experience by ensuring that we have work that contributes to increasing uptime via and SLS all while being agile and productive. We get there. When we move from a pass the Baton system to now having an interconnected developer workflow that increases velocity in every part of the cycle, we get to work better and smarter. >>And honestly, in a way that is so much more enjoyable because we automate away all the mundane and manual and boring tasks. So we get to focus on what really matters shipping, the things that humans get to use and love. Docker has been a big part of enabling this transformation. 10, 20 years ago, we had Tomcat containers, which are not Docker containers. And for y'all hearing this the first time go Google it. But that was the way we built our applications. We had to segment them on the server and give them resources. Today. We have Docker containers, these little mini Oasys and Docker images. You can do it multiple times in an orchestrated manner with the power of actions enabled and Docker. It's just so incredible what you can do. And by the way, I'm showing you actions in Docker, which I hope you use because both are great and free for open source. >>But the key takeaway is really the workflow and the automation, which you certainly can do with other tools. Okay, I'm going to show you just how easy this is, because believe me, if this is something I can learn and do anybody out there can, and in this demo, I'll show you about the basic components needed to create and use a package, Docker container actions. And like I said, you won't believe how awesome the combination of Docker and actions is because you can enable your workflow to do no matter what you're trying to do in this super baby example. We're so small. You could take like 10 seconds. Like I am here creating an action due to a simple task, like pushing a message to your logs. And the cool thing is you can use it on any the bit on this one. Like I said, we're going to use push. >>You can do, uh, even to order a pizza every time you roll into production, if you wanted, but at get hub, that'd be a lot of pizzas. And the funny thing is somebody out there is actually tried this and written that action. If you haven't used Docker and actions together, check out the docs on either get hub or Docker to get you started. And a huge shout out to all those doc writers out there. I built this demo today using those instructions. And if I can do it, I know you can too, but enough yapping let's get started to save some time. And since a lot of us are Docker and get hub nerds, I've already created a repo with a Docker file. So we're going to skip that step. Next. I'm going to create an action's Yammel file. And if you don't Yammer, you know, actions, the metadata defines my important log stuff to capture and the input and my time out per parameter to pass and puts to the Docker container, get up a build image from your Docker file and run the commands in a new container. >>Using the Sigma image. The cool thing is, is you can use any Docker image in any language for your actions. It doesn't matter if it's go or whatever in today's I'm going to use a shell script and an input variable to print my important log stuff to file. And like I said, you know me, I love me some. So let's see this action in a workflow. When an action is in a private repo, like the one I demonstrating today, the action can only be used in workflows in the same repository, but public actions can be used by workflows in any repository. So unfortunately you won't get access to the super awesome action, but don't worry in the Guild marketplace, there are over 8,000 actions available, especially the most important one, that pizza action. So go try it out. Now you can do this in a couple of ways, whether you're doing it in your preferred ID or for today's demo, I'm just going to use the gooey. I'm going to navigate to my actions tab as I've done here. And I'm going to in my workflow, select new work, hello, probably load some workflows to Claire to get you started, but I'm using the one I've copied. Like I said, the lazy developer I am in. I'm going to replace it with my action. >>That's it. So now we're going to go and we're going to start our commitment new file. Now, if we go over to our actions tab, we can see the workflow in progress in my repository. I just click the actions tab. And because they wrote the actions on push, we can watch the visualization under jobs and click the job to see the important stuff we're logging in the input stamp in the printed log. And we'll just wait for this to run. Hello, Mona and boom. Just like that. It runs automatically within our action. We told it to go run as soon as the files updated because we're doing it on push merge. That's right. Folks in just a few minutes, I built an action that writes an entry to a log file every time I push. So I don't have to do it manually. In essence, with automation, you can be kind to your future self and save time and effort to focus on what really matters. >>Imagine what I could do with even a little more time, probably order all y'all pieces. That is the power of the interconnected workflow. And it's amazing. And I hope you all go try it out, but why do we care about all of that? Just like in the demo, I took a manual task with both tape, which both takes time and it's easy to forget and automated it. So I don't have to think about it. And it's executed every time consistently. That means less time for me to worry about my human errors and mistakes, and more time to focus on actually building the cool stuff that people want. Obviously, automation, developer productivity, but what is even more important to me is the developer happiness tools like BS, code actions, Docker, Heroku, and many others reduce manual work, which allows us to focus on building things that are awesome. >>And to get into that wonderful state that we call flow. According to research by UC Irvine in Humboldt university in Germany, it takes an average of 23 minutes to enter optimal creative state. What we call the flow or to reenter it after distraction like your dog on your office store. So staying in flow is so critical to developer productivity and as a developer, it just feels good to be cranking away at something with deep focus. I certainly know that I love that feeling intuitive collaboration and automation features we built in to get hub help developer, Sam flow, allowing you and your team to do so much more, to bring the benefits of automation into perspective in our annual October's report by Dr. Nicole, Forsgren. One of my buddies here at get hub, took a look at the developer productivity in the stork year. You know what we found? >>We found that public GitHub repositories that use the Automational pull requests, merge those pull requests. 1.2 times faster. And the number of pooled merged pull requests increased by 1.3 times, that is 34% more poor requests merged. And other words, automation can con can dramatically increase, but the speed and quantity of work completed in any role, just like an open source development, you'll work more efficiently with greater impact when you invest the bulk of your time in the work that adds the most value and eliminate or outsource the rest because you don't need to do it, make the machines by elaborate by leveraging automation in their workflows teams, minimize manual work and reclaim that time for innovation and maintain that state of flow with development and collaboration. More importantly, their work is more enjoyable because they're not wasting the time doing the things that the machines or robots can do for them. >>And I remember what I said at the beginning. Many of us want to be efficient, heck even lazy. So why would I spend my time doing something I can automate? Now you can read more about this research behind the art behind this at October set, get hub.com, which also includes a lot of other cool info about the open source ecosystem and how it's evolving. Speaking of the open source ecosystem we at get hub are so honored to be the home of more than 65 million developers who build software together for everywhere across the globe. Today, we're seeing software development taking shape as the world's largest team sport, where development teams collaborate, build and ship products. It's no longer a solo effort like it was for me. You don't have to take my word for it. Check out this globe. This globe shows real data. Every speck of light you see here represents a contribution to an open source project, somewhere on earth. >>These arts reach across continents, cultures, and other divides. It's distributed collaboration at its finest. 20 years ago, we had no concept of dev ops, SecOps and lots, or the new ops that are going to be happening. But today's development and ops teams are connected like ever before. This is only going to continue to evolve at a rapid pace, especially as we continue to empower the next hundred million developers, automation helps us focus on what's important and to greatly accelerate innovation. Just this past year, we saw some of the most groundbreaking technological advancements and achievements I'll say ever, including critical COVID-19 vaccine trials, as well as the first power flight on Mars. This past month, these breakthroughs were only possible because of the interconnected collaborative open source communities on get hub and the amazing tools and workflows that empower us all to create and innovate. Let's continue building, integrating, and automating. So we collectively can give developers the experience. They deserve all of the automation and beautiful eye UIs that we can muster so they can continue to build the things that truly do change the world. Thank you again for having me today, Dr. Khan, it has been a pleasure to be here with all you nerds. >>Hello. I'm Justin. Komack lovely to see you here. Talking to developers, their world is getting much more complex. Developers are being asked to do everything security ops on goal data analysis, all being put on the rockers. Software's eating the world. Of course, and this all make sense in that view, but they need help. One team. I told you it's shifted all our.net apps to run on Linux from windows, but their developers found the complexity of Docker files based on the Linux shell scripts really difficult has helped make these things easier for your teams. Your ones collaborate more in a virtual world, but you've asked us to make this simpler and more lightweight. You, the developers have asked for a paved road experience. You want things to just work with a simple options to be there, but it's not just the paved road. You also want to be able to go off-road and do interesting and different things. >>Use different components, experiments, innovate as well. We'll always offer you both those choices at different times. Different developers want different things. It may shift for ones the other paved road or off road. Sometimes you want reliability, dependability in the zone for day to day work, but sometimes you have to do something new, incorporate new things in your pipeline, build applications for new places. Then you knew those off-road abilities too. So you can really get under the hood and go and build something weird and wonderful and amazing. That gives you new options. Talk as an independent choice. We don't own the roads. We're not pushing you into any technology choices because we own them. We're really supporting and driving open standards, such as ISEI working opensource with the CNCF. We want to help you get your applications from your laptops, the clouds, and beyond, even into space. >>Let's talk about the key focus areas, that frame, what DACA is doing going forward. These are simplicity, sharing, flexibility, trusted content and care supply chain compared to building where the underlying kernel primitives like namespaces and Seagraves the original Docker CLI was just amazing Docker engine. It's a magical experience for everyone. It really brought those innovations and put them in a world where anyone would use that, but that's not enough. We need to continue to innovate. And it was trying to get more done faster all the time. And there's a lot more we can do. We're here to take complexity away from deeply complicated underlying things and give developers tools that are just amazing and magical. One of the area we haven't done enough and make things magical enough that we're really planning around now is that, you know, Docker images, uh, they're the key parts of your application, but you know, how do I do something with an image? How do I, where do I attach volumes with this image? What's the API. Whereas the SDK for this image, how do I find an example or docs in an API driven world? Every bit of software should have an API and an API description. And our vision is that every container should have this API description and the ability for you to understand how to use it. And it's all a seamless thing from, you know, from your code to the cloud local and remote, you can, you can use containers in this amazing and exciting way. >>One thing I really noticed in the last year is that companies that started off remote fast have constant collaboration. They have zoom calls, apron all day terminals, shattering that always working together. Other teams are really trying to learn how to do this style because they didn't start like that. We used to walk around to other people's desks or share services on the local office network. And it's very difficult to do that anymore. You want sharing to be really simple, lightweight, and informal. Let me try your container or just maybe let's collaborate on this together. Um, you know, fast collaboration on the analysts, fast iteration, fast working together, and he wants to share more. You want to share how to develop environments, not just an image. And we all work by seeing something someone else in our team is doing saying, how can I do that too? I can, I want to make that sharing really, really easy. Ben's going to talk about this more in the interest of one minute. >>We know how you're excited by apple. Silicon and gravis are not excited because there's a new architecture, but excited because it's faster, cooler, cheaper, better, and offers new possibilities. The M one support was the most asked for thing on our public roadmap, EFA, and we listened and share that we see really exciting possibilities, usership arm applications, all the way from desktop to production. We know that you all use different clouds and different bases have deployed to, um, you know, we work with AWS and Azure and Google and more, um, and we want to help you ship on prime as well. And we know that you use huge number of languages and the containers help build applications that use different languages for different parts of the application or for different applications, right? You can choose the best tool. You have JavaScript hat or everywhere go. And re-ask Python for data and ML, perhaps getting excited about WebAssembly after hearing about a cube con, you know, there's all sorts of things. >>So we need to make that as easier. We've been running the whole month of Python on the blog, and we're doing a month of JavaScript because we had one specific support about how do I best put this language into production of that language into production. That detail is important for you. GPS have been difficult to use. We've added GPS suppose in desktop for windows, but we know there's a lot more to do to make the, how multi architecture, multi hardware, multi accelerator world work better and also securely. Um, so there's a lot more work to do to support you in all these things you want to do. >>How do we start building a tenor has applications, but it turns out we're using existing images as components. I couldn't assist survey earlier this year, almost half of container image usage was public images rather than private images. And this is growing rapidly. Almost all software has open source components and maybe 85% of the average application is open source code. And what you're doing is taking whole container images as modules in your application. And this was always the model with Docker compose. And it's a model that you're already et cetera, writing you trust Docker, official images. We know that they might go to 25% of poles on Docker hub and Docker hub provides you the widest choice and the best support that trusted content. We're talking to people about how to make this more helpful. We know, for example, that winter 69 four is just showing us as support, but the image doesn't yet tell you that we're working with canonical to improve messaging from specific images about left lifecycle and support. >>We know that you need more images, regularly updated free of vulnerabilities, easy to use and discover, and Donnie and Marie neuro, going to talk about that more this last year, the solar winds attack has been in the, in the news. A lot, the software you're using and trusting could be compromised and might be all over your organization. We need to reduce the risk of using vital open-source components. We're seeing more software supply chain attacks being targeted as the supply chain, because it's often an easier place to attack and production software. We need to be able to use this external code safely. We need to, everyone needs to start from trusted sources like photography images. They need to scan for known vulnerabilities using Docker scan that we built in partnership with sneak and lost DockerCon last year, we need just keep updating base images and dependencies, and we'll, we're going to help you have the control and understanding about your images that you need to do this. >>And there's more, we're also working on the nursery V2 project in the CNCF to revamp container signings, or you can tell way or software comes from we're working on tooling to make updates easier, and to help you understand and manage all the principals carrier you're using security is a growing concern for all of us. It's really important. And we're going to help you work with security. We can't achieve all our dreams, whether that's space travel or amazing developer products ever see without deep partnerships with our community to cloud is RA and the cloud providers aware most of you ship your occasion production and simple routes that take your work and deploy it easily. Reliably and securely are really important. Just get into production simply and easily and securely. And we've done a bunch of work on that. And, um, but we know there's more to do. >>The CNCF on the open source cloud native community are an amazing ecosystem of creators and lovely people creating an amazing strong community and supporting a huge amount of innovation has its roots in the container ecosystem and his dreams beyond that much of the innovation is focused around operate experience so far, but developer experience is really a growing concern in that community as well. And we're really excited to work on that. We also uses appraiser tool. Then we know you do, and we know that you want it to be easier to use in your environment. We just shifted Docker hub to work on, um, Kubernetes fully. And, um, we're also using many of the other projects are Argo from atheists. We're spending a lot of time working with Microsoft, Amazon right now on getting natural UV to ready to ship in the next few. That's a really detailed piece of collaboration we've been working on for a long term. Long time is really important for our community as the scarcity of the container containers and, um, getting content for you, working together makes us stronger. Our community is made up of all of you have. Um, it's always amazing to be reminded of that as a huge open source community that we already proud to work with. It's an amazing amount of innovation that you're all creating and where perhaps it, what with you and share with you as well. Thank you very much. And thank you for being here. >>Really excited to talk to you today and share more about what Docker is doing to help make you faster, make your team faster and turn your application delivery into something that makes you a 10 X team. What we're hearing from you, the developers using Docker everyday fits across three common themes that we hear consistently over and over. We hear that your time is super important. It's critical, and you want to move faster. You want your tools to get out of your way, and instead to enable you to accelerate and focus on the things you want to be doing. And part of that is that finding great content, great application components that you can incorporate into your apps to move faster is really hard. It's hard to discover. It's hard to find high quality content that you can trust that, you know, passes your test and your configuration needs. >>And it's hard to create good content as well. And you're looking for more safety, more guardrails to help guide you along that way so that you can focus on creating value for your company. Secondly, you're telling us that it's a really far to collaborate effectively with your team and you want to do more, to work more effectively together to help your tools become more and more seamless to help you stay in sync, both with yourself across all of your development environments, as well as with your teammates so that you can more effectively collaborate together. Review each other's work, maintain things and keep them in sync. And finally, you want your applications to run consistently in every single environment, whether that's your local development environment, a cloud-based development environment, your CGI pipeline, or the cloud for production, and you want that micro service to provide that consistent experience everywhere you go so that you have similar tools, similar environments, and you don't need to worry about things getting in your way, but instead things make it easy for you to focus on what you wanna do and what Docker is doing to help solve all of these problems for you and your colleagues is creating a collaborative app dev platform. >>And this collaborative application development platform consists of multiple different pieces. I'm not going to walk through all of them today, but the overall view is that we're providing all the tooling you need from the development environment, to the container images, to the collaboration services, to the pipelines and integrations that enable you to focus on making your applications amazing and changing the world. If we start zooming on a one of those aspects, collaboration we hear from developers regularly is that they're challenged in synchronizing their own setups across environments. They want to be able to duplicate the setup of their teammates. Look, then they can easily get up and running with the same applications, the same tooling, the same version of the same libraries, the same frameworks. And they want to know if their applications are good before they're ready to share them in an official space. >>They want to collaborate on things before they're done, rather than feeling like they have to officially published something before they can effectively share it with others to work on it, to solve this. We're thrilled today to announce Docker, dev environments, Docker, dev environments, transform how your team collaborates. They make creating, sharing standardized development environments. As simple as a Docker poll, they make it easy to review your colleagues work without affecting your own work. And they increase the reproducibility of your own work and decreased production issues in doing so because you've got consistent environments all the way through. Now, I'm going to pass it off to our principal product manager, Ben Gotch to walk you through more detail on Docker dev environments. >>Hi, I'm Ben. I work as a principal program manager at DACA. One of the areas that doc has been looking at to see what's hard today for developers is sharing changes that you make from the inner loop where the inner loop is a better development, where you write code, test it, build it, run it, and ultimately get feedback on those changes before you merge them and try and actually ship them out to production. Most amount of us build this flow and get there still leaves a lot of challenges. People need to jump between branches to look at each other's work. Independence. Dependencies can be different when you're doing that and doing this in this new hybrid wall of work. Isn't any easier either the ability to just save someone, Hey, come and check this out. It's become much harder. People can't come and sit down at your desk or take your laptop away for 10 minutes to just grab and look at what you're doing. >>A lot of the reason that development is hard when you're remote, is that looking at changes and what's going on requires more than just code requires all the dependencies and everything you've got set up and that complete context of your development environment, to understand what you're doing and solving this in a remote first world is hard. We wanted to look at how we could make this better. Let's do that in a way that let you keep working the way you do today. Didn't want you to have to use a browser. We didn't want you to have to use a new idea. And we wanted to do this in a way that was application centric. We wanted to let you work with all the rest of the application already using C for all the services and all those dependencies you need as part of that. And with that, we're excited to talk more about docket developer environments, dev environments are new part of the Docker experience that makes it easier you to get started with your whole inner leap, working inside a container, then able to share and collaborate more than just the code. >>We want it to enable you to share your whole modern development environment, your whole setup from DACA, with your team on any operating system, we'll be launching a limited beta of dev environments in the coming month. And a GA dev environments will be ID agnostic and supporting composts. This means you'll be able to use an extend your existing composed files to create your own development environment in whatever idea, working in dev environments designed to be local. First, they work with Docker desktop and say your existing ID, and let you share that whole inner loop, that whole development context, all of your teammates in just one collect. This means if you want to get feedback on the working progress change or the PR it's as simple as opening another idea instance, and looking at what your team is working on because we're using compose. You can just extend your existing oppose file when you're already working with, to actually create this whole application and have it all working in the context of the rest of the services. >>So it's actually the whole environment you're working with module one service that doesn't really understand what it's doing alone. And with that, let's jump into a quick demo. So you can see here, two dev environments up and running. First one here is the same container dev environment. So if I want to go into that, let's see what's going on in the various code button here. If that one open, I can get straight into my application to start making changes inside that dev container. And I've got all my dependencies in here, so I can just run that straight in that second application I have here is one that's opened up in compose, and I can see that I've also got my backend, my front end and my database. So I've got all my services running here. So if I want, I can open one or more of these in a dev environment, meaning that that container has the context that dev environment has the context of the whole application. >>So I can get back into and connect to all the other services that I need to test this application properly, all of them, one unit. And then when I've made my changes and I'm ready to share, I can hit my share button type in the refund them on to share that too. And then give that image to someone to get going, pick that up and just start working with that code and all my dependencies, simple as putting an image, looking ahead, we're going to be expanding development environments, more of your dependencies for the whole developer worst space. We want to look at backing up and letting you share your volumes to make data science and database setups more repeatable and going. I'm still all of this under a single workspace for your team containing images, your dev environments, your volumes, and more we've really want to allow you to create a fully portable Linux development environment. >>So everyone you're working with on any operating system, as I said, our MVP we're coming next month. And that was for vs code using their dev container primitive and more support for other ideas. We'll follow to find out more about what's happening and what's coming up next in the future of this. And to actually get a bit of a deeper dive in the experience. Can we check out the talk I'm doing with Georgie and girl later on today? Thank you, Ben, amazing story about how Docker is helping to make developer teams more collaborative. Now I'd like to talk more about applications while the dev environment is like the workbench around what you're building. The application itself has all the different components, libraries, and frameworks, and other code that make up the application itself. And we hear developers saying all the time things like, how do they know if their images are good? >>How do they know if they're secure? How do they know if they're minimal? How do they make great images and great Docker files and how do they keep their images secure? And up-to-date on every one of those ties into how do I create more trust? How do I know that I'm building high quality applications to enable you to do this even more effectively than today? We are pleased to announce the DACA verified polisher program. This broadens trusted content by extending beyond Docker official images, to give you more and more trusted building blocks that you can incorporate into your applications. It gives you confidence that you're getting what you expect because Docker verifies every single one of these publishers to make sure they are who they say they are. This improves our secure supply chain story. And finally it simplifies your discovery of the best building blocks by making it easy for you to find things that you know, you can trust so that you can incorporate them into your applications and move on and on the right. You can see some examples of the publishers that are involved in Docker, official images and our Docker verified publisher program. Now I'm pleased to introduce you to marina. Kubicki our senior product manager who will walk you through more about what we're doing to create a better experience for you around trust. >>Thank you, Dani, >>Mario Andretti, who is a famous Italian sports car driver. One said that if everything feels under control, you're just not driving. You're not driving fast enough. Maya Andretti is not a software developer and a software developers. We know that no matter how fast we need to go in order to drive the innovation that we're working on, we can never allow our applications to spin out of control and a Docker. As we continue talking to our, to the developers, what we're realizing is that in order to reach that speed, the developers are the, the, the development community is looking for the building blocks and the tools that will, they will enable them to drive at the speed that they need to go and have the trust in those building blocks. And in those tools that they will be able to maintain control over their applications. So as we think about some of the things that we can do to, to address those concerns, uh, we're realizing that we can pursue them in a number of different venues, including creating reliable content, including creating partnerships that expands the options for the reliable content. >>Um, in order to, in a we're looking at creating integrations, no link security tools, talk about the reliable content. The first thing that comes to mind are the Docker official images, which is a program that we launched several years ago. And this is a set of curated, actively maintained, open source images that, uh, include, uh, operating systems and databases and programming languages. And it would become immensely popular for, for, for creating the base layers of, of the images of, of the different images, images, and applications. And would we realizing that, uh, many developers are, instead of creating something from scratch, basically start with one of the official images for their basis, and then build on top of that. And this program has become so popular that it now makes up a quarter of all of the, uh, Docker poles, which essentially ends up being several billion pulse every single month. >>As we look beyond what we can do for the open source. Uh, we're very ability on the open source, uh, spectrum. We are very excited to announce that we're launching the Docker verified publishers program, which is continuing providing the trust around the content, but now working with, uh, some of the industry leaders, uh, in multiple, in multiple verticals across the entire technology technical spec, it costs entire, uh, high tech in order to provide you with more options of the images that you can use for building your applications. And it still comes back to trust that when you are searching for content in Docker hub, and you see the verified publisher badge, you know, that this is, this is the content that, that is part of the, that comes from one of our partners. And you're not running the risk of pulling the malicious image from an employee master source. >>As we look beyond what we can do for, for providing the reliable content, we're also looking at some of the tools and the infrastructure that we can do, uh, to create a security around the content that you're creating. So last year at the last ad, the last year's DockerCon, we announced partnership with sneak. And later on last year, we launched our DACA, desktop and Docker hub vulnerability scans that allow you the options of writing scans in them along multiple points in your dev cycle. And in addition to providing you with information on the vulnerability on, on the vulnerabilities, in, in your code, uh, it also provides you with a guidance on how to re remediate those vulnerabilities. But as we look beyond the vulnerability scans, we're also looking at some of the other things that we can do, you know, to, to, to, uh, further ensure that the integrity and the security around your images, your images, and with that, uh, later on this year, we're looking to, uh, launch the scope, personal access tokens, and instead of talking about them, I will simply show you what they look like. >>So if you can see here, this is my page in Docker hub, where I've created a four, uh, tokens, uh, read-write delete, read, write, read only in public read in public creeper read only. So, uh, earlier today I went in and I, I logged in, uh, with my read only token. And when you see, when I'm going to pull an image, it's going to allow me to pull an image, not a problem success. And then when I do the next step, I'm going to ask to push an image into the same repo. Uh, would you see is that it's going to give me an error message saying that they access is denied, uh, because there is an additional authentication required. So these are the things that we're looking to add to our roadmap. As we continue thinking about the things that we can do to provide, um, to provide additional building blocks, content, building blocks, uh, and, and, and tools to build the trust so that our DACA developer and skinned code faster than Mario Andretti could ever imagine. Uh, thank you to >>Thank you, marina. It's amazing what you can do to improve the trusted content so that you can accelerate your development more and move more quickly, move more collaboratively and build upon the great work of others. Finally, we hear over and over as that developers are working on their applications that they're looking for, environments that are consistent, that are the same as production, and that they want their applications to really run anywhere, any environment, any architecture, any cloud one great example is the recent announcement of apple Silicon. We heard from developers on uproar that they needed Docker to be available for that architecture before they could add those to it and be successful. And we listened. And based on that, we are pleased to share with you Docker, desktop on apple Silicon. This enables you to run your apps consistently anywhere, whether that's developing on your team's latest dev hardware, deploying an ARM-based cloud environments and having a consistent architecture across your development and production or using multi-year architecture support, which enables your whole team to collaborate on its application, using private repositories on Docker hub, and thrilled to introduce you to Hughie cower, senior director for product management, who will walk you through more of what we're doing to create a great developer experience. >>Senior director of product management at Docker. And I'd like to jump straight into a demo. This is the Mac mini with the apple Silicon processor. And I want to show you how you can now do an end-to-end arm workflow from my M one Mac mini to raspberry PI. As you can see, we have vs code and Docker desktop installed on a, my, the Mac mini. I have a small example here, and I have a raspberry PI three with an led strip, and I want to turn those LEDs into a moving rainbow. This Dockerfile here, builds the application. We build the image with the Docker, build X command to make the image compatible for all raspberry pies with the arm. 64. Part of this build is built with the native power of the M one chip. I also add the push option to easily share the image with my team so they can give it a try to now Dr. >>Creates the local image with the application and uploads it to Docker hub after we've built and pushed the image. We can go to Docker hub and see the new image on Docker hub. You can also explore a variety of images that are compatible with arm processors. Now let's go to the raspberry PI. I have Docker already installed and it's running Ubuntu 64 bit with the Docker run command. I can run the application and let's see what will happen from there. You can see Docker is downloading the image automatically from Docker hub and when it's running, if it's works right, there are some nice colors. And with that, if we have an end-to-end workflow for arm, where continuing to invest into providing you a great developer experience, that's easy to install. Easy to get started with. As you saw in the demo, if you're interested in the new Mac, mini are interested in developing for our platforms in general, we've got you covered with the same experience you've come to expect from Docker with over 95,000 arm images on hub, including many Docker official images. >>We think you'll find what you're looking for. Thank you again to the community that helped us to test the tech previews. We're so delighted to hear when folks say that the new Docker desktop for apple Silicon, it just works for them, but that's not all we've been working on. As Dani mentioned, consistency of developer experience across environments is so important. We're introducing composed V2 that makes compose a first-class citizen in the Docker CLI you no longer need to install a separate composed biter in order to use composed, deploying to production is simpler than ever with the new compose integration that enables you to deploy directly to Amazon ECS or Azure ACI with the same methods you use to run your application locally. If you're interested in running slightly different services, when you're debugging versus testing or, um, just general development, you can manage that all in one place with the new composed service to hear more about what's new and Docker desktop, please join me in the three 15 breakout session this afternoon. >>And now I'd love to tell you a bit more about bill decks and convince you to try it. If you haven't already it's our next gen build command, and it's no longer experimental as shown in the demo with built X, you'll be able to do multi architecture builds, share those builds with your team and the community on Docker hub. With build X, you can speed up your build processes with remote caches or build all the targets in your composed file in parallel with build X bake. And there's so much more if you're using Docker, desktop or Docker, CE you can use build X checkout tonus is talk this afternoon at three 45 to learn more about build X. And with that, I hope everyone has a great Dr. Khan and back over to you, Donnie. >>Thank you UA. It's amazing to hear about what we're doing to create a better developer experience and make sure that Docker works everywhere you need to work. Finally, I'd like to wrap up by showing you everything that we've announced today and everything that we've done recently to make your lives better and give you more and more for the single price of your Docker subscription. We've announced the Docker verified publisher program we've announced scoped personal access tokens to make it easier for you to have a secure CCI pipeline. We've announced Docker dev environments to improve your collaboration with your team. Uh, we shared with you Docker, desktop and apple Silicon, to make sure that, you know, Docker runs everywhere. You need it to run. And we've announced Docker compose version two, finally making it a first-class citizen amongst all the other great Docker tools. And we've done so much more recently as well from audit logs to advanced image management, to compose service profiles, to improve where you can run Docker more easily. >>Finally, as we look forward, where we're headed in the upcoming year is continuing to invest in these themes of helping you build, share, and run modern apps more effectively. We're going to be doing more to help you create a secure supply chain with which only grows more and more important as time goes on. We're going to be optimizing your update experience to make sure that you can easily understand the current state of your application, all its components and keep them all current without worrying about breaking everything as you're doing. So we're going to make it easier for you to synchronize your work. Using cloud sync features. We're going to improve collaboration through dev environments and beyond, and we're going to do make it easy for you to run your microservice in your environments without worrying about things like architecture or differences between those environments. Thank you so much. I'm thrilled about what we're able to do to help make your lives better. And now you're going to be hearing from one of our customers about what they're doing to launch their business with Docker >>I'm Matt Falk, I'm the head of engineering and orbital insight. And today I want to talk to you a little bit about data from space. So who am I like many of you, I'm a software developer and a software developer about seven companies so far, and now I'm a head of engineering. So I spend most of my time doing meetings, but occasionally I'll still spend time doing design discussions, doing code reviews. And in my free time, I still like to dabble on things like project oiler. So who's Oberlin site. What do we do? Portal insight is a large data supplier and analytics provider where we take data geospatial data anywhere on the planet, any overhead sensor, and translate that into insights for the end customer. So specifically we have a suite of high performance, artificial intelligence and machine learning analytics that run on this geospatial data. >>And we build them to specifically determine natural and human service level activity anywhere on the planet. What that really means is we take any type of data associated with a latitude and longitude and we identify patterns so that we can, so we can detect anomalies. And that's everything that we do is all about identifying those patterns to detect anomalies. So more specifically, what type of problems do we solve? So supply chain intelligence, this is one of the use cases that we we'd like to talk about a lot. It's one of our main primary verticals that we go after right now. And as Scott mentioned earlier, this had a huge impact last year when COVID hit. So specifically supply chain intelligence is all about identifying movement patterns to and from operating facilities to identify changes in those supply chains. How do we do this? So for us, we can do things where we track the movement of trucks. >>So identifying trucks, moving from one location to another in aggregate, same thing we can do with foot traffic. We can do the same thing for looking at aggregate groups of people moving from one location to another and analyzing their patterns of life. We can look at two different locations to determine how people are moving from one location to another, or going back and forth. All of this is extremely valuable for detecting how a supply chain operates and then identifying the changes to that supply chain. As I said last year with COVID, everything changed in particular supply chains changed incredibly, and it was hugely important for customers to know where their goods or their products are coming from and where they were going, where there were disruptions in their supply chain and how that's affecting their overall supply and demand. So to use our platform, our suite of tools, you can start to gain a much better picture of where your suppliers or your distributors are going from coming from or going to. >>So what's our team look like? So my team is currently about 50 engineers. Um, we're spread into four different teams and the teams are structured like this. So the first team that we have is infrastructure engineering and this team largely deals with deploying our Dockers using Kubernetes. So this team is all about taking Dockers, built by other teams, sometimes building the Dockers themselves and putting them into our production system, our platform engineering team, they produce these microservices. So they produce microservice, Docker images. They develop and test with them locally. Their entire environments are dockerized. They produce these doctors, hand them over to him for infrastructure engineering to be deployed. Similarly, our product engineering team does the same thing. They develop and test with Dr. Locally. They also produce a suite of Docker images that the infrastructure team can then deploy. And lastly, we have our R and D team, and this team specifically produces machine learning algorithms using Nvidia Docker collectively, we've actually built 381 Docker repositories and 14 million. >>We've had 14 million Docker pools over the lifetime of the company, just a few stats about us. Um, but what I'm really getting to here is you can see actually doctors becoming almost a form of communication between these teams. So one of the paradigms in software engineering that you're probably familiar with encapsulation, it's really helpful for a lot of software engineering problems to break the problem down, isolate the different pieces of it and start building interfaces between the code. This allows you to scale different pieces of the platform or different pieces of your code in different ways that allows you to scale up certain pieces and keep others at a smaller level so that you can meet customer demands. And for us, one of the things that we can largely do now is use Dockers as that interface. So instead of having an entire platform where all teams are talking to each other, and everything's kind of, mishmashed in a monolithic application, we can now say this team is only able to talk to this team by passing over a particular Docker image that defines the interface of what needs to be built before it passes to the team and really allows us to scalp our development and be much more efficient. >>Also, I'd like to say we are hiring. Um, so we have a number of open roles. We have about 30 open roles in our engineering team that we're looking to fill by the end of this year. So if any of this sounds really interesting to you, please reach out after the presentation. >>So what does our platform do? Really? Our platform allows you to answer any geospatial question, and we do this at three different inputs. So first off, where do you want to look? So we did this as what we call an AOI or an area of interest larger. You can think of this as a polygon drawn on the map. So we have a curated data set of almost 4 million AOIs, which you can go and you can search and use for your analysis, but you're also free to build your own. Second question is what you want to look for. We do this with the more interesting part of our platform of our machine learning and AI capabilities. So we have a suite of algorithms that automatically allow you to identify trucks, buildings, hundreds of different types of aircraft, different types of land use, how many people are moving from one location to another different locations that people in a particular area are moving to or coming from all of these different analyses or all these different analytics are available at the click of a button, and then determine what you want to look for. >>Lastly, you determine when you want to find what you're looking for. So that's just, uh, you know, do you want to look for the next three hours? Do you want to look for the last week? Do you want to look every month for the past two, whatever the time cadence is, you decide that you hit go and out pops a time series, and that time series tells you specifically where you want it to look what you want it to look for and how many, or what percentage of the thing you're looking for appears in that area. Again, we do all of this to work towards patterns. So we use all this data to produce a time series from there. We can look at it, determine the patterns, and then specifically identify the anomalies. As I mentioned with supply chain, this is extremely valuable to identify where things change. So we can answer these questions, looking at a particular operating facility, looking at particular, what is happening with the level of activity is at that operating facility where people are coming from, where they're going to, after visiting that particular facility and identify when and where that changes here, you can just see it's a picture of our platform. It's actually showing all the devices in Manhattan, um, over a period of time. And it's more of a heat map view. So you can actually see the hotspots in the area. >>So really the, and this is the heart of the talk, but what happened in 2020? So for men, you know, like many of you, 2020 was a difficult year COVID hit. And that changed a lot of what we're doing, not from an engineering perspective, but also from an entire company perspective for us, the motivation really became to make sure that we were lowering our costs and increasing innovation simultaneously. Now those two things often compete with each other. A lot of times you want to increase innovation, that's going to increase your costs, but the challenge last year was how to do both simultaneously. So here's a few stats for you from our team. In Q1 of last year, we were spending almost $600,000 per month on compute costs prior to COVID happening. That wasn't hugely a concern for us. It was a lot of money, but it wasn't as critical as it was last year when we really needed to be much more efficient. >>Second one is flexibility for us. We were deployed on a single cloud environment while we were cloud thought ready, and that was great. We want it to be more flexible. We want it to be on more cloud environments so that we could reach more customers. And also eventually get onto class side networks, extending the base of our customers as well from a custom analytics perspective. This is where we get into our traction. So last year, over the entire year, we computed 54,000 custom analytics for different users. We wanted to make sure that this number was steadily increasing despite us trying to lower our costs. So we didn't want the lowering cost to come as the sacrifice of our user base. Lastly, of particular percentage here that I'll say definitely needs to be improved is 75% of our projects never fail. So this is where we start to get into a bit of stability of our platform. >>Now I'm not saying that 25% of our projects fail the way we measure this is if you have a particular project or computation that runs every day and any one of those runs sale account, that is a failure because from an end-user perspective, that's an issue. So this is something that we know we needed to improve on and we needed to grow and make our platform more stable. I'm going to something that we really focused on last year. So where are we now? So now coming out of the COVID valley, we are starting to soar again. Um, we had, uh, back in April of last year, we had the entire engineering team. We actually paused all development for about four weeks. You had everyone focused on reducing our compute costs in the cloud. We got it down to 200 K over the period of a few months. >>And for the next 12 months, we hit that number every month. This is huge for us. This is extremely important. Like I said, in the COVID time period where costs and operating efficiency was everything. So for us to do that, that was a huge accomplishment last year and something we'll keep going forward. One thing I would actually like to really highlight here, two is what allowed us to do that. So first off, being in the cloud, being able to migrate things like that, that was one thing. And we were able to use there's different cloud services in a more particular, in a more efficient way. We had a very detailed tracking of how we were spending things. We increased our data retention policies. We optimized our processing. However, one additional piece was switching to new technologies on, in particular, we migrated to get lab CICB. >>Um, and this is something that the costs we use Docker was extremely, extremely easy. We didn't have to go build new new code containers or repositories or change our code in order to do this. We were simply able to migrate the containers over and start using a new CIC so much. In fact, that we were able to do that migration with three engineers in just two weeks from a cloud environment and flexibility standpoint, we're now operating in two different clouds. We were able to last night, I've over the last nine months to operate in the second cloud environment. And again, this is something that Docker helped with incredibly. Um, we didn't have to go and build all new interfaces to all new, different services or all different tools in the next cloud provider. All we had to do was build a base cloud infrastructure that ups agnostic the way, all the different details of the cloud provider. >>And then our doctors just worked. We can move them to another environment up and running, and our platform was ready to go from a traction perspective. We're about a third of the way through the year. At this point, we've already exceeded the amount of customer analytics we produce last year. And this is thanks to a ton more albums, that whole suite of new analytics that we've been able to build over the past 12 months and we'll continue to build going forward. So this is really, really great outcome for us because we were able to show that our costs are staying down, but our analytics and our customer traction, honestly, from a stability perspective, we improved from 75% to 86%, not quite yet 99 or three nines or four nines, but we are getting there. Um, and this is actually thanks to really containerizing and modularizing different pieces of our platform so that we could scale up in different areas. This allowed us to increase that stability. This piece of the code works over here, toxin an interface to the rest of the system. We can scale this piece up separately from the rest of the system, and that allows us much more easily identify issues in the system, fix those and then correct the system overall. So basically this is a summary of where we were last year, where we are now and how much more successful we are now because of the issues that we went through last year and largely brought on by COVID. >>But that this is just a screenshot of the, our, our solution actually working on supply chain. So this is in particular, it is showing traceability of a distribution warehouse in salt lake city. It's right in the center of the screen here. You can see the nice kind of orange red center. That's a distribution warehouse and all the lines outside of that, all the dots outside of that are showing where people are, where trucks are moving from that location. So this is really helpful for supply chain companies because they can start to identify where their suppliers are, are coming from or where their distributors are going to. So with that, I want to say, thanks again for following along and enjoy the rest of DockerCon.