 From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. The big three cloud players all announced earnings this past week. And as expected, the cloud growth is slowing. But don't kid yourselves. Hyperscale clouds remain the epicenter of innovation and tech. And foundation models like GPT will only serve to harden this fundamental fact. Our data suggests the deceleration in cloud is a function of two related factors, deceleration in cloud growth is what we're talking about here. Two factors, one, the macro spending environment has negatively impacted consumption and two, aggressive cloud optimization, which is being promoted by the big three cloud vendors in an attempt to lock in customers to longer-term commitments is having an effect. There is still no clear evidence in the numbers in the data that repatriation is a factor, rather the ability to quickly dial down spending and pause projects is an attractive feature of cloud computing and one that until now has never really been tested from a spending standpoint. Hello and welcome to this week's Wikibon Cube Insights, powered by ETR. In this Breaking Analysis, we try to explain the implications of this seemingly simple but nuanced dynamic. We'll review the latest hyperscale cloud data for the big three players, share our analysis of certain comments made by the cloud companies, CFOs and Andy Jassy in particular and show you the latest ETR data on spending and market presence. Here's a chart we showed last quarter, identifying the major factors impacting cloud demand. And today we want to focus in on the last one there, optimization. Somewhat newish cloud savings plans were introduced prior to the pandemic, late 2019ish, but they were largely overlooked during the COVID tech bubble because money was cheap and business was booming. But toward the end of 2021, we began to see early inning signs of optimization kicking in where customers took a harder look at the spectrum of pricing options. They kind of started out with the classic or starting out bottom right here. You can see this with the classic on demand. That's the most expensive, right? Just paying by the drink. And then spot pricing in the open market and then reserved instances, our eyes, and then savings plans, which yield the most credits. That's how these things go. So think of cloud pricing as always on demand, but with credits, it's like getting an instant coupon applied at checkout. And as we entered 2023, the shift toward more attractive pricing models really accelerated. And it's going to continue indefinitely in our view. Now cloud companies generally in AWS specifically have been transparent and even proactive about cloud optimization. The reason being, they're well aware of the customer spending climate and rather than fight fashion, they're leaning in and encouraging customers to sign up for one year or three year savings plans. The idea is commit to buying more and spend less per drink. Here's what all three hyperscale cloud companies, CFO said this week on their earnings call. Microsoft CFO Amy Hood said, in Azure customers continue to exercise some caution as optimization and new workload trends from the prior quarter continued as expected. Amazons Brian Olsavsky said, as expected customers continue to evaluate ways to optimize their cloud spend in response to these tough economic conditions in the first quarter. And Ruth Porat on Google Cloud quote, continued to see slower growth of consumption as customers optimized GCP costs reflecting the macro backdrop, which remains uncertain. So all three cited optimization and each company implied it was supportive of these customers trends. Amazon in particular emphasized its long game and our sources suggest that unquestionably, AWS is aggressively going after longer term deals to focus on lifetime value versus short-term revenue optimization. Having said that, optimization in and of itself is probably not as much of a revenue suppressor as you might think. Rather our data suggests it's the macro and the consumption trend that's hurting growth rates. This is a nuanced statement because they're definitely related but the importance is we believe the market is elastic and that as demand picks up, optimization will continue but in and of itself it won't negatively hit revenue. Rather when demand picks up optimization it's going to continue because the muscle memory is there for organizations but they'll consume more and that'll lift revenue. That's our working assumption at the moment. Okay, let's take a look at our quarterly hyperscale cloud data. Remember, we're one of the few firms that has been tracking IS and PAS revenue from the hyperscalers from the beginning and attempting to make apples to apples comparisons across the big three and now we added Alibaba, the big four clouds and then we share that data publicly for free. Awesome value we hope. So this chart shows our Q1 2023 revenue estimates for AWS, Azure, GCP and Alibaba as compared to the actuals. Note that Alibaba hasn't reported yet so there are still estimates. No change there. So you can see with the exception of GCP we were right on the numbers. AWS, we added 15% year on year growth and they came in at 16% or 21.4 billion. Azure we had at 30% they came in at 31% or 17.1 billion in GCP. We had a 28% growth but we've lowered that to 22% or 3.2 billion. We're going to come back to that in a moment. And by the way, these are a constant currency. We try to normalize for currency. Overall, we had the market growing at 21% and we've only slightly increased that to 45.2 billion for the quarter. We're now forecasting 192 billion for the year or 20.4% annual growth in 2023. So our Q1 estimates were slightly below what actually happened. We're lowering, somewhat lowering our year in forecast largely as a function of what we expect for Q2 and into the summer. Couple other points. Azure continues to gain share is now 80% of AWS's revenue by our estimates. Our latest read on Q2 is growth rates will continue to decelerate by around 400 basis points or 4 percentage points for those who don't like basis points. Now the action in the market today, Friday was interesting. Amazon and AWS earnings well exceeded expectations as AWS operating income was 5.1 billion or came in at 106% of Amazon's operating income. So this is relatively flat from Q4, the operating income. So sequentially it was comparable down a little bit but bigger than people expected. The stock went up, sort of shot up after hours but then retreated to the negative, to the red because of concerns over AWS's growth rates. So despite the consistent operating profit from AWS investors are concerned about the near term future. But as we've said, our data shows AWS is being very aggressive in trying to get customers to sign up for longer-term deals. And we see this as a positive long-term for the company. One other point is Google Cloud reported $191 million operating income reversing nearly half a billion dollar loss from last quarter. So good cost cutting by Google. And of course, all three companies, they pounded generative AI on their calls with AWS and the most recent entrant in the race was AWS with Bedrock. And it's interesting because it looked like Microsoft was behind, you know, they take last summer behind an AI and then from a business model standpoint cut to the front of the line with open AI and chat GPT and then all that buzz that they're getting all the marketing momentum. But Google is going to embed AI into everything as is Microsoft, but Google has been at this for a while as has AWS which exposed a different strategy. Essentially the same way it approaches cloud. Building blocks for developers with their announcement of new Silicon, new around Tranium and Inferentia, Bedrock, which is LLMs as a service, large language models as a service and then app builder support with something called Code Whisperer, kind of like this co-pilot thing. So somewhat different strategies with AWS being the most focused on letting you build your own which will be attractive to a lot of customers that don't want to allow their IP to leak. But Google and Microsoft undoubtedly will offer similar options as well, as well as they're kind of out of the box chat GPT, Bing integration and whatever Google decides to do with Bard. Now just coming back to Google for a moment we want to share something that we don't really hear anybody talking about and it's something that we pay close attention to because remember we're trying to get an apples to apples comparison with IS and PAS and only AWS makes that easy. Azure gives a growth rate and Microsoft gives a growth rate for Azure but Microsoft's overall cloud includes 365 and other software and Google doesn't give specific numbers on GCP. It has its overall cloud business which includes all of its applications and collaborative software. But take a look at how Alphabet's narrative has changed with respect to Google cloud platform. In Q4 2020 and prior, the language was like this, something to the effect of quote, with GCP growth remaining meaningfully above the growth rate for cloud overall. So meaningfully above. So we would infer from that and look at survey data and say, okay, what do we think that means? But it definitely means if cloud is growing at X that GCP was growing significantly above X, we would assume at least 10 points higher, 1,000 basis points. Then in Q4 2022, the narrative changed. Revenue growth in GCP was again greater than Google cloud reflecting strength in both infrastructure and platform services. And when we correlate that with some of the survey data we're like, hmm, feeling like maybe single digits as opposed to double digit growth. Now in Q1 2023, the statement was growth in GCP remained strong across geographies, industries, and products. And to us, this is an indication that for the first time GCP grew more slowly than Google cloud overall. Google cloud at a good quarter, evidently in terms of its applications, it's further up the stack with its work group products. And you can see this in the ETR data. The deceleration is not confined to Google, by the way. But if you go back and look at Azure when it was around the same size as GCP is this quarter, just over 3 billion. Azure was growing at 85% year over year at the time. So unfortunately for Google, that's the penalty for getting in late. And the challenge, of course, of the first tech downturn as Google's ramping up its cloud, really the first tech downturn since the cloud took off. In fact, the 2008 downturn was a benefit for the cloud because people were shifting CapEx to OpEx. But anyway, this next chart plots net score on the Y axis with provision or presence in the ETR data set on the horizontal axis. And we've highlighted the big three players with those squiggly lines that show the quarterly positions going back to 2019. So the bad news is that you can see the consistent deceleration, but all three have become more prominent in the data to the right, no surprise. But they're all, you know, because they're all playing the long game and they all have the resources to compete long-term. Now, remember that red dotted line at 40% means an elevated spending velocity. So all three remain above that line. We've also circled the so-called hybrid cloud folks that have a big on-prem presence and their momentum matches their kind of lower growth. And you can see they're well below the 40% line. And they were also late to cloud. And, you know, most of them are kind of in a steady state. Interesting, the Oracle has pulled to the right a little bit. You know, but generally speaking, they're sort of within a range for the most part. Now, and having said that, you know, the likes of Dell and HPE with GreenLake, Dell with Apex, relatively new, or new to the marketplace. So the buyers are just now getting their heads around, you know, on-prem cloud. So that's starting to show up in the data. Okay, now in thinking about how this all plays out in the future, let's take a look at some of the comments from Andy Jassy on the earnings call Thursday night. Jassy is sticking with the narrative that, quote, people sometimes forget that 90 plus percent of global IT spend is still on-premises. If you believe that equation is going to flip, which we do, we being Amazon, it's going to move to the cloud. And having the cloud infrastructure offering with the broadest functionality by a fair bit, the best operational performance and the largest partner ecosystem bodes well for us moving forward. By the way, we would agree with much of that, not necessarily all of it. But, and then one of the great attributes of the cloud is that you can scale seamlessly up or down as demand dictates, which is not the case with on-premise infrastructure. So a couple of things that we'd like to question here. First, that 90% figure, it's got to be changing. There's been 90% for the last two or three years. Cloud is growing much faster than on-prem. And the last several years, that 90%, it can't be flat because it's growing, cloud's growing so much faster than overall spend. So it's probably time to pick at that a little bit. So let's exclude telco for just a moment because that's kind of a different animal. But most IT spend is on services. And most services deals today, when you talk to companies in that services business, the Accentures, IBM, largely a services company, most deals have some type of public cloud component. Yeah, a lot of hybrid, but most of it, most of those deals have a public cloud component. And you look at AWS, they're going to be $90 billion this year. Azure's going to be $70 billion this year. They are now the largest enterprise tech vendors. Dell's the biggest, they're $100 billion. But if you exclude PCs, AWS is much, much bigger in the enterprise as is Azure. Now, a flip side of this is the second part of Jassy's quote that you can't scale up and down seamlessly with on-prem. Well, with services like GreenLake from HP and Apex from Dell, that's beginning to change. You know, sure, you got to install the equipment first, but once you seed that base, you know, that's going to take some time. But once you seed that base and you've done that, you're kind of, you know, you're simulating the cloud operating model, and that's definitely going to keep some folks spending on-prem. So the battle is just beginning here. Now, further challenging some of these assumptions, which is always a good thing to do, let's look at some of the ETR data on this and sort of poke at that 90%. In a drill down survey last fall, ETR asked customers their usage percentage between public and private cloud. And at that time, which was late last year, and then three years down the line. And we put a dotted line around those responses that said 70% or more would be on-prem. And it turns out, or are on-prem, and it turns out that in the fall of last year, that figure was 48%. And that was projected to decline to 25% by 2025. And only 22% of customers said they'd be mostly public cloud, i.e. 70% or more by 2025. And 80 to 85% see themselves as remaining hybrid. So look at that far-right, those two high bars at 14%, they basically stay flat. That's the all-in cloud. So that's kind of an interesting indicator as well. Now, AWS likes to use the phrase in the fullness of time, which most certainly extends beyond 2025. But we would say this, when you strip out services and isolate on compute networking and storage, well over 10% of spending is in the cloud, we think, probably closer to a third or more. Maybe even as this chart shows on the right-hand side, the mid-point averages could be 43% today, roughly or late last year, moving toward the mid-50s by 2025. Now, having said all that, when you start thinking about telecoms and Edge and satellites and a new set of emergent use cases, there's plenty of room for growth. But the big wave of cloud in terms of eliminating that undifferentiated heavy lifting in data centers has largely taken place. Is there more juice to squeeze out of that lemon? Yeah, there's some, but I mean, if you haven't really moved obvious applications to cloud by now, I don't know what you're thinking about. And so now the harder to move apps are probably next. And I think the on-prem guys are trying to make a real strong business case that you shouldn't move. And so now it's going to come down to how effective these incumbent vendors are at mimicking the cloud operating model and reducing the attractiveness of moving workloads to the cloud and to innovation for new data-driven workloads. So the cloud players, they have the leg up when it comes to this opportunity because they have the data, they have the tooling, they have the ecosystems and the massive cap X and infrastructure that continues to increase. And that brings us back to the hottest topic today, generative AI. We shared this chart a while back when we were opining about the future of semiconductors and the impact of arm designs in the data center and at the edge. And the point of the graphic is that most AI to date has been modeling in the cloud. And we predicted that over the next few years, the equation would flip to where AI inferencing would become a dominant force. And we highlighted NLP as a use case, this kind of bottom left is sort of, we're using mobile as the proxy, you know, smartphones, Alexa and other proxies from mobile to predict the ubiquitous use of AI in virtually all industries and applications. Now, admittedly, we didn't predict the chat GPT effect would storm the castle the way it has. But there are two points here. One, a lot of early generative AI activities is going to be happening in the cloud. And then eventually it's going to go across clouds and multiple clouds and the super cloud is going to extend out to the edge. It's early days and the cloud players, as he said, are the tools, the technologies, the partnerships and the scale economies to lead. Second point is massive data demands of lower power requirements distributed computing. They're all going to require new architectures from silicon to databases to apps all the way up the stack. Take Amazon's, you know, announcement, for example, the new chips for training and inference. They're timely, obviously given the AI hype but they're also instructive. As we've reported, AWS is on a new Silicon S curve and is leading Google, Microsoft and Alibaba are all falling with their own chip designs. They're all ARM based and the four hyperscalers are going to drive cost down. Cost now price might be a different story but their cost structures are going to be superior. And the other point is actually three points is we still believe that edge use cases will become a massively disruptive force and ARM based designs are going to be at the center of that disruption because of volume. Hey, look, Intel is doing everything it can to keep up but it doesn't have the volume advantage and there's no foreseeable path to Intel regaining the volume manufacturing leads. Certainly x86 doesn't appear it will happen and, you know, Intel is clearly challenged to do so. So can they do foundry? Can they cut costs? Can they chip away? Yes, but are they going to be able to lead in wafer volumes? ARM wafer volumes and TSM are the dominant economic forces right now thanks to Apple unless there's a radical event, I don't know, maybe like China invades and pirates TSM this is likely going to be the case for well over a decade. These things don't change overnight. Okay, let's bring it back now to cloud in the nearer term. The macro and the Fed are still the main drivers of buyer spending behavior. Now that said optimization as we said earlier is here to stay. Part of the IT muscle memory and it's going to continue. We expect cloud growth to decelerate in Q2. It's going to, by our forecast stay flat in Q3 and we think Q4 will bring an acceleration to cloud growth. Nothing crazy. We think we'll see growth rates up take a few percentage points in Q4 but it will depend of course on the broader economy what the Fed does, the stuff that we have no control over. All that said, cloud growth will continue to significantly outpace overall IT spending rates which are now projected to come in at mid 3% growth rates. Let's call it 3.5, 3.6% growth this year. While the hyperscalers will grow five to six X that rate. Foundation models are going to be a tailwind for all companies that can leverage them to cut costs and automate but they'll be especially beneficial to cloud players and their customers from Silicon to large language models and services up to the apps. Think about again, AWS's large language model stack the ARM based training and inferencing, bedrock LLM managed services and what we call co-pilot like functionality with code whisperer that can help write code. This model is going to be attractive to many builders especially those concerned about IP leakage but chat GPT and Bard models will also be simpler to access and alluring for many as well. And we fully expect both Google and Microsoft to offer sort of developer optionality and building blocks to build in-house models as well and build up their ecosystems. The outlook right now is mixed. Look, banks are down. Then you got GM that have beaten rays. You got autos are up, toothpaste and diapers and other consumer staples are more expensive. As is food, you go out to eat. It's like, wow, I don't remember being this expensive but yeah, that's the norm now. Housing is soft, advertising is down but yet meta-grew and had a nice quarter. Tech is generally beating earnings estimates, probably two thirds of the companies that have reported have beat but growth capital is drying up for these private companies. So look, maybe this is a signal that we're returning to let's call it a new normal where not everyone can just fall out of bed and do well. And when there's a downturn, one of the companies is negatively impacted by the macro. So I guess it's back to doing your own homework, analyzing the market, doing a risk analysis, placing bets and executing. Isn't that the way it's supposed to be? All right, that's a wrap. Many thanks to Alex Meyerson who's on production and manages the podcast. Ken Schiffman as well. Kristin Martin and Cheryl Knight helped get the word out on social media and in our newsletters and Rob Hof is our editor-in-chief over at siliconangle.com. Thank you to all. Remember, all these episodes are available as podcasts wherever you listen, just search breaking analysis podcast and check out the cube pod. John Furrier and I each week now we're in episode 10, I believe episode nine or 10. So we're just playing around with that. So check that out, the cube pod. I publish each week breaking analysis on wikibond.com and siliconangle.com. You want to reach out, you got an idea, you want to pitch us, email me directly david.volante at siliconangle.com or you can DM me at dvolante comment on our LinkedIn post if you got a good pitch, we'll respond and listen. If you don't, don't take it personally, we get hundreds every week. And please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for the cube insights powered by ETR. Thanks for watching everybody and we'll see you next time on breaking analysis.