 From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. Making technology predictions in 2022 was tricky business, especially if you were projecting the performance of markets or identifying IPO prospects and making binary forecasts on data, AI and the macro spending climate and other related topics in enterprise tech. 2022, of course, was characterized by a seesaw economy where central banks were restructuring their balance sheets, the war on Ukraine, fueled inflation, supply chains were a mess and the unintended consequences of a forced march to digital and the acceleration still being sorted out. Hello and welcome to this week's with you on Cube Insights powered by ETR. In this Breaking Analysis, we continue our annual tradition of transparently grading last year's enterprise tech predictions. And you may or may not agree with our self grading system, but look, we're gonna give you the data and you can draw your own conclusions and tell us what you think. All right, let's get right to it. So our first prediction was tech spending increases by 8% in 2022. And as we exited 2021, CIOs, they were optimistic about their digital transformation plans. You know, they rushed to make changes to their business and were eager to sharpen their focus and continue to iterate on their digital business models, and plug the holes in the learnings that they had. And so we predicted that 8% rise in enterprise tech spending, which looked pretty good until Ukraine and the Fed decided that, you know, had to rush and make up for lost time. We kind of nailed the momentum in the energy sector, but we can't give ourselves too much credit for that layup. And as of October, Gartner had IT spending growing at just over 5%, I think it was 5.1%. So we're gonna take a C plus on this one and move on. Our next prediction was basically kind of a slow ground ball of the second base, if I have to be honest, but we felt it was important to highlight that security would remain front and center as the number one priority for organizations in 2022. As is our tradition, you know, we try to up the degree of difficulty by specifically identifying companies that are gonna benefit from these trends. So we highlighted some possible IPO candidates, which of course didn't pan out. Sneak was on our radar. The company just had to do another raise. They recently took a valuation hit and it was a down round, they raised 196 million. So good chunk of cash, but not the IPO that we had predicted. Aqua security is focused on containers and cloud native. That was a trendy call. And we thought maybe an MSSP or multiple managed security service providers like Arctic Wolf would IPO, but no way that was happening in the crummy market. Nonetheless, we think these types of companies, they're still faring well as the talent shortage in security remains really acute, particularly in the sort of mid-size and small businesses that often don't have a sock. Lacework laid off 20% of its workforce in 2022 and co-CEO Dave Hatfield left the company. So that IPO didn't happen. It was probably too early for Lacework anyway. Meanwhile, you got Netscope, which we've cited as strong in the ETR data is particularly in the emerging technology survey and then, you know, Lumia holding its own. You know, we never liked that $7 billion price tag that Aqua paid for Auth0, but we loved the TAM expansion strategy to target developers beyond sort of Octa's enterprise strength. But we got to take some points off of the failure. Thus far of Octa to really nail the integration and to go to market model with Auth0 and then build, you know, bring that into the core Octa. So the focus on endpoint security, that was a winner in 2022 as CrowdStrike led that charge with others holding their own, not the least of which was Palo Alto Networks as it continued to expand beyond its core network security and firewall business, you know, through acquisition. So overall, we're going to give ourselves an A minus for this relatively easy call, but again, we had some specifics associated with it to make it a little tougher. And of course, we're watching very closely this coming year in 2023, the vendor consolidation trend, you know, according to a recent Palo Alto Network survey with 1,300 SecOps pros on average organizations have more than 30 tools to manage security tools. So this is a logical way to optimize costs, consolidating vendors and consolidating redundant vendors. The ETR data shows that's clearly a trend that's on the upswing. Now, moving on, a big theme of 2020 and 2021 of course was remote work and hybrid work and new ways to work and return to work. So we predicted in 2022 that hybrid work models would become the dominant protocol, which clearly is the case. We predicted that about 33% of the workforce would come back to the office in 2022. In September, the ETR data showed that figure was at 29%, but organizations expected that 32% would be in the office, you know, pretty much full time by year end. That hasn't quite happened, but we were pretty close with the projections. So we're going to take an A minus on this one. Now, supply chain disruption was another big theme that we felt would carry through 2022. And sure, that sounds like another easy one, but as is our tradition, again, we try to put some binary metrics around our predictions to put some meat on the bone, so to speak, and allow us than you to say, okay, did it come true or not? So we had some data that we presented last year about supply chain issues impacting hardware spend. We said at the time, you can see this on the left-hand side of this chart, the PC laptop demand would remain above pre-COVID levels, which would reverse a decade of year-on-year declines, which I think started in around 2011, 2012. Now, while demand is down this year, pretty substantially relative to 2021, IDC has worldwide unit shipments for PCs at just over 300 million for 22. You go back to 2019 and you're looking at around, let's say 260 million units shipped globally roughly. So, you know, pretty good call there, definitely much higher than pre-COVID levels. But so you might be asking, why the B? Well, we projected that 30% of customers would replace security appliances with cloud-based services, and that more than a third would replace their internal data center server and storage hardware with cloud services, like 30 and 40% respectively. And we don't have explicit survey data on exactly these metrics, but anecdotally, we see this happening in earnest. And we do have some data that was showing here on cloud adoption from ETR's October survey, where the midpoint of workloads running in the cloud is around 34% and forecast, as you can see, to grow steadily over the next three years. So, well, look, this is not, we understand, it's not a one-to-one correlation with our prediction, but it's a pretty good bet that we were right. But we got to take some points off, we think, for the lack of unequivocal proof. Because again, we always strive to make our predictions in ways that can be measured as accurate or not. Is it binary? Did it happen? Did it not? Kind of like an OKR. And we strive to provide data as proof. And in this case, it's a bit fuzzy. We have to admit that, although we're pretty comfortable that the prediction was accurate. And look, when you make it hard forecast, sometimes you got to pay the price. All right, next, we said in 2022 that the big four cloud players would generate $167 billion in IS and as revenue, combining for 38% market growth. And our current forecasts are shown here with a comparison to our January 2022 figures. So coming into this year, now where we are today. So currently we expect $162 billion in total revenue and a 33% growth rate, still very healthy, but not on our mark. So we think AWS is gonna miss our predictions by about a billion dollars, not bad for an $80 billion company. So they're not gonna hit that expectation though of getting really close to a $100 billion run rate. We thought they'd exit the year, closer to 25 billion a quarter. And we don't think they're gonna get there. Look, we pretty much nailed Azure, even though our prediction was correct about Google Cloud Platform surpassing Alibaba. We way overestimated the performance of both of those companies. So we're gonna give ourselves a C plus here. And we think, yeah, you might think it's a little bit harsh. We could argue for a B minus to the professor, but the misses on GCP and Alibaba, we think warrant a self-penalty on this one. All right, let's move on to our prediction about SuperCloud. We said it becomes a thing in 2022 and we think by many accounts it has. Despite the naysayers, we're seeing clear evidence that the concept of a layer of value ad that sits above and across clouds is taking shape. And on this slide, we showed just some of the pickup in the industry. And one of the most interesting is Cloudflare, the biggest SuperCloud antagonist, Charles Fitzgerald, even predicted that no vendor would ever use the term in their marketing. And that would be proof if that happened, that SuperCloud was a thing. And he said, it would never happen. Well, Cloudflare has, and they launched their version of SuperCloud at their developer week. Chris Miller of the register put out a SuperCloud block diagram, something else that Charles Fitzgerald was always pushing us for, which he rightly so. It was a good call on his part. And Chris Miller actually came up with one that's pretty good at David Lindicombe, also has produced a block diagram, kind of similar. David uses the term MetaCloud and he uses the term SuperCloud kind of interchangeably to describe that trend. And so we were aligned on that front. Brian Graceley has covered the concept on the popular Cloudcast podcast. Berkeley launched the Sky Computing Initiative. You read through that white paper and many of the concepts highlighted in the SuperCloud 3.0 community developed definition aligned with that. Walmart launched a platform with many of the SuperCloud salient attributes. So did Goldman Sachs, so did Capital One, so did NASDAQ. So, sorry, you can hate the term, but very clearly the evidence is gathering for the SuperCloud storm. And we're going to take an A plus on this one. Sorry, haters. All right, let's talk about data mesh. In our 21 predictions post, we said that in the 2020s, 75% of large organizations are going to re-architect their big data platforms. So kind of a decade long prediction. We don't like to do that always, but sometimes it's warranted. And because it was a longer term prediction, we at the time in coming into 22 when we were evaluating our 21 predictions, we took a grade of incomplete because that's sort of decade long or majority of the decade, better part of the decade prediction. So last year, early this year, we said our number seven prediction was data mesh gains momentum in 22, but it's largely confined to narrow data problems with limited scope, as you can see here with some of the key bullets. So there's a lot of discussion in the data community about data mesh. And while there are an increasing number of examples, JPMorgan Chase, Intuit, HSBC, HelloFresh, and others that are completely re-architecting parts of their data platform, completely re-architecting entire data platforms is non-trivial. There are organizational challenges, data ownership, debates, technical considerations. And in particular, two of the four fundamental data mesh principles that describe the need for a self-service infrastructure and federated computational governance are challenging. Look, democratizing data and facilitating data sharing creates conflicts with regulatory requirements around data privacy. As such, many organizations are being really selective with their data mesh implementations and hence our prediction of narrowing the scope of data mesh initiatives. I think that was right on. JPMC is a good example of this, where you got a single group within a division narrowly implementing the data mesh architecture, they're using AWS, they're using data lakes, they're using Amazon Glue, creating a catalog and a variety of other techniques to meet their objectives. They kind of automating data quality and is pretty well thought out an interesting approach. And I think it's going to be made easier by some of the announcements that Amazon made with the recent reinvent, particularly trying to eliminate ETL, better connections between Aurora and Redshift and better data sharing, the data clean room. So a lot of that is going to help, of course, Snowflake has been on this for a while. Now, many other companies are facing limitations, as we said here in the slide with their Hadoop data platforms, they need to do some new thinking around that to scale Hello Fresh is a really good example of this. But the bottom line is that organizations want to get more value from data and having a centralized, highly specialized teams that own the data problem, it's been a barrier and a blocker to success. The data mesh starts with organizational considerations as described in great detail by Ash Nasir of Warner Brothers. So take a listen to this clip. Yeah, so when people think of Warner Brothers, you always think of like the movie studio, but we're more than that, right? I mean, you think of HBO, you think of TNT, you think of CNN. We have 30 plus brands in our portfolio and each have their own needs. So the idea of a data mesh really helps us because what we can do is we can federate access across the company so that CNN can work at their own pace. When there's election season, they can ingest their own data and they don't have to bump up against, as an example, HBO, if Game of Thrones is going on. So it's often the case that data mesh is in the eyes of the implementer. While a company's implementation may not strictly adhere to Jamak Tagani's vision of data mesh, that's okay. The goal is to use data more effectively and despite Gartner's attempts to deposition data mesh in favor of the somewhat confusing or frankly far more confusing data fabric concept that they stole from NetApp, data mesh is taking hold in organizations globally today. So we're going to take a B on this one. The prediction is shaping up the way we envision, but as we previously reported, it's going to take some time, the better part of a decade in our view, new standards have to emerge to make this vision become reality and they'll come in the form of both open and de facto approaches. Okay, our eighth prediction last year focused on the face off between Snowflake and Databricks and we realized this popular topic and maybe one that's getting a little overplayed but these are two companies that initially, looked like they were shaping up as partners and by the way, they are still partnering in the field but you go back a couple of years ago, the idea of using an AWS infrastructure, Databricks machine intelligence and applying that on top of Snowflake as a facile data warehouse, still very viable but both of these companies, they have much larger ambitions, they got big total available markets to chase and large valuations that they have to justify. So what's happening is as we previously reported, each of these companies is moving toward the other firms core domain and they're building out an ecosystem that'll be critical for their future. So as part of that effort, we said, each is going to become aggressive investors and maybe start doing some M&A and they have in various companies and on this chart that we produced last year, we cited some of the companies that were targets and we've added some recent investments of both Snowflake and Databricks as you can see. They've both, for example, invested in Elation, Snowflake's put money into Lacework, the security firm ThoughtSpot, which is trying to democratize data with AI, Calibra as a governance platform and you can see Databricks investments and data transformation with DBT Labs, Matillion doing simplified business intelligence, Hunters, so that's their security investment and so forth. So other than our thought that we'd see Databricks IPO last year, this prediction has been pretty spot on. So we'll give ourselves an A on that one. Now, observability has been a hot topic and we've been covering it for a while with our friends at ETR, particularly Eric Bradley. Our number nine prediction last year was basically that if you're not cloud native in observability, you're going to be in big trouble. So everything guys got to go cloud native and that's clearly been the case. Splunk, the big player in the space has been transitioning to the cloud, hasn't always been pretty as we've reported. Datadog, Real Momentum, the Elkstack, that's open source model. You got new entrants that we've cited before like Observe, Honeycomb, Chaos Search and others that we've reported on. They're all born in the cloud. So we're going to take another A on this one. Admittedly, yeah, it's a reasonably easy call but you got to have a few of those in the mix. Okay, our last prediction, our number 10 was around events, something theCUBE knows a little bit about. We said that a new category of events would emerge as hybrid and that for the most part is happened. So that's going to be the main stay is what we said. That pure play virtual events are going to give way to hybrid and the narrative is that virtual only events are good for quick hits but lousy replacements for in-person events. That said, organizations of all shapes and sizes, they learn how to create better virtual content and support remote audiences during the pandemic. So when we said pure play is going to give way to hybrid, we said we implied or specified that the physical event that VIP experience is going to be defined that overall experience and those VIP events would create a little FOMO fear of missing out in a virtual component would overlay that serves an audience 10 X the size of the physical. We saw that two really good examples. Red Hat Summit in Boston, small event, couple of thousand people serve tens of thousands online. Second was Google Cloud Next VIP event in New York City. Everything else was virtual. You know, even examples of our prediction of metaverse like immersion have popped up and other companies are doing road shows as we predicted like a lot of companies are doing it. You're seeing that as a major trend where organizations are going with their sales teams out into the regions and doing a little belly to belly action as opposed to the big giant event. That's definitely a trend that we're seeing. So in reviewing this prediction, the grade we gave ourselves is maybe a bit unfair. It should be, you could argue for a higher grade, but the organizations still haven't figured it out. They have hybrid experiences, but they generally do a really poor job of leveraging the afterglow of an event. It still tends to be one and done. Let's move on to the next event or the next city. Let the sales team pick up the pieces if they were paying attention. So because of that, we're only taking a B plus on this one. Okay, so that's the review of last year's predictions. Overall, if you average out our grade on the 10 predictions that come out to a B plus, they don't know why we can't seem to get that elusive A, but we're going to keep trying. Our friends at ETR, and we are starting to look at the data for 2023 from the surveys and all the work that we've done on the cube and our analysis. And we're going to put together our predictions. We've had literally hundreds of inbound from PR pros pitching us. We've got this huge thick folder that we've started to review with our yellow highlighter. And our plan is to review it this month, take a look at all the data, get some ideas from the inbounds. And then the ETR January surveys in the field, it's probably got a little over a thousand responses right now, they'll get up to 1400 or so. And once we've digested all that, we're going to go back and publish our predictions for 2023 sometime in January. So stay tuned for that. All right, we're going to leave it there for today. You want to thank Alex Meyerson, who's on production and he manages the podcast. Ken Schiffman as well out of our Boston studio. I got a really heartfelt thank you to Kristen Martin and Cheryl Knight and their team. They helped get the word out on social and in our newsletters, Rob Hoth is our editor-in-chief over at Silicon Angle who does some great editing for us. Thank you all. Remember, all these podcasts are available or all these episodes are available as podcasts wherever you listen, just all you do, search, breaking analysis podcast, really getting some great traction there. Appreciate you guys subscribing. I publish each week on wikibon.com and siliconangle.com or you can email me directly at david.volante and siliconangle.com or DM me at dvolante or you can comment on my LinkedIn post. And please check out etr.ai for the very best survey data in the enterprise tech business. Some awesome stuff in there. This is Dave Vellante for theCUBE insights powered by ETR. Thanks for watching and we'll see you next time on breaking analysis.