>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> Recent conversations with IT decision makers show a stark contrast between exiting 2023 versus the mindset when we were leaving 2022. CIOs are generally funding new initiatives by pushing off or cutting lower priority items, while security efforts are still being funded. Those that enable business initiatives that generate revenue or taking priority over cleaning up legacy technical debt. The bottom line is, for the moment, at least, the mindset is not cut everything, rather, it's put a pause on cleaning up legacy hairballs and fund monetization. Hello, and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis, we tap recent discussions from two primary sources, year-end ETR roundtables with IT decision makers, and CUBE conversations with data, cloud, and IT architecture practitioners. The sources of data for this breaking analysis come from the following areas. Eric Bradley's recent ETR year end panel featured a financial services DevOps and SRE manager, a CSO in a large hospitality firm, a director of IT for a big tech company, the head of IT infrastructure for a financial firm, and a CTO for global travel enterprise, and for our upcoming Supercloud2 conference on January 17th, which you can register free by the way, at supercloud.world, we've had CUBE conversations with data and cloud practitioners, specifically, heads of data in retail and financial services, a cloud architect and a biotech firm, the director of cloud and data at a large media firm, and the director of engineering at a financial services company. Now we've curated commentary from these sources and now we share them with you today as anecdotal evidence supporting what we've been reporting on in the marketplace for these last couple of quarters. On this program, we've likened the economy to the slingshot effect when you're driving, when you're cruising along at full speed on the highway, and suddenly you see red brake lights up ahead, so, you tap your own brakes and then you speed up again, and traffic is moving along at full speed, so, you think nothing of it, and then, all of a sudden, the same thing happens. You slow down to a crawl and you start wondering, "What the heck is happening?" And you become a lot more cautious about the rate of acceleration when you start moving again. Well, that's the trend in IT spend right now. Back in June, we reported that despite the macro headwinds, CIOs were still expecting 6% to 7% spending growth for 2022. Now that was down from 8%, which we reported at the beginning of 2022. That was before Ukraine, and Fed tightening, but given those two factors, you know that that seemed pretty robust, but throughout the fall, we began reporting consistently declining expectations where CIOs are now saying Q4 will come in at around 3% growth relative to last year, and they're expecting, or should we say hoping that it pops back up in 2023 to 4% to 5%. The recent ETR panelists, when they heard this, are saying based on their businesses and discussions with their peers, they could see low single digit growth for 2023, so, 1%, 2%, 3%, so, this sort of slingshotting, or sometimes we call it a seesaw economy, has caught everyone off guard. Amazon is a good example of this, and there are others, but Amazon entered the pandemic with around 800,000 employees. It doubled that workforce during the pandemic. Now, right before Thanksgiving in 2022, Amazon announced that it was laying off 10,000 employees, and, Jassy, the CEO of Amazon, just last week announced that number is now going to grow to 18,000. Now look, this is a rounding error at Amazon from a headcount standpoint and their headcount remains far above 2019 levels. Its stock price, however, does not and it's back down to 2019 levels. The point is that visibility is very poor right now and it's reflected in that uncertainty. We've seen a lot of layoffs, obviously, the stock market's choppy, et cetera. Now importantly, not everything is on hold, and this downturn is different from previous tech pullbacks in that the speed at which new initiatives can be rolled out is much greater thanks to the cloud, and if you can show a fast return, you're going to get funding. Organizations are pausing on the cleanup of technical debt, unless it's driving fast business value. They're holding off on modernization projects. Those business enablement initiatives are still getting funded. CIOs are finding the money by consolidating redundant vendors, and they're stealing from other pockets of budget, so, it's not surprising that cybersecurity remains the number one technology priority in 2023. We've been reporting that for quite some time now. It's specifically cloud, cloud native security container and API security. That's where all the action is, because there's still holes to plug from that forced march to digital that occurred during COVID. Cloud migration, kind of showing here on number two on this chart, still a high priority, while optimizing cloud spend is definitely a strategy that organizations are taking to cut costs. It's behind consolidating redundant vendors by a long shot. There's very little evidence that cloud repatriation, i.e., moving workloads back on prem is a major cost cutting trend. The data just doesn't show it. What is a trend is getting more real time with analytics, so, companies can do faster and more accurate customer targeting, and they're really prioritizing that, obviously, in this down economy. Real time, we sometimes lose it, what's real time? Real time, we sometimes define as before you lose the customer. Now in the hiring front, customers tell us they're still having a hard time finding qualified site reliability engineers, SREs, Kubernetes expertise, and deep analytics pros. These job markets remain very tight. Let's stay with security for just a moment. We said many times that, prior to COVID, zero trust was this undefined buzzword, and the joke, of course, is, if you ask three people, "What is zero trust?" You're going to get three different answers, but the truth is that virtually every security company that was resisting taking a position on zero trust in an attempt to avoid... They didn't want to get caught up in the buzzword vortex, but they're now really being forced to go there by CISOs, so, there are some good quotes here on cyber that we want to share that came out of the recent conversations that we cited up front. The first one, "Zero trust is the highest ROI, because it enables business transformation." In other words, if I can have good security, I can move fast, it's not a blocker anymore. Second quote here, "ZTA," zero trust architecture, "Is more than securing the perimeter. It encompasses strong authentication and multiple identity layers. It requires taking a software approach to security instead of a hardware focus." The next one, "I'd love to have a security data lake that I could apply to asset management, vulnerability management, incident management, incident response, and all aspects for my security team. I see huge promise in that space," and the last one, I see NLP, natural language processing, as the foundation for email security, so, instead of searching for IP addresses, you can now read emails at light speed and identify phishing threats, so, look at, this is a small snapshot of the mindset around security, but I'll add, when you talk to the likes of CrowdStrike, and Zscaler, and Okta, and Palo Alto Networks, and many other security firms, they're listening to these narratives around zero trust. I'm confident they're working hard on skating to this puck, if you will. A good example is this idea of a security data lake and using analytics to improve security. We're hearing a lot about that. We're hearing architectures, there's acquisitions in that regard, and so, that's becoming real, and there are many other examples, because data is at the heart of digital business. This is the next area that we want to talk about. It's obvious that data, as a topic, gets a lot of mind share amongst practitioners, but getting data right is still really hard. It's a challenge for most organizations to get ROI and expected return out of data. Most companies still put data at the periphery of their businesses. It's not at the core. Data lives within silos or different business units, different clouds, it's on-prem, and increasingly it's at the edge, and it seems like the problem is getting worse before it gets better, so, here are some instructive comments from our recent conversations. The first one, "We're publishing events onto Kafka, having those events be processed by Dataproc." Dataproc is a Google managed service to run Hadoop, and Spark, and Flank, and Presto, and a bunch of other open source tools. We're putting them into the appropriate storage models within Google, and then normalize the data into BigQuery, and only then can you take advantage of tools like ThoughtSpot, so, here's a company like ThoughtSpot, and they're all about simplifying data, democratizing data, but to get there, you have to go through some pretty complex processes, so, this is a good example. All right, another comment. "In order to use Google's AI tools, we have to put the data into BigQuery. They haven't integrated in the way AWS and Snowflake have with SageMaker. Moving the data is too expensive, time consuming, and risky," so, I'll just say this, sharing data is a killer super cloud use case, and firms like Snowflake are on top of it, but it's still not pretty across clouds, and Google's posture seems to be, "We're going to let our database product competitiveness drive the strategy first, and the ecosystem is going to take a backseat." Now, in a way, I get it, owning the database is critical, and Google doesn't want to capitulate on that front. Look, BigQuery is really good and competitive, but you can't help but roll your eyes when a CEO stands up, and look, I'm not calling out Thomas Kurian, every CEO does this, and talks about how important their customers are, and they'll do whatever is right by the customer, so, look, I'm telling you, I'm rolling my eyes on that. Now let me also comment, AWS has figured this out. They're killing it in database. If you take Redshift for example, it's still growing, as is Aurora, really fast growing services and other data stores, but AWS realizes it can make more money in the long-term partnering with the Snowflakes and Databricks of the world, and other ecosystem vendors versus sub optimizing their relationships with partners and customers in order to sell more of their own homegrown tools. I get it. It's hard not to feature your own product. IBM chose OS/2 over Windows, and tried for years to popularize it. It failed. Lotus, go back way back to Lotus 1, 2, and 3, they refused to run on Windows when it first came out. They were running on DEC VAX. Many of you young people in the United States have never even heard of DEC VAX. IBM wanted to run every everything only in its cloud, the same with Oracle, originally. VMware, as you might recall, tried to build its own cloud, but, eventually, when the market speaks and reveals what seems to be obvious to analysts, years before, the vendors come around, they face reality, and they stop wasting money, fighting a losing battle. "The trend is your friend," as the saying goes. All right, last pull quote on data, "The hardest part is transformations, moving traditional Informatica, Teradata, or Oracle infrastructure to something more modern and real time, and that's why people still run apps in COBOL. In IT, we rarely get rid of stuff, rather we add on another coat of paint until the wood rots out or the roof is going to cave in. All right, the last key finding we want to highlight is going to bring us back to the cloud repatriation myth. Followers of this program know it's a real sore spot with us. We've heard the stories about repatriation, we've read the thoughtful articles from VCs on the subject, we've been whispered to by vendors that you should investigate this trend. It's really happening, but the data simply doesn't support it. Here's the question that was posed to these practitioners. If you had unlimited budget and the economy miraculously flipped, what initiatives would you tackle first? Where would you really lean into? The first answer, "I'd rip out legacy on-prem infrastructure and move to the cloud even faster," so, the thing here is, look, maybe renting infrastructure is more expensive than owning, maybe, but if I can optimize my rental with better utilization, turn off compute, use things like serverless, get on a steeper and higher performance over time, and lower cost Silicon curve with things like Graviton, tap best of breed tools in AI, and other areas that make my business more competitive. Move faster, fail faster, experiment more quickly, and cheaply, what's that worth? Even the most hard-o CFOs understand the business benefits far outweigh the possible added cost per gigabyte, and, again, I stress "possible." Okay, other interesting comments from practitioners. "I'd hire 50 more data engineers and accelerate our real-time data capabilities to better target customers." Real-time is becoming a thing. AI is being injected into data and apps to make faster decisions, perhaps, with less or even no human involvement. That's on the rise. Next quote, "I'd like to focus on resolving the concerns around cloud data compliance," so, again, despite the risks of data being spread out in different clouds, organizations realize cloud is a given, and they want to find ways to make it work better, not move away from it. The same thing in the next one, "I would automate the data analytics pipeline and focus on a safer way to share data across the states without moving it," and, finally, "The way I'm addressing complexity is to standardize on a single cloud." MonoCloud is actually a thing. We're hearing this more and more. Yes, my company has multiple clouds, but in my group, we've standardized on a single cloud to simplify things, and this is a somewhat dangerous trend, because it's creating even more silos and it's an opportunity that needs to be addressed, and that's why we've been talking so much about supercloud is a cross-cloud, unifying, architectural framework, or, perhaps, it's a platform. In fact, that's a question that we will be exploring later this month at Supercloud2 live from our Palo Alto Studios. Is supercloud an architecture or is it a platform? And in this program, we're featuring technologists, analysts, practitioners to explore the intersection between data and cloud and the future of cloud computing, so, you don't want to miss this opportunity. Go to supercloud.world. You can register for free and participate in the event directly. All right, thanks for listening. That's a wrap. I'd like to thank Alex Myerson, who's on production and manages our podcast, Ken Schiffman as well, Kristen Martin and Cheryl Knight, they helped get the word out on social media, and in our newsletters, and Rob Hof is our editor-in-chief over at siliconangle.com. He does some great editing. Thank you, all. Remember, all these episodes are available as podcasts wherever you listen. All you've got to do is search "breaking analysis podcasts." I publish each week on wikibon.com and siliconangle.com where you can email me directly at david.vellante@siliconangle.com or DM me, @Dante, or comment on our LinkedIn posts. By all means, check out etr.ai. They get the best survey data in the enterprise tech business. We'll be doing our annual predictions post in a few weeks, once the data comes out from the January survey. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, everybody, and we'll see you next time on "Breaking Analysis." (upbeat 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 last 10 months have forced upon us a new digital reality. If you weren't a digital business, you were basically out of business. Hello everybody. This is Dave Vellante and welcome to this week's Wikibon CUBE Insights powered by ETR. In this Breaking Analysis, we're going to share with you some fresh data from ETR on CIO spending, which is giving us a lot of optimism for 2021. We'll also set forth our thinking on the new digital economy, and really talk a little bit about where we see some of the opportunities and some of the spending and how those shifts are going to occur in the near term and midterm and even long term. Let's bring up sort of the first set of talking points that I want to share with you. 2020 has been a year of instant pivots, as we all know, and it's forced us to march toward a new digital reality, digital transformation, as everybody talks about, has been compressed by two to three years, but it's really been a Petri dish for everybody. Now, earlier this year, and we've been consistent since we first came out with this forecast of minus four to five percent in IT spending this year. The survey data suggests that, and even though Q3 saw a big bounce back in spending in GDP, we've still really maintained that -4 to -5%. We're seeing a comeback in the lockdown and the virus, and as such, we, you know, maintain that conservative forecast. Our current 2% growth for 2021 appears to be conservative based on the latest data we have. It could be as high as four to 5% growth in 2021. And we'll update that formally in January, but hold that thought. As part of that, as I said, we've seen accelerated digital business initiatives, led to really strong pockets in many sectors. We've seen that in video conferencing, in laptops, obviously, we've seen that in certain security sectors that we've detailed, like identity access management, like endpoint, like cloud security, cloud itself, and we've seen a big trend toward application modernization. So those sectors of the business, including those other data sectors, we certainly see the ascendancy of Snowflake, Snowflake closed the day on Friday, evaluation of Snowflake on Friday was now above that of ServiceNow, Snowflake's valuation is currently around the same, just slightly under that of IBM's, think about that. A company that was formed in 2015 is now as valuable almost as IBM, a 100 plus year old company. That's quite amazing to think about, why is that? It's because data now is at the center of the universe, and that's obviously what Snowflake's transformation is all about. The pace of the vaccine distribution appears to be accelerated. But as I said earlier, winter is coming in the Northern Hemisphere, and that's causing some concern. But overall, ETR survey data suggests that there's really positive signs in recovery, and we'll get into that. Companies are learning to leverage the cloud, cloud migration was a big priority in the last 10 months, that, including security, and people are realizing that, "Wow, we can actually change the operating model with cloud and it's helping with our agility." And we're going to show you some data that really supports that. As I kind of alluded to earlier, COVID created this massive digital business proof of concept, and the learnings from that experiment are going to get operationalized in 2021. And it's going to be a rapid year of invention and reinvention. And so that's why we think IT spending could snap back dramatically in 2021. Now ETR, when it does its surveys, will oftentimes do drill downs. And I want to share now with you, the next slide shows some drill downs from the COVID study, ETR since early this year, since March has been doing COVID studies, we've been reporting on that extensively, ETR was really the first to report that whole work from home pivot really, really early on in the cycle. So we use that as sort of a harbinger of things to come. This slide asked organizations in the past 12 months, "What is your thinking on when spending is going to bounce back to 2019 levels?" And that's really what's shown in this chart. So, you know, pre-COVID levels really was the question. "When does your organization expect IT budgets to return to pre-COVID levels?" You can see here on the left-hand side, 11% have said they increased budgets since the start of COVID. And those are the ones that are really in the best position. Certain e-commerce companies, those where COVID was actually a tailwind. 24% said, "We're already back to those 2019 pre-COVID levels." And then you can see as well, approximately 30% say that within 12 months they'll be back. 22% say within 24 months. And I know that's a big chunk of the economy in the CIO spend base, but only 4% that it's going to be more than two years. So a very large portion of the survey base, which is over 1400, suggest that there's optimism in the near term. Now, what we want to show you in the next chart is the factors that really enabled the organizations to be agile and resilient during COVID-19. Now it's no surprise that 84% said that being prepared for a remote workforce. Now, were it not for technology, we really would not have been able to respond to COVID in the way in which we have. And I think everybody really understands that. 44% said business continuity plans as we've reported in the past, many people told us their business continuity was far too DR-focused, they've shifted that focus in the last 10 months, really toward being able to pivot their businesses, and identify new opportunities. And so, that's something that we feel is going to carry through into 2021 and beyond. 39% said C-suite flexibility, I think this is a really important point, where the C-suite recognized the importance of investing in technology, and really understanding that it's now a strategic enabler, of course always has been, but now more than ever. You can see also that 30% said budget flexibility enabled them, and that is a function of we've got low interest rates, many many corporations if not most corporations improved their balance sheets by tapping corporate debt. And only 27% said emerging technologies, I shouldn't say "only", 27% cited emerging technologies as a primary factor that enabled their business resiliency, and I would argue that many of that emerging technologies probably falls into that 84% on that left-hand bar. So overall, you can see that the priorities of CIOs have shifted in the last 10 months, and it's not just going to snap back to where we were pre-COVID. As we've said many times, and many believe, these are permanent changes. Now, you may be asking, "Okay, where is the action going? Where are people spending? What are they adopting as new technologies?" And that's really what we want to show you here in this next slide. So what this slide does, you may recall the net score methodology that ETR uses. Net score is a measure of spending momentum. Basically, what it does is it breaks down those companies that are spending more, or a company, it breaks down the percentage of that company that's spending more versus spending less on a particular technology. So it's really, there's several components to it, one is new adoptions, the other is spending more, the other is flat, spending less, or retiring. So what we're isolating here in this chart is the new adoptions. And you can see here, that we've highlighted a few areas, container orchestration and container platforms. You can see those high, and we're showing three survey bases, October 19, July 20, which is the blue, and October 20, which is the yellow. And yes, while the spending is down from some of the previous highs, you can see the elevated levels of container orchestration, container platforms, machine learning and AI, and robotic process automation. What is that telling you? It says that people are modernizing their applications portfolios, they're applying machine learning and machine intelligence to get more value from data, AI plus data plus cloud is that new innovation cocktail that we've talked about a lot. And then we've also talked about the automation mandate, that we haven't seen the productivity improvements in the US and Europe over the last two decades that we would've liked to seen, so there really is an automation mandate, that's what the RPA adoption is all about. So really trying to drive those productivity gains. Now interestingly, you may look at this slide and say "Wow, look at how low cloud is. We hear all the time that cloud migration is a big priority, why is cloud so low?" So let's bring up the next chart and address that. This chart takes that increased spend portion of the net score, and remember I said it's broken down adoptions, spend more, spend less, et cetera, this is the increased spend, the spend more. Now look at cloud computing, it's up in the 46% range, that's 46% of the customers that responded in the cloud computing sector said they're increasing spending on cloud. So how do you interpret that from the previous slide? They're already in the cloud, that's why the new adoptions was low, 'cause everybody's doing some form of cloud, but this is a real tell sign. People are dramatically increasing their spending in cloud relative to some of these other areas, of course, same with container orchestration, container platforms, all about developer productivity, write once, run anywhere type of thing, it hedges for multicloud, bringing on-prem infrastructure into the cloud or on-prem apps into the cloud, that's what sort of you're seeing there with container. So this is the sort of 40% club, cloud computing, containers, machine learning and AI up at 40% spending more, and then again, robotic process automation. So, that sort of explains the cloud component, and you can see the container, the container orchestration and the automation piece also at very elevated levels. Let me wrap here by talking about some factors to watch, and I'll highlight them on this slide. Look, the propensity toward a lockdown definitely creates uncertainty and caution, you've got a new administration, there seems to be more of a willingness to lock down, the slowdown the economy, there's still uncertainty around fiscal stimulus, although it looks like that's going to be addressed hopefully in the near term. But there's still uncertainty around that. While that does potentially dampen spend for Q4, because of that uncertainty, it also creates further pent-up demand. As I said before, there's been 10 months of learnings from this forced march to digital transformations, and that is informing 2021 tactical plans, and then even longer term plans, long term planning has changed. When you talk to the C-suite and the conversation's going on at boards of directors, speed and the ability to turn on a dime, they're now fundamental principles that are being designed into businesses. This is a mainstay of the digital economy, we are entering a new era of digital business, and there's going to be the haves and the have nots. And the have nots are going to disappear, and the haves are going to do better. As I say, boards and CEOs, they got a glimpse of the future in 2021, but it was forced on them, it really wasn't planned. But it was an awesome Petri dish and experiment to understand what works, what doesn't, and they're now going to double down on those things that are sure bets. And those that don't act, as I say, they're going to be out of business. At the macro, yes, you've got, again, haves and have nots, and the have nots are going to potentially dampen, you're going to see companies that really got hurt, are going to constrict spending, no question, and that could dampen spending at the macro. But in our view, the survivors are going to prop up spending in 2021, it could be significantly above our initial estimates of 2%, could be as high as double that, maybe even four to 5% in 2021. So we're going to continue to watch that, we'll continue to check out the survey data, we'll have a complete update in the January survey, and in the meantime, we'll continue to report on the latest trends, both from the CUBE community, and also from ETR. So that's it for now, thanks for watching, don't forget, all these episodes are available on podcasts, wherever you listen. I publish weekly on SiliconAngle.com and Wikibon.com, check out ETR+ for all the survey action, and please do comment on my LinkedIn posts, you can also reach me @DVellante on Twitter, or you can email me at David.Vellante@SiliconAngle.com. This is Dave Vellante for theCUBE Insights powered by ETR, thanks for watching, everybody, see you next time. (calm music)

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante cios in the most recent september etr spending survey tell us that they expect a slight sequential improvement in q4 spending relative to q3 but still down four percent from q4 2019 so this picture is still not pretty but it's not bleak either to whit firms are adjusting to the new abnormal and are taking positive actions that can be described as a slow thawing of the deep freeze hello everyone this is dave vellante and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we're going to review fresh survey data from etr and provide our outlook for both q4 of 2020 and into 2021. now we're still holding at our four to five percent decline in tech spending for 2020 but we do see light at the end of the tunnel with some cautions specifically more than a thousand cios and it buyers have we've surveyed expect tech spending to show a slight upward trend of roughly two percent in 2021. this is off of a q4 decline of 4 relative to q4 2019 but i would put it this way a slightly less worse decline sequentially from q3 last quarter we saw a 5 decline in spending okay so generally more of the same but things seem to be improving again with caveats now in particular we'll show data that suggests technology project freezes are slowly coming back and we see remote workers returning at a fairly significant rate however executives expect nearly double the percentage of employees working remotely in the midterm and even long term than they did pre-covert that suggests that the work from home trend is not cyclical but showing signs of permanence and why not cios report that on balance productivity has been maintained or even improved during covit now of course this all has to be framed in the context of the unknowns like the fall and even winter surge what about fiscal policy there's uncertainty in the election social unrest all right so let's dig into some of the specifics of the etr data now i mentioned uh the number of respondents at over a thousand i have to say this was predominantly a us-based survey so it's it's 80 sort of bias to the u.s and but it's also weighted to the big spenders in larger organizations with a nice representation across industries so it's good data here now you can see here the slow progression of improvement relative to q3 which as i said was down five percent year-on-year with the four percent decline expected in q4 now etr is calling for a roughly four percent decline for the year you know i've been consistently in the four to five percent decline range and agree with that outlook and you can see cios are planning for a two percent uptick in 2021 as we said at the open now in our view this represents some prudent caution and i think there's probably some upside but it's a good planning assumption for the market overall in my view now let's look at some of the actions that organizations are taking and how that's changed over time you can see here that organizations they're slowly releasing that grip on tech spending overall you know still no material change in employees working from home or traveling we can see that hiring freezes are down that's that's positive in the green as our new i.t deployment freezes and a slight uptick in acceleration of new deployments now as well you see fewer companies are planning layoffs and while small the percent of companies adding head count has doubled from last quarter's you know minimal number all right so this is based on survey data at the end of the summer so it reflects that end of summer sentiment so we got to be a little bit cautious here and i think cios are you know by nature cautious on their projections of two percent up in 2021. now importantly remember this does not get us back to 20 20 19 spending levels so we may be seeing a kind of a long slow climb out of this you know tepid market maybe 2022 gets back over 2019 before we start to see sustained growth again and remember these recoveries are rarely smooth they're not straight lines so you got to expect some choppiness with you know some pockets of opportunity which we'll discuss here in this slide we're showing the top areas that respondents cited as spending priorities for q4 and into 2021 so the chart shows the ratings based on a seven-point scale and these are the top spending initiatives heading into the year end now as we've been saying for the better part of a decade cyber security is a do-over and i've joked you know if it ain't broke don't fix it well coven broke everything and cyber is an area that's seeing long-term change in my opinion endpoint security identity access management cloud security security as a service these are all trends that we're seeing as really major waves as a result of covid now it's coming at the expense of large install bases of things like traditional hardware-based firewalls and we've talked about this a lot in previous segments cloud migration is interesting and i really think it needs some interpretation i mean nobody likes to do migrations so i would suggest this includes things like i have a bunch of people answering phones and offices or i had and then overnight boom the offices are closed so i needed a cloud-based solution i didn't just lift and ship my shift my entire phone routing system you know from the office into the cloud but i probably pivoted to a cloud solution to support those work from home employees now my guess is i think that would be included in these responses i mean i do know an example of an insurance company that did migrate its claims application to the cloud during coven but this was something that they were you know planning to do pre-covered and i guess the point here is twofold again like i said migrations are hairy nobody wants to do them and i think this category really means i'm increasing my use of the cloud so i'm kind of migrating my my operations over time to the cloud all right look at collaboration no shocker here we've pounded you know zoom and webex to death analytics is really interesting we have talked extensively uh and have been covering snowflake and we pointed out that there's a new workload that has emerged in the cloud it's not just snowflake you know there are others aws redshift google with bigquery and and others but snowflake is the off the charts you know hot ipo and so we we talk a lot about it but it relates to this easy setup and access to a data layer with having you know requisite security and governance and this market is exploding adding ai on top and really doing this in the cloud so you can scale it up or down and really only pay for what you need that's a real benefit to people compare that to the traditional edw snake swallowing a basketball i got to get every new intel chip you're not dialing up down down you're over provisioning and half the time you're not using you know half most of the time you're not utilizing what you've paid for all right look at networking you know traffic patterns changed overnight with covet ddos attacks are up 25 to 40 percent uh since coven cyber attacks overall are up 400 percent this year so these all have impacts on the network machine learning and ai i talked about a little bit earlier about that but organizations are realizing that infusing ai into the application portfolio it's becoming really an imperative much more important as the automation mandate that we've talked about becomes more acute people you can't scale humans at this at the pace of technology so automation becomes much more important that of course leads us to rpa now you might think rpa should be a higher priority but i think what's happening here is i t organizations they were scrambling to plug holes in the dike rpa is somewhat more strategic and planful our data suggests that rpa remains one of the most elevated spending categories in terms of net score etr's measure of spending momentum so this means way more people are spending more than spending less in the rpa category so it really has a lot of legs in fact with the exception of container orchestration i think rpa is a sector that has the highest net score i think you'll see that in the upcoming surveys it's as high or even higher than ai i think it's higher than cloud it's just that it remember this is an it survey and a lot of the rpa stuff is going on at the business level but it had to keep the ship afloat when coveted hit which somewhat shifted priorities but but rpa remains strong now let's go back uh to the work from home trend for a moment i know it's been been played out and kind of beat on really heavily covered but i got to tell you etr was the very first on this trend it was way back in march and the data here is instructive it shows that the percentage of employees working from home prior to cor covid currently working from home the percent expected in six months and then those expected essentially permanently and this is primarily work from home versus yeah i don't work a day or two per week it's really the the five day a week i i work remotely as you can see only 16 percent of employees were working from home pre pandemic whereas more than 70 percent are at home today and cios they actually see a meaningful decline in that number over the next six months you know we'll see based on how covid comes back and you know this fall and winter surge and how will that will affect these plans but look what it does long term it settles in at like 34 percent that's double pre-covet so really a meaningful and permanent impact is expected from the isolation economy that we're in today and again why not look at this data it shows the distribution of productivity improvements so that while 23 of respondents said work from home productivity impacts were neutral nearly half i think it was 48 if you add up those bars on the right nearly half are seeing productivity improvements well less than 30 percent see a decline in productivity and you can see the etr quants they peg the average gain at between three and five percent that's pretty significant now of course not everyone can work from home if you're working at a restaurant you really you know unless you're in finance you really can't work from home but we're seeing in this digital economy with cloud and other technologies that we actually can work from pretty much anywhere in the world and many employees are going to look at work from home options as a benefit you know it was just a couple years ago remember that we were talking about companies like ibm and yahoo who mandated coming into the office i mean that was like 2017 2018 time frame well that trend is over now let me give you a quick preview of some of the other things that we're seeing and what the etr data shows now let me also say i'm just scratching the surface here etr has deep deep data cuts they have the sas platform allows you to look at the data all different ways and if you're not working with them you should be because the data gets updated so frequently every quarter there's new data there's drill down surveys and it's forward-looking so you know a lot of the survey data or a lot of the data that we use market share data and other data are sort of looking back you know you use your sales data your sales forecast that's obviously forward-looking but but the etr survey data can actually give an observation space outside of your sales force and no i'm not getting paid by etr but but it's been such a valuable resource i want to make it available and make the community aware of it all right so let's do a little speed round on on some of the the vendors of interest that we've talked about in the last several segments last couple years actually many years decade anyway start with aws aws continues to be strong but they they have less momentum than microsoft this is sort of a recurring pattern here but aws churn is low low low not a lot of people leaving the aws platform despite what we hear about this repatriation trend data warehousing is a little bit soft whereas we see snowflake very very strong but aws share is really strong inside of large companies so cloud and teams and security are strong from microsoft whereas data warehouse and ai aren't as robust as we've seen before but but microsoft azure cloud continues to see a little bit more momentum than aws so we'll watch that next quarter for aws earnings call now google has good momentum and they're steady especially in cloud database ai and analytics we've talked a lot about how google's behind the big two but nonetheless they're showing good good momentum servicenow very low churn but they're kind of hitting the law of large numbers still super strong in large accounts but not the same red hot hat red hot momentum as we've seen in the past octa is showing continued momentum they're holding you know close to number one or that top spot in security that we talked about last time no surprise given the increased importance of identity access management that we've been talking about so much crowdstrike last survey in july they showed some softness despite a good quarter and and we we're seeing continued to sell it to deceleration in the survey now that's from extremely elevated levels but it's significantly down from where crowdstrike was at the height of the lockdown i mean we like the sector of endpoint security and crowdstrike is definitely a leader there and you know well-managed company company but you know maybe they got hit with uh with you know a quick covet injection with with a step up function that's maybe moderating somewhat you know maybe there's some competition you know vmware freezing the market with carbon black i i really don't see that i think it's it's it's you know maybe there's some survey data isn't reflective of of what what crowdstrike is seeing we're going to see in the upcoming earnings release but it's something that we're watching very closely you know two survey snapshots with crowdstrike being a little bit softer it doesn't make a sustained trend but we would have liked to seen you know a little bit stronger this this quarter the data's still coming in so we'll see sale point is one we focused on recently and we see very little negative in their numbers so they're holding solid z scalar showing pretty strong momentum and while there was some concern last survey within large organizations it seemed that might have been a survey anomaly because z scalar they had a strong quarter a good outlook and we're seeing a strong recovery in the most recent data so it also looks like z z scaler is pressuring some of palo alto network's dominance and momentum heading into the quarter so we'll pay close attention to that we've said we like palo alto networks but they're so big uh they've got some exposures but they can offset those you know and they're doing a better job in cloud with their pricing models and sort of leaning into some of the the market waves uh sale point appears to be holding serve you know heading into the fourth quarter snowflake i mean what can we say it continues to show some of the strongest spending momentum going into q4 and into 2021 no signs of slowing down they're going to have their first earnings reports coming up you know in a few months so i i got to believe they got it together and and they're going to be strong reports uipath and momentum is is slowing down a bit but existing customers keep spending with ui path and there's very few defections so it looks like their land and expand is working pretty well automation anywhere continues to be strong despite comments about the sector earlier which showed you know maybe it wasn't as high a priority some other sectors but as i said you know it's still really really strong strong in terms of momentum and automation anywhere in uipath they continue to battle it out for the the top spot within the data set within the automation data set well i should say within rpa i mean companies like pega systems have a broader automation agenda and we really like their strategy and their execution databricks you know hot company once a hot company and still hot but we're seeing a little bit of a deceleration in the survey even though new customer acquisition is quite strong put it this way databricks is strong but not the off the chart outperformer that it used to be this is how etr frame that their analysis so i want to obviously credit that to them datadog showing the most strength in the application performance management or monitoring sector whichever you prefer but generally the the net scores in that sector as we talked about last week they're not great as a sector when you compare it to other leading sectors like cloud or automation rpa as an example container orchestration you know apm is kind of you know significantly lower it's not it's not as low as some of the on-prem on-prem infrastructure or some of the on-prem software but you know given datadog's high valuation it's somewhat of a concern so keep an eye on that mongodb you know they got virtually no customer churn but they're losing some momentum in terms of net score in the survey which is something we're keeping an eye on and a big downtick in in large organization acquisitions within the data so in other words they had a lot of new acquisitions within large companies but that's down now again that could be anomalies in the data i don't want to you know go to the bank on that necessarily but that's something to watch zoom they keep growing but etr data cites a churn of actually up to seven percent due to some security concerns so that was widely reported in the press and somewhere slower velocity for zoom overall due to possible competition from microsoft teams but i tell you it has an amazing stat that etr threw out pre-cove at zoom penetration in the education vertical was 15 today it's over 80 percent wowza cisco cisco's core is weak as we've said you've seen that in their earnings numbers it's it's there's softness there but security meraki those are two areas that remain strong same kind of similar story to last quarter survey pure storage you know they're the the high flyer they're like the one-eyed man in the land of the the storage blind so storage you know not a great market we've talked about that we've seen some softness in the the data set from uh in pure storage and really often sympathy with the generally back burner storage market you know again they they still outperforming their peers but we've seen slower growth rates there in the in in the survey and that's been reflected in their earnings uh so we've been talking about that for a while really keeping an eye on on on pure they made some acquisitions trying to expand their market enough said about that rubric rubric's interesting they kind of were off the charts in a couple surveys ago and they really come off of those highs you know anecdotally we're hearing some concerns in in the market it's hard to tell the private company cohesity has overtaken rubric and spending momentum now for the second quarter in a row you know they're still not as prevalent in the data set we'd like to see more ends from cohesity remember this is sort of a random sample across multiple industries we let the or etr lets the the respondents tell them what they're buying and what they're spending on you know but because cohesity has the highest net score relative to to compares like rubric like veeam you know i even threw in when i looked at nutanix pure dell emcs vxrail those are not direct competitors but they're you know kind of quasi compares if you will new relic they're showing some concerning trends on churn and the company is way off its 2018 momentum highs in the survey and we talked about this last week some of the challenges new relic is facing but we like their tech the nrdb is purpose-built for monitoring and performance management and we feel like you know they can retain their leadership if they can can pull it together we talked about elliott management being in there so that's something that we're watching red hat is showing strength in open shift really really strong ibm you know services exposure uh it's it's not the greatest business in the world right now at the same time there's there's crosswinds there at the same time people you know need some services and they need some help there but the certainly the outsourcing business so there's you know countervailing you know crosswinds uh within ibm but openshift bright spot i i think you know when i look at at the the red hat acquisition yeah 34 billion but but it's it's pretty obvious why ibm made that move um but anyway ibm's core business continues to be under under pressure that's why red hat is such an important component which brings me to vmware vmware has been an execution machine they had vmworld this past week uh we talked last month about the strength of vmware cloud on aws and it's still strong and and vmware cloud portfolio with vmware cloud foundation and other offerings but other than tanzu vmware is in this october survey of the first first look shows some deceleration really across the board you know one potential saving grace etr shared with me is that the fortune 500 spending for vmware is stronger so maybe on a spend basis when i say stronger stronger stronger than the mean so maybe on a spend basis vmware is okay but there seems to be some potential exposure there you know we won't know for sure until late next year uh how the dell reshuffle is going to affect them but it's going to be interesting to see how dell restructures vmware's balance sheet to get its own house in order and remember dell wants to get to investment grade for its own balance sheet yet at the same time it wants to keep vmware at investment grade but the interesting thing to watch is what impact that's going to have on vmware's ability to fund its future and we're not going to know that for a long long time but you know we'll keep an eye on on those developments now dell for its part showing strength and work from home and also strengthen giant public and privates which is a bellwether in the etr data set uh you know these are huge private companies for example uh koch industries would be one you know massive private companies mars would be another example not necessarily that they're the ones responding although my guess is they are it's it's anonymous but actually etr actually knows and they can identify who those bell weathers are and it's been a it's been a predictor of performance for the last you know better part of a decade so we'll see vxrail is strong um you know servers and storage they're they're still muted relative to last year but not really down from july so you know holding on dell holding on to it to to a tepid spending outlook they got such huge exposure on-prem you know so on balance i wouldn't expect you know a barn burner out of dell you know but they got a big portfolio and they've got a lot of a lot of options there and remember they still have the the still have they have a pc uh business unlike hpe which i'll talk about in in in a moment talk about now aruba is the bright spot for hpe but servers and storage those seem to be off you know similar to dell uh but but but maybe even down further i think you know dell is kind of holding relative to last quarter survey you know down from earlier this year and certainly down from from last year uh but hpe seems to be on a steeper downward trajectory uh in storage and service from the survey you know we'll see again you know one one snapshot quarter this is not a trend to make uh but again storage looks particularly soft which is a bit of a concern and we saw that you know in hpe's numbers you know last quarter um customer acquisition is strong for nutanix but overall spending is decelerating versus a year ago levels uh we know about the 750 million dollar injection uh from from bain capital basically you know in talking to bain what essentially they're doing is they they're betting on upside in the hyper-converged marketplace it's true that from a penetration standpoint there's a long long way to go and it's also true that nutanix is shifting from a you know perpetual model you know boom by the the capex to a in an annual occurring revenue model and they kind of need a bridge of cash to sort of soften that blow we've seen companies like tableau make that transition adobe successfully made that transition splunk is in that transition now and it's you know kind of funky for them but at any rate you know within that infrastructure software and virtualization sectors you know nutanix is showing some softness but in things like storage actually nutanix looking pretty strong very strong actually so again this theme of of these crosswinds uh supporting some companies whereas they're exposed in other areas you certainly see that with large companies and and nutanix looks like it's got some momentum in some areas and you know challenges in in others okay so that's just a quick speed dating round with some of the vendor previews for the upcoming survey so i just want to summarize now and we'll wrap so we see overall tech spending off four to five percent in 2020 with a slightly less bad slightly less bad q4 sequentially relative to q3 all this is relative to last year so we see continued headwinds coming into 2021 expect low single-digit spending growth next year let's call it two percent and there are some clear pockets of growth taking advantage of what we see is a more secular work from home trend particularly in security although we're watching some of the leaders shift positions cloud despite the commentary earlier remains very very strong aws azure google red hat open shift serverless kubernetes analytic cloud databases all very very strong automation also stands out as as a a priority in what we think is the coming decade with an automation mandate and some of the themes we've talked about for a long time particularly the impact of cloud relative to on-prem you know we don't see this so-called repatriation as much of a trend as it is a bunch of fun from on-prem vendors that don't own a public cloud so just you just don't see it i mean i'm sure there are examples of oh we did something in the cloud we lifted and shifted it didn't work out we didn't change our operating model okay but the the number of successes in cloud is like many orders of magnitude you know greater than the numbers of failures on the plus side however the for the on-prem guys the hybrid and multi-cloud spaces are increasingly becoming strategic for customers so that's something that i've said for a long time particularly with multi-cloud we've kind of been waiting it's been a lot of vendor power points but that really we talked to customers now they're hedging their bets in cloud they're they're putting horses for courses in terms of workloads they're they're they're not betting their business necessarily on a single cloud and as a result they need security and governance and performance and management across clouds that's consistent so that's actually a a really reasonable and significant opportunity for a lot of the on-prem vendors and as we've said before they're probably not necessarily going to trust the cloud players the public cloud players to deliver that they're going to want somebody that's cloud agnostic okay that's it for this week remember all these episodes are available as podcasts wherever you listen so please subscribe i publish weekly on wikibon.com and siliconangle.com and don't forget to check out etr.plus for all the survey action and the analytics these guys are amazing i always appreciate the comments on my linkedin posts thank you very much you can dm me at d vallante or email me at david.volante at siliconangle.com and this is dave vellante thanks for watching this episode of cube insights powered by etr be well and we'll see you next time you

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation as we've been reporting the Koba 19 pandemic has created a bifurcated IT spending picture and over the last several weeks we've reported both on the macro and even some come at it from from a vendor and a sector view I mean for example we've reported on some of the companies that have really continued to thrive we look at the NASDAQ and its you know near at all-time highs companies like oh and in CrowdStrike we've reported on snowflake uipath the sectors are PA some of the analytic databases around AI maybe even to a lesser extent cloud but still has a lot of tailwind relative to some of those on-prem infrastructure plays even companies like Cisco bifurcated in and of themselves where you see this Meraki side of the house you know doing quite well the work from home stuff but maybe some of the traditional networking not as much well now what if you flip that to really try to understand what's going on with the shape of the recovery which is the main narrative right now is it a v-shape does it a u-shape what is what's that what do people expect and now you understand that you really have to look at different industries because different industries are going to come back at a different pace with me again is Sagar khadiyah who's the director of research at EGR Sagar you guys are all over this as usual timely information it's great to see you again hope all is well in New York City thanks so much David it's a pleasure to be back on again yeah so where are we in the cycle we give dividend a great job and very timely ETR was the first to really put out data on the koban impact with the survey that ran from mid-march to to mid-april and now everybody's attention sagar is focused on okay we're starting to come back stores are starting to open people are beginning to to go out again and everybody wants to know what the shape of the recovery looks like so where are we actually in that research cycle for you guys yeah no problem so like you said you know in that kind of march/april timeframe we really want to go out there and get an idea of what we're doing the budget impacts you know as it relates to IT because of kovat 19 right so we kind of ended off there around a decline of 5% and coming into the year the consensus was of growth of 4 or 5% right so we saw about a 900,000 basis points wing you know to the negative side and the public covered in March and April were you know which sectors and vendors were going to benefit as a result of work from home and so now as we kind of fast forward to the research cycle as we kind of go more into May and into the summer rather than asking those exact same question to get again because it's just been you know maybe 40 or 50 days we really want Singh on the recovery type as well as kind of more emerging private vendors right we want to understand what's gonna be the impact on on these vendors that typically rely on you know larger conferences more in-person meetings because these are younger technologies there's not a lot of information about them and so last Thursday we launched our biannual emerging technology study it covers roughly 300 private emerging technologies across maybe 60 sectors of technology and in tandem we've launched a co-ed flash poll right what we wanted to do was kind of twofold one really understand from CIOs the recovery type they had in mind as well as if they were seeing any any kind of permanent changes in their IT stacks IT spend because of koban 19 and so if we kind of look at the first chart here and kind of get more into that first question around recovery type what we asked CIOs and this kind of COBIT flash poll again we did it last Thursday was what type of recovery are you expecting is it v-shaped so kind of a brief decline you know maybe one quarter and then you're gonna start seeing growth in 2 to H 20 is it you shaped so two to three quarters of a decline or deceleration revenue and you're kind of forecasting that growth in revenue as an organization to come back in 2021 is it l-shaped right so maybe three four five quarters of a decline or deceleration and then you know very minimal to moderate growth or none of the above you know your organization is actually benefiting from from from koban 19 as you know we've seen some many reports so those are kind of the options that we gave CIOs and you kind of see it on that first chart here interesting and this is a survey a flash service 700 CIOs or approximately and the interesting thing I really want to point out here is this you know the koban pandemic was it didn't suppress you know all companies you know and in the return it's not going to be a rising tide lifts all ships you really got to do your research you have to understand the different sectors really try to peel back the onion skin and understand why there's certain momentum how certain organizations are accommodating the work from home we heard you know several weeks ago how there's a major change in in networking mindsets we're talking about how security is changing we're going to talk about some of the permanence but it's really really important to try to understand these different trends by different industries which you're going to talk about in a minute but if you take a look at this slide I mean obviously most people expect this u-shaped decline I mean a you know a u-shaped recovery rather so it's two or three quarters followed by some growth next year but as we'll see some of these industries are gonna really go deeper with an l-shape recovery and then it's really interesting that a pretty large and substantial portion see this as a tailwind presumably those with you know strong SAS models some annual recurring revenue models your thoughts if we kind of star on this kind of aggregate chart you know you're looking at about forty four percent of CIOs anticipated u-shaped recovery right that's the largest bucket and then you can see another 15 percent and to say an l-shape recovery 14 on the v-shaped and then 16 percent to your point that are kind of seeing this this tailwind but if we kind of focus on that largest bucket that you shaped you know one of the thing to remember and again when we asked is two CIOs within the within this kind of coded flash poll we also asked can you give us some commentary and so one of the things that or one of the themes that are kind of coming along with this u-shaped recovery is you know CIOs are cautiously optimistic about this u-shaped recovery you know they believe that they can get back on to a growth cycle into 2021 as long as there's a vaccine available we don't go into a second wave of lockdowns economic activity picks up a lot of the government actions you know become effective so there are some kind of let's call it qualifiers with this bucket of CIOs that are anticipating a u-shape recovery what they're saying is that look we are expecting these things to happen we're not expecting that our lock down we are expecting a vaccine and if that takes place then we do expect an uptick in growth or going back to kind of pre coded levels in in 2021 but you know I think it's fair to assume that if one or more of these are apps and and things do get worse as all these states are opening up maybe the recovery cycle gets pushed along so kind of at the aggregate this is where we are right now yeah so as I was saying and you really have to understand the different not only different sectors and all the different vendors but you got to look into the industries and then even within industries so if we pull up the next chart we have the industry to the breakdown and sort of the responses by the industries v-shape you shape or shape I had a conversation with a CIO of a major resort just the other day and even he was saying what was actually I'll tell you it was Windham Resorts public company I mean and obviously that business got a good crush they had their earnings call the other day they talked about how they cut their capex in half but the stock sagar since the March lows is more than doubled yeah and you know that's amazing and now but even there within that sector they're peeling that on you're saying well certain parts are going to come back sooner or certain parts are going to longer depending on you know what type of resort what type of hotel so it really is a complicated situation so take us through what you're seeing by industry sure so let's start with kind of the IT telco retail consumer space Dave to your point there's gonna be a tremendous amount of bifurcation within both of those verticals look if we start on the IT telco side you know you're seeing a very large bucket of individuals right over twenty percent that indicated they're seeing a tail with our additional revenue because of covin 19 and you know Dave we spoke about this all the way back in March right all these work from home vendors you know CIOs were doubling down on cloud and SAS and we've seen how some of these events have reported in April you know with this very good reports all the major cloud vendors right select security vendors and so that's why you're seeing on the kind of telco side definitely more positivity right as it relates to recovery type right some of them are not even going through recovery they're they're seeing an acceleration same thing on the retail consumer side you're seeing another large bucket of people who are indicating what we've benefited and again there's going to be a lot of bifurcation here there's been a lot of retail consumers you just mentioned with the hotel lines that are definitely hurting but you know if you have a good online presence as a retailer and you know you had essential goods or groceries you benefited and and those are the organizations that we're seeing you know really indicate that they saw an acceleration due to Koga 19 so I thought those two those two verticals between kind of the IT and retail side there was a big bucket or you know of people who indicated positivity so I thought that was kind of the first kind of you know I was talking about kind of peeling this onion back you know that was really interesting you know tech continues to power on and I think you know a lot of people try I think that somebody was saying that the record of the time in which we've developed a fit of vaccine previously was like mumps or something and it was I mean it was just like years but now today 2020 we've got a I we've got all this data you've got these great companies all working on this and so you know wow if we can compress that that's going to change the equation a couple other things sagar that jump out at me here in this chart I want to ask you about I mean the education you know colleges are really you know kind of freaking out right now some are coming back I know like for instance my daughter University Arizona they're coming back in the fall evidently others are saying and no you can clearly see the airlines and transportation as the biggest sort of l-shape which is the most negative I'm sure restaurants and hospitality are kind of similar and then you see energy you know which got crushed we had you know oil you know negative people paying it big barrels of oil but now look at that you know expectation of a pretty strong you know you shape recovery as people start driving again and the economy picks up so maybe you could give us some thoughts on on some of those sort of outliers yeah so I kind of bucket you know the the next two outliers as from an l-shaped in a u-shaped so on the l-shaped side like like you said education airlines transportation and probably to a little bit lesser extent industrials materials manufacturing services consulting these verticals are indicating the highest percentages from an l-shaped recovery right so three plus orders of revenue declines and deceleration followed by kind of you know minimal to moderate growth and look there's no surprise here those are the verticals that have been impacted the most by less demand from consumers and and businesses and then as you mentioned on the energy utility side and then I would probably bucket maybe healthcare Pharma those have some of the largest percentages of u-shaped recovery and it's funny like I read a lot of commentary from some of the energy in the healthcare CIOs and they were said they were very optimistic about a u-shaped type of recovery and so it kind of you know maybe with those two issues then you could even kind of lump them into you know probably to a lesser extent but you could probably open into the prior one with the airlines and the education and services consulting and IMM where you know these are definitely the verticals that are going to see the longest longest recoveries it's probably a little bit more uniform versus what we've kind of talked about a few minutes ago with you know IT and and retail consumer where it's definitely very bifurcated you know there's definitely winners and losers there yeah and again it's a very complicated situation a lot of people that I've talked to are saying look you know we really don't have a clear picture that's why all these companies have are not giving guidance many people however are optimistic not only for a vet a vaccine but but but also they're thinking as young people with disposable income they're gonna kind of say dorm damn the torpedoes I'm not really going to be exposed and you know they can come back much stronger you know there seems to be pent up demand for some of the things like elective surgery or even the weather is sort of more important health care needs so that obviously could be a snap back so you know obviously we're really closely looking at this one thing though is is certain is that people are expecting a permanent change and you've got data that really shows that on the on the next chart that's right so one of the one of the last questions that we asked on this you know quick coded flash poll was do you anticipate permanent changes to your kind of IT stack IT spend based on the last few months you know as everyone has been working remotely and you know rarely do you see results point this much in one direction but 92% of CIOs and and kind of IT you know high level ITN users indicated yes there are going to be permanent changes and you know one of the things we talked about in March and look we were really the first ones you know you know in our discussion where we were talking about work from home spend kind of negating or balancing out all these declines right we were saying look yes we are seeing a lot of budgets come down but surprisingly we're seeing 2030 percent of organizations accelerate spent and even the ones that are spending less they even then you know some of their some of their budgets are kind of being negated by this work from home spend right when you think about collaboration tool is an additional VPN and networking bandwidth in laptops and then security all that stuff CIOs now continue to spend on because what what CIO is now understand as productivity has remained at very high levels right in March CIOs were very with the catastrophe and productivity that has not come true so on the margin CIOs and organizations are probably much more positive on that front and so now because there is no vaccine where you know CIOs and just in general the population we don't know when one is coming and so remote work seems to be the new norm moving forward especially that productivity you know levels are are pretty good with people working from home so from that perspective everything that looked like it was maybe going to be temporary just for the next few months as people work from home that's how organizations are now moving forward well and we saw Twitter basically said we're gonna make work from home permanent that's probably cuz their CEO wants to you know live in Africa Google I think is going to the end of the year I think many companies are going to look at a hybrid and give employees a choice say look if you want to work from home and you can be productive you get your stuff done you know we're cool with that I think the other point is you know everybody talks about these digital transformations you know leading into Kovan and I got to tell you I think a lot of companies were sort of complacent they talked the talk but they weren't walking the walk meaning they really weren't becoming digital businesses they really weren't putting data at the core and I think now it's really becoming an imperative there's no question that that what we've been talking about and forecasting has been pulled forward and you you're either going to have to step up your digital game or you're going to be in big trouble and the other thing that's I'm really interested in is will companies sub optimize profitability in the near term in order to put better business resiliency in place and better flexibility will they make those investments and I think if they do you know longer term they're going to be in better shape you know if they don't they could maybe be okay in the near term but I'm gonna put a caution sign a little longer term no look I think everything that's been done in the last few months you know in terms of having those continuation plans because you know do two pandemics all that stuff that is now it look you got to have that in your playbook right and so to your point you know this is where CIOs are going and if you're not transforming yourself or you didn't or you know lesson learned because now you're probably having to move twice as fast to support all your employees so I think you know this pandemic really kind of sped up you know digital transformation initiatives which is why you know you're seeing some companies desks and cloud related companies with very good earnings reports that are guiding well and then you're seeing other companies that are pulling their guidance because of uncertainty but it's it's likely more on the side of they're just not seeing the same levels of spend because if they haven't oriented themselves on that digital transformation side so I think you know events like this they typically you know Showcase winners and losers then you know when when things are going well and you know everything is kind of going up well I think that - there's a big you know discussion around is the ESPY overvalued right now I won't make that call but I will say this then there's a lot of data out there there's data and earnings reports there's data about this pandemic which change continues to change maybe not so much daily but you're getting new information multiple times a week so you got to look to that data you got to make your call pick your spot so you talk about a stock pickers market I think it's very much true here there are some some gonna be really strong companies emerging out of this you know don't gamble but do your research and I think you'll you'll find some you know some Dems out there you know maybe Warren Buffett can't find them okay but the guys at Main Street I think you know the I am I'm optimistic I wonder how you feel about about the recovery I I think we may be tainted by tech you know I'm very much concerned about certain industries but I think the tech industry which is our business is gonna come out of this pretty strong yeah we look at the one thing we we should we should have stated this earlier the majority of organizations are not expecting a v-shaped recovery and yet I still think there's part of the consensus is expecting a v-shaped recovery you can see as we demonstrate in some of the earlier charts the you know almost the majority of organizations are expecting a u-shaped recovery and even then as we mentioned right that you shape there is some cautious up around there and I have it you probably have it where yes if everything goes well it looks like 2021 we can really get back on track but there's so much unknown and so yes that does give I think everyone pause when it comes from an investment perspective and even just bringing on technologies and into your organization right which ones are gonna work which ones are it so I'm definitely on the boat of this is a more u-shaped in a v-shaped recovery I think the data backs that up I think you know when it comes to cloud and SAS players those areas and I think you've seen this on the investment side a lot of money has come out of all these other sectors that we mentioned that are having these l-shaped recoveries a lot of it has gone into the tech space I imagine that will continue and so that might be kind of you know it's tough to sometimes balance what's going on on the investor in the stock market side with you know how organizations are recovering I think people are really looking out in two to three quarters and saying look you know to your point where you set up earlier is there a lot of that pent up demand are things gonna get right back to normal because I think you know a lot of people are anticipating that and if we don't see that I think you know the next time we do some of these kind of coded flash bolts you know I'm interested to see whether or not you know maybe towards the end of the summer these recovery cycles are actually longer because maybe we didn't see some of that stuff so there's still a lot of unknowns but what we do know right now is it's not a v-shaped recovery agree especially on the unknowns there's monetary policy there's fiscal policy there's an election coming up there's a third there's escalating tensions with China there's your thoughts on the efficacy of the vaccine what about therapeutics you know do people who have this yet immunity how many people actually have it what about testing so the point I'm making here is it's very very important that you update your forecast regularly that's why it's so great that I have this partnership with you guys because we you know you're constantly updating the numbers it's not just a one-shot deal so suck it you know thanks so much for coming on looking forward to having you on in in the coming weeks really appreciate it absolutely yeah well I will really start kind of digging into how a lot of these emerging technologies are faring because of kovat 19 so that's I'm actually interested to start thinking through the data myself so yeah well we'll do some reporting in the coming weeks about that as well well thanks everybody for watching this episode of the cube insights powered by ETR I'm Dave Volante for sauger kuraki check out ETR dot plus that's where all the ETR data lives i published weekly on wiki bon calm and silicon angle calm and reach me at evil on Tay we'll see you next time [Music]

(upbeat music) >> From theCUBE Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a Cube Conversation. >> As we've been reporting, the COVID-19 pandemic has created a bifurcated IT spending picture. And over the last several weeks, we've reported both in the macro and even some come at it from a vendor and a sector view. I mean, for example, we've reported on some of the companies that have really continued to thrive, we look at the NASDAQ and its near a toll-time hard. Companies like Okta and CrowdStrike, we've reported on Snowflake, UiPath. The sectors, RPA, some of the analytic databases around AI, maybe even to a lesser extent Cloud but still has a lot tailwinds relative to some of those on-prem infrastructure plays. Even companies like Cisco, bifurcated in and of themselves, where you see this more rocky side of the house doing quite well. The work-from-home stuff but maybe some of the traditional networking not as much. Well, now what if you flip that to really try to understand what's going on with the shape of the recovery which is the main narrative right now. Is it a V shape? Is it a U shape? What do people expect? And now to understand that, you really have to look at different industries because different industries are going to come back at a different pace. With me again is Sagar Kadakia, who's the Director of Research at ETR. Sagar, you guys are all over this, as usual timely information, it's great to see you again. Hope all is well in New York City. >> Thanks so much David, it's a pleasure to be back on again. >> Yeah, so where are we in the cycle? You've done a great job and very timely, ETR was the first to really put out data on the Covid impact with the server that ran from mid March to mid April. And now everybody's attention Sagar, is focused on, okay, we've started to come back, stores are starting to open, people are beginning to go out again and everybody wants to know what the shape of the recovery looks like. So, where are we actually in that research cycle for you guys? >> Yeah, no problem. So, like you said, in that kind of March, April timeframe, we really want to go out there and get an idea of what are going to be the budget impacts as it relates to IT because of COVID-19, right? So, we kind of ended off there around a decline of 5%. And coming into the year, the consensus was a growth of 4% or 5%, right? So, we saw about a 900 or 1000 base point swing, to the negative side. And then (murmurs) topic we covered in March and April were which sectors of vendors were going to benefit as a result of work-from-home. And so, now as we kind of fast forward to the research cycle as we kind of go more into May and into the summer, rather than asking those exact same question again, because it's just been maybe 40 or 50 days. We really want to (murmurs) on the recovery type as well as well as kind of more emerging private vendors, right? We want it to understand what's going to be the impact on these vendors that typically rely on larger conferences, more in person meetings, because these are younger technologies. There's not a lot of information about them. And so, last Thursday we launched our biannual emerging technology study. It covers roughly 300 private emerging technologies across maybe 60 sectors of technology. And in tandem, we've launched a COVID Flash Poll, right? What we want to do was kind of twofold. One really understand from CIOs the recovery type they had in mind, as well as if they were seeing any kind of permanent changes in their IT, stacks IT spend because of COVID-19. And so, if we kind of look at the first chart here, and kind of get more into that first question around recovery type, what we asked CIOs in this kind of COVID Flash Poll, again, we did it last Thursday was, what type of recovery are you expecting? Is it V-shaped so kind of of a brief decline, maybe 1/4, and then you're going to start seeing growth into 2 each 20. Is it U-shaped? So two to 3/4 of a decline or deceleration revenue, and you're kind of forecasting that growth in revenue as an organization to come back in 2021. Is it L-shaped, right? So, maybe three, four or 5/4 of a decline or deceleration. And very minimal to moderate growth or none of the above, your organization is actually benefiting from COVID-19, as we've seen some many reports. So, those are kind of the options that we gave CIOs and you kind of see them at first chart here. >> Well, interesting. And this is a survey, a flash of survey, 700 CIOs or approximately. And the interesting thing I really want to point out here is, the COVID pandemic, it didn't suppress all companies, and the return is it's not going to be a rising tide that lifts all ships. You really got to do your research. You have to understand the different sectors, really try to peel back the onion skin and understand why there are certain momentum, how certain organizations are accommodating the work from home. We heard several weeks ago, how there's a major change in networking mindsets we're talking about how security is changing. We're going to talk about some of the permanents, but it's really, really important to try to understand these different trends by different industries, which we're going to talk about in a minute. But if you take a look at this slide, I mean, obviously most people expect this U-shape decline. I mean, U-shape recovery rather. So it's two or 3/4 followed by some growth next year. But as we'll see, some of these industries are going to really go deeper with an L-shape recovery. And then it's really interesting that a pretty large and substantial portion see this as a tailwind, presumably those with strong SAS models, annual recurring revenue models, your thoughts? >> If we kind of start on this kind of aggregate chart, you're looking at about 44% of CEO's anticipate a U-shaped recovery, right? That's the largest bucket. Then you can see another 15% anticipate an L-shape recovery 14 on the V-shaped, and then 16% to your point that are kind of seeing this tailwind. But if we kind of focus on that largest bucket that U-shaped, one of the things to remember and again, when we asked this to CIOs within this kind of COVID Flash Poll, we also asked, can you give us some commentary? And so, one of the things that, or one of the themes that are kind of coming along with this U-shape recovery is CIOs are cautiously optimistic about this U-shape recovery. They believe that they can get back onto a growth cycle, into 2021, as long as there's a vaccine available. We don't go into a second wave of lockdowns. Economic activity picks up, a lot of the government actions become effective. So there are some kind of let's call it qualifiers, with this bucket of CIOs that are anticipating a U-shape recovery. What they're saying is that, "look, we are expecting these things to happen, "we're not expecting a lockdown, "we are expecting a vaccine. "And if that takes place, "then we do expect an uptake in growth, "or going back to kind of pre COVID levels in 2021." But I think it's fair to assume that if one or more of these are ups and things do get worse as all these States are opening up, maybe the recovery cycle gets pushed along. So kind of at the aggregate, this is where we are right now. >> Yeah. So as I was saying, you really have to understand the different, not only different sectors not only the different vendors, but you can really get to look into the industries, and then even within industries. So if we pull up the next chart, we have the industry sort of break down, and sort of the responses by the industry's V-shape, U-shape or L-shape. I had a conversation with a CIO of a major resort, just the other day. And even he was saying, well, it was actually, I'll tell you it was Wyndham Resorts, public company. I mean, and obviously that business got crushed. They had their earnings call the other day. They talked about how they cut their capex in half. But the stock, Sagar, since the March loss is more than doubled. >> Yeah. >> It was just amazing. And now, but even there, within that sector, they're appealing that on you are doing well, certain parts are going to come back sooner, certain parts are going to take longer, depending on, what type of resort, what type of hotel. So, it really is a complicated situation. So, take us through what you're seeing by industry. >> Yeah, sure. So let's start with kind of the IT-Telco, retail, consumer space. Dave to your point, there's going to be a tremendous amount of bifurcation within both of those verticals. Look, if we start on the IT-Telco side, you're seeing a very large bucket of individuals, right over 20%? That indicated they're seeing a tailwind or additional revenue because of COVID-19 and Dave, we spoke about this all the way back in March, right? All these work from home vendors. CIOs were doubling down on Cloud and SAS and we've seen how some of these vendors have reported in April, with very good reports, all the major Cloud vendors, right? Like Select Security vendors. And so, that's why you're seeing on the kind of Telco side, definitely more positivity, right? As you relates to recovery type, right? Some of them are not even going through recovery. They're seeing an acceleration, same thing on the retail consumer side. You're seeing another large bucket of people who are indicating, "look, we've benefited." And again, there's going to be a lot of bifurcation, there's been a lot of retail consumers. You just mentioned with the hotel lines, that are definitely hurting. But if you have a good online presence as a retailer, and you had essential goods or groceries, you benefited. And those are the organizations that we're seeing really indicate that they saw an acceleration due to COVID-19. So, I thought those two verticals between kind of the IT and retail side, there was a big bucket of people who indicated positivity. So I thought that was kind of the first kind of as we talked about kind of feeling this onion back. That was really interesting. >> Tech continues to power on, and I think a lot of people try, I think somebody was saying that the record time in which we've developed a vaccine previously was like mumps or something. I mean, it was just like years. But now today, 2020, we've got AI, we've got all this data, you've got these great companies all working on this. And so, wow, if we can compress that, that's going to change the equation. A couple of other things Sagar that jump out at me here in this chart that I want to ask you about. I mean, the education, the colleges, are really kind of freaking out right now, some are coming back. I know, like for instance, my daughter at University of Arizona, they're coming back in the fall indefinitely, others are saying, no. You can clearly see the airlines and transportation, has the biggest sort of L-shape, which is the most negative. I'm sure restaurants and hospitality are kind of similar. And then you see energy which got crushed. We had oil (laughs) negative people paying it, big barrels of oil. But now look at that, expectation of a pretty strong, U-shape recovery as people start driving again, and the economy picks up. So, maybe you could give us some thoughts on some of those sort of outliers. >> Yeah. So I kind of bucket the next two outliers as from an L-shaped and a U-shaped. So on the L-shaped side, like you said, education airlines, transportation, and probably to a little bit lesser extent, industrials materials, manufacturing services consulting. These verticals are indicating the highest percentages from an L-shaped recovery, right? So, three plus 1/4 of revenue declines in deceleration, followed by kind of minimal to moderate growth. And look, there's no surprise here. Those are the verticals that have been impacted the most, by less demand from consumers and businesses. And then as you mentioned on the energy utility side, and then I would probably bucket maybe healthcare, pharma, those have some of the largest, percentages of U-shaped recovery. And it's funny, like I read a lot of commentary from some of the energy and the healthcare CIOs, and they were saying they were very optimistic (laughs) about a U-shaped type of recovery. And so it kind of, maybe with those two issues that we could even kind of lump them into, probably to a lesser extent, but you could probably lump it into the prior one with the airlines and the education and services consulting, and IMM, where these are definitely the verticals that are going to see the longest, longest recoveries. And it's probably a little bit more uniform, versus what we've kind of talked about a few minutes ago with IT and retail consumer where it's definitely very bifurcated. There's definitely winners and losers there. >> Yeah. And again, it's a very complicated situation. A lot of people that I've talked to are saying, "look, we really don't have a clear picture, "that's why all these companies are not giving guidance." Many people, however, are optimistic only for a vaccine, but also their thinking is young people with disposable income, they're going to kind of say,"Damn the torpedoes, "I'm not really going to be exposed." >> And they could come back much stronger, there seems to be pent up demand for some of the things like elective surgery, or even some other sort of more important, healthcare needs. So, that obviously could be a snapback. So, obviously we're really closely looking at this, one thing though is certain, is that people are expecting a permanent change, and you've got data that really shows that on the next chart. >> That's right. So, one of the last questions that we ask kind of this quick COVID Flash Poll was, do you anticipate permanent changes to your kind of IT stack, IT spend, based on the last few months? As everyone has been working remotely, and rarely do you see results point this much in one direction, but 92% of CIOs and kind of high level IT end users indicated yes, there are all going to be permanent changes. And one of the things we talked about in March, and look, we were really the first ones, in our discussion, where we were talking about work from home spend, kind of negating or bouncing out all these declines, right? We were saying, look, yes, we are seeing a lot of budgets come down, but surprisingly, we're seeing 20,30% of organizations accelerate spend. And even the ones that are spending less, even them, some of their budgets are kind of being negated by this work from home spend, right? When you think about collaboration tools and additional VPN and networking bandwidth, and laptops and then security, all that stuff. CIOs now continue to spend on, because what CIOs now understand is productivity has remained at very high levels, right? In March CIOs were very concerned with the catastrophe and productivity that has not come true. So on the margin CIOs and organizations are probably much more positive on that front. And so now, because there is no vaccine, where we know CIOs and just in general, the population, we don't know when one is coming. And so remote work seems to be the new norm moving forward, especially that productivity levels are pretty good with people working from home. So, from that perspective, everything that looked like it was maybe going to be temporary, just for the next few months, as people work from home, that's how organizations are now moving forward. >> Well, and we saw Twitter, basically said, "we're going to make work from home permanent." That's probably because their CEO wants to live in Africa. Google, I think, is going to the end of the year. >> I think many companies are going to look at a hybrid, and give employees a choice, say, "look, if you want to work from home "and you can be productive, you get your stuff done, we're cool with that." I think the other point is, everybody talks about these digital transformations leading into COVID. I got to tell you, I think a lot of companies were sort of complacent. They talk the talk, but they weren't walking the walk, meaning they really weren't becoming digital businesses. They really weren't putting data at the core. And I think now it's really becoming an imperative. And there's no question that what we've been talking about and forecasting has been pulled forward, and you're either going to have to step up your digital game or you're going to be in big trouble. And the other thing I'm really interested in is will companies sub-optimize profitability in the near term, in order to put better business resiliency in place, and better flexibility, will they make those investments? And I think if they do, longer term, they're going to be in better shape. If they don't, they could maybe be okay in the near term, but I'm going to put up a caution sign, although the longer term. >> Now look, I think everything that's been done in the last few months, in terms of having those continuation plans, due to pandemics and all that stuff, look, you got to have that in your playbook, right? And so to your point, this is where CIOs are going and if you're not transforming yourself or you didn't before, lesson learned, because now you're probably having to move twice as fast to support all your employees. So I think this pandemic really kind of sped up digital transformation initiatives, which is why, you're seeing some companies, SAS and Cloud related companies, with very good earnings reports that are guiding well. And then you're seeing other companies that are pulling their guidance because of uncertainty, but it's likely more on the side if they're just not seeing the same levels of spend, because if they haven't oriented themselves, on that digital transformation side. So I think events like this, they typically showcase winners and losers than when things are going well. and everything's kind of going up. >> Well, I think that too, there's a big discussion around is the S&P over valued right now. I won't make that call, but I will say this, that there's a lot of data out there. There's data in earnings reports, there's data about this pandemic, which it continues to change. Maybe not so much daily, but we're getting new information, multiple times a week. So you got to look to that data. You got to make your call, pick your spots, earlier you talk about a stock pickers market. I think it's very much true here. There are some going to be really strong companies. emerging out of this, don't gamble but do your research. And I think you'll find some gems out there, maybe Warren buffet can't find them okay. (laughs) But the guys at main street. I'm optimistic, I wonder how you feel about the recovery. I think I maybe tainted by tech. (laughs). I'm very much concerned about certain industries, but I think the tech industry, which is our business's, going to come out of this pretty strong? >> Yeah. Look, the one thing we should have stated this earlier, the majority of organizations are not expecting a V-shaped recovery. And yet I still think there's part of the consensus is expecting a V-shaped recovery. You can see as we demonstrate in some of the earlier charts, That U-shaped, there is some cautious optimism around there, almost the majority of organizations are expecting a U-shape recovery. And even then, as we mentioned, right? That U-shape, there is some cautious optimism around there, and I have it, you probably have it where. Yes, if everything goes well, it looks like 2021 we can really get back on track. But there's so much unknown. And so yes, that does give I think everyone pause when it comes from an investment perspective, and even just bringing on technologies. into your organization, right? Which ones are going to work, which ones aren't? So, I'm definitely on the boat of, this is a more U-shaped in a V-shape recovery. I think the data backs that up. I think when it comes to Cloud and SAS players, those areas, and I think you've seen this on the investment side, a lot of money has come out of all these other sectors that we mentioned that are having these L-shaped recoveries. A lot of it has gone into the text-based. I imagine that will continue. And so that might be kind of, it's tough to sometimes balance what's going on, on the investment that stock market side, with how organizations are recovering. I think people are really looking out into two, 3/4 and saying, look to your point where you said that earlier, is there a lot of that pent up demand, are things going to get right back to normal? Because I think a lot of people are anticipating that. And if we don't see that, I think the next time we do some of these kind of COVID Flash Polls I'm interested to see whether or not, maybe towards the end of the summer, these recovery cycles are actually longer because maybe we didn't see some of that stuff. So there's still a lot of unknowns. But what we do know right now is it's not a V-shaped recovery. >> I agree, especially on the unknowns, there's monetary policy, there's fiscal policy, there's an election coming up. >> That's fine. >> There's escalating tensions with China. There's your thoughts on the efficacy of the vaccine? what about therapeutics? Do people who've had this get immunity? How many people actually have it? What about testing? So the point I'm making here is it's very, very important that you update your forecast regularly That's why it's so great to have this partnership with you guys, because you're constantly updating the numbers. It's not just a one shot deal. So Sagar, thanks so much for coming on. I'm looking forward to having you on in the coming weeks. Really appreciate it. >> Absolutely. Yeah, we'll really start kind of digging into how a lot of these emerging technologies are fairing because of COVID-19. So, I'm actually interested to start digging through the data myself. So yeah, we'll do some reporting in the coming weeks about that as well. >> Well, thanks everybody for watching this episode of theCUBE Insights powered by ETR. I'm Dave Vellante for Sagar Kadakia, check out etr.plus, that's where all the ETR data lives, I publish weekly on wikibond.com and siliconangle.com. And you can reach me @dvellante. We'll see you next time. (gentle music).

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation CIOs and CISOs of industries that have been hard hit see significant near term and many permanent shifts to their IT and security strategies this was the consensus of four technology executives at leading companies that are feeling the brunt of the corona virus pandemic welcome to this week's cube insights powered by ETR my name is Dave Volante and in this breaking analysis we want to accomplish three things first we want to tap into a new piece of research from ETR it involves an intimate focus group like set up via an open discussion with leading technology executives we interviewed Eric Bradley the managing director of et ours then program and we'll bring him into this discussion the next thing we want to do is we want to drill in to the various sector commentaries from the four leaders third we're gonna comment an hour take try to add some color and then share with you some of the specific vendor commentary that was called out by the executives let's start by looking at what et our event is et our van is a roundtable discussion it applies a tried-and-true methodology similar to a focus group or in-depth interviews what we sometimes in the research business call ID is ETR invites execs in from its community to participate in a private but open conversation et our clients get to listen in the names of the execs and their companies are transparent but the cube is only allowed to refer to them generically as shown on this slide now we can validate these participants they are legit CIOs and CISOs some and very well-known firms now what I want to do is summarize the CIO and seaso sentiment from this then discussion the overall budget impact for these four organizations is very very severe essentially large project projects are being put on hold although digital transformation initiatives remain a priority there were really four significant areas of emphasis that were cited by these execs cloud-first on-prem is losing out to cloud SAS and of course remote access solutions in fact the best comment on the panel was as a service is saving our SAS traditional networking is shifting to SD win especially rigid MPLS networks securing endpoints and zero trust solutions are the winners and there are a number of vendors rising to the occasion that will talk about it let's see how Eric Bradley of ETR summarizes the venn to summarize what we're seeing here was the real winners and losers are clear not everyone was prepared to have it work from home strategy not everyone was prepared to send their workers out there VPN wasn't didn't have enough bandwidth so there was a real quick uptick in spending but longer-term we're starting to see that these changes will be become more permanent so the real winners and losers right now we're going to see on the losers side traditional networking the MPLS networking isn't a lot of trouble according to all the data and the commentary that we see it's expensive it's difficult to ramp up bandwidth as quickly as you need and it doesn't support remote ok what I want to do now is I want to take a look at some of the verbatim comments and I'll just I'll read them from this slide all spending is shut down 70% of big projects are cut all next-gen projects have been shelled the relationship with our SAS vendor has been a miracle we're accelerating from MPLS to sd when on top of secure gateway technologies these will win this was interesting our business continuity plans were way too DR focused essentially we weren't prepared now let's unpack the cloud first commentary and give you some additional color I feel like all we do around here sometimes is talk about the cloud but it's clear from the data in the ETR data set surveys and the venn that in other data from the cube that that the cloud is only going to be accelerated we said this in 2008 in the 2009 downturns have been good to cloud one of the execs literally said I would like to see my data centers completely deleted Wow let's listen to Erik Bradley's take on this comment I was also shocked about that comment that gentleman also stated that his executives outside of the eyeteeth area the CEO the CFO had never ever ever wanted to discuss cloud they did not want to discuss work from home they did not want to discuss remote access he said that conversation has changed immediately so we've been talking a lot about those aspects of people and process and technology that might be permanent post kovat and clearly you see c-level execs as having a bit of an awakening for things like cloud and work from home not that they didn't see them before but these things are gonna accelerate in our view I want to spend a minute talking about networks SAS and bring cloud again into the discussion I gotta say the panel members really trashed MPLS networks in a big way let me explain MPLS stands for multi-protocol label switching you find this type of infrastructure in big telecom networks and it's there to route traffic and pls is used to create dedicated and and essentially reliable connections it enables things like VPNs quality a service management traffic engineering or shaping but well MPLS is definitely cheaper than t1 it's more expensive than Ethernet now I came into prominence well before the cloud and these execs see it is as outdated and inflexible and this is where SD wind comes into play software-defined wide area networks they're gaining popularity especially with the Sassa fication of applications and of course the general trend toward cloud here's Eric Bradley again explaining what the panel members said from his perspectives winners there or in the SD web space it's gonna be impossible to ignore that going forward and some of our CIO and even CISO panelists said that change will be also we're seeing at the same time what they were calling a on on SAS and cloud now we know these trends obviously were already happening but there be they're being exacerbated they're happening even more quickly and more strong and I don't see that changing anytime soon that of course is at the expense of network sorry data centers whether it be your own or hosted which has huge ramifications on from on from Hardware even the firewall providers so and it really seems as if as networking refresh starts to come up and it's coming up with a lot of large in writes when your network refresh comes up people are going to do an RFP for SD web they are sick and tired of paying MPLS network vendors and they really want to look at something else that was even prior to this situation now what we're hearing is this is a permanent change I particularly had one person say I wanted to find this quote real quickly by then but basically they were basically saying that from a permanency perspective the freedom from MPLS will reduce our network spend by over half while more than doubling or tripling or bandwidth now the challenge of course is customers have multiple MPLS contracts with several different vendors and often they just rubber-stamp the renewal but what customers are gonna start doing is layering in SD win and letting those agreements expire ok I want to talk about secure endpoints in this notion of zero trust solutions as I've said in the cube many many times the idea of digging a moat around the castle doesn't protect your queen anymore because the Queen ie the data has left the castle so companies that can secure gateways and secure endpoints they are going to have more momentum during and post kovat now in the panel Z scalar came up a lot in this context as well as fortunate who as I've reported has done a good job in getting its cloud products to market and of course the et our data shows that fortunate and Z scalar both have strong net scores or spending momentum and fort net especially has really strong pervasiveness in the et our dataset as I've reported previously I've also analyzed that there's been evaluation divergence between Palo Alto Networks and fortunate and house II scalar as well is a disruptor in this space I want you to listen to what Eric Bradley said specifically about Z scalar in Palo Alto Networks roll the clip yes it is and I'm glad you brought up Z scalar to very recently by client request we did a very in-depth research on Z scale and versus Palo Alto charisma access and they were very interested this is before all this happened you know does Palo Alto have a chance of catching up taking share from Z scalar and I've had the pleasure myself personally hosting J the CEO of Z scalar at an event here at City and I have nothing but incredible respect for the company but what we found out through this research is Z scalar at the moment their technology is still ahead according to their and there is no doubt however there doesn't seem to be any real secret sauce that will stop palo alto from inching up so if I had to choose that in a year from now Palo Alto might have had a better chance so in this panel as you brought up Z scalar was mentioned numerous times as just the wave of the future along with Cosby brokers right whether you're talking about a net scope or a force point they're all those people that also play in The Cosby space to secure your access zero Trust is no longer a marketing hype term it is real and it is becoming more real by the week now I personally agree with Eric that palo alto is is definitely going to be in the mix customers that we've talked to they want to work with palo alto networks but there's a sea change going on and it's being driven by sass and cloud and now accelerating because a co vid of course that the trend of remote workers is we think here to stay now i want to end by talking about some specific vendor mentions in addition to the ones we've talked about already and this chart shows some of the vendors and their logos that were called out as either being really really helpful during the this pandemic or super important to the CIOs and CISOs these executives really stressed how thankful they are to these companies and that the fact that these companies have worked very closely with them they've been flexible on pricing and payments and they also specifically mentioned how off-put they were by you know this notion of ambulance-chasing for example trials that required them to make some kind of commitment or swipe a credit card they just don't have time for that right now and then of the patience for it now let me call out a few of the companies that were cited in a positive light look at microsoft is all for the ETR data set in so many sectors Microsoft teams security solutions cloud really came up a lot on on this ven IBM was mentioned as being a great partner as what's oracle many many times we talked about fortunate and Z scalar already Cisco was called out as a strategic vendor was very helpful both the networking and with Cisco teams for collaboration CrowdStrike came up a number of times from CISOs as did Trend Micro and carbon black got a mention that's the VMware acquisition insecurity of course MobileIron that makes sense as well because they're securing and managing remote worker devices now finally interesting Lee Salesforce was brought up many times as a critical vendor one exec said that before coronavirus multiple workers could share a Salesforce license by you know sharing passwords but with the spike and work from home they had to purchase more licenses now one last thing that I want to bring up is start ups I got this question the other day from a client who said how a start-ups fair you might think that in this climate especially among for hard-hit customers that there might be risk-averse as it pertains to using startups once cio however said the following paraphrasing you always hear about the guy that says we'll pick three companies in the upper right hand corner the Gartner Magic Quadrant will test them out and this C so said that one of the things that he's always done is picked two from the upper right and one from the lower left one of the emerging techs and he gives them a shot let's listen to how Eric Bradley describes this dynamic roll the clip it's a great comment and honestly if you're in charge of procurement you'd be stupid not to do that not only just to see what the technology is but now I can play you off the big guys because I have negotiating leverage and I could say oh well I could always just take their contract so it's silly not to do it from a business perspective so it's really interesting and somewhat non-intuitive these comments on startups which of course means despite all the consolidation and acquisitions that you see in the industry you know there's still gonna be a lot of fragmentations a fragmentation especially as I've said many many times in the security space people still want best to breed and innovation and if it can drive business value they're gonna they're gonna go for it ok so look I realize that these are narrow comments from for CIOs and CISOs but they give us some added texture and flavor and color to the core ETR data set and we're going to continue to report on these trends and share more details as they become available both from the ETR data set and from other vents and remember we're gonna be digging into the latest ETR survey over the over the coming weeks as ETR exits its self-imposed quiet period so you can always check out ETR dot plus I publish weekly on wiki bang calm and on Silicon angle calm and of course our YouTube library has all these videos that's youtube.com slash silicon angle by the way these segments are also available as podcasts you can DM me or tweet me at devil ante and please by all means comment on my LinkedIn posts or email me at David Galante at Silicon angle com always appreciate the feedback thanks for watching everybody this is breaking analysis brought to you by the cube powered by ETR this is Dave Volante and we'll see you next time thanks for watching [Music]

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation [Music] hello everybody and welcome to this week wiki bond cube insights powered by ETR in this breaking analysis we want to update you on the latest spending data from EGR as you know we've been tracking this weekly saga kodachi is here he's the director of research at ET our saga thanks for coming on thanks for having me again Dave really appreciate it yes so so let me remind everybody so we entered the Year this year 2020 with a consensus IT spend for cast of plus 4% once coronavirus hit ET are launched its latest survey in March and we saw those numbers you'll come down last week we reported well the first report we made was it looked like it was flat last week we reported a slight negative and today we want to update you guys on those numbers so saga before we get into the data just give us the high level on where you guys are at in terms of your survey yeah no problem so currently we are forecasting a decline in global IT budgets about negative 4% I think what's happened you know over the last you know 10 or 15 days is you've just seen more and more information released that's given organizations more of an understanding of just how severe this you know epidemic is and so what we've been able to do on our end is kind of do an event study analysis or simulation analysis kind of what you're seeing here a really pinpoint the time period where organizations understood the severity of the epidemic and then really trying to measure the declines in IT budgets from there great so guys bring that slide back up I want to share with our audience what's happening here so what ETR has done is an event-based analysis and what you can see is where the survey launched on 3/11 you could see how sentiment has declined literally daily as the data rolled in then you see the US declared a national emergency you saw that the federal plan leaked for that you know penned pandemic protect projection and obviously New York became a hot spot and then you can see this the stimulus package in it and sagger it looks like there's a slight uptick here but generally speaking it's down now it could be worse but you guys were the first to report the offset from work it worked from home infrastructure we'll talk about that a little bit talk about this event analysis and what you're seeing here and how you compressed the analysis hosting these events no problem so let's start with a blue line here and just so the audience knows the x-axis is going to be date and the y-axis is going to be annual growth or decline in nit budgets what you're seeing here and if we start with the blue line is we started pulling on 3/11 and on that date we started to ask you know fortune 100 is fortune 500 how their budget was going to change based on the impacts of coded nineteen versus their original expectations coming into coming into the year and again consensus estimates coming to the year were positive four percent so if you track that line all the way through you get to a decline of about one percent now what's the issue of starting polling on 3/11 or using that blue line well one of the big issues is a few days later the US declared a national emergency so more information was released right I think organizations that took the survey in the first two days didn't have a complete picture as to what's going on and then effectively a week later you saw federal documents get leaked stating how bad this epidemic was right in terms of the last 18 18 plus months and so what we did was we did it effectively an event based analysis or defuse different simulation where if you take a look at the yellow and red lines to start what we're doing is we're effectively saying okay let's ignore everyone that took the survey prior to that let's take their budgets in terms of how they indicated change versus their original expectations for 2020 and then let's go ahead and map that and if you look at the yellow line as an example that goes to a decline of 2% and then once I think you know the next shoe dropped in terms of organizations understanding this is not going to be a few weeks or this is not the common cold or flu once organizations knew this was going to be an 18 plus epidemic you can see if we started pulling respondents from there how much more negative it gets and of course once NYC became the epicenter you saw a little another shoe drop so now those those scenarios or simulations are taking us between a decline of three and four percent and then of course if we look at that last purple line there when the stimulus got announced what we are seeing is it looks like it may have bottomed down we have to continue tracking it because you know again it's just a few days since the stimulus is was passed and so let's see if the data starts improve a little bit or at least stabilize but I think from the last three events in terms of the the federal plan being leaked NYC becoming the epicenter and the stimulus it looks like the market now is fully aware of what's going on and now we're kind of seeing some stabilization in the data in terms of the declines for 2020 so between the feds action and the the fiscal stimulus we've we've seen some optimism although people are really cautious of course remember folks this would be worse were it not for the shift in spend to work from home infrastructure not just collaboration and visualization tools but other infrastructure around that network bandwidth security desktop virtualization etc so guys if you bring up the next chart I want to set this up we've been reporting this framework for a while now what this shows is what the sentiment is in terms of the budget change and you can see the gray bar now is 35% it started at 40% so that's dropped so the percentage of CIO saying no change the green is held pretty steady at around 20 to 22% that's it's roughly in there and the red you know has been has been shifting and you can see most of the green ie spending more in 2020 is focused on that you know one to two ten percent but but Sagar bring us up to date now we're going to settle in it right now about three and a half to four percent on the negative side give us some color on this chart please yeah no problem so the best way to connect this chart with what we saw earlier is this is a snapshot so this is a single day so this is the data that is feeding the time series chart kind of help the audience understand what's going on so if we were to look at this exact chart Oh since March 11 you would see that midpoint Average effectively coming down every day and that's effectively what's making up that time series in terms of this chart you know Dave you kind of hit it right on the nail you're kind of seeing the positivity remain or be stable and again that's that work from home infrastructure as you as you mentioned right the collaboration pools no the virtualization support services networking bandwidth all that stuff right being more and more security but on the negative side I think what you're seeing is that again as organizations now understand the severity of the epidemic I think as we understand further and we've talked about this you know a few weeks ago that organizations were anticipating less demand they were anticipating an uptick in broken supply chains now you're starting to see some of that play out and as a result you're seeing organizations get more and more negative and that's why that midpoint average it keeps declining that's why those red bars keep going up is the the impacts in you know based on the data are are now starting to be to be seen and so you know let's see if the stimulus stabilizes this data and we'll continue tracking that you know over the next few weeks the next few months okay so basically we're coming in - three and a half to four percent that's where we are today we're not going to get detailed into some of the vendors today we talked a little bit about that last week and go back to last week's breaking analysis you can see some of that vendor commentary I want to talk about what happens next ETR now we'll go into a two-week quite self-imposed quiet period and really start crunching the data at the end of that quiet period they will release to their private clients the their latest thinking in a webcast after that time we at the cube are allowed to share public information and we're gonna drill down into some of the segments that our community is most interested in but-but-but etrs going quiet now so saga maybe you can explain that sequence and fill in any holes that I missed there yeah no problem the next two weeks so we've we've collected a tremendous amount of data you know we're over you know we're at a hundred fortune 100 organizations you know almost three four hundred global two thousand organizations and so we're at a point now where it's time to start aggregating the data start really analyzing it going through this Koga drill down that we conducted but also we conducted a tremendous study on technology spending intentions of crossing over 350 vendors dozens of Technology sectors and so now it's really a time to kind of drill in and you know what what we're looking for or even some of the biggest takeaways from from this Cove it you know drill down is you know if if you started polling before 3:23 chances are your forecast is gonna come in light and I think that's one of the things that we've learned as we're kind of going into this to hear it is we really want to measure the impact starting right around that 3:23 timeframe it looks right around then based on that time series chart that we showed earlier that's when the market fully understood the impact of this epidemic and so as we start over the next two weeks even though we started pulling a little bit early we really want to focus on that second set a second half of responses because that's probably gonna be more indicative of what's going on I think the second thing is gonna be look if condition of conditions continue to deteriorate things can get worse and so we may come out of the next two weeks with this data that we collected and again have to continue indicating that you know the environment has continued coming down and you know maybe we may have to make adjustments as we see fit so I think that's kind of you know this whole situation is so dynamic still and so we're gonna do our best in the next week and a half to kind of get this data to market to at least give everyone an idea here's how everything stands right now and so that people have a good benchmark and then move forward yeah so this is as close to real time really as you can get in some of this IT spending world saga mentioned some of the numbers and in the global 2000 fortune fortune 100 1000 this this end now just the reminder is up over 1200 I believe right Sahra the total and that you've collected this this month that's correct exactly every time we've been doing one of these it's been going up another a couple hundred respondents so yeah we're at a very comfortable level now our sample right now represents five hundred and fifty five billion dollars in annual IP spend you know and global IT spend every year is a little over you know three trillion so this is a significant significant portion of a global IT spend and we feel comfortable at this point kind of going into that quiet period as you mentioned and really start to dig through the results that you know now that we've kind of you know covered the the 10,000 foot or the macro layer so to speak in terms of where budgets are going now it's really time to start drilling down and do the sectors and vendors because this is this is not going to be a every vendors going down or whatever maybe there's so many different dynamics here some vendors are going to do very well because the work for MoMA infrastructure and I think some vendors are gonna do very poorly because one they're not only on the legacy side but they're not really aligned from this whole work from home infrastructure movement so you're gonna see a lot of bifurcation you know as we get into 53 that's right and we're gonna dig into all those segments we're gonna look at the work from home we're gonna look at the traditional stuff we're gonna look at cloud we're gonna drill into specific segments that are that are of interest to our community it's a pleasure to really have you on here Sagar thank you for for sharing giving us access to this data and and stay safe and we will be watching go to ETR dot plus and you know check out what's happening there Silicon Engel Tom will obviously cover this and I published weekly on wiki bond comm again that saga thanks so much for coming on the cube yeah no problem thank you so much and looking forward to catching up in a few weeks all right then thank you for watching everybody this is Dave a latte for the cube or wiki bounce cube insights powered by ETR we'll see you next time [Music]

(soft electronic music) >> Okay, we're back with Tim Yocum who is the Director of Engineering at InfluxData. Tim, welcome, good to see you. >> Good to see you, thanks for having me. >> You're really welcome. Listen, we've been covering opensource software on theCUBE for more than a decade and we've kind of watched the innovation from the big data ecosystem, the cloud is being built out on opensource, mobile, social platforms, key databases, and of course, InfluxDB. And InfluxData has been a big consumer and crontributor of opensource software. So my question to you is where have you seen the biggest bang for the buck from opensource software? >> So yeah, you know, Influx really, we thrive at the intersection of commercial services and opensource software, so OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service from our core storage engine technologies to web services, templating engines. Our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants. And like you've mentioned, even better, we contribute a lot back to the projects that we use, as well as our own product InfluxDB. >> But I got to ask you, Tim, because one of the challenge that we've seen, in particular, you saw this in the heyday of Hadoop, the innovations come so fast and furious, and as a software company, you got to place bets, you got to commit people, and sometimes those bets can be risky and not pay off. So how have you managed this challenge? >> Oh, it moves fast, yeah. That's a benefit, though, because the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we tend to do is we fail fast and fail often; we try a lot of things. You know, you look at Kubernetes, for example. That ecosystem is driven by thousands of intelligent developers, engineers, builders. They're adding value every day, so we have to really keep up with that. And as the stack changes, we try different technologies, we try different methods. And at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's something that we just do every day. >> So we have a survey partner down in New York City called Enterprise Technology Research, ETR, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes, is one of the areas that is kind of, it's been off the charts and seen the most significant adoption and velocity particularly along with cloud, but really, Kubernetes is just, you know, still up and to the right consistently, even with the macro headwinds and all of the other stuff that we're sick of talking about. So what do you do with Kubernetes in the platform? >> Yeah, it's really central to our ability to run the product. When we first started out, we were just on AWS and the way we were running was a little bit like containers junior. Now we're running Kubernetes everywhere at AWS, Azure, Google cloud. It allows us to have a consistent experience across three different cloud providers and we can manage that in code. So our developers can focus on delivering services not trying to learn the intricacies of Amazon, Azure, and Google, and figure out how to deliver services on those three clouds with all of their differences. >> Just a followup on that, is it now, so I presume it sounds like there's a PaaS layer there to allow you guys to have a consistent experience across clouds and out to the edge, wherever. Is that correct? >> Yeah, so we've basically built more or less platform engineering is this the new, hot phrase. Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on and they only have to learn one way of deploying their application, managing their application. And so that just gets all of the underlying infrastructure out of the way and lets them focus on delivering Influx cloud. >> And I know I'm taking a little bit of a tangent, but is that, I'll call it a PaaS layer, if I can use that term, are there specific attributes to InfluxDB or is it kind of just generally off-the-shelf PaaS? Is there any purpose built capability there that is value-add or is it pretty much generic? >> So we really build, we look at things with a build versus buy, through a build versus buy lens. Some things we want to leverage, cloud provider services, for instance, POSTGRES databases for metadata, perhaps. Get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can deliver on, that has consistency, that is all generated from code. that we can, as an SRE group, as an OPS team, that we can manage with very few people, really, and we can stamp out clusters across multiple regions in no time. >> So sometimes you build, sometimes you buy it. How do you make those decisions and what does that mean for the platform and for customers? >> Yeah, so what we're doing is, it's like everybody else will do. We're looking for trade-offs that make sense. We really want to protect our customers' data, so we look for services that support our own software with the most up-time reliability and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team and of course, for our customers; you don't even see that. But we don't want to try to reinvent the wheel, like I had mentioned with SQL datasource for metadata, perhaps. Let's build on top of what of these three large cloud providers have already perfected and we can then focus on our platform engineering and we can help our developers then focus on the InfluxData software, the Influx cloud software. >> So take it to the customer level. What does it mean for them, what's the value that they're going to get out of all these innovations that we've been talking about today, and what can they expect in the future? >> So first of all, people who use the OSS product are really going to be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you, but then you want to scale up. We have some 270 terabytes of data across over four billion series keys that people have stored, so there's a proven ability to scale. Now in terms of the opensource software and how we've developed the platform, you're getting highly available, high cardinality time-series platform. We manage it and really, as I had mentioned earlier, we can keep up with the state of the art. We keep reinventing, we keep deploying things in realtime. We deploy to our platform every day, repeatedly, all the time. And it's that continuous deployment that allow us to continue testing things in flight, rolling things out that change, new features, better ways of doing deployments, safer ways of doing deployments. All of that happens behind the scenes and like we had mentioned earllier, Kubernetes, I mean, that allows us to get that done. We couldn't do it without having that platform as a base layer for us to then put our software on. So we iterate quickly. When you're on the Influx cloud platform, you really are able to take advantage of new features immediately. We roll things out every day and as those things go into production, you have the ability to use them. And so in the then, we want you to focus on getting actual insights from your data instead of running infrastructure, you know, let us do that for you. >> That makes sense. Are the innovations that we're talking about in the evolution of InfluxDB, do you see that as sort of a natural evolution for existing customers? Is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >> Yeah, it really is. It's a little bit of both. Any engineer will say, "Well it depends." So cloud-native technologies are really the hot thing, IoT, industrial IoT especially. People want to just shove tons of data out there and be able to do queries immediately and they don't want to manage infrastructure. What we've started to see are people that use the cloud service as their datastore backbone and then they use edge computing with our OSS product to ingest data from say, multiple production lines, and down-sample that data, send the rest of that data off to Influx cloud where the heavy processing takes place. So really, us being in all the different clouds and iterating on that, and being in all sorts of different regions, allows for people to really get out of the business of trying to manage that big data, have us take care of that. And, of course, as we change the platform, endusers benefit from that immediately. >> And so obviously you've taken away a lot of the heavy lifting for the infrastructure. Would you say the same things about security, especially as you go out to IoT at the edge? How should we be thinking about the value that you bring from a security perspective? >> We take security super seriously. It's built into our DNA. We do a lot of work to ensure that our platform is secure, that the data that we store is kept private. It's, of course, always a concern, you see in the news all the time, companies being compromised. That's something that you can have an entire team working on which we do, to make sure that the data that you have, whether it's in transit, whether it's at rest is always kept secure, is only viewable by you. You look at things like software bill of materials, if you're running this yourself, you have to go vet all sorts of different pieces of software and we do that, you know, as we use new tools. That's something, that's just part of our jobs to make sure that the platform that we're running has fully vetted software. And you know, with opensource especially, that's a lot of work, and so it's definitely new territory. Supply chain attacks are definitely happening at a higher clip that they used to but that is really just part of a day in the life for folks like us that are building platforms. >> And that's key, especially when you start getting into the, you know, that we talk about IoT and the operations technologies, the engineers running that infrastrucutre. You know, historically, as you know, Tim, they would air gap everything; that's how they kept it safe. But that's not feasible anymore. Everything's-- >> Can't do that. >> connected now, right? And so you've got to have a partner that is, again, take away that heavy lifting to R&D so you can focus on some of the other activities. All right, give us the last word and the key takeaways from your perspective. >> Well, you know, from my perspective, I see it as a two-lane approach, with Influx, with any time-series data. You've got a lot of stuff that you're going to run on-prem. What you had mentioned, air gapping? Sure, there's plenty of need for that. But at the end of the day, people that don't want to run big datacenters, people that want to entrust their data to a company that's got a full platform set up for them that they can build on, send that data over to the cloud. The cloud is not going away. I think a more hybrid approach is where the future lives and that's what we're prepared for. >> Tim, really appreciate you coming to the program. Great stuff, good to see you. >> Thanks very much, appreciate it. >> Okay in a moment, I'll be back to wrap up today's session. You're watching theCUBE. (soft electronic music)

>>This past May, The Cube in collaboration with Influx data shared with you the latest innovations in Time series databases. We talked at length about why a purpose built time series database for many use cases, was a superior alternative to general purpose databases trying to do the same thing. Now, you may, you may remember the time series data is any data that's stamped in time, and if it's stamped, it can be analyzed historically. And when we introduced the concept to the community, we talked about how in theory, those time slices could be taken, you know, every hour, every minute, every second, you know, down to the millisecond and how the world was moving toward realtime or near realtime data analysis to support physical infrastructure like sensors and other devices and IOT equipment. A time series databases have had to evolve to efficiently support realtime data in emerging use cases in iot T and other use cases. >>And to do that, new architectural innovations have to be brought to bear. As is often the case, open source software is the linchpin to those innovations. Hello and welcome to Evolving Influx DB into the smart Data platform, made possible by influx data and produced by the Cube. My name is Dave Valante and I'll be your host today. Now in this program we're going to dig pretty deep into what's happening with Time series data generally, and specifically how Influx DB is evolving to support new workloads and demands and data, and specifically around data analytics use cases in real time. Now, first we're gonna hear from Brian Gilmore, who is the director of IOT and emerging technologies at Influx Data. And we're gonna talk about the continued evolution of Influx DB and the new capabilities enabled by open source generally and specific tools. And in this program you're gonna hear a lot about things like Rust, implementation of Apache Arrow, the use of par k and tooling such as data fusion, which powering a new engine for Influx db. >>Now, these innovations, they evolve the idea of time series analysis by dramatically increasing the granularity of time series data by compressing the historical time slices, if you will, from, for example, minutes down to milliseconds. And at the same time, enabling real time analytics with an architecture that can process data much faster and much more efficiently. Now, after Brian, we're gonna hear from Anna East Dos Georgio, who is a developer advocate at In Flux Data. And we're gonna get into the why of these open source capabilities and how they contribute to the evolution of the Influx DB platform. And then we're gonna close the program with Tim Yokum, he's the director of engineering at Influx Data, and he's gonna explain how the Influx DB community actually evolved the data engine in mid-flight and which decisions went into the innovations that are coming to the market. Thank you for being here. We hope you enjoy the program. Let's get started. Okay, we're kicking things off with Brian Gilmore. He's the director of i t and emerging Technology at Influx State of Bryan. Welcome to the program. Thanks for coming on. >>Thanks Dave. Great to be here. I appreciate the time. >>Hey, explain why Influx db, you know, needs a new engine. Was there something wrong with the current engine? What's going on there? >>No, no, not at all. I mean, I think it's, for us, it's been about staying ahead of the market. I think, you know, if we think about what our customers are coming to us sort of with now, you know, related to requests like sql, you know, query support, things like that, we have to figure out a way to, to execute those for them in a way that will scale long term. And then we also, we wanna make sure we're innovating, we're sort of staying ahead of the market as well and sort of anticipating those future needs. So, you know, this is really a, a transparent change for our customers. I mean, I think we'll be adding new capabilities over time that sort of leverage this new engine, but you know, initially the customers who are using us are gonna see just great improvements in performance, you know, especially those that are working at the top end of the, of the workload scale, you know, the massive data volumes and things like that. >>Yeah, and we're gonna get into that today and the architecture and the like, but what was the catalyst for the enhancements? I mean, when and how did this all come about? >>Well, I mean, like three years ago we were primarily on premises, right? I mean, I think we had our open source, we had an enterprise product, you know, and, and sort of shifting that technology, especially the open source code base to a service basis where we were hosting it through, you know, multiple cloud providers. That was, that was, that was a long journey I guess, you know, phase one was, you know, we wanted to host enterprise for our customers, so we sort of created a service that we just managed and ran our enterprise product for them. You know, phase two of this cloud effort was to, to optimize for like multi-tenant, multi-cloud, be able to, to host it in a truly like sass manner where we could use, you know, some type of customer activity or consumption as the, the pricing vector, you know, And, and that was sort of the birth of the, of the real first influx DB cloud, you know, which has been really successful. >>We've seen, I think like 60,000 people sign up and we've got tons and tons of, of both enterprises as well as like new companies, developers, and of course a lot of home hobbyists and enthusiasts who are using out on a, on a daily basis, you know, and having that sort of big pool of, of very diverse and very customers to chat with as they're using the product, as they're giving us feedback, et cetera, has has, you know, pointed us in a really good direction in terms of making sure we're continuously improving that and then also making these big leaps as we're doing with this, with this new engine. >>Right. So you've called it a transparent change for customers, so I'm presuming it's non-disruptive, but I really wanna understand how much of a pivot this is and what, what does it take to make that shift from, you know, time series, you know, specialist to real time analytics and being able to support both? >>Yeah, I mean, it's much more of an evolution, I think, than like a shift or a pivot. You know, time series data is always gonna be fundamental and sort of the basis of the solutions that we offer our customers, and then also the ones that they're building on the sort of raw APIs of our platform themselves. You know, the time series market is one that we've worked diligently to lead. I mean, I think when it comes to like metrics, especially like sensor data and app and infrastructure metrics, if we're being honest though, I think our, our user base is well aware that the way we were architected was much more towards those sort of like backwards looking historical type analytics, which are key for troubleshooting and making sure you don't, you know, run into the same problem twice. But, you know, we had to ask ourselves like, what can we do to like better handle those queries from a performance and a, and a, you know, a time to response on the queries, and can we get that to the point where the results sets are coming back so quickly from the time of query that we can like limit that window down to minutes and then seconds. >>And now with this new engine, we're really starting to talk about a query window that could be like returning results in, in, you know, milliseconds of time since it hit the, the, the ingest queue. And that's, that's really getting to the point where as your data is available, you can use it and you can query it, you can visualize it, and you can do all those sort of magical things with it, you know? And I think getting all of that to a place where we're saying like, yes to the customer on, you know, all of the, the real time queries, the, the multiple language query support, but, you know, it was hard, but we're now at a spot where we can start introducing that to, you know, a a limited number of customers, strategic customers and strategic availability zones to start. But you know, everybody over time. >>So you're basically going from what happened to in, you can still do that obviously, but to what's happening now in the moment? >>Yeah, yeah. I mean if you think about time, it's always sort of past, right? I mean, like in the moment right now, whether you're talking about like a millisecond ago or a minute ago, you know, that's, that's pretty much right now, I think for most people, especially in these use cases where you have other sort of components of latency induced by the, by the underlying data collection, the architecture, the infrastructure, the, you know, the, the devices and you know, the sort of highly distributed nature of all of this. So yeah, I mean, getting, getting a customer or a user to be able to use the data as soon as it is available is what we're after here. >>I always thought, you know, real, I always thought of real time as before you lose the customer, but now in this context, maybe it's before the machine blows up. >>Yeah, it's, it's, I mean it is operationally or operational real time is different, you know, and that's one of the things that really triggered us to know that we were, we were heading in the right direction, is just how many sort of operational customers we have. You know, everything from like aerospace and defense. We've got companies monitoring satellites, we've got tons of industrial users, users using us as a processes storing on the plant floor, you know, and, and if we can satisfy their sort of demands for like real time historical perspective, that's awesome. I think what we're gonna do here is we're gonna start to like edge into the real time that they're used to in terms of, you know, the millisecond response times that they expect of their control systems, certainly not their, their historians and databases. >>I, is this available, these innovations to influx DB cloud customers only who can access this capability? >>Yeah. I mean commercially and today, yes. You know, I think we want to emphasize that's a, for now our goal is to get our latest and greatest and our best to everybody over time. Of course. You know, one of the things we had to do here was like we double down on sort of our, our commitment to open source and availability. So like anybody today can take a look at the, the libraries in on our GitHub and, you know, can ex inspect it and even can try to, you know, implement or execute some of it themselves in their own infrastructure. You know, we are, we're committed to bringing our sort of latest and greatest to our cloud customers first for a couple of reasons. Number one, you know, there are big workloads and they have high expectations of us. I think number two, it also gives us the opportunity to monitor a little bit more closely how it's working, how they're using it, like how the system itself is performing. >>And so just, you know, being careful, maybe a little cautious in terms of, of, of how big we go with this right away, just sort of both limits, you know, the risk of, of, you know, any issues that can come with new software rollouts. We haven't seen anything so far, but also it does give us the opportunity to have like meaningful conversations with a small group of users who are using the products, but once we get through that and they give us two thumbs up on it, it'll be like, open the gates and let everybody in. It's gonna be exciting time for the whole ecosystem. >>Yeah, that makes a lot of sense. And you can do some experimentation and, you know, using the cloud resources. Let's dig into some of the architectural and technical innovations that are gonna help deliver on this vision. What, what should we know there? >>Well, I mean, I think foundationally we built the, the new core on Rust. You know, this is a new very sort of popular systems language, you know, it's extremely efficient, but it's also built for speed and memory safety, which goes back to that us being able to like deliver it in a way that is, you know, something we can inspect very closely, but then also rely on the fact that it's going to behave well. And if it does find error conditions, I mean we, we've loved working with Go and, you know, a lot of our libraries will continue to, to be sort of implemented in Go, but you know, when it came to this particular new engine, you know, that power performance and stability rust was critical. On top of that, like, we've also integrated Apache Arrow and Apache Parque for persistence. I think for anybody who's really familiar with the nuts and bolts of our backend and our TSI and our, our time series merged Trees, this is a big break from that, you know, arrow on the sort of in MI side and then Par K in the on disk side. >>It, it allows us to, to present, you know, a unified set of APIs for those really fast real time inquiries that we talked about, as well as for very large, you know, historical sort of bulk data archives in that PARQUE format, which is also cool because there's an entire ecosystem sort of popping up around Parque in terms of the machine learning community, you know, and getting that all to work, we had to glue it together with aero flight. That's sort of what we're using as our, our RPC component. You know, it handles the orchestration and the, the transportation of the Coer data. Now we're moving to like a true Coer database model for this, this version of the engine, you know, and it removes a lot of overhead for us in terms of having to manage all that serialization, the deserialization, and, you know, to that again, like blurring that line between real time and historical data. It's, you know, it's, it's highly optimized for both streaming micro batch and then batches, but true streaming as well. >>Yeah. Again, I mean, it's funny you mentioned Rust. It is, it's been around for a long time, but it's popularity is, is you know, really starting to hit that steep part of the S-curve. And, and we're gonna dig into to more of that, but give us any, is there anything else that we should know about Bryan? Give us the last word? >>Well, I mean, I think first I'd like everybody sort of watching just to like take a look at what we're offering in terms of early access in beta programs. I mean, if, if, if you wanna participate or if you wanna work sort of in terms of early access with the, with the new engine, please reach out to the team. I'm sure you know, there's a lot of communications going out and you know, it'll be highly featured on our, our website, you know, but reach out to the team, believe it or not, like we have a lot more going on than just the new engine. And so there are also other programs, things we're, we're offering to customers in terms of the user interface, data collection and things like that. And, you know, if you're a customer of ours and you have a sales team, a commercial team that you work with, you can reach out to them and see what you can get access to because we can flip a lot of stuff on, especially in cloud through feature flags. >>But if there's something new that you wanna try out, we'd just love to hear from you. And then, you know, our goal would be that as we give you access to all of these new cool features that, you know, you would give us continuous feedback on these products and services, not only like what you need today, but then what you'll need tomorrow to, to sort of build the next versions of your business. Because you know, the whole database, the ecosystem as it expands out into to, you know, this vertically oriented stack of cloud services and enterprise databases and edge databases, you know, it's gonna be what we all make it together, not just, you know, those of us who were employed by Influx db. And then finally I would just say please, like watch in ICE in Tim's sessions, like these are two of our best and brightest, They're totally brilliant, completely pragmatic, and they are most of all customer obsessed, which is amazing. And there's no better takes, like honestly on the, the sort of technical details of this, then there's, especially when it comes to like the value that these investments will, will bring to our customers and our communities. So encourage you to, to, you know, pay more attention to them than you did to me, for sure. >>Brian Gilmore, great stuff. Really appreciate your time. Thank you. >>Yeah, thanks Dave. It was awesome. Look forward to it. >>Yeah, me too. Looking forward to see how the, the community actually applies these new innovations and goes, goes beyond just the historical into the real time really hot area. As Brian said in a moment, I'll be right back with Anna East dos Georgio to dig into the critical aspects of key open source components of the Influx DB engine, including Rust, Arrow, Parque, data fusion. Keep it right there. You don't wanna miss this >>Time series Data is everywhere. The number of sensors, systems and applications generating time series data increases every day. All these data sources producing so much data can cause analysis paralysis. Influx DB is an entire platform designed with everything you need to quickly build applications that generate value from time series data influx. DB Cloud is a serverless solution, which means you don't need to buy or manage your own servers. There's no need to worry about provisioning because you only pay for what you use. Influx DB Cloud is fully managed so you get the newest features and enhancements as they're added to the platform's code base. It also means you can spend time building solutions and delivering value to your users instead of wasting time and effort managing something else. Influx TVB Cloud offers a range of security features to protect your data, multiple layers of redundancy ensure you don't lose any data access controls ensure that only the people who should see your data can see it. >>And encryption protects your data at rest and in transit between any of our regions or cloud providers. InfluxDB uses a single API across the entire platform suite so you can build on open source, deploy to the cloud and then then easily query data in the cloud at the edge or on prem using the same scripts. And InfluxDB is schemaless automatically adjusting to changes in the shape of your data without requiring changes in your application. Logic. InfluxDB Cloud is production ready from day one. All it needs is your data and your imagination. Get started today@influxdata.com slash cloud. >>Okay, we're back. I'm Dave Valante with a Cube and you're watching evolving Influx DB into the smart data platform made possible by influx data. Anna ETOs Georgio is here, she's a developer advocate for influx data and we're gonna dig into the rationale and value contribution behind several open source technologies that Influx DB is leveraging to increase the granularity of time series analysis analysis and bring the world of data into real-time analytics and is welcome to the program. Thanks for coming on. >>Hi, thank you so much. It's a pleasure to be here. >>Oh, you're very welcome. Okay, so IX is being touted as this next gen open source core for Influx db. And my understanding is that it leverages in memory of course for speed. It's a kilo store, so it gives you a compression efficiency, it's gonna give you faster query speeds, you store files and object storage, so you got very cost effective approach. Are these the salient points on the platform? I know there are probably dozens of other features, but what are the high level value points that people should understand? >>Sure, that's a great question. So some of the main requirements that IOx is trying to achieve and some of the most impressive ones to me, the first one is that it aims to have no limits on cardinality and also allow you to write any kind of event data that you want, whether that's live tag or a field. It also wants to deliver the best in class performance on analytics queries. In addition to our already well served metrics queries, we also wanna have operator control over memory usage. So you should be able to define how much memory is used for buffering caching and query processing. Some other really important parts is the ability to have bulk data export and import super useful. Also broader ecosystem compatibility where possible we aim to use and embrace emerging standards in the data analytics ecosystem and have compatibility with things like sql, Python, and maybe even pandas in the future. >>Okay, so lot there. Now we talked to Brian about how you're using Rust and which is not a new programming language and of course we had some drama around Rust during the pandemic with the Mozilla layoffs, but the formation of the Rust Foundation really addressed any of those concerns. You got big guns like Amazon and Google and Microsoft throwing their collective weights behind it. It's really, the adoption is really starting to get steep on the S-curve. So lots of platforms, lots of adoption with rust, but why rust as an alternative to say c plus plus for example? >>Sure, that's a great question. So Russ was chosen because of his exceptional performance and reliability. So while Russ is synt tactically similar to c plus plus and it has similar performance, it also compiles to a native code like c plus plus. But unlike c plus plus, it also has much better memory safety. So memory safety is protection against bugs or security vulnerabilities that lead to excessive memory usage or memory leaks. And rust achieves this memory safety due to its like innovative type system. Additionally, it doesn't allow for dangling pointers. And dangling pointers are the main classes of errors that lead to exploitable security vulnerabilities in languages like c plus plus. So Russ like helps meet that requirement of having no limits on ality, for example, because it's, we're also using the Russ implementation of Apache Arrow and this control over memory and also Russ Russ's packaging system called crates IO offers everything that you need out of the box to have features like AY and a weight to fix race conditions, to protection against buffering overflows and to ensure thread safe async cashing structures as well. So essentially it's just like has all the control, all the fine grain control, you need to take advantage of memory and all your resources as well as possible so that you can handle those really, really high ity use cases. >>Yeah, and the more I learn about the, the new engine and, and the platform IOCs et cetera, you know, you, you see things like, you know, the old days not even to even today you do a lot of garbage collection in these, in these systems and there's an inverse, you know, impact relative to performance. So it looks like you really, you know, the community is modernizing the platform, but I wanna talk about Apache Arrow for a moment. It it's designed to address the constraints that are associated with analyzing large data sets. We, we know that, but please explain why, what, what is Arrow and and what does it bring to Influx db? >>Sure, yeah. So Arrow is a, a framework for defining in memory calmer data. And so much of the efficiency and performance of IOx comes from taking advantage of calmer data structures. And I will, if you don't mind, take a moment to kind of of illustrate why column or data structures are so valuable. Let's pretend that we are gathering field data about the temperature in our room and also maybe the temperature of our stove. And in our table we have those two temperature values as well as maybe a measurement value, timestamp value, maybe some other tag values that describe what room and what house, et cetera we're getting this data from. And so you can picture this table where we have like two rows with the two temperature values for both our room and the stove. Well usually our room temperature is regulated so those values don't change very often. >>So when you have calm oriented st calm oriented storage, essentially you take each row, each column and group it together. And so if that's the case and you're just taking temperature values from the room and a lot of those temperature values are the same, then you'll, you might be able to imagine how equal values will then enable each other and when they neighbor each other in the storage format, this provides a really perfect opportunity for cheap compression. And then this cheap compression enables high cardinality use cases. It also enables for faster scan rates. So if you wanna define like the men and max value of the temperature in the room across a thousand different points, you only have to get those a thousand different points in order to answer that question and you have those immediately available to you. But let's contrast this with a row oriented storage solution instead so that we can understand better the benefits of calmer oriented storage. >>So if you had a row oriented storage, you'd first have to look at every field like the temperature in, in the room and the temperature of the stove. You'd have to go across every tag value that maybe describes where the room is located or what model the stove is. And every timestamp you'd then have to pluck out that one temperature value that you want at that one time stamp and do that for every single row. So you're scanning across a ton more data and that's why Rowe Oriented doesn't provide the same efficiency as calmer and Apache Arrow is in memory calmer data, commoner data fit framework. So that's where a lot of the advantages come >>From. Okay. So you basically described like a traditional database, a row approach, but I've seen like a lot of traditional database say, okay, now we've got, we can handle colo format versus what you're talking about is really, you know, kind of native i, is it not as effective? Is the, is the foreman not as effective because it's largely a, a bolt on? Can you, can you like elucidate on that front? >>Yeah, it's, it's not as effective because you have more expensive compression and because you can't scan across the values as quickly. And so those are, that's pretty much the main reasons why, why RO row oriented storage isn't as efficient as calm, calmer oriented storage. Yeah. >>Got it. So let's talk about Arrow Data Fusion. What is data fusion? I know it's written in Rust, but what does it bring to the table here? >>Sure. So it's an extensible query execution framework and it uses Arrow as it's in memory format. So the way that it helps in influx DB IOCs is that okay, it's great if you can write unlimited amount of cardinality into influx Cbis, but if you don't have a query engine that can successfully query that data, then I don't know how much value it is for you. So Data fusion helps enable the, the query process and transformation of that data. It also has a PANDAS API so that you could take advantage of PANDAS data frames as well and all of the machine learning tools associated with Pandas. >>Okay. You're also leveraging Par K in the platform cause we heard a lot about Par K in the middle of the last decade cuz as a storage format to improve on Hadoop column stores. What are you doing with Parque and why is it important? >>Sure. So parque is the column oriented durable file format. So it's important because it'll enable bulk import, bulk export, it has compatibility with Python and Pandas, so it supports a broader ecosystem. Par K files also take very little disc disc space and they're faster to scan because again, they're column oriented in particular, I think PAR K files are like 16 times cheaper than CSV files, just as kind of a point of reference. And so that's essentially a lot of the, the benefits of par k. >>Got it. Very popular. So and he's, what exactly is influx data focusing on as a committer to these projects? What is your focus? What's the value that you're bringing to the community? >>Sure. So Influx DB first has contributed a lot of different, different things to the Apache ecosystem. For example, they contribute an implementation of Apache Arrow and go and that will support clearing with flux. Also, there has been a quite a few contributions to data fusion for things like memory optimization and supportive additional SQL features like support for timestamp, arithmetic and support for exist clauses and support for memory control. So yeah, Influx has contributed a a lot to the Apache ecosystem and continues to do so. And I think kind of the idea here is that if you can improve these upstream projects and then the long term strategy here is that the more you contribute and build those up, then the more you will perpetuate that cycle of improvement and the more we will invest in our own project as well. So it's just that kind of symbiotic relationship and appreciation of the open source community. >>Yeah. Got it. You got that virtuous cycle going, the people call the flywheel. Give us your last thoughts and kind of summarize, you know, where what, what the big takeaways are from your perspective. >>So I think the big takeaway is that influx data is doing a lot of really exciting things with Influx DB IOx and I really encourage, if you are interested in learning more about the technologies that Influx is leveraging to produce IOCs, the challenges associated with it and all of the hard work questions and you just wanna learn more, then I would encourage you to go to the monthly Tech talks and community office hours and they are on every second Wednesday of the month at 8:30 AM Pacific time. There's also a community forums and a community Slack channel look for the influx DDB unders IAC channel specifically to learn more about how to join those office hours and those monthly tech tech talks as well as ask any questions they have about iacs, what to expect and what you'd like to learn more about. I as a developer advocate, I wanna answer your questions. So if there's a particular technology or stack that you wanna dive deeper into and want more explanation about how INFLUX DB leverages it to build IOCs, I will be really excited to produce content on that topic for you. >>Yeah, that's awesome. You guys have a really rich community, collaborate with your peers, solve problems, and, and you guys super responsive, so really appreciate that. All right, thank you so much Anise for explaining all this open source stuff to the audience and why it's important to the future of data. >>Thank you. I really appreciate it. >>All right, you're very welcome. Okay, stay right there and in a moment I'll be back with Tim Yoakum, he's the director of engineering for Influx Data and we're gonna talk about how you update a SAS engine while the plane is flying at 30,000 feet. You don't wanna miss this. >>I'm really glad that we went with InfluxDB Cloud for our hosting because it has saved us a ton of time. It's helped us move faster, it's saved us money. And also InfluxDB has good support. My name's Alex Nada. I am CTO at Noble nine. Noble Nine is a platform to measure and manage service level objectives, which is a great way of measuring the reliability of your systems. You can essentially think of an slo, the product we're providing to our customers as a bunch of time series. So we need a way to store that data and the corresponding time series that are related to those. The main reason that we settled on InfluxDB as we were shopping around is that InfluxDB has a very flexible query language and as a general purpose time series database, it basically had the set of features we were looking for. >>As our platform has grown, we found InfluxDB Cloud to be a really scalable solution. We can quickly iterate on new features and functionality because Influx Cloud is entirely managed, it probably saved us at least a full additional person on our team. We also have the option of running InfluxDB Enterprise, which gives us the ability to even host off the cloud or in a private cloud if that's preferred by a customer. Influx data has been really flexible in adapting to the hosting requirements that we have. They listened to the challenges we were facing and they helped us solve it. As we've continued to grow, I'm really happy we have influx data by our side. >>Okay, we're back with Tim Yokum, who is the director of engineering at Influx Data. Tim, welcome. Good to see you. >>Good to see you. Thanks for having me. >>You're really welcome. Listen, we've been covering open source software in the cube for more than a decade, and we've kind of watched the innovation from the big data ecosystem. The cloud has been being built out on open source, mobile, social platforms, key databases, and of course influx DB and influx data has been a big consumer and contributor of open source software. So my question to you is, where have you seen the biggest bang for the buck from open source software? >>So yeah, you know, influx really, we thrive at the intersection of commercial services and open, so open source software. So OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service from our core storage engine technologies to web services temping engines. Our, our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants and like you've mentioned, even better, we contribute a lot back to the projects that we use as well as our own product influx db. >>You know, but I gotta ask you, Tim, because one of the challenge that that we've seen in particular, you saw this in the heyday of Hadoop, the, the innovations come so fast and furious and as a software company you gotta place bets, you gotta, you know, commit people and sometimes those bets can be risky and not pay off well, how have you managed this challenge? >>Oh, it moves fast. Yeah, that, that's a benefit though because it, the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we, what we tend to do is, is we fail fast and fail often. We try a lot of things. You know, you look at Kubernetes for example, that ecosystem is driven by thousands of intelligent developers, engineers, builders, they're adding value every day. So we have to really keep up with that. And as the stack changes, we, we try different technologies, we try different methods, and at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's, it's something that we just do every day. >>So we have a survey partner down in New York City called Enterprise Technology Research etr, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes is one of the areas that has kind of, it's been off the charts and seen the most significant adoption and velocity particularly, you know, along with cloud. But, but really Kubernetes is just, you know, still up until the right consistently even with, you know, the macro headwinds and all, all of the stuff that we're sick of talking about. But, so what are you doing with Kubernetes in the platform? >>Yeah, it, it's really central to our ability to run the product. When we first started out, we were just on AWS and, and the way we were running was, was a little bit like containers junior. Now we're running Kubernetes everywhere at aws, Azure, Google Cloud. It allows us to have a consistent experience across three different cloud providers and we can manage that in code so our developers can focus on delivering services, not trying to learn the intricacies of Amazon, Azure, and Google and figure out how to deliver services on those three clouds with all of their differences. >>Just to follow up on that, is it, no. So I presume it's sounds like there's a PAs layer there to allow you guys to have a consistent experience across clouds and out to the edge, you know, wherever is that, is that correct? >>Yeah, so we've basically built more or less platform engineering, This is the new hot phrase, you know, it, it's, Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on and they only have to learn one way of deploying their application, managing their application. And so that, that just gets all of the underlying infrastructure out of the way and, and lets them focus on delivering influx cloud. >>Yeah, and I know I'm taking a little bit of a tangent, but is that, that, I'll call it a PAs layer if I can use that term. Is that, are there specific attributes to Influx db or is it kind of just generally off the shelf paths? You know, are there, is, is there any purpose built capability there that, that is, is value add or is it pretty much generic? >>So we really build, we, we look at things through, with a build versus buy through a, a build versus by lens. Some things we want to leverage cloud provider services, for instance, Postgres databases for metadata, perhaps we'll get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can, can deliver on that has consistency that is, is all generated from code that we can as a, as an SRE group, as an ops team, that we can manage with very few people really, and we can stamp out clusters across multiple regions and in no time. >>So how, so sometimes you build, sometimes you buy it. How do you make those decisions and and what does that mean for the, for the platform and for customers? >>Yeah, so what we're doing is, it's like everybody else will do, we're we're looking for trade offs that make sense. You know, we really want to protect our customers data. So we look for services that support our own software with the most uptime, reliability, and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team. And of course for customers you don't even see that, but we don't want to try to reinvent the wheel, like I had mentioned with SQL data stores for metadata, perhaps let's build on top of what of these three large cloud providers have already perfected. And we can then focus on our platform engineering and we can have our developers then focus on the influx data, software, influx, cloud software. >>So take it to the customer level, what does it mean for them? What's the value that they're gonna get out of all these innovations that we've been been talking about today and what can they expect in the future? >>So first of all, people who use the OSS product are really gonna be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you, but then you want to scale up. We have some 270 terabytes of data across, over 4 billion series keys that people have stored. So there's a proven ability to scale now in terms of the open source, open source software and how we've developed the platform. You're getting highly available high cardinality time series platform. We manage it and, and really as, as I mentioned earlier, we can keep up with the state of the art. We keep reinventing, we keep deploying things in real time. We deploy to our platform every day repeatedly all the time. And it's that continuous deployment that allows us to continue testing things in flight, rolling things out that change new features, better ways of doing deployments, safer ways of doing deployments. >>All of that happens behind the scenes. And like we had mentioned earlier, Kubernetes, I mean that, that allows us to get that done. We couldn't do it without having that platform as a, as a base layer for us to then put our software on. So we, we iterate quickly. When you're on the, the Influx cloud platform, you really are able to, to take advantage of new features immediately. We roll things out every day and as those things go into production, you have, you have the ability to, to use them. And so in the end we want you to focus on getting actual insights from your data instead of running infrastructure, you know, let, let us do that for you. So, >>And that makes sense, but so is the, is the, are the innovations that we're talking about in the evolution of Influx db, do, do you see that as sort of a natural evolution for existing customers? I, is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >>Yeah, it really is it, it's a little bit of both. Any engineer will say, well, it depends. So cloud native technologies are, are really the hot thing. Iot, industrial iot especially, people want to just shove tons of data out there and be able to do queries immediately and they don't wanna manage infrastructure. What we've started to see are people that use the cloud service as their, their data store backbone and then they use edge computing with R OSS product to ingest data from say, multiple production lines and downsample that data, send the rest of that data off influx cloud where the heavy processing takes place. So really us being in all the different clouds and iterating on that and being in all sorts of different regions allows for people to really get out of the, the business of man trying to manage that big data, have us take care of that. And of course as we change the platform end users benefit from that immediately. And, >>And so obviously taking away a lot of the heavy lifting for the infrastructure, would you say the same thing about security, especially as you go out to IOT and the Edge? How should we be thinking about the value that you bring from a security perspective? >>Yeah, we take, we take security super seriously. It, it's built into our dna. We do a lot of work to ensure that our platform is secure, that the data we store is, is kept private. It's of course always a concern. You see in the news all the time, companies being compromised, you know, that's something that you can have an entire team working on, which we do to make sure that the data that you have, whether it's in transit, whether it's at rest, is always kept secure, is only viewable by you. You know, you look at things like software, bill of materials, if you're running this yourself, you have to go vet all sorts of different pieces of software. And we do that, you know, as we use new tools. That's something that, that's just part of our jobs to make sure that the platform that we're running it has, has fully vetted software and, and with open source especially, that's a lot of work. And so it's, it's definitely new territory. Supply chain attacks are, are definitely happening at a higher clip than they used to, but that is, that is really just part of a day in the, the life for folks like us that are, are building platforms. >>Yeah, and that's key. I mean especially when you start getting into the, the, you know, we talk about IOT and the operations technologies, the engineers running the, that infrastructure, you know, historically, as you know, Tim, they, they would air gap everything. That's how they kept it safe. But that's not feasible anymore. Everything's >>That >>Connected now, right? And so you've gotta have a partner that is again, take away that heavy lifting to r and d so you can focus on some of the other activities. Right. Give us the, the last word and the, the key takeaways from your perspective. >>Well, you know, from my perspective I see it as, as a a two lane approach with, with influx, with Anytime series data, you know, you've got a lot of stuff that you're gonna run on-prem, what you had mentioned, air gaping. Sure there's plenty of need for that, but at the end of the day, people that don't want to run big data centers, people that want torus their data to, to a company that's, that's got a full platform set up for them that they can build on, send that data over to the cloud, the cloud is not going away. I think more hybrid approach is, is where the future lives and that's what we're prepared for. >>Tim, really appreciate you coming to the program. Great stuff. Good to see you. >>Thanks very much. Appreciate it. >>Okay, in a moment I'll be back to wrap up. Today's session, you're watching The Cube. >>Are you looking for some help getting started with InfluxDB Telegraph or Flux Check >>Out Influx DB University >>Where you can find our entire catalog of free training that will help you make the most of your time series data >>Get >>Started for free@influxdbu.com. >>We'll see you in class. >>Okay, so we heard today from three experts on time series and data, how the Influx DB platform is evolving to support new ways of analyzing large data sets very efficiently and effectively in real time. And we learned that key open source components like Apache Arrow and the Rust Programming environment Data fusion par K are being leveraged to support realtime data analytics at scale. We also learned about the contributions in importance of open source software and how the Influx DB community is evolving the platform with minimal disruption to support new workloads, new use cases, and the future of realtime data analytics. Now remember these sessions, they're all available on demand. You can go to the cube.net to find those. Don't forget to check out silicon angle.com for all the news related to things enterprise and emerging tech. And you should also check out influx data.com. There you can learn about the company's products. You'll find developer resources like free courses. You could join the developer community and work with your peers to learn and solve problems. And there are plenty of other resources around use cases and customer stories on the website. This is Dave Valante. Thank you for watching Evolving Influx DB into the smart data platform, made possible by influx data and brought to you by the Cube, your leader in enterprise and emerging tech coverage.

>>This past May, The Cube in collaboration with Influx data shared with you the latest innovations in Time series databases. We talked at length about why a purpose built time series database for many use cases, was a superior alternative to general purpose databases trying to do the same thing. Now, you may, you may remember the time series data is any data that's stamped in time, and if it's stamped, it can be analyzed historically. And when we introduced the concept to the community, we talked about how in theory, those time slices could be taken, you know, every hour, every minute, every second, you know, down to the millisecond and how the world was moving toward realtime or near realtime data analysis to support physical infrastructure like sensors and other devices and IOT equipment. A time series databases have had to evolve to efficiently support realtime data in emerging use cases in iot T and other use cases. >>And to do that, new architectural innovations have to be brought to bear. As is often the case, open source software is the linchpin to those innovations. Hello and welcome to Evolving Influx DB into the smart Data platform, made possible by influx data and produced by the Cube. My name is Dave Valante and I'll be your host today. Now in this program we're going to dig pretty deep into what's happening with Time series data generally, and specifically how Influx DB is evolving to support new workloads and demands and data, and specifically around data analytics use cases in real time. Now, first we're gonna hear from Brian Gilmore, who is the director of IOT and emerging technologies at Influx Data. And we're gonna talk about the continued evolution of Influx DB and the new capabilities enabled by open source generally and specific tools. And in this program you're gonna hear a lot about things like Rust, implementation of Apache Arrow, the use of par k and tooling such as data fusion, which powering a new engine for Influx db. >>Now, these innovations, they evolve the idea of time series analysis by dramatically increasing the granularity of time series data by compressing the historical time slices, if you will, from, for example, minutes down to milliseconds. And at the same time, enabling real time analytics with an architecture that can process data much faster and much more efficiently. Now, after Brian, we're gonna hear from Anna East Dos Georgio, who is a developer advocate at In Flux Data. And we're gonna get into the why of these open source capabilities and how they contribute to the evolution of the Influx DB platform. And then we're gonna close the program with Tim Yokum, he's the director of engineering at Influx Data, and he's gonna explain how the Influx DB community actually evolved the data engine in mid-flight and which decisions went into the innovations that are coming to the market. Thank you for being here. We hope you enjoy the program. Let's get started. Okay, we're kicking things off with Brian Gilmore. He's the director of i t and emerging Technology at Influx State of Bryan. Welcome to the program. Thanks for coming on. >>Thanks Dave. Great to be here. I appreciate the time. >>Hey, explain why Influx db, you know, needs a new engine. Was there something wrong with the current engine? What's going on there? >>No, no, not at all. I mean, I think it's, for us, it's been about staying ahead of the market. I think, you know, if we think about what our customers are coming to us sort of with now, you know, related to requests like sql, you know, query support, things like that, we have to figure out a way to, to execute those for them in a way that will scale long term. And then we also, we wanna make sure we're innovating, we're sort of staying ahead of the market as well and sort of anticipating those future needs. So, you know, this is really a, a transparent change for our customers. I mean, I think we'll be adding new capabilities over time that sort of leverage this new engine, but you know, initially the customers who are using us are gonna see just great improvements in performance, you know, especially those that are working at the top end of the, of the workload scale, you know, the massive data volumes and things like that. >>Yeah, and we're gonna get into that today and the architecture and the like, but what was the catalyst for the enhancements? I mean, when and how did this all come about? >>Well, I mean, like three years ago we were primarily on premises, right? I mean, I think we had our open source, we had an enterprise product, you know, and, and sort of shifting that technology, especially the open source code base to a service basis where we were hosting it through, you know, multiple cloud providers. That was, that was, that was a long journey I guess, you know, phase one was, you know, we wanted to host enterprise for our customers, so we sort of created a service that we just managed and ran our enterprise product for them. You know, phase two of this cloud effort was to, to optimize for like multi-tenant, multi-cloud, be able to, to host it in a truly like sass manner where we could use, you know, some type of customer activity or consumption as the, the pricing vector, you know, And, and that was sort of the birth of the, of the real first influx DB cloud, you know, which has been really successful. >>We've seen, I think like 60,000 people sign up and we've got tons and tons of, of both enterprises as well as like new companies, developers, and of course a lot of home hobbyists and enthusiasts who are using out on a, on a daily basis, you know, and having that sort of big pool of, of very diverse and very customers to chat with as they're using the product, as they're giving us feedback, et cetera, has has, you know, pointed us in a really good direction in terms of making sure we're continuously improving that and then also making these big leaps as we're doing with this, with this new engine. >>Right. So you've called it a transparent change for customers, so I'm presuming it's non-disruptive, but I really wanna understand how much of a pivot this is and what, what does it take to make that shift from, you know, time series, you know, specialist to real time analytics and being able to support both? >>Yeah, I mean, it's much more of an evolution, I think, than like a shift or a pivot. You know, time series data is always gonna be fundamental and sort of the basis of the solutions that we offer our customers, and then also the ones that they're building on the sort of raw APIs of our platform themselves. You know, the time series market is one that we've worked diligently to lead. I mean, I think when it comes to like metrics, especially like sensor data and app and infrastructure metrics, if we're being honest though, I think our, our user base is well aware that the way we were architected was much more towards those sort of like backwards looking historical type analytics, which are key for troubleshooting and making sure you don't, you know, run into the same problem twice. But, you know, we had to ask ourselves like, what can we do to like better handle those queries from a performance and a, and a, you know, a time to response on the queries, and can we get that to the point where the results sets are coming back so quickly from the time of query that we can like limit that window down to minutes and then seconds. >>And now with this new engine, we're really starting to talk about a query window that could be like returning results in, in, you know, milliseconds of time since it hit the, the, the ingest queue. And that's, that's really getting to the point where as your data is available, you can use it and you can query it, you can visualize it, and you can do all those sort of magical things with it, you know? And I think getting all of that to a place where we're saying like, yes to the customer on, you know, all of the, the real time queries, the, the multiple language query support, but, you know, it was hard, but we're now at a spot where we can start introducing that to, you know, a a limited number of customers, strategic customers and strategic availability zones to start. But you know, everybody over time. >>So you're basically going from what happened to in, you can still do that obviously, but to what's happening now in the moment? >>Yeah, yeah. I mean if you think about time, it's always sort of past, right? I mean, like in the moment right now, whether you're talking about like a millisecond ago or a minute ago, you know, that's, that's pretty much right now, I think for most people, especially in these use cases where you have other sort of components of latency induced by the, by the underlying data collection, the architecture, the infrastructure, the, you know, the, the devices and you know, the sort of highly distributed nature of all of this. So yeah, I mean, getting, getting a customer or a user to be able to use the data as soon as it is available is what we're after here. >>I always thought, you know, real, I always thought of real time as before you lose the customer, but now in this context, maybe it's before the machine blows up. >>Yeah, it's, it's, I mean it is operationally or operational real time is different, you know, and that's one of the things that really triggered us to know that we were, we were heading in the right direction, is just how many sort of operational customers we have. You know, everything from like aerospace and defense. We've got companies monitoring satellites, we've got tons of industrial users, users using us as a processes storing on the plant floor, you know, and, and if we can satisfy their sort of demands for like real time historical perspective, that's awesome. I think what we're gonna do here is we're gonna start to like edge into the real time that they're used to in terms of, you know, the millisecond response times that they expect of their control systems, certainly not their, their historians and databases. >>I, is this available, these innovations to influx DB cloud customers only who can access this capability? >>Yeah. I mean commercially and today, yes. You know, I think we want to emphasize that's a, for now our goal is to get our latest and greatest and our best to everybody over time. Of course. You know, one of the things we had to do here was like we double down on sort of our, our commitment to open source and availability. So like anybody today can take a look at the, the libraries in on our GitHub and, you know, can ex inspect it and even can try to, you know, implement or execute some of it themselves in their own infrastructure. You know, we are, we're committed to bringing our sort of latest and greatest to our cloud customers first for a couple of reasons. Number one, you know, there are big workloads and they have high expectations of us. I think number two, it also gives us the opportunity to monitor a little bit more closely how it's working, how they're using it, like how the system itself is performing. >>And so just, you know, being careful, maybe a little cautious in terms of, of, of how big we go with this right away, just sort of both limits, you know, the risk of, of, you know, any issues that can come with new software rollouts. We haven't seen anything so far, but also it does give us the opportunity to have like meaningful conversations with a small group of users who are using the products, but once we get through that and they give us two thumbs up on it, it'll be like, open the gates and let everybody in. It's gonna be exciting time for the whole ecosystem. >>Yeah, that makes a lot of sense. And you can do some experimentation and, you know, using the cloud resources. Let's dig into some of the architectural and technical innovations that are gonna help deliver on this vision. What, what should we know there? >>Well, I mean, I think foundationally we built the, the new core on Rust. You know, this is a new very sort of popular systems language, you know, it's extremely efficient, but it's also built for speed and memory safety, which goes back to that us being able to like deliver it in a way that is, you know, something we can inspect very closely, but then also rely on the fact that it's going to behave well. And if it does find error conditions, I mean we, we've loved working with Go and, you know, a lot of our libraries will continue to, to be sort of implemented in Go, but you know, when it came to this particular new engine, you know, that power performance and stability rust was critical. On top of that, like, we've also integrated Apache Arrow and Apache Parque for persistence. I think for anybody who's really familiar with the nuts and bolts of our backend and our TSI and our, our time series merged Trees, this is a big break from that, you know, arrow on the sort of in MI side and then Par K in the on disk side. >>It, it allows us to, to present, you know, a unified set of APIs for those really fast real time inquiries that we talked about, as well as for very large, you know, historical sort of bulk data archives in that PARQUE format, which is also cool because there's an entire ecosystem sort of popping up around Parque in terms of the machine learning community, you know, and getting that all to work, we had to glue it together with aero flight. That's sort of what we're using as our, our RPC component. You know, it handles the orchestration and the, the transportation of the Coer data. Now we're moving to like a true Coer database model for this, this version of the engine, you know, and it removes a lot of overhead for us in terms of having to manage all that serialization, the deserialization, and, you know, to that again, like blurring that line between real time and historical data. It's, you know, it's, it's highly optimized for both streaming micro batch and then batches, but true streaming as well. >>Yeah. Again, I mean, it's funny you mentioned Rust. It is, it's been around for a long time, but it's popularity is, is you know, really starting to hit that steep part of the S-curve. And, and we're gonna dig into to more of that, but give us any, is there anything else that we should know about Bryan? Give us the last word? >>Well, I mean, I think first I'd like everybody sort of watching just to like take a look at what we're offering in terms of early access in beta programs. I mean, if, if, if you wanna participate or if you wanna work sort of in terms of early access with the, with the new engine, please reach out to the team. I'm sure you know, there's a lot of communications going out and you know, it'll be highly featured on our, our website, you know, but reach out to the team, believe it or not, like we have a lot more going on than just the new engine. And so there are also other programs, things we're, we're offering to customers in terms of the user interface, data collection and things like that. And, you know, if you're a customer of ours and you have a sales team, a commercial team that you work with, you can reach out to them and see what you can get access to because we can flip a lot of stuff on, especially in cloud through feature flags. >>But if there's something new that you wanna try out, we'd just love to hear from you. And then, you know, our goal would be that as we give you access to all of these new cool features that, you know, you would give us continuous feedback on these products and services, not only like what you need today, but then what you'll need tomorrow to, to sort of build the next versions of your business. Because you know, the whole database, the ecosystem as it expands out into to, you know, this vertically oriented stack of cloud services and enterprise databases and edge databases, you know, it's gonna be what we all make it together, not just, you know, those of us who were employed by Influx db. And then finally I would just say please, like watch in ICE in Tim's sessions, like these are two of our best and brightest, They're totally brilliant, completely pragmatic, and they are most of all customer obsessed, which is amazing. And there's no better takes, like honestly on the, the sort of technical details of this, then there's, especially when it comes to like the value that these investments will, will bring to our customers and our communities. So encourage you to, to, you know, pay more attention to them than you did to me, for sure. >>Brian Gilmore, great stuff. Really appreciate your time. Thank you. >>Yeah, thanks Dave. It was awesome. Look forward to it. >>Yeah, me too. Looking forward to see how the, the community actually applies these new innovations and goes, goes beyond just the historical into the real time really hot area. As Brian said in a moment, I'll be right back with Anna East dos Georgio to dig into the critical aspects of key open source components of the Influx DB engine, including Rust, Arrow, Parque, data fusion. Keep it right there. You don't wanna miss this >>Time series Data is everywhere. The number of sensors, systems and applications generating time series data increases every day. All these data sources producing so much data can cause analysis paralysis. Influx DB is an entire platform designed with everything you need to quickly build applications that generate value from time series data influx. DB Cloud is a serverless solution, which means you don't need to buy or manage your own servers. There's no need to worry about provisioning because you only pay for what you use. Influx DB Cloud is fully managed so you get the newest features and enhancements as they're added to the platform's code base. It also means you can spend time building solutions and delivering value to your users instead of wasting time and effort managing something else. Influx TVB Cloud offers a range of security features to protect your data, multiple layers of redundancy ensure you don't lose any data access controls ensure that only the people who should see your data can see it. >>And encryption protects your data at rest and in transit between any of our regions or cloud providers. InfluxDB uses a single API across the entire platform suite so you can build on open source, deploy to the cloud and then then easily query data in the cloud at the edge or on prem using the same scripts. And InfluxDB is schemaless automatically adjusting to changes in the shape of your data without requiring changes in your application. Logic. InfluxDB Cloud is production ready from day one. All it needs is your data and your imagination. Get started today@influxdata.com slash cloud. >>Okay, we're back. I'm Dave Valante with a Cube and you're watching evolving Influx DB into the smart data platform made possible by influx data. Anna ETOs Georgio is here, she's a developer advocate for influx data and we're gonna dig into the rationale and value contribution behind several open source technologies that Influx DB is leveraging to increase the granularity of time series analysis analysis and bring the world of data into real-time analytics and is welcome to the program. Thanks for coming on. >>Hi, thank you so much. It's a pleasure to be here. >>Oh, you're very welcome. Okay, so IX is being touted as this next gen open source core for Influx db. And my understanding is that it leverages in memory of course for speed. It's a kilo store, so it gives you a compression efficiency, it's gonna give you faster query speeds, you store files and object storage, so you got very cost effective approach. Are these the salient points on the platform? I know there are probably dozens of other features, but what are the high level value points that people should understand? >>Sure, that's a great question. So some of the main requirements that IOx is trying to achieve and some of the most impressive ones to me, the first one is that it aims to have no limits on cardinality and also allow you to write any kind of event data that you want, whether that's live tag or a field. It also wants to deliver the best in class performance on analytics queries. In addition to our already well served metrics queries, we also wanna have operator control over memory usage. So you should be able to define how much memory is used for buffering caching and query processing. Some other really important parts is the ability to have bulk data export and import super useful. Also broader ecosystem compatibility where possible we aim to use and embrace emerging standards in the data analytics ecosystem and have compatibility with things like sql, Python, and maybe even pandas in the future. >>Okay, so lot there. Now we talked to Brian about how you're using Rust and which is not a new programming language and of course we had some drama around Rust during the pandemic with the Mozilla layoffs, but the formation of the Rust Foundation really addressed any of those concerns. You got big guns like Amazon and Google and Microsoft throwing their collective weights behind it. It's really, the adoption is really starting to get steep on the S-curve. So lots of platforms, lots of adoption with rust, but why rust as an alternative to say c plus plus for example? >>Sure, that's a great question. So Russ was chosen because of his exceptional performance and reliability. So while Russ is synt tactically similar to c plus plus and it has similar performance, it also compiles to a native code like c plus plus. But unlike c plus plus, it also has much better memory safety. So memory safety is protection against bugs or security vulnerabilities that lead to excessive memory usage or memory leaks. And rust achieves this memory safety due to its like innovative type system. Additionally, it doesn't allow for dangling pointers. And dangling pointers are the main classes of errors that lead to exploitable security vulnerabilities in languages like c plus plus. So Russ like helps meet that requirement of having no limits on ality, for example, because it's, we're also using the Russ implementation of Apache Arrow and this control over memory and also Russ Russ's packaging system called crates IO offers everything that you need out of the box to have features like AY and a weight to fix race conditions, to protection against buffering overflows and to ensure thread safe async cashing structures as well. So essentially it's just like has all the control, all the fine grain control, you need to take advantage of memory and all your resources as well as possible so that you can handle those really, really high ity use cases. >>Yeah, and the more I learn about the, the new engine and, and the platform IOCs et cetera, you know, you, you see things like, you know, the old days not even to even today you do a lot of garbage collection in these, in these systems and there's an inverse, you know, impact relative to performance. So it looks like you really, you know, the community is modernizing the platform, but I wanna talk about Apache Arrow for a moment. It it's designed to address the constraints that are associated with analyzing large data sets. We, we know that, but please explain why, what, what is Arrow and and what does it bring to Influx db? >>Sure, yeah. So Arrow is a, a framework for defining in memory calmer data. And so much of the efficiency and performance of IOx comes from taking advantage of calmer data structures. And I will, if you don't mind, take a moment to kind of of illustrate why column or data structures are so valuable. Let's pretend that we are gathering field data about the temperature in our room and also maybe the temperature of our stove. And in our table we have those two temperature values as well as maybe a measurement value, timestamp value, maybe some other tag values that describe what room and what house, et cetera we're getting this data from. And so you can picture this table where we have like two rows with the two temperature values for both our room and the stove. Well usually our room temperature is regulated so those values don't change very often. >>So when you have calm oriented st calm oriented storage, essentially you take each row, each column and group it together. And so if that's the case and you're just taking temperature values from the room and a lot of those temperature values are the same, then you'll, you might be able to imagine how equal values will then enable each other and when they neighbor each other in the storage format, this provides a really perfect opportunity for cheap compression. And then this cheap compression enables high cardinality use cases. It also enables for faster scan rates. So if you wanna define like the men and max value of the temperature in the room across a thousand different points, you only have to get those a thousand different points in order to answer that question and you have those immediately available to you. But let's contrast this with a row oriented storage solution instead so that we can understand better the benefits of calmer oriented storage. >>So if you had a row oriented storage, you'd first have to look at every field like the temperature in, in the room and the temperature of the stove. You'd have to go across every tag value that maybe describes where the room is located or what model the stove is. And every timestamp you'd then have to pluck out that one temperature value that you want at that one time stamp and do that for every single row. So you're scanning across a ton more data and that's why Rowe Oriented doesn't provide the same efficiency as calmer and Apache Arrow is in memory calmer data, commoner data fit framework. So that's where a lot of the advantages come >>From. Okay. So you basically described like a traditional database, a row approach, but I've seen like a lot of traditional database say, okay, now we've got, we can handle colo format versus what you're talking about is really, you know, kind of native i, is it not as effective? Is the, is the foreman not as effective because it's largely a, a bolt on? Can you, can you like elucidate on that front? >>Yeah, it's, it's not as effective because you have more expensive compression and because you can't scan across the values as quickly. And so those are, that's pretty much the main reasons why, why RO row oriented storage isn't as efficient as calm, calmer oriented storage. Yeah. >>Got it. So let's talk about Arrow Data Fusion. What is data fusion? I know it's written in Rust, but what does it bring to the table here? >>Sure. So it's an extensible query execution framework and it uses Arrow as it's in memory format. So the way that it helps in influx DB IOCs is that okay, it's great if you can write unlimited amount of cardinality into influx Cbis, but if you don't have a query engine that can successfully query that data, then I don't know how much value it is for you. So Data fusion helps enable the, the query process and transformation of that data. It also has a PANDAS API so that you could take advantage of PANDAS data frames as well and all of the machine learning tools associated with Pandas. >>Okay. You're also leveraging Par K in the platform cause we heard a lot about Par K in the middle of the last decade cuz as a storage format to improve on Hadoop column stores. What are you doing with Parque and why is it important? >>Sure. So parque is the column oriented durable file format. So it's important because it'll enable bulk import, bulk export, it has compatibility with Python and Pandas, so it supports a broader ecosystem. Par K files also take very little disc disc space and they're faster to scan because again, they're column oriented in particular, I think PAR K files are like 16 times cheaper than CSV files, just as kind of a point of reference. And so that's essentially a lot of the, the benefits of par k. >>Got it. Very popular. So and he's, what exactly is influx data focusing on as a committer to these projects? What is your focus? What's the value that you're bringing to the community? >>Sure. So Influx DB first has contributed a lot of different, different things to the Apache ecosystem. For example, they contribute an implementation of Apache Arrow and go and that will support clearing with flux. Also, there has been a quite a few contributions to data fusion for things like memory optimization and supportive additional SQL features like support for timestamp, arithmetic and support for exist clauses and support for memory control. So yeah, Influx has contributed a a lot to the Apache ecosystem and continues to do so. And I think kind of the idea here is that if you can improve these upstream projects and then the long term strategy here is that the more you contribute and build those up, then the more you will perpetuate that cycle of improvement and the more we will invest in our own project as well. So it's just that kind of symbiotic relationship and appreciation of the open source community. >>Yeah. Got it. You got that virtuous cycle going, the people call the flywheel. Give us your last thoughts and kind of summarize, you know, where what, what the big takeaways are from your perspective. >>So I think the big takeaway is that influx data is doing a lot of really exciting things with Influx DB IOx and I really encourage, if you are interested in learning more about the technologies that Influx is leveraging to produce IOCs, the challenges associated with it and all of the hard work questions and you just wanna learn more, then I would encourage you to go to the monthly Tech talks and community office hours and they are on every second Wednesday of the month at 8:30 AM Pacific time. There's also a community forums and a community Slack channel look for the influx DDB unders IAC channel specifically to learn more about how to join those office hours and those monthly tech tech talks as well as ask any questions they have about iacs, what to expect and what you'd like to learn more about. I as a developer advocate, I wanna answer your questions. So if there's a particular technology or stack that you wanna dive deeper into and want more explanation about how INFLUX DB leverages it to build IOCs, I will be really excited to produce content on that topic for you. >>Yeah, that's awesome. You guys have a really rich community, collaborate with your peers, solve problems, and, and you guys super responsive, so really appreciate that. All right, thank you so much Anise for explaining all this open source stuff to the audience and why it's important to the future of data. >>Thank you. I really appreciate it. >>All right, you're very welcome. Okay, stay right there and in a moment I'll be back with Tim Yoakum, he's the director of engineering for Influx Data and we're gonna talk about how you update a SAS engine while the plane is flying at 30,000 feet. You don't wanna miss this. >>I'm really glad that we went with InfluxDB Cloud for our hosting because it has saved us a ton of time. It's helped us move faster, it's saved us money. And also InfluxDB has good support. My name's Alex Nada. I am CTO at Noble nine. Noble Nine is a platform to measure and manage service level objectives, which is a great way of measuring the reliability of your systems. You can essentially think of an slo, the product we're providing to our customers as a bunch of time series. So we need a way to store that data and the corresponding time series that are related to those. The main reason that we settled on InfluxDB as we were shopping around is that InfluxDB has a very flexible query language and as a general purpose time series database, it basically had the set of features we were looking for. >>As our platform has grown, we found InfluxDB Cloud to be a really scalable solution. We can quickly iterate on new features and functionality because Influx Cloud is entirely managed, it probably saved us at least a full additional person on our team. We also have the option of running InfluxDB Enterprise, which gives us the ability to even host off the cloud or in a private cloud if that's preferred by a customer. Influx data has been really flexible in adapting to the hosting requirements that we have. They listened to the challenges we were facing and they helped us solve it. As we've continued to grow, I'm really happy we have influx data by our side. >>Okay, we're back with Tim Yokum, who is the director of engineering at Influx Data. Tim, welcome. Good to see you. >>Good to see you. Thanks for having me. >>You're really welcome. Listen, we've been covering open source software in the cube for more than a decade, and we've kind of watched the innovation from the big data ecosystem. The cloud has been being built out on open source, mobile, social platforms, key databases, and of course influx DB and influx data has been a big consumer and contributor of open source software. So my question to you is, where have you seen the biggest bang for the buck from open source software? >>So yeah, you know, influx really, we thrive at the intersection of commercial services and open, so open source software. So OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service from our core storage engine technologies to web services temping engines. Our, our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants and like you've mentioned, even better, we contribute a lot back to the projects that we use as well as our own product influx db. >>You know, but I gotta ask you, Tim, because one of the challenge that that we've seen in particular, you saw this in the heyday of Hadoop, the, the innovations come so fast and furious and as a software company you gotta place bets, you gotta, you know, commit people and sometimes those bets can be risky and not pay off well, how have you managed this challenge? >>Oh, it moves fast. Yeah, that, that's a benefit though because it, the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we, what we tend to do is, is we fail fast and fail often. We try a lot of things. You know, you look at Kubernetes for example, that ecosystem is driven by thousands of intelligent developers, engineers, builders, they're adding value every day. So we have to really keep up with that. And as the stack changes, we, we try different technologies, we try different methods, and at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's, it's something that we just do every day. >>So we have a survey partner down in New York City called Enterprise Technology Research etr, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes is one of the areas that has kind of, it's been off the charts and seen the most significant adoption and velocity particularly, you know, along with cloud. But, but really Kubernetes is just, you know, still up until the right consistently even with, you know, the macro headwinds and all, all of the stuff that we're sick of talking about. But, so what are you doing with Kubernetes in the platform? >>Yeah, it, it's really central to our ability to run the product. When we first started out, we were just on AWS and, and the way we were running was, was a little bit like containers junior. Now we're running Kubernetes everywhere at aws, Azure, Google Cloud. It allows us to have a consistent experience across three different cloud providers and we can manage that in code so our developers can focus on delivering services, not trying to learn the intricacies of Amazon, Azure, and Google and figure out how to deliver services on those three clouds with all of their differences. >>Just to follow up on that, is it, no. So I presume it's sounds like there's a PAs layer there to allow you guys to have a consistent experience across clouds and out to the edge, you know, wherever is that, is that correct? >>Yeah, so we've basically built more or less platform engineering, This is the new hot phrase, you know, it, it's, Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on and they only have to learn one way of deploying their application, managing their application. And so that, that just gets all of the underlying infrastructure out of the way and, and lets them focus on delivering influx cloud. >>Yeah, and I know I'm taking a little bit of a tangent, but is that, that, I'll call it a PAs layer if I can use that term. Is that, are there specific attributes to Influx db or is it kind of just generally off the shelf paths? You know, are there, is, is there any purpose built capability there that, that is, is value add or is it pretty much generic? >>So we really build, we, we look at things through, with a build versus buy through a, a build versus by lens. Some things we want to leverage cloud provider services, for instance, Postgres databases for metadata, perhaps we'll get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can, can deliver on that has consistency that is, is all generated from code that we can as a, as an SRE group, as an ops team, that we can manage with very few people really, and we can stamp out clusters across multiple regions and in no time. >>So how, so sometimes you build, sometimes you buy it. How do you make those decisions and and what does that mean for the, for the platform and for customers? >>Yeah, so what we're doing is, it's like everybody else will do, we're we're looking for trade offs that make sense. You know, we really want to protect our customers data. So we look for services that support our own software with the most uptime, reliability, and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team. And of course for customers you don't even see that, but we don't want to try to reinvent the wheel, like I had mentioned with SQL data stores for metadata, perhaps let's build on top of what of these three large cloud providers have already perfected. And we can then focus on our platform engineering and we can have our developers then focus on the influx data, software, influx, cloud software. >>So take it to the customer level, what does it mean for them? What's the value that they're gonna get out of all these innovations that we've been been talking about today and what can they expect in the future? >>So first of all, people who use the OSS product are really gonna be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you, but then you want to scale up. We have some 270 terabytes of data across, over 4 billion series keys that people have stored. So there's a proven ability to scale now in terms of the open source, open source software and how we've developed the platform. You're getting highly available high cardinality time series platform. We manage it and, and really as, as I mentioned earlier, we can keep up with the state of the art. We keep reinventing, we keep deploying things in real time. We deploy to our platform every day repeatedly all the time. And it's that continuous deployment that allows us to continue testing things in flight, rolling things out that change new features, better ways of doing deployments, safer ways of doing deployments. >>All of that happens behind the scenes. And like we had mentioned earlier, Kubernetes, I mean that, that allows us to get that done. We couldn't do it without having that platform as a, as a base layer for us to then put our software on. So we, we iterate quickly. When you're on the, the Influx cloud platform, you really are able to, to take advantage of new features immediately. We roll things out every day and as those things go into production, you have, you have the ability to, to use them. And so in the end we want you to focus on getting actual insights from your data instead of running infrastructure, you know, let, let us do that for you. So, >>And that makes sense, but so is the, is the, are the innovations that we're talking about in the evolution of Influx db, do, do you see that as sort of a natural evolution for existing customers? I, is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >>Yeah, it really is it, it's a little bit of both. Any engineer will say, well, it depends. So cloud native technologies are, are really the hot thing. Iot, industrial iot especially, people want to just shove tons of data out there and be able to do queries immediately and they don't wanna manage infrastructure. What we've started to see are people that use the cloud service as their, their data store backbone and then they use edge computing with R OSS product to ingest data from say, multiple production lines and downsample that data, send the rest of that data off influx cloud where the heavy processing takes place. So really us being in all the different clouds and iterating on that and being in all sorts of different regions allows for people to really get out of the, the business of man trying to manage that big data, have us take care of that. And of course as we change the platform end users benefit from that immediately. And, >>And so obviously taking away a lot of the heavy lifting for the infrastructure, would you say the same thing about security, especially as you go out to IOT and the Edge? How should we be thinking about the value that you bring from a security perspective? >>Yeah, we take, we take security super seriously. It, it's built into our dna. We do a lot of work to ensure that our platform is secure, that the data we store is, is kept private. It's of course always a concern. You see in the news all the time, companies being compromised, you know, that's something that you can have an entire team working on, which we do to make sure that the data that you have, whether it's in transit, whether it's at rest, is always kept secure, is only viewable by you. You know, you look at things like software, bill of materials, if you're running this yourself, you have to go vet all sorts of different pieces of software. And we do that, you know, as we use new tools. That's something that, that's just part of our jobs to make sure that the platform that we're running it has, has fully vetted software and, and with open source especially, that's a lot of work. And so it's, it's definitely new territory. Supply chain attacks are, are definitely happening at a higher clip than they used to, but that is, that is really just part of a day in the, the life for folks like us that are, are building platforms. >>Yeah, and that's key. I mean especially when you start getting into the, the, you know, we talk about IOT and the operations technologies, the engineers running the, that infrastructure, you know, historically, as you know, Tim, they, they would air gap everything. That's how they kept it safe. But that's not feasible anymore. Everything's >>That >>Connected now, right? And so you've gotta have a partner that is again, take away that heavy lifting to r and d so you can focus on some of the other activities. Right. Give us the, the last word and the, the key takeaways from your perspective. >>Well, you know, from my perspective I see it as, as a a two lane approach with, with influx, with Anytime series data, you know, you've got a lot of stuff that you're gonna run on-prem, what you had mentioned, air gaping. Sure there's plenty of need for that, but at the end of the day, people that don't want to run big data centers, people that want torus their data to, to a company that's, that's got a full platform set up for them that they can build on, send that data over to the cloud, the cloud is not going away. I think more hybrid approach is, is where the future lives and that's what we're prepared for. >>Tim, really appreciate you coming to the program. Great stuff. Good to see you. >>Thanks very much. Appreciate it. >>Okay, in a moment I'll be back to wrap up. Today's session, you're watching The Cube. >>Are you looking for some help getting started with InfluxDB Telegraph or Flux Check >>Out Influx DB University >>Where you can find our entire catalog of free training that will help you make the most of your time series data >>Get >>Started for free@influxdbu.com. >>We'll see you in class. >>Okay, so we heard today from three experts on time series and data, how the Influx DB platform is evolving to support new ways of analyzing large data sets very efficiently and effectively in real time. And we learned that key open source components like Apache Arrow and the Rust Programming environment Data fusion par K are being leveraged to support realtime data analytics at scale. We also learned about the contributions in importance of open source software and how the Influx DB community is evolving the platform with minimal disruption to support new workloads, new use cases, and the future of realtime data analytics. Now remember these sessions, they're all available on demand. You can go to the cube.net to find those. Don't forget to check out silicon angle.com for all the news related to things enterprise and emerging tech. And you should also check out influx data.com. There you can learn about the company's products. You'll find developer resources like free courses. You could join the developer community and work with your peers to learn and solve problems. And there are plenty of other resources around use cases and customer stories on the website. This is Dave Valante. Thank you for watching Evolving Influx DB into the smart data platform, made possible by influx data and brought to you by the Cube, your leader in enterprise and emerging tech coverage.

(upbeat music) >> Okay, we're back with Tim Yoakum, who is the Director of Engineering at Influx Data. Tim, welcome. Good to see you. >> Good to see you. Thanks for having me. >> You're really welcome. Listen, we've been covering open source software on the Cube for more than a decade, and we've kind of watched the innovation from the big data ecosystem, the cloud is being built out on open source, mobile social platforms, key databases, and of course Influx DB, and Influx Data has been a big consumer and contributor of open source software. So my question to you is where have you seen the biggest bang for the buck from open source software? >> So, yeah, you know, Influx, really, we thrive at the intersection of commercial services and open source software. So OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service, from our core storage engine technologies to web services, templating engines. Our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants. And like you've mentioned, even better, we contribute a lot back to the projects that we use as well as our own product, Influx DB. >> You know, but I got to ask you, Tim, because one of the challenge that we've seen, in particular, you saw this in the heyday of Hadoop. The innovations come so fast and furious, and as a software company, you got to place bets, you got to, you know, commit people, and sometimes those bets can be risky and not pay off. How have you managed this challenge? >> Oh, it moves fast, yeah. That's a benefit though, because the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we tend to do is we fail fast and fail often. We try a lot of things. You know, you look at Kubernetes for example. That ecosystem is driven by thousands of intelligent developers, engineers, builders. They're adding value every day. So we have to really keep up with that. And as the stack changes, we try different technologies, we try different methods, and at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's something that we just do every day. >> So we have a survey partner down in New York City called Enterprise Technology Research, ETR, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes, is one of the areas that has kind of, it's been off the charts and seen the most significant adoption and velocity, particularly, you know, along with cloud. But really Kubernetes is just, you know, still up and to the right consistently, even with, you know the macro headwinds and all of the other stuff that we're sick of talking about. So what are you doing with Kubernetes in the platform? >> Yeah, it's really central to our ability to run the product. When we first started out, we were just on AWS, and the way we were running was a little bit like containers junior. Now we're running Kubernetes everywhere, at AWS, Azure, Google Cloud. It allows us to have a consistent experience across three different cloud providers, and we can manage that in code. So our developers can focus on delivering services, not trying to learn the intricacies of Amazon, Azure, and Google, and figure out how to deliver services on those three clouds with all of their differences. >> Just a follow up on that, is it, now, so I presume it sounds like there's a PaaS layer there to allow you guys to have a consistent experience across clouds and up to the edge, you know, wherever. Is that, is that correct? >> Yeah, so we've basically built, more or less, platform engineering. This is the new hot phrase. You know, Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on, and they only have to learn one way of deploying their application, managing their application. And so that just gets all of the underlying infrastructure out of the way and lets them focus on delivering Influx Cloud. >> Yeah, and I know I'm taking a little bit of a tangent, but is that, I'll call it a PaaS layer if I can use that term, are there specific attributes to Influx DB, or is it kind of just generally off the shelf PaaS? You know, is there any purpose built capability there that is value add, or is it pretty much generic? >> So we really build, we look at things with a build versus buy, through a build versus buy lens. Some things we want to leverage, cloud provider services for instance, Postgres databases for metadata perhaps, get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can deliver on, that has consistency, that is all generated from code that we can, as an SRE group, as an ops team, that we can manage with very few people really, and we can stamp out clusters across multiple regions in no time. >> So how, so sometimes you build, sometimes you buy it. How do you make those decisions, and what does that mean for the platform and for customers? >> Yeah, so what we're doing is, it's like everybody else will do. We're looking for trade offs that make sense. You know, we really want to protect our customers' data. So we look for services that support our own software with the most uptime, reliability, and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team. And of course for customers, you don't even see that, but we don't want to try to reinvent the wheel. Like I had had mentioned with SQL data storage for metadata perhaps. Let's build on top of what these three large cloud providers have already perfected, and we can then focus on our platform engineering, and we can have our developers then focus on the Influx Data software, Influx Cloud software. >> So take it to the customer level. What does it mean for them? What's the value that they're going to get out of all these innovations that we've been been talking about today? And what can they expect in the future? >> So first of all, people who use the OSS product are really going to be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you. But then you want to scale up. We have some 270 terabytes of data across over 4 billion series keys that people have stored. So there's a proven ability to scale. Now, in terms of the open source software, and how we've developed the platform, you're getting highly available, high cardinality time series platform. We manage it, and really as I mentioned earlier, we can keep up with the state of the art. We keep reinventing. We keep deploying things in real time. We deploy to our platform every day repeatedly, all the time. And it's that continuous deployment that allows us to continue testing things in flight, rolling things out that change, new features, better ways of doing deployments, safer ways of doing deployments. All of that happens behind the scenes. And we had mentioned earlier Kubernetes, I mean that allows us to get that done. We couldn't do it without having that platform as a base layer for us to then put our software on. So we iterate quickly. When you're on the Influx Cloud platform, you really are able to take advantage of new features immediately. We roll things out every day. And as those things go into production, you have the ability to use them. And so in the end, we want you to focus on getting actionable insights from your data instead of running infrastructure. You know, let us do that for you. >> And that makes sense, but so is the, are the innovations that we're talking about in the evolution of Influx DB, do you see that as sort of a natural evolution for existing customers? Is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >> Yeah, it really is. It's a little bit of both. Any engineer will say, well, it depends. So cloud native technologies are really the hot thing. IoT, industrial IoT especially, people want to just shove tons of data out there and be able to do queries immediately, and they don't want to manage infrastructure. What we've started to see are people that use the cloud service as their data store backbone, and then they use edge computing with our OSS product to ingest data from say multiple production lines and down-sample that data, send the rest of that data off to Influx Cloud where the heavy processing takes place. So really us being in all the different clouds and iterating on that, and being in all sorts of different regions allows for people to really get out of the business of trying to manage that big data, have us take care of that. And of course, as we change the platform, end users benefit from that immediately. >> And so obviously, taking away a lot of the heavy lifting for the infrastructure, would you say the same thing about security, especially as you go out to IoT and the edge? How should we be thinking about the value that you bring from a security perspective? >> Yeah, we take security super seriously. It's built into our DNA. We do a lot of work to ensure that our platform is secure, that the data we store is kept private. It's of course always a concern. You see in the news all the time companies being compromised. You know, that's something that you can have an entire team working on, which we do, to make sure that the data that you have, whether it's in transit, whether it's at rest, is always kept secure, is only viewable by you. You look at things like software bill of materials. If you're running this yourself, you have to go vet all sorts of different pieces of software. And we do that, you know, as we use new tools. That's something that's just part of our jobs, to make sure that the platform that we're running has fully vetted software. And with open source especially, that's a lot of work. And so it's definitely new territory. Supply chain attacks are definitely happening at a higher clip than they used to. But that is really just part of a day in the life for folks like us that are building platforms. >> Yeah, and that's key. I mean, especially when you start getting into the, you know, we talk about IoT and the operations technologies, the engineers running that infrastructure. You know, historically, as you know, Tim, they would air gap everything. That's how they kept it safe. But that's not feasible anymore. Everything's >> Can't do that. >> connected now, right? And so you've got to have a partner that is, again, take away that heavy lifting to R and D so you can focus on some of the other activities. All right. Give us the last word and the key takeaways from your perspective. >> Well, you know, from my perspective, I see it as a a two lane approach. With Influx, with any any time series data, you know, you've got a lot of stuff that you're going to run on-prem. What you mentioned, air gaping, sure there's plenty of need for that, but at the end of the day, people that don't want to run big data centers, people that want to entrust their data to a company that's got a full platform set up for them that they can build on, send that data over to the cloud. The cloud is not going away. I think a more hybrid approach is where the future lives, and that's what we're prepared for. >> Tim, really appreciate you coming to the program. Great stuff. Good to see you. >> Thanks very much. Appreciate it. >> Okay, in a moment, I'll be back to wrap up today's session. You're watching the Cube. (gentle music)

[Music] the cyber security landscape has changed dramatically over the past 24 to 36 months rapid cloud migration has created a new layer of security defense sure but that doesn't mean csos can relax in many respects it further complicates or at least changes the cso's scope of responsibilities in particular the threat surface has expanded and that creates more seams and csos have to make sure their teams pick up where the hyperscaler clouds leave off application developers have become a critical execution point for cyber assurance shift left is the kind of new buzz phrase for devs but organizations still have to shield right meaning the operational teams must continue to partner with secops to make sure infrastructure is resilient so it's no wonder that an etr's latest survey of nearly 1500 cios and it buyers that business technology executives cite security as their number one priority well ahead of other critical technology initiatives including collaboration software cloud computing and analytics rounding out the top four but budgets are under pressure and csos have to prioritize it's not like they have an open checkbook they have to contend with other key initiatives like those just mentioned to secure the funding and what about zero trust can you go out and buy zero trust or is it a framework a mindset in a series of best practices applied to create a security consciousness throughout the organization can you implement zero trust in other words if a machine or human is not explicitly allowed access then access is denied can you implement that policy without constricting organizational agility the question is what's the most practical way to apply that premise and what role does infrastructure play as the enforcer how does automation play in the equation the fact is that today's approach to cyber resilient type resilience can't be an either or it has to be an and conversation meaning you have to ensure data protection while at the same time advancing the mission of the organization with as little friction as possible and don't even talk to me about the edge that's really going to keep you up at night hello and welcome to the special cube presentation a blueprint for trusted infrastructure made possible by dell technologies in this program we explore the critical role that trusted infrastructure plays in cyber security strategies how organizations should think about the infrastructure side of the cyber security equation and how dell specifically approaches securing infrastructure for your business we'll dig into what it means to transform and evolve toward a modern security infrastructure that's both trusted and agile first up are pete gear and steve kenniston they're both senior cyber security consultants at dell technologies and they're going to talk about the company's philosophy and approach to trusted infrastructure and then we're going to speak to paris our godaddy who's a senior consultant for storage at dell technologies to understand where and how storage plays in this trusted infrastructure world and then finally rob emsley who heads product marketing for data protection and cyber security he's going to take a deeper dive with rob into data protection and explain how it has become a critical component of a comprehensive cyber security strategy okay let's get started pete gear steve kenniston welcome to the cube thanks for coming into the marlboro studios today great to be here dave thanks dave good to see you great to see you guys pete start by talking about the security landscape you heard my little rap up front what are you seeing i thought you wrapped it up really well and you touched on all the key points right technology is ubiquitous today it's everywhere it's no longer confined to a monolithic data center it lives at the edge it lives in front of us it lives in our pockets and smartphones along with that is data and as you said organizations are managing sometimes 10 to 20 times the amount of data that they were just five years ago and along with that cyber crime has become a very profitable uh enterprise in fact it's been more than 10 years since uh the nsa chief actually called cybercrime the biggest transfer of wealth in history that was 10 years ago and we've seen nothing but accelerating cybercrime and really sophistication of how those attacks are are perpetrated and so the new security landscape is really more of an evolution we're finally seeing security catch up with all of the technology adoption all the build out the work from home and work from anywhere that we've seen over the last couple of years we're finally seeing organizations and really it goes beyond the i.t directors it's a board level discussion today security's become a board level discussion so yeah i think that's true as well it's like it used to be the security was okay the sec ops team you're responsible for security now you've got the developers are involved the business lines are involved it's part of onboarding for most companies you know steve this concept of zero trust it was kind of a buzzword before the pandemic and i feel like i've often said it's now become a a mandate but it's it's it's still fuzzy to a lot of people how do you guys think about zero trust what does it mean to you how does it fit yeah i thought again i thought your opening was fantastic in this whole lead into to what is zero trust it had been a buzzword for a long time and now ever since the federal government came out with their implementation or or desire to drive zero trust a lot more people are taking a lot more seriously because i don't think they've seen the government do this but ultimately let's see ultimately it's just like you said right if you don't have trust to those particular devices applications or data you can't get at it the question is and and you phrase it perfectly can you implement that as well as allow the business to be as agile as it needs to be in order to be competitive because we're seeing with your whole notion around devops and the ability to kind of build make deploy build make deploy right they still need that functionality but it also needs to be trusted it needs to be secure and things can't get away from you yeah so it's interesting we attended every uh reinforce since 2019 and the narrative there is hey everything in this in the cloud is great you know and this narrative around oh security is a big problem is you know doesn't help the industry the fact is that the big hyperscalers they're not strapped for talent but csos are they don't have the the capabilities to really apply all these best practices they're they're playing whack-a-mole so they look to companies like yours to take their your r d and bake it into security products and solutions so what are the critical aspects of the so-called dell trusted infrastructure that we should be thinking about yeah well dell trusted infrastructure for us is a way for us to describe uh the the work that we do through design development and even delivery of our it system so dell trusted infrastructure includes our storage it includes our servers our networking our data protection our hyper-converged everything that infrastructure always has been it's just that today customers consume that infrastructure at the edge as a service in a multi-cloud environment i mean i view the cloud as really a way for organizations to become more agile and to become more flexible and also to control costs i don't think organizations move to the cloud or move to a multi-cloud environment to enhance security so i don't see cloud computing as a panacea for security i see it as another attack surface and another uh aspect in front that organizations and and security organizations and departments have to manage it's part of their infrastructure today whether it's in their data center in a cloud or at the edge i mean i think it's a huge point because a lot of people think oh the data's in the cloud i'm good it's like steve we've talked about oh why do i have to back up my data it's in the cloud well you might have to recover it someday so i don't know if you have anything to add to that or any additional thoughts on it no i mean i think i think like what pete was saying when it comes to when it comes to all these new vectors for attack surfaces you know people did choose the cloud in order to be more agile more flexible and all that did was open up to the csos who need to pay attention to now okay where can i possibly be attacked i need to be thinking about is that secure and part of the part of that is dell now also understands and thinks about as we're building solutions is it is it a trusted development life cycle so we have our own trusted development life cycle how many times in the past did you used to hear about vendors saying you got to patch your software because of this we think about what changes to our software and what implementations and what enhancements we deliver can actually cause from a security perspective and make sure we don't give up or or have security become a whole just in order to implement a feature we got to think about those things yeah and as pete alluded to our secure supply chain so all the way through knowing what you're going to get when you actually receive it is going to be secure and not be tampered with becomes vitally important and pete and i were talking earlier when you have tens of thousands of devices that need to be delivered whether it be storage or laptops or pcs or or whatever it is you want to be tr you want to know that that that those devices are can be trusted okay guys maybe pete you could talk about the how dell thinks about it's its framework and its philosophy of cyber security and then specifically what dell's advantages are relative to the competition yeah definitely dave thank you so i we've talked a lot about dell as a technology provider but one thing dell also is is a partner in this larger ecosystem we realize that security whether it's a zero trust paradigm or any other kind of security environment is an ecosystem with a lot of different vendors so we look at three areas uh one is protecting data in systems we know that it starts with and ends with data that helps organizations combat threats across their entire infrastructure and what it means is dell's embedding security features consistently across our portfolios of storage servers networking the second is enhancing cyber resiliency over the last decade a lot of the funding and spending has been in protecting or trying to prevent cyber threats not necessarily in responding to and recovering from threats right we call that resiliency organizations need to build resiliency across their organization so not only can they withstand a threat but they can respond recover and continue with their operations and the third is overcoming security complexity security is hard it's more difficult because of the the things we've talked about about distributed data distributed technology and and attack surfaces everywhere and so we're enabling organizations to scale confidently to continue their business but know that all all the i.t decisions that they're making um have these intrinsic security features and are built and delivered in a consistent security so those are kind of the three pillars maybe we could end on what you guys see as the key differentiators uh that people should know about that that dell brings to the table maybe each of you could take take a shot at that yeah i i think first of all from from a holistic portfolio perspective right the secure supply chain and the secure development life cycle permeate through everything dell does when building things so we build things with security in mind all the way from as pete mentioned from from creation to delivery we want to make sure you have that that secure device or or asset that permeates everything from servers networking storage data protection through hyper converge through everything that to me is really a key asset because that means you can you understand when you receive something it's a trusted piece of your infrastructure i think the other core component to think about and pete mentioned as dell being a partner for um making sure you can deliver these things is that even though those are that's part of our framework these pillars are our framework of how we want to deliver security it's also important to understand that we are partners and that you don't need to rip and replace but as you start to put in new components you can be you can be assured that the components that you're replacing as you're evolving as you're growing as you're moving to the cloud as you're moving to more on-prem type services or whatever that your environment is secure i think those are two key things got it okay pete bring us home yeah i think one of one of the big advantages of dell uh is our scope and our scale right we're a large technology vendor that's been around for decades and we develop and sell almost every piece of technology we also know that organizations are might make different decisions and so we have a large services organization with a lot of experienced services people that can help customers along their security journey depending on uh whatever type of infrastructure or solutions that they're looking at the other thing we do is make it very easy to consume our technology whether that's traditional on-premise in a multi-cloud environment uh or as a service and so the best of breed technology can be consumed in any variety of fashion and know that you're getting that consistent secure infrastructure that dell provides well and dell's forgot the probably top supply chain not only in the tech business but probably any business and so you can actually take take your dog food and then and allow other your champagne sorry allow other people to you know share share best practices with your with your customers all right guys thanks so much for coming thank you appreciate it okay keep it right there after this short break we'll be back to drill into the storage domain you're watching a blueprint for trusted infrastructure on the cube the leader in enterprise and emerging tech coverage be right back you

the cyber security landscape has changed dramatically over the past 24 to 36 months rapid cloud migration has created a new layer of security defense sure but that doesn't mean csos can relax in many respects it further complicates or at least changes the ciso's scope of responsibilities in particular the threat surface has expanded and that creates more seams and cisos have to make sure their teams pick up where the hyperscaler clouds leave off application developers have become a critical execution point for cyber assurance shift left is the kind of new buzz phrase for devs but organizations still have to shield right meaning the operational teams must continue to partner with secops to make sure infrastructure is resilient so it's no wonder that in etr's latest survey of nearly 1500 cios and it buyers that business technology executives cite security as their number one priority well ahead of other critical technology initiatives including collaboration software cloud computing and analytics rounding out the top four but budgets are under pressure and csos have to prioritize it's not like they have an open checkbook they have to contend with other key initiatives like those just mentioned to secure the funding and what about zero trust can you go out and buy xero trust or is it a framework a mindset in a series of best practices applied to create a security consciousness throughout the organization can you implement zero trust in other words if a machine or human is not explicitly allowed access then access is denied can you implement that policy without constricting organizational agility the question is what's the most practical way to apply that premise and what role does infrastructure play as the enforcer how does automation play in the equation the fact is that today's approach to cyber resilient type resilience can't be an either or it has to be an and conversation meaning you have to ensure data protection while at the same time advancing the mission of the organization with as little friction as possible and don't even talk to me about the edge that's really going to keep you up at night hello and welcome to the special cube presentation a blueprint for trusted infrastructure made possible by dell technologies in this program we explore the critical role that trusted infrastructure plays in cyber security strategies how organizations should think about the infrastructure side of the cyber security equation and how dell specifically approaches securing infrastructure for your business we'll dig into what it means to transform and evolve toward a modern security infrastructure that's both trusted and agile first up are pete gear and steve kenniston they're both senior cyber security consultants at dell technologies and they're going to talk about the company's philosophy and approach to trusted infrastructure and then we're going to speak to paris arcadi who's a senior consultant for storage at dell technologies to understand where and how storage plays in this trusted infrastructure world and then finally rob emsley who heads product marketing for data protection and cyber security he's going to take a deeper dive with rob into data protection and explain how it has become a critical component of a comprehensive cyber security strategy okay let's get started pete gear steve kenniston welcome to the cube thanks for coming into the marlboro studios today great to be here dave thanks dave good to see you great to see you guys pete start by talking about the security landscape you heard my little rap up front what are you seeing i thought you wrapped it up really well and you touched on all the key points right technology is ubiquitous today it's everywhere it's no longer confined to a monolithic data center it lives at the edge it lives in front of us it lives in our pockets and smartphones along with that is data and as you said organizations are managing sometimes 10 to 20 times the amount of data that they were just five years ago and along with that cyber crime has become a very profitable enterprise in fact it's been more than 10 years since uh the nsa chief actually called cyber crime the biggest transfer of wealth in history that was 10 years ago and we've seen nothing but accelerating cyber crime and really sophistication of how those attacks are perpetrated and so the new security landscape is really more of an evolution we're finally seeing security catch up with all of the technology adoption all the build out the work from home and work from anywhere that we've seen over the last couple of years we're finally seeing organizations and really it goes beyond the i t directors it's a board level discussion today security's become a board level discussion yeah i think that's true as well it's like it used to be the security was okay the secops team you're responsible for security now you've got the developers are involved the business lines are involved it's part of onboarding for most companies you know steve this concept of zero trust it was kind of a buzzword before the pandemic and i feel like i've often said it's now become a mandate but it's it's it's still fuzzy to a lot of people how do you guys think about zero trust what does it mean to you how does it fit yeah i thought again i thought your opening was fantastic in in this whole lead into to what is zero trust it had been a buzzword for a long time and now ever since the federal government came out with their implementation or or desire to drive zero trust a lot more people are taking a lot more seriously because i don't think they've seen the government do this but ultimately let's see ultimately it's just like you said right if if you don't have trust to those particular devices uh applications or data you can't get at it the question is and and you phrase it perfectly can you implement that as well as allow the business to be as agile as it needs to be in order to be competitive because we're seeing with your whole notion around devops and the ability to kind of build make deploy build make deploy right they still need that functionality but it also needs to be trusted it needs to be secure and things can't get away from you yeah so it's interesting we attended every uh reinforce since 2019 and the narrative there is hey everything in this in the cloud is great you know and this narrative around oh security is a big problem is you know doesn't help the industry the fact is that the big hyperscalers they're not strapped for talent but csos are they don't have the the capabilities to really apply all these best practices they're they're playing whack-a-mole so they look to companies like yours to take their r your r d and bake it into security products and solutions so what are the critical aspects of the so-called dell trusted infrastructure that we should be thinking about yeah well dell trusted infrastructure for us is a way for us to describe uh the the work that we do through design development and even delivery of our it system so dell trusted infrastructure includes our storage it includes our servers our networking our data protection our hyper converged everything that infrastructure always has been it's just that today customers consume that infrastructure at the edge as a service in a multi-cloud environment i mean i view the cloud as really a way for organizations to become more agile and to become more flexible and also to control costs i don't think organizations move to the cloud or move to a multi-cloud environment to enhance security so i don't see cloud computing as a panacea for security i see it as another attack surface and another uh aspect in front that organizations and and security organizations and departments have to manage it's part of their infrastructure today whether it's in their data center in a cloud or at the edge i mean i think it's a huge point because a lot of people think oh data's in the cloud i'm good it's like steve we've talked about oh why do i have to back up my data it's in the cloud well you might have to recover it someday so i don't know if you have anything to add to that or any additional thoughts on it no i mean i think i think like what pete was saying when it comes to when it comes to all these new vectors for attack surfaces you know people did choose the cloud in order to be more agile more flexible and all that did was open up to the csos who need to pay attention to now okay where can i possibly be attacked i need to be thinking about is that secure and part of the part of that is dell now also understands and thinks about as we're building solutions is it is it a trusted development life cycle so we have our own trusted development life cycle how many times in the past did you used to hear about vendors saying you got to patch your software because of this we think about what changes to our software and what implementations and what enhancements we deliver can actually cause from a security perspective and make sure we don't give up or or have security become a whole just in order to implement a feature we got to think about those things yeah and as pete alluded to our secure supply chain so all the way through knowing what you're going to get when you actually receive it is going to be secure and not be tampered with becomes vitally important and pete and i were talking earlier when you have tens of thousands of devices that need to be delivered whether it be storage or laptops or pcs or or whatever it is you want to be you want to know that that that those devices are can be trusted okay guys maybe pete you could talk about the how dell thinks about it's its framework and its philosophy of cyber security and then specifically what dell's advantages are relative to the competition yeah definitely dave thank you so we've talked a lot about dell as a technology provider but one thing dell also is is a partner in this larger ecosystem we realize that security whether it's a zero trust paradigm or any other kind of security environment is an ecosystem uh with a lot of different vendors so we look at three areas one is protecting data in systems we know that it starts with and ends with data that helps organizations combat threats across their entire infrastructure and what it means is dell's embedding security features consistently across our portfolios of storage servers networking the second is enhancing cyber resiliency over the last decade a lot of the funding and spending has been in protecting or trying to prevent cyber threats not necessarily in responding to and recovering from threats right we call that resiliency organizations need to build resiliency across their organization so not only can they withstand a threat but they can respond recover and continue with their operations and the third is overcoming security complexity security is hard it's more difficult because of the things we've talked about about distributed data distributed technology and and attack surfaces everywhere and so we're enabling organizations to scale confidently to continue their business but know that all all the i.t decisions that they're making um have these intrinsic security features and are built and delivered in a consistent security so those are kind of the three pillars maybe we could end on what you guys see as the key differentiators that people should know about that that dell brings to the table maybe each of you could take take a shot at that yeah i think first of all from from a holistic portfolio perspective right the uh secure supply chain and the secure development life cycle permeate through everything dell does when building things so we build things with security in mind all the way from as pete mentioned from from creation to delivery we want to make sure you have that that secure device or or asset that permeates everything from servers networking storage data protection through hyper converge through everything that to me is really a key asset because that means you can you understand when you receive something it's a trusted piece of your infrastructure i think the other core component to think about and pete mentioned as dell being a partner for making sure you can deliver these things is that even though those are that's part of our framework these pillars are our framework of how we want to deliver security it's also important to understand that we are partners and that you don't need to rip and replace but as you start to put in new components you can be you can be assured that the components that you're replacing as you're evolving as you're growing as you're moving to the cloud as you're moving to a more on-prem type services or whatever that your environment is secure i think those are two key things got it okay pete bring us home yeah i think one of one of the big advantages of dell is our scope and our scale right we're a large technology vendor that's been around for decades and we develop and sell almost every piece of technology we also know that organizations are might make different decisions and so we have a large services organization with a lot of experienced services people that can help customers along their security journey depending on whatever type of infrastructure or solutions that they're looking at the other thing we do is make it very easy to consume our technology whether that's traditional on-premise in a multi-cloud environment uh or as a service and so the best of breed technology can be consumed in any variety of fashion and know that you're getting that consistent secure infrastructure that dell provides well and dell's forgot the probably top supply chain not only in the tech business but probably any business and so you can actually take take your dog food and then and allow other billionaire champagne sorry allow other people to you know share share best practices with your with your customers all right guys thanks so much for coming thank you appreciate it okay keep it right there after this short break we'll be back to drill into the storage domain you're watching a blueprint for trusted infrastructure on the cube the leader in enterprise and emerging tech coverage be right back concern over cyber attacks is now the norm for organizations of all sizes the impact of these attacks can be operationally crippling expensive and have long-term ramifications organizations have accepted the reality of not if but when from boardrooms to i.t departments and are now moving to increase their cyber security preparedness they know that security transformation is foundational to digital transformation and while no one can do it alone dell technologies can help you fortify with modern security modern security is built on three pillars protect your data and systems by modernizing your security approach with intrinsic features and hardware and processes from a provider with a holistic presence across the entire it ecosystem enhance your cyber resiliency by understanding your current level of resiliency for defending your data and preparing for business continuity and availability in the face of attacks overcome security complexity by simplifying and automating your security operations to enable scale insights and extend resources through service partnerships from advanced capabilities that intelligently scale a holistic presence throughout it and decades as a leading global technology provider we'll stop at nothing to help keep you secure okay we're back digging into trusted infrastructure with paris sarcadi he's a senior consultant for product marketing and storage at dell technologies parasaur welcome to the cube good to see you great to be with you dave yeah coming from hyderabad awesome so i really appreciate you uh coming on the program let's start with talking about your point of view on what cyber security resilience means to to dell generally but storage specifically yeah so for something like storage you know we are talking about the data layer name and if you look at cyber security it's all about securing your data applications and infrastructure it has been a very mature field at the network and application layers and there are a lot of great technologies right from you know enabling zero trust advanced authentications uh identity management systems and so on and and in fact you know with the advent of you know the the use of artificial intelligence and machine learning really these detection tools for cyber securities have really evolved in the network and the application spaces so for storage what it means is how can you bring them to the data layer right how can you bring you know the principles of zero trust to the data layer uh how can you leverage artificial intelligence and machine learning to look at you know access patterns and make intelligent decisions about maybe an indicator of a compromise and identify them ahead of time just like you know how it's happening and other ways of applications and when it comes to cyber resilience it's it's basically a strategy which assumes that a threat is imminent and it's a good assumption with the severity of the frequency of the attacks that are happening and the question is how do we fortify the infrastructure in the switch infrastructure to withstand those attacks and have a plan a response plan where we can recover the data and make sure the business continuity is not affected so that's uh really cyber security and cyber resiliency and storage layer and of course there are technologies like you know network isolation immutability and all these principles need to be applied at the storage level as well let me have a follow up on that if i may the intelligence that you talked about that ai and machine learning is that do you do you build that into the infrastructure or is that sort of a separate software module that that points at various you know infrastructure components how does that work both dave right at the data storage level um we have come with various data characteristics depending on the nature of data we developed a lot of signals to see what could be a good indicator of a compromise um and there are also additional applications like cloud iq is the best example which is like an infrastructure wide health monitoring system for dell infrastructure and now we have elevated that to include cyber security as well so these signals are being gathered at cloud iq level and other applications as well so that we can make those decisions about compromise and we can either cascade that intelligence and alert stream upstream for uh security teams um so that they can take actions in platforms like sign systems xtr systems and so on but when it comes to which layer the intelligence is it has to be at every layer where it makes sense where we have the information to make a decision and being closest to the data we have we are basically monitoring you know the various parallels data access who is accessing um are they crossing across any geo fencing uh is there any mass deletion that is happening or a mass encryption that is happening and we are able to uh detect uh those uh patterns and flag them as indicators of compromise and in allowing automated response manual control and so on for it teams yeah thank you for that explanation so at dell technologies world we were there in may it was one of the first you know live shows that that we did in the spring certainly one of the largest and i interviewed shannon champion and a huge takeaway from the storage side was the degree to which you guys emphasized security uh within the operating systems i mean really i mean powermax more than half i think of the features were security related but also the rest of the portfolio so can you talk about the the security aspects of the dell storage portfolio specifically yeah yeah so when it comes to data security and broadly data availability right in the context of cyber resiliency dell storage this you know these elements have been at the core of our um a core strength for the portfolio and the source of differentiation for the storage portfolio you know with almost decades of collective experience of building highly resilient architectures for mission critical data something like power max system which is the most secure storage platform for high-end enterprises and now with the increased focus on cyber security we are extending those core technologies of high availability and adding modern detection systems modern data isolation techniques to offer a comprehensive solution to the customer so that they don't have to piece together multiple things to ensure data security or data resiliency but a well-designed and well-architected solution by design is delivered to them to ensure cyber protection at the data layer got it um you know we were talking earlier to steve kenniston and pete gear about this notion of dell trusted infrastructure how does storage fit into that as a component of that sort of overall you know theme yeah and you know and let me say this if you could adjust because a lot of people might be skeptical that i can actually have security and at the same time not constrict my organizational agility that's old you know not an ore it's an end how do you actually do that if you could address both of those that would be great definitely so for dell trusted infrastructure cyber resiliency is a key component of that and just as i mentioned you know uh air gap isolation it really started with you know power protect cyber recovery you know that was the solution more than three years ago we launched and that was first in the industry which paved way to you know kind of data isolation being a core element of data management and uh for data infrastructure and since then we have implemented these technologies within different storage platforms as well so that customers have the flexibility depending on their data landscape they can approach they can do the right data isolation architecture right either natively from the storage platform or consolidate things into the backup platform and isolate from there and and the other key thing we focus in trusted infrastructure dell infra dell trusted infrastructure is you know the goal of simplifying security for the customers so one good example here is uh you know being able to respond to these cyber threats or indicators of compromise is one thing but an i.t security team may not be looking at the dashboard of the storage systems constantly right storage administration admins may be looking at it so how can we build this intelligence and provide this upstream platforms so that they have a single pane of glass to understand security landscape across applications across networks firewalls as well as storage infrastructure and in compute infrastructure so that's one of the key ways where how we are helping simplify the um kind of the ability to uh respond ability to detect and respond these threads uh in real time for security teams and you mentioned you know about zero trust and how it's a balance of you know not uh kind of restricting users or put heavy burden on you know multi-factor authentication and so on and this really starts with you know what we're doing is provide all the tools you know when it comes to advanced authentication uh supporting external identity management systems multi-factor authentication encryption all these things are intrinsically built into these platforms now the question is the customers are actually one of the key steps is to identify uh what are the most critical parts of their business or what are the applications uh that the most critical business operations depend on and similarly identify uh mission critical data where part of your response plan where it cannot be compromised where you need to have a way to recover once you do this identification then the level of security can be really determined uh by uh by the security teams by the infrastructure teams and you know another you know intelligence that gives a lot of flexibility uh for for even developers to do this is today we have apis um that so you can not only track these alerts at the data infrastructure level but you can use our apis to take concrete actions like blocking a certain user or increasing the level of authentication based on the threat level that has been perceived at the application layer or at the network layer so there is a lot of flexibility that is built into this by design so that depending on the criticality of the data criticality of the application number of users affected these decisions have to be made from time to time and it's as you mentioned it's it's a balance right and sometimes you know if if an organization had a recent attack you know the level of awareness is very high against cyber attacks so for a time you know these these settings may be a bit difficult to deal with but then it's a decision that has to be made by security teams as well got it so you're surfacing what may be hidden kpis that are being buried inside for instance the storage system through apis upstream into a dashboard so that somebody could you know dig into the storage tunnel extract that data and then somehow you know populate that dashboard you're saying you're automating that that that workflow that's a great example and you may have others but is that the correct understanding absolutely and it's a two-way integration let's say a detector an attack has been detected at a completely different layer right in the application layer or at a firewall we can respond to those as well so it's a two-way integration we can cascade things up as well as respond to threats that have been detected elsewhere um uh through the api that's great all right hey api for power skill is the best example for that uh excellent so thank you appreciate that give us the last word put a bow on this and and bring this segment home please absolutely so a dell storage portfolio um using advanced data isolation um with air gap having machine learning based algorithms to detect uh indicators of compromise and having rigor mechanisms with granular snapshots being able to recover data and restore applications to maintain business continuity is what we deliver to customers uh and these are areas where a lot of innovation is happening a lot of product focus as well as you know if you look at the professional services all the way from engineering to professional services the way we build these systems the way we we configure and architect these systems um cyber security and protection is a key focus uh for all these activities and dell.com securities is where you can learn a lot about these initiatives that's great thank you you know at the recent uh reinforce uh event in in boston we heard a lot uh from aws about you know detent and response and devops and machine learning and some really cool stuff we heard a little bit about ransomware but i'm glad you brought up air gaps because we heard virtually nothing in the keynotes about air gaps that's an example of where you know this the cso has to pick up from where the cloud leaves off but that was in front and so number one and number two we didn't hear a ton about how the cloud is making the life of the cso simpler and that's really my takeaway is is in part anyway your job and companies like dell so paris i really appreciate the insights thank you for coming on thecube thank you very much dave it's always great to be in these uh conversations all right keep it right there we'll be right back with rob emsley to talk about data protection strategies and what's in the dell portfolio you're watching thecube data is the currency of the global economy it has value to your organization and cyber criminals in the age of ransomware attacks companies need secure and resilient it infrastructure to safeguard their data from aggressive cyber attacks [Music] as part of the dell technologies infrastructure portfolio powerstor and powermax combine storage innovation with advanced security that adheres to stringent government regulations and corporate compliance requirements security starts with multi-factor authentication enabling only authorized admins to access your system using assigned roles tamper-proof audit logs track system usage and changes so it admins can identify suspicious activity and act with snapshot policies you can quickly automate the protection and recovery process for your data powermax secure snapshots cannot be deleted by any user prior to the retention time expiration dell technologies also make sure your data at rest stays safe with power store and powermax data encryption protects your flash drive media from unauthorized access if it's removed from the data center while adhering to stringent fips 140-2 security requirements cloud iq brings together predictive analytics anomaly detection and machine learning with proactive policy-based security assessments monitoring and alerting the result intelligent insights that help you maintain the security health status of your storage environment and if a security breach does occur power protect cyber recovery isolates critical data identifies suspicious activity and accelerates data recovery using the automated data copy feature unchangeable data is duplicated in a secure digital vault then an operational air gap isolates the vault from the production and backup environments [Music] architected with security in mind dell emc power store and powermax provides storage innovation so your data is always available and always secure wherever and whenever you need it [Music] welcome back to a blueprint for trusted infrastructure we're here with rob emsley who's the director of product marketing for data protection and cyber security rob good to see a new role yeah good to be back dave good to see you yeah it's been a while since we chatted last and you know one of the changes in in my world is that i've expanded my responsibilities beyond data protection marketing to also focus on uh cyber security marketing specifically for our infrastructure solutions group so certainly that's you know something that really has driven us to you know to come and have this conversation with you today so data protection obviously has become an increasingly important component of the cyber security space i i don't think necessarily of you know traditional backup and recovery as security it's to me it's an adjacency i know some companies have said oh yeah now we're a security company they're kind of chasing the valuation for sure bubble um dell's interesting because you you have you know data protection in the form of backup and recovery and data management but you also have security you know direct security capability so you're sort of bringing those two worlds together and it sounds like your responsibility is to to connect those those dots is that right absolutely yeah i mean i think that uh the reality is is that security is a a multi-layer discipline um i think the the days of thinking that it's one uh or another um technology that you can use or process that you can use to make your organization secure uh are long gone i mean certainly um you actually correct if you think about the backup and recovery space i mean people have been doing that for years you know certainly backup and recovery is all about the recovery it's all about getting yourself back up and running when bad things happen and one of the realities unfortunately today is that one of the worst things that can happen is cyber attacks you know ransomware malware are all things that are top of mind for all organizations today and that's why you see a lot of technology and a lot of innovation going into the backup and recovery space because if you have a copy a good copy of your data then that is really the the first place you go to recover from a cyber attack and that's why it's so important the reality is is that unfortunately the cyber criminals keep on getting smarter i don't know how it happens but one of the things that is happening is that the days of them just going after your production data are no longer the only challenge that you have they go after your your backup data as well so over the last half a decade dell technologies with its backup and recovery portfolio has introduced the concept of isolated cyber recovery vaults and that is really the you know we've had many conversations about that over the years um and that's really a big tenant of what we do in the data protection portfolio so this idea of of cyber security resilience that definition is evolving what does it mean to you yeah i think the the analyst team over at gartner they wrote a very insightful paper called you will be hacked embrace the breach and the whole basis of this analysis is so much money has been spent on prevention is that what's out of balance is the amount of budget that companies have spent on cyber resilience and cyber resilience is based upon the premise that you will be hacked you have to embrace that fact and be ready and prepared to bring yourself back into business you know and that's really where cyber resiliency is very very different than cyber security and prevention you know and i think that balance of get your security disciplines well-funded get your defenses as good as you can get them but make sure that if the inevitable happens and you find yourself compromised that you have a great recovery plan and certainly a great recovery plan is really the basis of any good solid data protection backup and recovery uh philosophy so if i had to do a swot analysis we don't have to do the wot but let's focus on the s um what would you say are dell's strengths in this you know cyber security space as it relates to data protection um one is we've been doing it a long time you know we talk a lot about dell's data protection being proven and modern you know certainly the experience that we've had over literally three decades of providing enterprise scale data protection solutions to our customers has really allowed us to have a lot of insight into what works and what doesn't as i mentioned to you one of the unique differentiators of our solution is the cyber recovery vaulting solution that we introduced a little over five years ago five six years parapatek cyber recovery is something which has become a unique capability for customers to adopt uh on top of their investment in dell technologies data protection you know the the unique elements of our solution already threefold and it's we call them the three eyes it's isolation it's immutability and it's intelligence and the the isolation part is really so important because you need to reduce the attack surface of your good known copies of data you know you need to put it in a location that the bad actors can't get to it and that really is the the the the essence of a cyber recovery vault interestingly enough you're starting to see the market throw out that word um you know from many other places but really it comes down to having a real discipline that you don't allow the security of your cyber recovery vault to be compromised insofar as allowing it to be controlled from outside of the vault you know allowing it to be controlled by your backup application our cyber recovery vaulting technology is independent of the backup infrastructure it uses it but it controls its own security and that is so so important it's like having a vault that the only way to open it is from the inside you know and think about that if you think about you know volts in banks or volts in your home normally you have a keypad on the outside think of our cyber recovery vault as having its security controlled from inside of the vault so nobody can get in nothing can get in unless it's already in and if it's already in then it's trusted exactly yeah exactly yeah so isolation is the key and then you mentioned immutability is the second piece yeah so immutability is is also something which has been around for a long time people talk about uh backup immunoability or immutable backup copies so immutability is just the the the additional um technology that allows the data that's inside of the vault to be unchangeable you know but again that immutability you know your mileage varies you know when you look across the uh the different offers that are out there in the market especially in the backup industry you make a very valid point earlier that the backup vendors in the market seems to be security washing their marketing messages i mean everybody is leaning into the ever-present danger of cyber security not a bad thing but the reality is is that you have to have the technology to back it up you know quite literally yeah no pun intended and then actually pun intended now what about the intelligence piece of it uh that's that's ai ml where does that fit for sure so the intelligence piece is delivered by um a solution called cybersense and cybersense for us is what really gives you the confidence that what you have in your cyber recovery vault is a good clean copy of data so it's looking at the backup copies that get driven into the cyber vault and it's looking for anomalies so it's not looking for signatures of malware you know that's what your antivirus software does that's what your endpoint protection software does that's on the prevention side of the equation but what we're looking for is we're looking to ensure that the data that you need when all hell breaks loose is good and that when you get a request to restore and recover your business you go right let's go and do it and you don't have any concern that what you have in the vault has been compromised so cyber sense is really a unique analytic solution in the market based upon the fact that it isn't looking at cursory indicators of of um of of of malware infection or or ransomware introduction it's doing full content analytics you know looking at you know has the data um in any way changed has it suddenly become encrypted has it suddenly become different to how it was in the previous scan so that anomaly detection is very very different it's looking for um you know like different characteristics that really are an indicator that something is going on and of course if it sees it you immediately get flagged but the good news is is that you always have in the vault the previous copy of good known data which now becomes your restore point so we're talking to rob emsley about how data protection fits into what dell calls dti dell trusted infrastructure and and i want to come back rob to this notion of and not or because i think a lot of people are skeptical like how can i have great security and not introduce friction into my organization is that an automation play how does dell tackle that problem i mean i think a lot of it is across our infrastructure is is security has to be built in i mean intrinsic security within our servers within our storage devices uh within our elements of our backup infrastructure i mean security multi-factor authentication you know elements that make the overall infrastructure secure you know we have capabilities that you know allow us to identify whether or not configurations have changed you know we'll probably be talking about that a little bit more to you later in the segment but the the essence is is um security is not a bolt-on it has to be part of the overall infrastructure and that's so true um certainly in the data protection space give us the the bottom line on on how you see dell's key differentiators maybe you could talk about dell of course always talks about its portfolio but but why should customers you know lead in to dell in in this whole cyber resilience space um you know staying on the data protection space as i mentioned the the the work we've been doing um to introduce this cyber resiliency solution for data protection is in our opinion as good as it gets you know the you know you've spoken to a number of our of our best customers whether it be bob bender from founders federal or more recently at delton allergies world you spoke to tony bryson from the town of gilbert and these are customers that we've had for many years that have implemented cyber recovery vaults and at the end of the day they can now sleep at night you know that's really the the peace of mind that they have is that the insurance that a data protection from dell cyber recovery vault a parapatex cyber recovery solution gives them you know really allows them to you know just have the assurance that they don't have to pay a ransom if they have a an insider threat issue and you know all the way down to data deletion is they know that what's in the cyber recovery vault is good and ready for them to recover from great well rob congratulations on the new scope of responsibility i like how you know your organization is expanding as the threat surface is expanding as we said data protection becoming an adjacency to security not security in and of itself a key component of a comprehensive security strategy rob emsley thank you for coming back in the cube good to see you again you too dave thanks all right in a moment i'll be back to wrap up a blueprint for trusted infrastructure you're watching the cube every day it seems there's a new headline about the devastating financial impacts or trust that's lost due to ransomware or other sophisticated cyber attacks but with our help dell technologies customers are taking action by becoming more cyber resilient and deterring attacks so they can greet students daily with a smile they're ensuring that a range of essential government services remain available 24 7 to citizens wherever they're needed from swiftly dispatching public safety personnel or sending an inspector to sign off on a homeowner's dream to protecting restoring and sustaining our precious natural resources for future generations with ever-changing cyber attacks targeting organizations in every industry our cyber resiliency solutions are right on the money providing the security and controls you need we help customers protect and isolate critical data from ransomware and other cyber threats delivering the highest data integrity to keep your doors open and ensuring that hospitals and healthcare providers have access to the data they need so patients get life-saving treatment without fail if a cyber incident does occur our intelligence analytics and responsive team are in a class by themselves helping you reliably recover your data and applications so you can quickly get your organization back up and running with dell technologies behind you you can stay ahead of cybercrime safeguarding your business and your customers vital information learn more about how dell technology's cyber resiliency solutions can provide true peace of mind for you the adversary is highly capable motivated and well equipped and is not standing still your job is to partner with technology vendors and increase the cost of the bad guys getting to your data so that their roi is reduced and they go elsewhere the growing issues around cyber security will continue to drive forward thinking in cyber resilience we heard today that it is actually possible to achieve infrastructure security while at the same time minimizing friction to enable organizations to move quickly in their digital transformations a xero trust framework must include vendor r d and innovation that builds security designs it into infrastructure products and services from the start not as a bolt-on but as a fundamental ingredient of the cloud hybrid cloud private cloud to edge operational model the bottom line is if you can't trust your infrastructure your security posture is weakened remember this program is available on demand in its entirety at thecube.net and the individual interviews are also available and you can go to dell security solutions landing page for for more information go to dell.com security solutions that's dell.com security solutions this is dave vellante thecube thanks for watching a blueprint for trusted infrastructure made possible by dell we'll see you next time

>> From The Cube Studios in Palo Alto and Boston, bringing you data driven insights from The Cube at ETR. This is "Breaking Analysis" with Dave Vellante. >> The reverse momentum in tech stocks caused by rising interest rates, less attractive discounted cash flow models, and more tepid forward guidance, can be easily measured by public market valuations. And while there's lots of discussion about the impact on private companies and cash runway and 409A valuations, measuring the performance of non-public companies isn't as easy. IPOs have dried up and public statements by private companies, of course, they accentuate the good and they kind of hide the bad. Real data, unless you're an insider, is hard to find. Hello and welcome to this week's "Wikibon Cube Insights" powered by ETR. In this "Breaking Analysis", we unlock some of the secrets that non-public, emerging tech companies may or may not be sharing. And we do this by introducing you to a capability from ETR that we've not exposed you to over the past couple of years, it's called the Emerging Technologies Survey, and it is packed with sentiment data and performance data based on surveys of more than a thousand CIOs and IT buyers covering more than 400 companies. And we've invited back our colleague, Erik Bradley of ETR to help explain the survey and the data that we're going to cover today. Erik, this survey is something that I've not personally spent much time on, but I'm blown away at the data. It's really unique and detailed. First of all, welcome. Good to see you again. >> Great to see you too, Dave, and I'm really happy to be talking about the ETS or the Emerging Technology Survey. Even our own clients of constituents probably don't spend as much time in here as they should. >> Yeah, because there's so much in the mainstream, but let's pull up a slide to bring out the survey composition. Tell us about the study. How often do you run it? What's the background and the methodology? >> Yeah, you were just spot on the way you were talking about the private tech companies out there. So what we did is we decided to take all the vendors that we track that are not yet public and move 'em over to the ETS. And there isn't a lot of information out there. If you're not in Silicon (indistinct), you're not going to get this stuff. So PitchBook and Tech Crunch are two out there that gives some data on these guys. But what we really wanted to do was go out to our community. We have 6,000, ITDMs in our community. We wanted to ask them, "Are you aware of these companies? And if so, are you allocating any resources to them? Are you planning to evaluate them," and really just kind of figure out what we can do. So this particular survey, as you can see, 1000 plus responses, over 450 vendors that we track. And essentially what we're trying to do here is talk about your evaluation and awareness of these companies and also your utilization. And also if you're not utilizing 'em, then we can also figure out your sales conversion or churn. So this is interesting, not only for the ITDMs themselves to figure out what their peers are evaluating and what they should put in POCs against the big guys when contracts come up. But it's also really interesting for the tech vendors themselves to see how they're performing. >> And you can see 2/3 of the respondents are director level of above. You got 28% is C-suite. There is of course a North America bias, 70, 75% is North America. But these smaller companies, you know, that's when they start doing business. So, okay. We're going to do a couple of things here today. First, we're going to give you the big picture across the sectors that ETR covers within the ETS survey. And then we're going to look at the high and low sentiment for the larger private companies. And then we're going to do the same for the smaller private companies, the ones that don't have as much mindshare. And then I'm going to put those two groups together and we're going to look at two dimensions, actually three dimensions, which companies are being evaluated the most. Second, companies are getting the most usage and adoption of their offerings. And then third, which companies are seeing the highest churn rates, which of course is a silent killer of companies. And then finally, we're going to look at the sentiment and mindshare for two key areas that we like to cover often here on "Breaking Analysis", security and data. And data comprises database, including data warehousing, and then big data analytics is the second part of data. And then machine learning and AI is the third section within data that we're going to look at. Now, one other thing before we get into it, ETR very often will include open source offerings in the mix, even though they're not companies like TensorFlow or Kubernetes, for example. And we'll call that out during this discussion. The reason this is done is for context, because everyone is using open source. It is the heart of innovation and many business models are super glued to an open source offering, like take MariaDB, for example. There's the foundation and then there's with the open source code and then there, of course, the company that sells services around the offering. Okay, so let's first look at the highest and lowest sentiment among these private firms, the ones that have the highest mindshare. So they're naturally going to be somewhat larger. And we do this on two dimensions, sentiment on the vertical axis and mindshare on the horizontal axis and note the open source tool, see Kubernetes, Postgres, Kafka, TensorFlow, Jenkins, Grafana, et cetera. So Erik, please explain what we're looking at here, how it's derived and what the data tells us. >> Certainly, so there is a lot here, so we're going to break it down first of all by explaining just what mindshare and net sentiment is. You explain the axis. We have so many evaluation metrics, but we need to aggregate them into one so that way we can rank against each other. Net sentiment is really the aggregation of all the positive and subtracting out the negative. So the net sentiment is a very quick way of looking at where these companies stand versus their peers in their sectors and sub sectors. Mindshare is basically the awareness of them, which is good for very early stage companies. And you'll see some names on here that are obviously been around for a very long time. And they're clearly be the bigger on the axis on the outside. Kubernetes, for instance, as you mentioned, is open source. This de facto standard for all container orchestration, and it should be that far up into the right, because that's what everyone's using. In fact, the open source leaders are so prevalent in the emerging technology survey that we break them out later in our analysis, 'cause it's really not fair to include them and compare them to the actual companies that are providing the support and the security around that open source technology. But no survey, no analysis, no research would be complete without including these open source tech. So what we're looking at here, if I can just get away from the open source names, we see other things like Databricks and OneTrust . They're repeating as top net sentiment performers here. And then also the design vendors. People don't spend a lot of time on 'em, but Miro and Figma. This is their third survey in a row where they're just dominating that sentiment overall. And Adobe should probably take note of that because they're really coming after them. But Databricks, we all know probably would've been a public company by now if the market hadn't turned, but you can see just how dominant they are in a survey of nothing but private companies. And we'll see that again when we talk about the database later. >> And I'll just add, so you see automation anywhere on there, the big UiPath competitor company that was not able to get to the public markets. They've been trying. Snyk, Peter McKay's company, they've raised a bunch of money, big security player. They're doing some really interesting things in developer security, helping developers secure the data flow, H2O.ai, Dataiku AI company. We saw them at the Snowflake Summit. Redis Labs, Netskope and security. So a lot of names that we know that ultimately we think are probably going to be hitting the public market. Okay, here's the same view for private companies with less mindshare, Erik. Take us through this one. >> On the previous slide too real quickly, I wanted to pull that security scorecard and we'll get back into it. But this is a newcomer, that I couldn't believe how strong their data was, but we'll bring that up in a second. Now, when we go to the ones of lower mindshare, it's interesting to talk about open source, right? Kubernetes was all the way on the top right. Everyone uses containers. Here we see Istio up there. Not everyone is using service mesh as much. And that's why Istio is in the smaller breakout. But still when you talk about net sentiment, it's about the leader, it's the highest one there is. So really interesting to point out. Then we see other names like Collibra in the data side really performing well. And again, as always security, very well represented here. We have Aqua, Wiz, Armis, which is a standout in this survey this time around. They do IoT security. I hadn't even heard of them until I started digging into the data here. And I couldn't believe how well they were doing. And then of course you have AnyScale, which is doing a second best in this and the best name in the survey Hugging Face, which is a machine learning AI tool. Also doing really well on a net sentiment, but they're not as far along on that access of mindshare just yet. So these are again, emerging companies that might not be as well represented in the enterprise as they will be in a couple of years. >> Hugging Face sounds like something you do with your two year old. Like you said, you see high performers, AnyScale do machine learning and you mentioned them. They came out of Berkeley. Collibra Governance, InfluxData is on there. InfluxDB's a time series database. And yeah, of course, Alex, if you bring that back up, you get a big group of red dots, right? That's the bad zone, I guess, which Sisense does vis, Yellowbrick Data is a NPP database. How should we interpret the red dots, Erik? I mean, is it necessarily a bad thing? Could it be misinterpreted? What's your take on that? >> Sure, well, let me just explain the definition of it first from a data science perspective, right? We're a data company first. So the gray dots that you're seeing that aren't named, that's the mean that's the average. So in order for you to be on this chart, you have to be at least one standard deviation above or below that average. So that gray is where we're saying, "Hey, this is where the lump of average comes in. This is where everyone normally stands." So you either have to be an outperformer or an underperformer to even show up in this analysis. So by definition, yes, the red dots are bad. You're at least one standard deviation below the average of your peers. It's not where you want to be. And if you're on the lower left, not only are you not performing well from a utilization or an actual usage rate, but people don't even know who you are. So that's a problem, obviously. And the VCs and the PEs out there that are backing these companies, they're the ones who mostly are interested in this data. >> Yeah. Oh, that's great explanation. Thank you for that. No, nice benchmarking there and yeah, you don't want to be in the red. All right, let's get into the next segment here. Here going to look at evaluation rates, adoption and the all important churn. First new evaluations. Let's bring up that slide. And Erik, take us through this. >> So essentially I just want to explain what evaluation means is that people will cite that they either plan to evaluate the company or they're currently evaluating. So that means we're aware of 'em and we are choosing to do a POC of them. And then we'll see later how that turns into utilization, which is what a company wants to see, awareness, evaluation, and then actually utilizing them. That's sort of the life cycle for these emerging companies. So what we're seeing here, again, with very high evaluation rates. H2O, we mentioned. SecurityScorecard jumped up again. Chargebee, Snyk, Salt Security, Armis. A lot of security names are up here, Aqua, Netskope, which God has been around forever. I still can't believe it's in an Emerging Technology Survey But so many of these names fall in data and security again, which is why we decided to pick those out Dave. And on the lower side, Vena, Acton, those unfortunately took the dubious award of the lowest evaluations in our survey, but I prefer to focus on the positive. So SecurityScorecard, again, real standout in this one, they're in a security assessment space, basically. They'll come in and assess for you how your security hygiene is. And it's an area of a real interest right now amongst our ITDM community. >> Yeah, I mean, I think those, and then Arctic Wolf is up there too. They're doing managed services. You had mentioned Netskope. Yeah, okay. All right, let's look at now adoption. These are the companies whose offerings are being used the most and are above that standard deviation in the green. Take us through this, Erik. >> Sure, yet again, what we're looking at is, okay, we went from awareness, we went to evaluation. Now it's about utilization, which means a survey respondent's going to state "Yes, we evaluated and we plan to utilize it" or "It's already in our enterprise and we're actually allocating further resources to it." Not surprising, again, a lot of open source, the reason why, it's free. So it's really easy to grow your utilization on something that's free. But as you and I both know, as Red Hat proved, there's a lot of money to be made once the open source is adopted, right? You need the governance, you need the security, you need the support wrapped around it. So here we're seeing Kubernetes, Postgres, Apache Kafka, Jenkins, Grafana. These are all open source based names. But if we're looking at names that are non open source, we're going to see Databricks, Automation Anywhere, Rubrik all have the highest mindshare. So these are the names, not surprisingly, all names that probably should have been public by now. Everyone's expecting an IPO imminently. These are the names that have the highest mindshare. If we talk about the highest utilization rates, again, Miro and Figma pop up, and I know they're not household names, but they are just dominant in this survey. These are applications that are meant for design software and, again, they're going after an Autodesk or a CAD or Adobe type of thing. It is just dominant how high the utilization rates are here, which again is something Adobe should be paying attention to. And then you'll see a little bit lower, but also interesting, we see Collibra again, we see Hugging Face again. And these are names that are obviously in the data governance, ML, AI side. So we're seeing a ton of data, a ton of security and Rubrik was interesting in this one, too, high utilization and high mindshare. We know how pervasive they are in the enterprise already. >> Erik, Alex, keep that up for a second, if you would. So yeah, you mentioned Rubrik. Cohesity's not on there. They're sort of the big one. We're going to talk about them in a moment. Puppet is interesting to me because you remember the early days of that sort of space, you had Puppet and Chef and then you had Ansible. Red Hat bought Ansible and then Ansible really took off. So it's interesting to see Puppet on there as well. Okay. So now let's look at the churn because this one is where you don't want to be. It's, of course, all red 'cause churn is bad. Take us through this, Erik. >> Yeah, definitely don't want to be here and I don't love to dwell on the negative. So we won't spend as much time. But to your point, there's one thing I want to point out that think it's important. So you see Rubrik in the same spot, but Rubrik has so many citations in our survey that it actually would make sense that they're both being high utilization and churn just because they're so well represented. They have such a high overall representation in our survey. And the reason I call that out is Cohesity. Cohesity has an extremely high churn rate here about 17% and unlike Rubrik, they were not on the utilization side. So Rubrik is seeing both, Cohesity is not. It's not being utilized, but it's seeing a high churn. So that's the way you can look at this data and say, "Hm." Same thing with Puppet. You noticed that it was on the other slide. It's also on this one. So basically what it means is a lot of people are giving Puppet a shot, but it's starting to churn, which means it's not as sticky as we would like. One that was surprising on here for me was Tanium. It's kind of jumbled in there. It's hard to see in the middle, but Tanium, I was very surprised to see as high of a churn because what I do hear from our end user community is that people that use it, like it. It really kind of spreads into not only vulnerability management, but also that endpoint detection and response side. So I was surprised by that one, mostly to see Tanium in here. Mural, again, was another one of those application design softwares that's seeing a very high churn as well. >> So you're saying if you're in both... Alex, bring that back up if you would. So if you're in both like MariaDB is for example, I think, yeah, they're in both. They're both green in the previous one and red here, that's not as bad. You mentioned Rubrik is going to be in both. Cohesity is a bit of a concern. Cohesity just brought on Sanjay Poonen. So this could be a go to market issue, right? I mean, 'cause Cohesity has got a great product and they got really happy customers. So they're just maybe having to figure out, okay, what's the right ideal customer profile and Sanjay Poonen, I guarantee, is going to have that company cranking. I mean they had been doing very well on the surveys and had fallen off of a bit. The other interesting things wondering the previous survey I saw Cvent, which is an event platform. My only reason I pay attention to that is 'cause we actually have an event platform. We don't sell it separately. We bundle it as part of our offerings. And you see Hopin on here. Hopin raised a billion dollars during the pandemic. And we were like, "Wow, that's going to blow up." And so you see Hopin on the churn and you didn't see 'em in the previous chart, but that's sort of interesting. Like you said, let's not kind of dwell on the negative, but you really don't. You know, churn is a real big concern. Okay, now we're going to drill down into two sectors, security and data. Where data comprises three areas, database and data warehousing, machine learning and AI and big data analytics. So first let's take a look at the security sector. Now this is interesting because not only is it a sector drill down, but also gives an indicator of how much money the firm has raised, which is the size of that bubble. And to tell us if a company is punching above its weight and efficiently using its venture capital. Erik, take us through this slide. Explain the dots, the size of the dots. Set this up please. >> Yeah. So again, the axis is still the same, net sentiment and mindshare, but what we've done this time is we've taken publicly available information on how much capital company is raised and that'll be the size of the circle you see around the name. And then whether it's green or red is basically saying relative to the amount of money they've raised, how are they doing in our data? So when you see a Netskope, which has been around forever, raised a lot of money, that's why you're going to see them more leading towards red, 'cause it's just been around forever and kind of would expect it. Versus a name like SecurityScorecard, which is only raised a little bit of money and it's actually performing just as well, if not better than a name, like a Netskope. OneTrust doing absolutely incredible right now. BeyondTrust. We've seen the issues with Okta, right. So those are two names that play in that space that obviously are probably getting some looks about what's going on right now. Wiz, we've all heard about right? So raised a ton of money. It's doing well on net sentiment, but the mindshare isn't as well as you'd want, which is why you're going to see a little bit of that red versus a name like Aqua, which is doing container and application security. And hasn't raised as much money, but is really neck and neck with a name like Wiz. So that is why on a relative basis, you'll see that more green. As we all know, information security is never going away. But as we'll get to later in the program, Dave, I'm not sure in this current market environment, if people are as willing to do POCs and switch away from their security provider, right. There's a little bit of tepidness out there, a little trepidation. So right now we're seeing overall a slight pause, a slight cooling in overall evaluations on the security side versus historical levels a year ago. >> Now let's stay on here for a second. So a couple things I want to point out. So it's interesting. Now Snyk has raised over, I think $800 million but you can see them, they're high on the vertical and the horizontal, but now compare that to Lacework. It's hard to see, but they're kind of buried in the middle there. That's the biggest dot in this whole thing. I think I'm interpreting this correctly. They've raised over a billion dollars. It's a Mike Speiser company. He was the founding investor in Snowflake. So people watch that very closely, but that's an example of where they're not punching above their weight. They recently had a layoff and they got to fine tune things, but I'm still confident they they're going to do well. 'Cause they're approaching security as a data problem, which is probably people having trouble getting their arms around that. And then again, I see Arctic Wolf. They're not red, they're not green, but they've raised fair amount of money, but it's showing up to the right and decent level there. And a couple of the other ones that you mentioned, Netskope. Yeah, they've raised a lot of money, but they're actually performing where you want. What you don't want is where Lacework is, right. They've got some work to do to really take advantage of the money that they raised last November and prior to that. >> Yeah, if you're seeing that more neutral color, like you're calling out with an Arctic Wolf, like that means relative to their peers, this is where they should be. It's when you're seeing that red on a Lacework where we all know, wow, you raised a ton of money and your mindshare isn't where it should be. Your net sentiment is not where it should be comparatively. And then you see these great standouts, like Salt Security and SecurityScorecard and Abnormal. You know they haven't raised that much money yet, but their net sentiment's higher and their mindshare's doing well. So those basically in a nutshell, if you're a PE or a VC and you see a small green circle, then you're doing well, then it means you made a good investment. >> Some of these guys, I don't know, but you see these small green circles. Those are the ones you want to start digging into and maybe help them catch a wave. Okay, let's get into the data discussion. And again, three areas, database slash data warehousing, big data analytics and ML AI. First, we're going to look at the database sector. So Alex, thank you for bringing that up. Alright, take us through this, Erik. Actually, let me just say Postgres SQL. I got to ask you about this. It shows some funding, but that actually could be a mix of EDB, the company that commercializes Postgres and Postgres the open source database, which is a transaction system and kind of an open source Oracle. You see MariaDB is a database, but open source database. But the companies they've raised over $200 million and they filed an S-4. So Erik looks like this might be a little bit of mashup of companies and open source products. Help us understand this. >> Yeah, it's tough when you start dealing with the open source side and I'll be honest with you, there is a little bit of a mashup here. There are certain names here that are a hundred percent for profit companies. And then there are others that are obviously open source based like Redis is open source, but Redis Labs is the one trying to monetize the support around it. So you're a hundred percent accurate on this slide. I think one of the things here that's important to note though, is just how important open source is to data. If you're going to be going to any of these areas, it's going to be open source based to begin with. And Neo4j is one I want to call out here. It's not one everyone's familiar with, but it's basically geographical charting database, which is a name that we're seeing on a net sentiment side actually really, really high. When you think about it's the third overall net sentiment for a niche database play. It's not as big on the mindshare 'cause it's use cases aren't as often, but third biggest play on net sentiment. I found really interesting on this slide. >> And again, so MariaDB, as I said, they filed an S-4 I think $50 million in revenue, that might even be ARR. So they're not huge, but they're getting there. And by the way, MariaDB, if you don't know, was the company that was formed the day that Oracle bought Sun in which they got MySQL and MariaDB has done a really good job of replacing a lot of MySQL instances. Oracle has responded with MySQL HeatWave, which was kind of the Oracle version of MySQL. So there's some interesting battles going on there. If you think about the LAMP stack, the M in the LAMP stack was MySQL. And so now it's all MariaDB replacing that MySQL for a large part. And then you see again, the red, you know, you got to have some concerns about there. Aerospike's been around for a long time. SingleStore changed their name a couple years ago, last year. Yellowbrick Data, Fire Bolt was kind of going after Snowflake for a while, but yeah, you want to get out of that red zone. So they got some work to do. >> And Dave, real quick for the people that aren't aware, I just want to let them know that we can cut this data with the public company data as well. So we can cross over this with that because some of these names are competing with the larger public company names as well. So we can go ahead and cross reference like a MariaDB with a Mongo, for instance, or of something of that nature. So it's not in this slide, but at another point we can certainly explain on a relative basis how these private names are doing compared to the other ones as well. >> All right, let's take a quick look at analytics. Alex, bring that up if you would. Go ahead, Erik. >> Yeah, I mean, essentially here, I can't see it on my screen, my apologies. I just kind of went to blank on that. So gimme one second to catch up. >> So I could set it up while you're doing that. You got Grafana up and to the right. I mean, this is huge right. >> Got it thank you. I lost my screen there for a second. Yep. Again, open source name Grafana, absolutely up and to the right. But as we know, Grafana Labs is actually picking up a lot of speed based on Grafana, of course. And I think we might actually hear some noise from them coming this year. The names that are actually a little bit more disappointing than I want to call out are names like ThoughtSpot. It's been around forever. Their mindshare of course is second best here but based on the amount of time they've been around and the amount of money they've raised, it's not actually outperforming the way it should be. We're seeing Moogsoft obviously make some waves. That's very high net sentiment for that company. It's, you know, what, third, fourth position overall in this entire area, Another name like Fivetran, Matillion is doing well. Fivetran, even though it's got a high net sentiment, again, it's raised so much money that we would've expected a little bit more at this point. I know you know this space extremely well, but basically what we're looking at here and to the bottom left, you're going to see some names with a lot of red, large circles that really just aren't performing that well. InfluxData, however, second highest net sentiment. And it's really pretty early on in this stage and the feedback we're getting on this name is the use cases are great, the efficacy's great. And I think it's one to watch out for. >> InfluxData, time series database. The other interesting things I just noticed here, you got Tamer on here, which is that little small green. Those are the ones we were saying before, look for those guys. They might be some of the interesting companies out there and then observe Jeremy Burton's company. They do observability on top of Snowflake, not green, but kind of in that gray. So that's kind of cool. Monte Carlo is another one, they're sort of slightly green. They are doing some really interesting things in data and data mesh. So yeah, okay. So I can spend all day on this stuff, Erik, phenomenal data. I got to get back and really dig in. Let's end with machine learning and AI. Now this chart it's similar in its dimensions, of course, except for the money raised. We're not showing that size of the bubble, but AI is so hot. We wanted to cover that here, Erik, explain this please. Why TensorFlow is highlighted and walk us through this chart. >> Yeah, it's funny yet again, right? Another open source name, TensorFlow being up there. And I just want to explain, we do break out machine learning, AI is its own sector. A lot of this of course really is intertwined with the data side, but it is on its own area. And one of the things I think that's most important here to break out is Databricks. We started to cover Databricks in machine learning, AI. That company has grown into much, much more than that. So I do want to state to you Dave, and also the audience out there that moving forward, we're going to be moving Databricks out of only the MA/AI into other sectors. So we can kind of value them against their peers a little bit better. But in this instance, you could just see how dominant they are in this area. And one thing that's not here, but I do want to point out is that we have the ability to break this down by industry vertical, organization size. And when I break this down into Fortune 500 and Fortune 1000, both Databricks and Tensorflow are even better than you see here. So it's quite interesting to see that the names that are succeeding are also succeeding with the largest organizations in the world. And as we know, large organizations means large budgets. So this is one area that I just thought was really interesting to point out that as we break it down, the data by vertical, these two names still are the outstanding players. >> I just also want to call it H2O.ai. They're getting a lot of buzz in the marketplace and I'm seeing them a lot more. Anaconda, another one. Dataiku consistently popping up. DataRobot is also interesting because all the kerfuffle that's going on there. The Cube guy, Cube alum, Chris Lynch stepped down as executive chairman. All this stuff came out about how the executives were taking money off the table and didn't allow the employees to participate in that money raising deal. So that's pissed a lot of people off. And so they're now going through some kind of uncomfortable things, which is unfortunate because DataRobot, I noticed, we haven't covered them that much in "Breaking Analysis", but I've noticed them oftentimes, Erik, in the surveys doing really well. So you would think that company has a lot of potential. But yeah, it's an important space that we're going to continue to watch. Let me ask you Erik, can you contextualize this from a time series standpoint? I mean, how is this changed over time? >> Yeah, again, not show here, but in the data. I'm sorry, go ahead. >> No, I'm sorry. What I meant, I should have interjected. In other words, you would think in a downturn that these emerging companies would be less interesting to buyers 'cause they're more risky. What have you seen? >> Yeah, and it was interesting before we went live, you and I were having this conversation about "Is the downturn stopping people from evaluating these private companies or not," right. In a larger sense, that's really what we're doing here. How are these private companies doing when it comes down to the actual practitioners? The people with the budget, the people with the decision making. And so what I did is, we have historical data as you know, I went back to the Emerging Technology Survey we did in November of 21, right at the crest right before the market started to really fall and everything kind of started to fall apart there. And what I noticed is on the security side, very much so, we're seeing less evaluations than we were in November 21. So I broke it down. On cloud security, net sentiment went from 21% to 16% from November '21. That's a pretty big drop. And again, that sentiment is our one aggregate metric for overall positivity, meaning utilization and actual evaluation of the name. Again in database, we saw it drop a little bit from 19% to 13%. However, in analytics we actually saw it stay steady. So it's pretty interesting that yes, cloud security and security in general is always going to be important. But right now we're seeing less overall net sentiment in that space. But within analytics, we're seeing steady with growing mindshare. And also to your point earlier in machine learning, AI, we're seeing steady net sentiment and mindshare has grown a whopping 25% to 30%. So despite the downturn, we're seeing more awareness of these companies in analytics and machine learning and a steady, actual utilization of them. I can't say the same in security and database. They're actually shrinking a little bit since the end of last year. >> You know it's interesting, we were on a round table, Erik does these round tables with CISOs and CIOs, and I remember one time you had asked the question, "How do you think about some of these emerging tech companies?" And one of the executives said, "I always include somebody in the bottom left of the Gartner Magic Quadrant in my RFPs. I think he said, "That's how I found," I don't know, it was Zscaler or something like that years before anybody ever knew of them "Because they're going to help me get to the next level." So it's interesting to see Erik in these sectors, how they're holding up in many cases. >> Yeah. It's a very important part for the actual IT practitioners themselves. There's always contracts coming up and you always have to worry about your next round of negotiations. And that's one of the roles these guys play. You have to do a POC when contracts come up, but it's also their job to stay on top of the new technology. You can't fall behind. Like everyone's a software company. Now everyone's a tech company, no matter what you're doing. So these guys have to stay in on top of it. And that's what this ETS can do. You can go in here and look and say, "All right, I'm going to evaluate their technology," and it could be twofold. It might be that you're ready to upgrade your technology and they're actually pushing the envelope or it simply might be I'm using them as a negotiation ploy. So when I go back to the big guy who I have full intentions of writing that contract to, at least I have some negotiation leverage. >> Erik, we got to leave it there. I could spend all day. I'm going to definitely dig into this on my own time. Thank you for introducing this, really appreciate your time today. >> I always enjoy it, Dave and I hope everyone out there has a great holiday weekend. Enjoy the rest of the summer. And, you know, I love to talk data. So anytime you want, just point the camera on me and I'll start talking data. >> You got it. I also want to thank the team at ETR, not only Erik, but Darren Bramen who's a data scientist, really helped prepare this data, the entire team over at ETR. I cannot tell you how much additional data there is. We are just scratching the surface in this "Breaking Analysis". So great job guys. I want to thank Alex Myerson. Who's on production and he manages the podcast. Ken Shifman as well, who's just coming back from VMware Explore. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE. Does some great editing for us. Thank you. All of you guys. Remember these episodes, they're all available as podcast, wherever you listen. All you got to do is just search "Breaking Analysis" podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me to get in touch david.vellante@siliconangle.com. You can DM me at dvellante or comment on my LinkedIn posts and please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for Erik Bradley and The Cube Insights powered by ETR. Thanks for watching. Be well. And we'll see you next time on "Breaking Analysis". (upbeat music)