Breaking Analysis with Dave Vellante (SiliconANGLE)

We’ve often said that the next ten years in cloud computing won’t be like the last ten. Cloud has firmly planted its footprint on the other side of the chasm with the momentum of the entire multi-trillion dollar technology business behind it. Both sellers and buyers are leaning in by adopting cloud technologies and many are building their own value layers on top of cloud. In the coming years we expect innovation will continue to coalesce around the big 3 U.S. clouds, plus Alibaba in APAC, with the ecosystem building value on top of the hardware, software and tools provided by the hyperscalers. Importantly, we don’t see this as a race to the bottom. Rather our expectation is that the large public cloud players will continue to take cost out of their platforms through innovation, automation and integration. Other cloud providers and the ecosystem, including traditional IT buyers, will leverage hyperscale clouds and mine opportunities in their respective markets. This is not a zero sum game. 

In this Breaking Analysis we’ll update you on our latest projections in the cloud market, share some new ETR survey data with some surprising nuggets; and drill into the important cloud database landscape. 

The rise of Kubernetes came about through a combination of forces that were in hindsight, quite a long shot. AWS’ dominance created momentum for cloud native application development and the need for simpler experiences beyond easily spinning up compute as a service. This wave crashed into innovations from a startup named Docker and a reluctant open source benefactor in Google that needed a way to change the game on Amazon in the cloud. Factor in Red Hat, which needed a path beyond Linux and was just about to opt for an alternative to Kubernetes to power OpenShift. Finally, figure out a governance structure to herd all the cats in the ecosystem so you can win out over other competition and create a de facto standard. Make all that happen and you get the remarkable ascendancy of Kubernetes. 

Such was the story unveiled recently in a new two-part documentary series from Honeypot simply titled “Kubernetes.” In this Breaking Analysis we tap the back stories of this documentary, which explains the improbable events leading to the creation of Kubernetes. We’ll share commentary from early Kubernetes committers and key players who came on theCUBE to piece together how it all happened. Finally, we’ll present new survey data from ETR on containers.  

The pandemic precipitated what is shaping up to be a permanent shift in cyber security spending patterns. As a direct result of hybrid work, CISOs have invested heavily in endpoint security, identity access management, cloud security and further hardening the network beyond the HQ. Moreover, the need to build security into applications from the start, rather than bolting protection on as an afterthought, has led to vastly heightened awareness around DevSecOps. Finally, attacking security as a data problem with automation and AI is fueling new innovations in cyber products and services; and is spawning well-funded, disruptive startups. 

In this Breaking Analysis we present our quarterly findings on the security sector. We’ll share the latest ETR survey data, identify the companies with customer spending momentum and share some of the market movers.

In its early days, robotic process automation emerged from rudimentary screen scraping, macros and workflow automation software. Once a script-heavy and limited tool that was almost exclusively used to perform mundane tasks for individual users, RPA has evolved into an enterprise-wide megatrend that puts automation at the center of digital business initiatives. 

In this Breaking Analysis we present our quarterly update of the trends in RPA and share the latest survey data from Enterprise Technology Research. 

Intel’s future would be a disaster without Pat Gelsinger. Even with his clear vision, fantastic leadership, deep technical and business acumen and amazing positivity, the company’s future is in serious jeopardy. It’s the same story we’ve been telling for years. Volume is king in the semiconductor industry and Intel no longer is the volume leader. Despite Intel’s efforts to change that dynamic with several recent moves, including making another go at its foundry business, the company is years away from reversing its lagging position relative to today’s leading foundries and design shops. Intel’s best chance to survive as a leader in our view will come from a combination of a massive market, continued supply constraints, government money and luck – perhaps in the form of a deal with Apple in the mid- to long term. 

In this Breaking Analysis we’ll update you on our latest assessment of Intel’s competitive position and unpack nuggets from the company’s February investor conference.

Snowflake…they love the stock at 400 and hate it at 165. That’s the nature of the business isn’t it? Especially in this crazy cycle over the last two years of lockdowns, free money, exploding demand and now rising inflation and rates. But with the Fed providing some clarity on its actions, the time has come to really look at the fundamentals of companies and there’s no tech company more fun to analyze than Snowflake. 

In this breaking analysis we take look at the action of Snowflake’s stock since its IPO, why it’s behaved the way it has, how some sharp traders are looking at the stock and most importantly, what customer demand looks like. 

There are very few political issues that get bipartisan support these days, never mind consensus spanning geopolitical boundaries. But whether we’re talking across the aisle or over the pond, there seems to be common agreement that the power of big tech firms should be regulated. However the government’s track record when it comes to antitrust aimed at tech is mixed, at best. History shows that market forces, rather than public policy, have been much more effective at curbing monopoly power in the technology industry. Moreover, the standard for antitrust action has always been demonstrating consumer harm. Many of today’s policy makers are challenging that notion and using market dominance and the potential for consumer harm as the new benchmark for intervention. 


In this week’s Breaking Analysis we welcome in frequent CUBE contributor David Moschella, author and senior fellow at the Information Technology and Innovation Foundation. We explore several issues including the efficacy of governments’ antitrust actions against big tech, what types of remedies have been and can be most effective and a first pass assessment of the new rules EU regulators just agreed to try and rein in big tech companies.

Fresh survey data from ETR shows a clear deceleration in spending and a more cautious posture from technology buyers. Just this week we saw sell side downgrades in hardware companies like Dell and HP; and revised guidance from high flier UiPath, citing exposure to Russia, Europe and certain sales execution challenges. But these headlines we think are a canary in the coal mine pointing to broader tech spending softness. According to ETR analysis and channel checks in theCUBE community, the real story is these issues are not isolated. Rather we’re seeing signs of caution from buyers across the board in enterprise tech. 

In this Breaking Analysis we are the bearers of bad news, relatively speaking. We’ll share a first look at new data that suggest a tightening in tech spending, calling for 6% growth this year, which is below our January prediction of 8% for 2022. 

The recent security breach of an Okta third party supplier has been widely reported. The criticisms of Okta’s response have been harsh and the impact on Okta’s value has been obvious. Investors shaved about $6B off the company’s market cap during the week the hack was made public. We believe Okta’s claim that the customer technical impact was “near zero,” may be semantically correct. However, based on customer data, we feel Okta has a blind spot. There are customer ripple effects that require clear action, which are missed in Okta’s public statements. Okta’s product portfolio remains solid. It is a clear leader in the identity space. But in our view, one part of the long journey back to credibility requires Okta to fully understand and recognize the true scope of this breach on its customers. 

In this week’s Breaking Analysis we welcome our ETR colleague Erik Bradley to share new data from the community. In addition, we’ll analyze some of the statements made by Okta CEO Todd McKinnon in an interview with Emily Chang on Bloomberg to see how they align with what customers tell us.

The introduction and socialization of data mesh has caused practitioners, business technology executives and technologists to pause and ask some probing questions about the organization of their data teams, their data strategies, future investments and their current architectural approaches. Some in the technology community have embraced the concept, others have twisted the definition while still others remain oblivious to the momentum building around data mesh. 

We are in the early days of data mesh adoption. Organizations that have taken the plunge will tell you aligning stakeholders is a non-trivial effort. But one that is necessary to break through the limitations that monolithic data architectures and highly specialized teams have imposed over frustrated business and domain leaders. However, practical data mesh examples often lie in the eyes of the implementer and may not strictly adhere to the principles of data mesh. Part of the problem is the lack of open technologies and standards that can accelerate adoption and reduce friction.

This is the topic of today’s Breaking Analysis where we investigate some of the key technology and architectural questions around data mesh. To do so, we welcome back the founder of data mesh and Director of Emerging Technologies at ThoughtWorks, Zhamak Dehghani. 

The ascendancy of cloud and SaaS has shone new light on how organizations think about, pay for, and value hardware. Once-sought-after skills for practitioners with expertise in hardware troubleshooting, configuring ports, tuning storage arrays and maximizing server utilization have been superseded by demand for cloud architects, DevOps pros and developers with expertise in microservices, container app development and similar skills. Even a company like Dell, the largest hardware company in enterprise tech, touts that it has more software engineers than those working in hardware. It begs the question: Is hardware going the way of COBOL? Well, not likely — software has to run on something. But the labor and skills needed to deploy, troubleshoot and manage hardware infrastructure is shifting quite dramatically. 

At the same time we’ve seen the value flow also changing in hardware. Once a world dominated by x86 processors, value is flowing to alternatives like Nvidia and Arm-based designs. Moreover, other components like NICs, accelerators and storage controllers are becoming more advanced, integrated and increasingly important. 

The question is: Does it matter? If so, why does it matter and to whom? What does it mean to customers, workloads, OEMs and the broader society? 

In this Breaking Analysis we try to answer these questions and to do so we’ve organized a special CUBE Power Panel of industry analysts and experts to address the question: Does Hardware (Still) Matter?

Despite a mixed bag of earnings reports from tech companies, negative GDP growth this past quarter and rising inflation…the cloud continues its relentless expansion on the IT landscape. AWS, Microsoft and Alphabet have all reported earnings and, when you include Alibaba’s cloud in the mix, the big 4 hyperscalers are on track to generate $167B in revenue this year based on our projections. But as we’ve said many times the definition of cloud is expanding. And hybrid environments are becoming the norm at major organizations. We’re seeing the largest enterprise tech companies focus on solving for hybrid and every public cloud company now has a strategy to bring their environments closer to where customers’ workloads live – in data centers and the edge. 

Hello and welcome to this week’s Wikibon CUBE Insights, Powered by ETR. In this Breaking Analysis we’ll update you on our latest cloud projections and outlook. We’ll share the latest ETR data and some commentary on what’s happening in the “hybrid zone” of cloud.

In the pre-cloud era, hardware companies would run benchmarks showing how database and application performance ran best on their systems relative to competitors and previous generation boxes. They would make a big deal out of it and the independent software vendors would do a “golf clap” in the form of a joint press release. It was a game of leapfrog amongst hardware competitors that became pretty commonplace over the years. The Dell-Snowflake deal underscores that the value prop between hardware companies and ISVs is changing and has much more to do with distribution channels and the amount of data that lives on-prem in various storage platforms. For cloud-native ISVs like Snowflake, they are realizing that despite their cloud-only dogma, they have to grit their teeth and deal with on-premises data or risk getting shut out of evolving data architectures. 

In this Breaking Analysis we unpack what little is known about the Snowflake announcement from Dell Technologies World… and discuss the implications of a changing cloud ecosystem landscape. We’ll also share some new ETR data for cloud and database platforms that shows Snowflake has actually entered the earth’s orbit when it comes to spending momentum on its platform. 

Cybersecurity stocks have been sending mixed signals as of late…Mostly negative like much of tech. But some, such as Palo Alto Networks, despite a tough go of it recently, have held up better than most tech names. Others like CrowdStrike had been outperforming broader tech in March but then flipped in May. Okta’s performance was somewhat tracking along with CrowdStrike for most of the past several months but then the Okta hack changed the trajectory of that name. Zscaler has crossed the critical $1B ARR revenue milestone and sees a path to $5B, but the company’s stock fell sharply after its last earnings report and has been on a downtrend since last November…Meanwhile CyberArk’s recent beat and raise was encouraging and the stock acted well after its last report. 

Security remains the #1 initiative priority amongst IT organizations and the spending momentum for many high flying cyber names remains strong. So what gives in cybersecurity? In this Breaking Analysis we focus on security and will update you on the latest data from ETR to try and make sense out of the market and read into what this all means in both the near and long term for some of our favorite names in the sector.

In the words of  CUBE analyst and former CTO David Nicholson, Broadcom buys old cars. Not to restore them to their original beauty…nope…they buy classic cars to extract the platinum that’s inside the catalytic converter. Broadcom’s planned $61B acquisition of VMware will mark yet another new era for the virtualization leader, a mere seven months after finally getting spun out as a fully independent company by Dell. For VMware this means a dramatically different operating model, with financial performance and shareholder value creation as the dominant and perhaps sole agenda. For customers it will mean a more focused portfolio, less aspirational vision pitches and most certainly higher prices. 

In this Breaking Analysis we’ll share data, opinions and customer insights about this blockbuster deal and forecast the future of VMware, Broadcom and the broader ecosystem. 

Earnings season has shown a conflicting mix of signals for software companies. Most firms are expressing caution over macro headwinds citing a combination of Ukraine, inflation, interest rates, EMEA softness, currency, supply chain and general demand for technology. But MongoDB, along with a few other names appeared more sanguine, thanks to a beat in the recent quarter and a cautious but upbeat outlook for the near term. 

In this Breaking Analysis, ahead of MongoDB World 2022, we drill into the company’s business and what ETR survey data tells us in the context of overall demand and the patterns from other software companies.  

When Frank Slootman took ServiceNow public, many people undervalued the company, positioning it as just a better help desk tool. It turns out the firm actually had a massive TAM expansion opportunity in ITSM, HR, logistics, security, marketing and customer service management. NOW’s stock price followed the stellar execution under Slootman and CFO Mike Scarpelli’s leadership. When they took the reins at Snowflake, expectations were already set that they’d repeat the feat but this time, if anything, the company was overvalued out of the gate. 

It can be argued that most people didn’t really understand the market opportunity any better this time around. Other than that it was a bet on Slootman’s track record of execution…and data. Good bets; but folks really didn’t appreciate that Snowflake wasn’t just a better data warehouse. That it was building what the company calls a data cloud…and we’ve termed a data supercloud. 

In this Breaking Analysis and ahead of Snowflake Summit, we’ll do four things: 1) Review the recent narrative and concerns about Snowflake and its value; 2) Share survey data from ETR that will confirm almost precisely what the company’s CFO has been telling anyone who will listen; 3) Share our view of what Snowflake is building – i.e. trying to become the de facto standard data platform; and 4) Convey our expectations for the upcoming Snowflake Summit next week at Caesar’s Palace in Las Vegas.

Originally published on May 21, 2022
Last year we noted in a Breaking Analysis that the cloud ecosystem is innovating beyond the notion of multicloud. We’ve said for years that multicloud is really not a strategy but rather a symptom of multivendor. We used the term supercloud to describe an abstraction layer that resides above and across hyperscale infrastructure, connects on premises workloads and eventually stretches to the edge. Our premise is that supercloud goes beyond running services in native mode on each individual cloud. Rather supercloud hides the underlying primitives and APIs of the respective cloud vendors and creates a new connection layer across locations. 

Since our initial post, we’ve found many examples within the ecosystem of technology companies working on so-called supercloud in various forms. Including some examples that actually do not try to hide cloud primitives but rather are focused on creating a consistent experience for developers across the devsecops tool chain, while preserving access to low level cloud services. 

In this Breaking Analysis we share some recent examples of supercloud that we’ve uncovered. We also tap theCUBE network to access direct quotes about supercloud from the many CUBE guests we’ve recently had on the program. Here we test the concept’s technical and business feasibility. We’ll also post some recent ETR data to put into context some of the players we think are going after this opportunity and where they’re at in their supercloud buildout. 

Much of the energy around data innovation that dispersed with the decline of Hadoop’s relevance is coalescing in a new ecosystem spawned by the ascendency of Snowflake’s Data Cloud. What was once seen as a simpler cloud data warehouse and good marketing with Data Cloud, is evolving rapidly with new workloads, a vertical industry focus, data applications, monetization and more. The question is will the promises of data be fulfilled this time around or is it same wine, new bottle? 

Despite fears of inflation, supply chain issues, skyrocketing energy and home prices and global instability caused by the Ukraine crisis, CIOs and IT buyers continue to expect overall spending to increase more than 6% in 2022. While this is lower than our 8% prediction made in January of this year, it remains in line with last year’s roughly 6-7% growth and is holding firm with the expectations reported by tech executives last quarter. 

In this Breaking Analysis we update you on our latest look at tech spending with a preliminary take from ETR’s latest macro drill down survey. We’ll share some insights as to which vendors have shown the biggest change in spending trajectory and ask the technical analysts in our community to give us a read on what they think it means for technology stocks going forward. 

After a two year epic run in tech, 2022 has been an epically bad year in the market. Through yesterday, the Nasdaq composite is down 30%, the S&P 500 is off 21%, the DJIA down 16% and the poor HODLers of BTC have had to endure a nearly 60% decline year to date. 

As we exited the isolation economy last year, supercloud is a term we introduced to describe something new that was happening in the world of cloud. In this Breaking Analysis we address the ten most frequently asked questions we get on supercloud. 

Organizations have considerable room to improve their performance without making expensive changes to their talent, structure or fundamental business model. You don’t need a slew of consultants to tell you what to do. You already know. What you need is to immediately ratchet up expectations, energy, urgency and intensity. Fight mediocrity every step of the way. Amp it up and the results will follow. 

This is the fundamental premise of a hard hitting new book written by Frank Slootman, CEO of Snowflake, and published earlier this year. It’s called, Amp it Up, Leading for Hypergrowth by Raising Expectations, Increasing Urgency and Elevating Intensity. 

At Snowflake Summit last month, I was invited to interview Frank on stage about his book. I’ve read it several times and if you haven’t picked it up, you should. Even if you have read it, in this Breaking Analysis we’ll dig deeper into the book and share some clarifying insights and unpublished nuances of Frank’s philosophy. You’ll hear directly from Slootman himself with excerpts from my one on one conversation with him. 

After a two year hiatus, AWS re:Inforce is back on as an in-person event in Boston next week. Like the all-star break in baseball, re:Inforce gives us an opportunity to evaluate the cybersecurity market overall, the state of cloud security and what AWS is up to in the sector. 

In this Breaking Analysis, we’ll share our view of what’s changed since our last cyber update in May, we’ll look at the macro environment, how it’s impacting cybersecurity plays in the market, what the ETR data tells us and what to expect at next week’s AWS re:Inforce.

The rapid pace of cloud adoption has changed the way organizations approach cybersecurity. Specifically, the cloud is increasingly becoming the first line of cyber defense. As such, along with communicating to the board and creating a security-aware culture, the CISO must ensure that the shared responsibility model is being applied properly. The DevSecOps team has emerged as the critical link between strategy and execution, while audit becomes the “free safety” in the equation – i.e. the last line of defense. 

In this Breaking Analysis we share our puts and takes from AWS re:Inforce with an update on the latest hyperscale IaaS market shares; and insights from ETR survey data. We’ll also dig deeper into some technical aspects of AWS Nitro, a system we believe is one of AWS’ secret weapons, with a focus on confidential computing and what it means for the future of systems architecture. 

The term supercloud is relatively new, but the concepts behind it have been bubbling for years. Early last decade when NIST put forth its original definition of cloud computing, it said services had to be accessible over a public network…essentially cutting the on-prem crowd out of the conversation. A guy named Chuck Hollis, a CTO at EMC and prolific blogger objected to that criterion and laid out his vision for what he termed a private cloud. In that post he showed a workload running both on premises and in a public cloud, sharing the underlying resources in an automated and seamless manner – what later became more broadly known as hybrid cloud.

That vision, as we now know, really never materialized and we were left with multi-cloud…sets of largely incompatible and disconnected cloud services running in separate silos. The point is, what Hollis put forth – i.e. the ability to abstract underlying infrastructure complexity and run workloads across multiple heterogeneous estates with an identical experience – is what supercloud is all about.

At our inaugural Supercloud22 event we sought community input to evolve the concept of a supercloud by iterating on the definition, the salient attributes and examples of what is and is not a supercloud. We asked several technologists including experts from VMware, Snowflake, Databricks, HashiCorp, Confluent, Intuit, Cohesity and others to help test the supercloud definition, operational models, service models and principles. 

In this Breaking Analysis we unpack our discussions with these technology leaders and apply their input to iterate the definition of supercloud. We then go in-depth to examine Snowflake’s Data Cloud architecture as a leading example of supercloud.

Black Hat 2022 was held in Las Vegas last week, at the same time as theCUBE’s supercloud event. Unlike AWS re:Inforce, where words are carefully chosen to put a positive spin on security, Black Hat exposes all the warts of cybersecurity and openly discusses its hard truths. It’s a conference attended by technical experts who proudly share some of the vulnerabilities they’ve discovered and of course by numerous vendors marketing their products and services. 

In this Breaking Analysis we summarize what we learned from discussions with several people who attended Black Hat and our analysis from reviewing dozens of keynotes, articles, videos, session talks, Dark Reading interviews and data from a recent Black Hat attendees survey conducted by Black Hat and Informa. We’ll also share data from ETR in a recent post discussing how Zscaler became the last line of defense for a manufacturing firm.

We’ll end with a discussion of what it all means for the challenges around securing the Supercloud.

While the precise direction of VMware’s future is unknown, given the planned Broadcom acquisition, one thing is clear; the subject of what Hock E. Tan plans will not be the main focus of the agenda at the upcoming VMware Explore event next week in San Francisco. We believe that despite any uncertainty, VMware will lay out for its customers what it sees as its future. And that future is multi-cloud or cross cloud services; what we would call supercloud. 

In this Breaking Analysis we drill into the latest ETR survey data on VMware. We’ll share with you the next iteration of the supercloud definition based on feedback from dozens of contributors. And we’ll give you our take on what to expect at VMware Explore next week. 

The negative sentiment in tech stocks, caused by rising interest rates, less attractive discounted cash flow models and more tepid forward guidance, is easily measured by public market valuations. And while there’s lots of talk about the impact on private companies, their cash runways and 409A valuations, measuring the performance of non-public companies isn’t as easy. IPOs have dried up and public statements by private companies accentuate the good and hide the bad. Real data, unless you’re an insider, is hard to find. 

In this Breaking Analysis we unlock some of the secrets that non-public, emerging tech companies may or may not be sharing. We do this by introducing you to a capability from ETR that we’ve not previously exposed in Breaking Analysis. It’s called the ETR Emerging Technology Survey and is packed with sentiment and performance data based on surveys of more than 1,000 CIOs & IT buyers covering more than 400 private companies. The survey will highlight metrics on the evaluation, adoption and churn rates for private companies and the mindshare they’re able to capture. 

We’ve invited back our colleague Erik Bradley of ETR to help explain the survey and the data we’re going to cover in this post.

In just over ten years, CrowdStrike has become a leading independent security firm. It has more than $2B in annual recurring revenue, nearly 60% ARR growth, a roughly $40B market capitalization, very high retention and a path to $5B in revenue by mid-decade. The company has joined Palo Alto Networks as a gold standard pure play cyber firm.

It has achieved this lofty status with an architecture that enables it to go beyond point product. Combine this with outstanding go to market, solid financial execution, some sharp acquisitions and an ever-increasing total available market and you have the formula for a great company.

In this Breaking Analysis and ahead of Fal.Con, CrowdStrike’s user conference, we take a deeper look into the company, its performance, its platform and customer survey data from our partner ETR.

Like a marathon runner pumped up on adrenaline, UiPath sprinted to the lead in what is surely going to be a long journey toward enabling the modern automated enterprise. In doing so, the company has established itself as a leader in enterprise automation, while at the same time getting out over its skis on critical execution items and disappointing investors along the way. In our view, the company has plenty of upside potential but will have to slog through its current challenges including restructuring its go to market, prioritizing investments, balancing growth with profitability and dealing with a difficult macro environment. 

In this Breaking Analysis and ahead of Forward5, UiPath’s customer conference, we once again dig into RPA and automation leader UiPath, to share our most current data and view of the company’s prospects, its performance relative to the competition and market overall.

Virtually all tech companies have expressed caution on their respective earnings calls. And why not… the macroeconomic environment is full of uncertainties and there’s no upside to providing aggressive guidance when sellers punish even the slightest miss. Moreover, the spending data confirms the market is softening across the board, so it’s becoming expected that CFOs will guide cautiously. But companies facing execution challenges can’t hide behind the macro. Which is why it’s important to understand which firms are best positioned to maintain momentum through the headwinds and come out the other side stronger. 

In this Breaking Analysis we’ll do three things: 1) Share a high-level view of the spending squeeze almost all sectors are experiencing; 2) Highlight some of those companies that continue to show notably strong momentum – and relative high spending velocity on their platforms – albeit less robust than last year; and 3) give you a peek at how one senior technology leader in the financial sector sees the competitive dynamic between AWS, Snowflake and Databricks. 

Is the glass half full or half empty? Well, it depends on how you want to look at it. CIOs are tapping the brakes on spending that’s clear. The latest macro survey from ETR quantifies what we already know to be true, that IT spend is decelerating. CIOs and IT buyers forecast that their tech spend will grow by 5.5% this year, a meaningful deceleration from their year end 2021 expectations…but these levels are still well above historical norms – so while the feel good factor may be in some jeopardy, overall things are pretty good – at least for now. 

In this Breaking Analysis, we update you on the latest macro tech spending data from Enterprise Technology Research, including strategies organizations are employing to cut costs…and which project categories continue to see the most traction.

Dave Vellante provides his take on the transformation of Dell to Dell EMC to Dell Technologies, the impact of the VMware spin out and what the future holds for this bellwether infrastructure player.

This past week, we saw two of the “Big 3” cloud providers present an update of their respective cloud visions, business progress, announcements and innovations. The content at these events had many overlapping themes including modern cloud infrastructure at global scale, applying advanced machine intelligence, end-to-end data platforms, the future of work, automation and a taste of the metaverse/Web 3.0. And more. 

Despite the striking similarities, the differences between these two cloud platforms, and that of AWS, remain significant with Microsoft leveraging its massive application software footprint to dominate virtually all markets; AndGoogle doing everything in its power to keep up with the frenetic pace of today’s cloud innovation which was set into motion a decade and a half ago by AWS. 

In this Breaking Analysis, we unpack the immense amount of content presented by the CEOs of Microsoft and Google Cloud at Microsoft Ignite and Google Cloud Next. We’ll also quantify with ETR survey data, the relative position of these two cloud giants in four key sectors – Cloud IaaS, BI analytics, data platforms and collaboration software.

The overall technology spending outlook is deteriorating. And yet there are positive signs making things unpredictable. The negative sentiment is of course being driven by macroeconomic factors and earnings forecasts that have been coming down all year while interest rates keep rising. Making matters worse is many people think earnings estimates are still too high. It’s understandable why there’s so much uncertainty. Technology continues to boom. Digital transformations are happening in earnest. Leading companies have momentum and long cash runways. Moreover, the CEOs of these leading companies are still really optimistic. But strong guidance in an environment of uncertainty is risky and makes navigation more challenging. 

In this Breaking Analysis we try to put some guardrails on the market by sharing takeaways from from ETRs latest spending survey, which was released to their private clients on the 21st of October. Today we’re going to review the macro spending data, convey where CIOs think their cloud spend is headed, look at the actions organizations are taking to manage uncertainty and then review some of the technology companies that have the most positive and negative outlooks in the ETR data set. 

Have you ever driven on the highway and traffic suddenly slows way down? And then after a little while it picks up again and you’re cruising along thinking…ok that was weird but it’s clear sailing now…only to find out in a bit that that traffic is building up again, forcing you to pump the brakes as the traffic patterns ebb and flow? Well welcome to the seesaw economy. The Fed induced fire that prompted a rally in tech is being purposely extinguished by that same Fed and virtually every sector of the tech industry is having to reset its expectations – including the cloud. 

In this Breaking Analysis we’ll review the implications of this week’s earnings announcements from the big 3 cloud players. The growth of AWS and Azure slowed while Google Cloud Platform’s growth accelerated. We’ll explain why GCP’s growth is still not fast enough. We’ll update you on our quarterly IaaS forecasts and share the latest cloud survey data from ETR.

Over the past decade, Cloudflare has built a global network that has the potential to become the fourth U.S.-based hyperscale-class cloud. In our view, the company is building a durable revenue model with hooks into many important markets. These include the more mature DDoS protection space, but also extend to growth sectors such as zero trust, a serverless platform for application development and an increasing number of services such as database and object storage. 

In essence, Cloudflare can be thought of as a giant, distributed supercomputer that can connect multiple clouds and act as a highly efficient scheduling engine– allocating and optimizing resources at scale. Its disruptive DNA is increasingly attracting novel startups and established global firms looking for a reliable, secure, high performance, low latency and more cost effective alternative to AWS and legacy infrastructure solutions. 

In this Breaking Analysis we initiate deeper coverage of Cloudflare. While the stock got hammered this past week on tepid guidance, we are optimistic about the company’s future. In this post, we’ll briefly explain our take on the company and its unique business model. We’ll then share some peer comparisons with both a financial snapshot and some fresh ETR survey data. Finally we’ll show some examples of how we think Cloudflare could be a disruptive force with a supercloud-like offering that, in many respects, is what multi-cloud should have been. 

A better than expected earnings report in late August got people excited about Snowflake again but the negative sentiment in the market has weighed heavily on virtually all growth tech stocks.  Snowflake is no exception. As we’ve stressed many times, the company’s management is on a long term mission to simplify the way organizations use data. Snowflake is tapping into a multi-hundred billion dollar total available market and continues to grow at a rapid pace. In our view the company is embarking on its third major wave of innovation, data apps, while its first and second waves are still bearing significant fruit. For short term traders focused on the next 90 or 180 days, that probably doesn’t matter much. But those taking a longer view are asking, should we still be optimistic about the future of this high flier or is it just another over-hyped tech play? 

In this Breaking Analysis we take a look at the most recent survey data from ETR to see what clues and nuggets we can extract to predict the near future and the long term outlook for Snowflake.

The ascendency of AWS under the leadership of Andy Jassy was marked by a tsunami of data and corresponding cloud services to leverage data. Those services mainly came in the form of primitives – i.e. basic building blocks that were used by developers to create more sophisticated capabilities.

AWS in the 2020s, led by CEO Adam Selipsky, will be marked by four high level trends in our view: 1) A rush of data that will dwarf anything previously seen; 2) Doubling down on investments in the basic elements of cloud – compute, storage, database, security, etc; 3) Greater emphasis on end-to-end integration of AWS services to make data accessible to more professionals and further accelerate cloud adoption; and 4) Significantly deeper business integration of cloud, beyond IT, as an underlying element of organizational transformation.

In this Breaking Analysis we extract and analyze nuggets from John Furrier’s annual sit down with the CEO of AWS. We’ll share data from ETR and other sources to set the context for the market and competition in cloud and we’ll give you our glimpse of what to expect at re:Invent 2022. 

While by no means a safe haven, the cybersecurity sector has outpaced the broader tech market by a meaningful margin. That is up until very recently. Cyber security remains the number one technology priority for the c-suite but as we’ve previously reported, the CISO’s budget has constraints; just like other technology investments. Recent trends show that economic headwinds have elongated sales cycles, pushed deals into future quarters and, just like other tech initiatives, are pacing cybersecurity investments and breaking them into smaller chunks. 

In this Breaking Analysis we explain how cybersecurity trends are reverting to the mean and tracking more closely with other technology investments. We’ll make a couple of valuation comparisons to show the magnitude of the challenge and which cyber firms are feeling the heat, and which aren’t as much. We’ll then show the latest survey data from ETR to quantify the contraction in spending momentum and close with a glimpse at the landscape of emerging cybersecurity companies that could be ripe for acquisition, consolidation or disruptive to the broader market.

Palo Alto Networks has earned a reputation as the leader in security. You can measure this in revenue, market cap, execution and, most importantly, conversations with CISOs. The company is on track to double its revenues to nearly $7B in FY23 from FY20. This despite macro headwinds which will likely continue through next year. Palo Alto owes its position to a clarity of vision and strong execution of a TAM expansion strategy bolstered by key acquisitions and integrations into its cloud & SaaS offerings.  

In this Breaking Analysis, and ahead of Palo Alto Ignite, we bring you the next chapter on top of last week’s cybersecurity update. We’ll dig into the ETR spending data on Palo Alto Networks, provide a glimpse of what to look for at Ignite and posit what Palo Alto needs to do to stay on top of the hill.

Nailing technology predictions in 2022 was tricky business. Projections on the performance of markets, identifying IPO prospects and making binary forecasts on data, AI, the macro spending climate, along with other related topics in enterprise tech, carried much uncertainty. 2022 was characterized by a seesaw economy where central banks were restructuring their balance sheets, the war in Ukraine fueled inflation, supply chains were a mess and the unintended consequences of digital acceleration are still being sorted. 

In this Breaking Analysis we continue our annual tradition of openly grading our previous year’s enterprise tech predictions. You may or may not agree with our self-grading system but we give you the data to draw your own conclusions. 

With Andy Thurai, VP & Principal Analyst, Constellation Research

A decade of big data investments combined with cloud scalability, the rise of more cost effective processing and the introduction of advanced tooling has catapulted machine intelligence to the forefront of technology investments. No matter what job you have, your operation will be AI powered within five years and machines may be doing your job in the future. 

Artificial intelligence is being infused into applications, infrastructure, equipment and virtually every aspect of our lives. AI is proving to be extremely helpful at controlling vehicles, speeding medical diagnoses, processing language, advancing science and generally raising the stakes on what it means to apply technology for business advantage. 

But business value realization has been a challenge for most organizations due to lack of skills, complexity of programming models, immature technology integration, sizable up front investments, ethical concerns and lack of business alignment. Mastering AI technology and a focus on features will not be a requirement for success in our view. Rather figuring out how and where to apply AI to your business will be the crucial gate. That means understanding the business case, picking the right technology partner, experimenting in bite sized chunks and quickly identifying winners to double down on from an investment standpoint. 

In this Breaking Analysis we update you on the state of AI with a focus on interpreting the latest ETR survey data around ML/AI and data. We’ll explore what it means for the competitive environment and what to look for in the future. To do so we invite into our studios Andy Thurai of Constellation Research. Andy covers AI deeply, he knows the players and the pitfalls of AI investment.

Recent conversations with IT decision makers show a stark contrast between the period exiting 2023 versus the mindset 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 take priority over cleaning up legacy technical debt. The bottom line is, for the moment at least, the mindset is not to cut everything, rather it’s to put a pause on cleaning up legacy hairballs and continue to fund initiatives to drive monetization. Cloud has become fundamental and getting data “right” is a consistent theme that appears to be an underpinning of initiatives getting funded today. 

In this Breaking Analysis we tap recent discussions from two primary sources: year-end ETR roundtables with IT decision makers and conversations on theCUBE with data, cloud and IT architecture practitioners. 

Enterprise tech practitioners, like most of us, want to make their lives easier so they can focus on delivering more value to their business. They want to tap best of breed services in the public cloud and at the same time connect their on-prem intellectual property to emerging applications which drive top line revenue and bottom line profits. But creating a consistent experience across clouds and on-prem estates has been an elusive capability for most organizations, forcing tradeoffs and injecting friction into the system. The need to create seamless experiences is clear and the technology industry is starting to respond with platforms, architectures and visions of what we call Supercloud. 

In this Breaking Analysis we give you a preview of Supercloud2, share key findings leading up to the event and highlight some of the areas we’ll be probing in the live program.

Making predictions about the future of enterprise tech is more challenging if you strive to lay down forecasts that are measurable. In other words if you make a prediction, you should be able to look back a year later and say with some degree of certainty whether the prediction came true or not. With evidence to back that up. 

In this Breaking Analysis we aim to do just that with predictions about the macro IT spending environment, cost optimization, security – lots to talk about there – generative AI, cloud and supercloud, blockchain adoption, data platforms, including commentary on Databricks, Snowflake and other key players, automation, events and we may even have some bonus predictions. 

To make all this happen we welcome back for the third year in a row, Erik Bradley our colleague from ETR.  As well, you can check out how we did with our 2022 predictions. 

The unraveling of market enthusiasm continued in Q4 of 2022 with the earnings reports from the U.S. hyperscalers now all in. As we said earlier this year, even the cloud is not immune from the macro headwinds and the cracks in the armor we saw from the data we shared last summer are playing out into 2023. For the most part, actuals are disappointing beyond expectations, including our own. It turns out that our estimates for the big 3 hyperscale revenue missed by $1.2 billion or 2.7% lower than we had forecast from our most recent November estimates. We expect decelerating growth rates for the hyperscalers will continue through the summer of 2023 and won’t abate until comparisons get easier. 

In this Breaking Analysis we share our view of what’s happening in cloud markets – not just for the hyperscalers but other firms that have hitched a ride on the cloud. And we’ll share new ETR data that shows why these trends are playing out, tactics customers are employing to deal with their cost challenges and how long the pain is likely to last. 

Confidential computing is a technology that aims to enhance data privacy and security by providing encrypted computation on sensitive data in use and isolating data from apps and other host resources in fenced off enclaves. The concept of confidential computing is gaining popularity, especially in the cloud computing space where sensitive data is commonly stored and processed. However, there are some who view confidential computing as an unnecessary technology and a marketing ploy by cloud providers, aimed at calming customers who are cloud-phobic.

In this Breaking Analysis we revisit the notion of confidential computing and explore whether it’s just marketing or a key part of a trusted security strategy. To do so we’ll invite two Google experts to the show. But before we get there let’s summarize the overall market climate briefly with some ETR data.

The world’s leading telcos are often branded as monopolies that lack innovation. Telcos have been great at operational efficiency, connectivity and living off of transmission services. But in a world beyond telephone poles and basic wireless services, how will telcos modernize, become more agile and monetize new opportunities brought about by 5G, private wireless and a spate of new innovations in infrastructure, cloud, data, AI and apps? It’s become table stakes for carriers to evolve their hardened, proprietary infrastructure stacks to more open, flexible, cloud-like models. But doing so brings risks that telcos must carefully balance as they strive to deliver consistent quality of service while at the same time moving faster and avoiding disruption. 

In this Breaking Analysis and ahead of MWC23, we explore the evolution of the telco business and how the industry is in many ways, mimicking a transformation that took place decades ago in enterprise IT. We’ll model some of the traditional enterprise vendors using ETR data and investigate how they’re faring in the telecomms vertical. And we’ll pose some of the key issues facing the industry this decade. 

While never really meant to be a consumer tech event, over time, the rapid ascendancy of smartphones captured much of the agenda at Mobile World Congress, now MWC. And while device manufacturers continue to have a major presence at the show, the maturity of intelligent devices, longer lifecycles and the disaggregation of the network stack have created more interest in enterprise-class technologies than ever before. Semiconductor manufacturers, network equipment players, infrastructure companies, cloud vendors, software providers and a spate of startups are eyeing the trillion dollar plus telecommunications industry as one of the next big things to watch this decade. 

In this Breaking Analysis we bring you part 2 of our ongoing coverage of MWC 2023. With some new data on enterprise players specifically within large telco environments. We’ll also take a brief glimpse at some of the pre-announcement news from the show and corresponding themes ahead of MWC. We’ll close with the key innovation areas we’ll be covering at the show on theCUBE. 

FULL ARTICLE: https://wikibon.com/breaking-analysis-mwc-2023-goes-beyond-consumer-deep-into-enterprise-tech/

With George Gilbert

When Apache Spark became a top level project in 2014, and shortly thereafter burst onto the big data scene, it along with the public cloud disrupted the big data market. Databricks cleverly optimized its tech stack for Spark and took advantage of the cloud to deliver a managed service that has become a leading AI and data platform among data scientists and data engineers. However, emerging customer data requirements and market forces are conspiring in a way that we believe will cause modern data platform players generally and Databricks specifically to make some key directional decisions and perhaps even reinvent themselves. 

In this Breaking Analysis we do a deeper dive into Databricks. We explore its current impressive market momentum using ETR survey data. We’ll also lay out how customer data requirements are changing and what we think the ideal data platform will look like in the mid-term. We’ll then evaluate core elements of the Databricks portfolio against that future vision and close with some strategic decisions we believe the company and its customers face. 

To do so we welcome in our good friend George Gilbert, former equities analyst, market analyst and principal at Tech Alpha Partners. 

FULL ARTCILE: https://wikibon.com/breaking-analysis-databricks-faces-critical-strategic-decisionsheres-why/

The viral awareness and adoption of foundation models like ChatGPT have created both an opportunity and threat to automation platforms generally and RPA point tools specifically. On the one hand, large language models can reduce complexity and accelerate the adoption of enterprise automation platforms. The flip side is software robots are designed to improve human productivity through intelligent automation and GPT models could cannibalize some, if not many use cases initially targeted by RPA vendors. This reality is causing customers to rethink their automation strategies and vendors to rapidly evolve their messaging to position foundation models as an accelerant to their platforms. 

In this Breaking Analysis we provide you with a perspective on how foundation models could impact automation platforms. We review ETR data that quantifies the ascendency of OpenAI. We also show survey data that measures the overlap between ML/AI systems and automation platforms. Then we review the recent quarterly performance of UiPath and share how we think the company must position itself with respect to the onslaught of noise and potential disruption from GPT models.

FULL ARTICLE: https://wikibon.com/breaking-analysis-gpt-models-are-a-two-edged-sword-for-automation-platforms/

The viral awareness and adoption of foundation models like ChatGPT have created both an opportunity and threat to automation platforms generally and RPA point tools specifically. On the one hand, large language models can reduce complexity and accelerate the adoption of enterprise automation platforms. The flip side is software robots are designed to improve human productivity through intelligent automation and GPT models could cannibalize some, if not many use cases initially targeted by RPA vendors. This reality is causing customers to rethink their automation strategies and vendors to rapidly evolve their messaging to position foundation models as an accelerant to their platforms. 

In this Breaking Analysis we provide you with a perspective on how foundation models could impact automation platforms. We review ETR data that quantifies the ascendency of OpenAI. We also show survey data that measures the overlap between ML/AI systems and automation platforms. Then we review the recent quarterly performance of UiPath and share how we think the company must position itself with respect to the onslaught of noise and potential disruption from GPT models.

A rebound in semiconductor stocks has many investors asking if this is a harbinger of good news for the broader enterprise tech sector. Indeed the SOXX semiconductor ETF is up nearly 30% year to date as of this posting, as are bellwether fab suppliers like Applied Materials and Lam Research. Nvidia is up over 90% YTD and AMD over 50%. Even the beleaguered Intel is up 22%. But key enterprise software names have not yet rebounded and according to this week’s guest, the divergence between semis and B2B software is getting hard to ignore. 

In this Breaking analysis we examine the the bifurcation between the performance of semis and broader enterprise tech. And we’ll try to answer the question: Is the uptick in semiconductors an early indicator of a broader enterprise tech recovery, or is this a false signal that warrants continued caution? To examine these issues we welcome back Ivana Delevska, the founder and chief investment officer of SPEAR Invest. 

All statements made regarding companies or securities are strictly beliefs, points of view and opinions held by SiliconANGLE Media, Enterprise Technology Research, other guests on theCUBE and guest writers. Such statements are not recommendations by these individuals to buy, sell or hold any security. The content presented does not constitute investment advice and should not be used as the basis for any investment decision. You and only you are responsible for your investment decisions.

Disclosure: Many of the companies cited in Breaking Analysis are sponsors of theCUBE and/or clients of Wikibon. None of these firms or other companies have any editorial control over or advanced viewing of what’s published in Breaking Analysis.

On Tuesday, April 4, HPE invited a number of industry analysts to participate in HPE GreenLake Storage Day. Notably, HPE declared 2023 the year of storage. While the company made several storage-related announcements, perhaps even more interesting was what the event tells us about HPE’s culture, its strategy and the future direction of the company.

In this Breaking Analysis we’ll share our takeaways from HPE’s event, held in Houston, Texas, which included attendance at Antonio Neri’s quarterly all-hands meeting. We’ll try to emphasize areas that have not necessarily been the focus of most press and industry analyst write ups to date. We’ll also take a look at the latest ETR survey data to put HPE’s market position in context across several of its major segments.

Best articles:

Nice analysis by Steve McDowell on Forbes:

https://www.forbes.com/sites/stevemcdowell/2023/04/06/hpe-kicks-off-its-year-of-storage-with-help-from-vast-data/?sh=6a548ee45b3b

Chris Mellor’s summary has all the news

https://blocksandfiles.com/2023/04/04/hpe-greenlake-vast-data/

CRN’s channel perspective emphasizing the consumption model:

https://www.crn.com/news/storage/alletra-storage-mp-puts-hpe-far-ahead-of-competitors-in-hybrid-cloud-storage-management-battle?itc=refresh

SiliconANGLE writeup by Paul Gillin:

https://siliconangle.com/2023/04/04/hpe-greenlake-gets-hybrid-block-file-storage-expanded-data-protection/

TechTarget article w/ quotes from Marc Staimer, Ray Luchessi & Scott Sinclair w/ an emphasis on how well Vast is doing:

https://www.techtarget.com/searchstorage/news/365534832/Vast-dips-into-HPE-GreenLake-with-new-file-storage-service

Vast Data press release that emphasizes AI workloads:

https://www.businesswire.com/news/home/20230404005358/en/VAST-Data-Announces-Strategic-Partnership-with-Hewlett-Packard-Enterprise-to-Provide-Software-for-HPE-GreenLake-for-File-Storage

RSA Conference takes place in the last week of April this year at a time when the industry is at a crossroads. Once hopeful that the security industry would be shielded from macroeconomic conditions, the past year has been painful for many investors with some exceptions – most notably those investors who stuck with Palo Alto Networks and Fortinet. That said, Q1 saw a rebound in tech but for the most part cyber lagged. The tech rally was largely attributable to an uptick in semis, a leading indicator in normal times. But these aren’t normal times and RSA gives us a nice opportunity to assess the situation in the market.

In this Breaking Analysis we’ll update you on the latest trends in the market and what to expect at RSA this year. We’ll also share the latest ETR spending data and drill into the areas of cybersecurity that are seeing the most action. As always we’ll highlight those companies with the strongest (and weakest) momentum and close with a look at some of the emerging technology players in security that might be ripe for acquisition. To do all this we once again welcome in our colleague Erik Bradley from ETR. 

The big three US cloud players all announced earnings this past week and, as expected, cloud growth is slowing. But don’t kid yourselves. Hyperscale clouds remain the epicenter of innovation in tech and foundation models like GPT will only serve to harden this fundamental fact. Our data suggests the deceleration in cloud spend is a function of two related factors: 1) Cautious consumption patterns; and 2) Aggressive cloud optimization, which is being promoted by the big three cloud vendors in an attempt to lock in customers to longer term commitments. There is still no clear evidence in the numbers 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 seen on a broad market basis.

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 cloud executives and show you the latest ETR data on spending and market presence in the cloud. 

While we’ve been skeptical about repatriation as a notable movement, anecdotal evidence suggests that it is happening in certain pockets. Even though we still don’t see cloud repatriation broadly showing in the numbers, certain examples have caught our attention. In addition, the potential impact of AI raises some interesting questions about where infrastructure should be physically located and causes us to revisit our premise that repatriation is an isolated and negligible trend. 

In this Breaking Analysis we look at a number of sources, including the experiences of 37signals, which has documented its departure from public clouds. We’ll also examine the relationship between repatriation and SRE Ops skill sets. As always we’ll look at survey data from our partners at ETR, a recent FinOps study published by Vega Cloud and revisit the Cloud Repatriation Index, which we believe is breaking a three-year trend.

The cost of cloud, a Trillion Dollar Paradox: https://a16z.com/2021/05/27/cost-of-cloud-paradox-market-cap-cloud-lifecycle-scale-growth-repatriation-optimization/

IDC Repatriation Report: https://img1.wsimg.com/blobby/go/a76227cd-a662-4f4e-9b26-1a6fdca9f0fd/downloads/1cnptggfe_976725.pdf

The connection between cloud repatriation and SRE Ops by Lori MacVittie: https://devops.com/the-curious-connection-between-cloud-repatriation-and-sre-ops/#disqus_thread

Snowflake March 2023 10K: Read the notes! https://d18rn0p25nwr6d.cloudfront.net/CIK-0001640147/ba7caf53-f000-4fc0-b8a3-ef379d21b99d.pdf

Why we’re leaving the cloud (37signals) https://world.hey.com/dhh/why-we-re-leaving-the-cloud-654b47e0

Sovereign clouds (37signals): https://world.hey.com/dhh/sovereign-clouds-661eb5e4

The Platformanomics Repatriation Index: https://www.platformonomics.com/2022/11/introducing-the-platformonomics-repatriation-index/

Vega Cloud Optimization Report: https://www.vegacloud.io/_files/ugd/e67781_49124f7bd58d4b358ddd0845aac33cff.pdf

The cost of cloud, a Trillion Dollar Paradox: https://a16z.com/2021/05/27/cost-of-cloud-paradox-market-cap-cloud-lifecycle-scale-growth-repatriation-optimization/

The true cost of scale out file storage [The Cloudcast Podcast] https://www.thecloudcast.net/2023/03/scale-out-cloud-storage.html

The AI gold rush is on. The paths to monetization are seemingly endless but the most obvious converge on making humans more productive or supercharging existing business models like search advertising or subscription licenses. Much of AI adoption in enterprise IT is hidden. Our research shows a very high overlap (around 40-60%) between AI adoption in enterprise tech and embedded AI inside software from the likes of Salesforce, ServiceNow, Workday, SAP, Oracle and other major players. But the rapid advancements of tools from AI leaders and an emerging group of independent firms is causing customers to think differently. Catalyzed by the OpenAI Microsoft partnership, organizations are rapidly trying to figure out how to apply these tools to create competitive advantage. Every firm on the planet wants to ride the AI wave. Virtually overnight, investment capital has shifted to fund early stage AI startups with much less funding required relative to previous boom cycles. 

In this Breaking Analysis we review ETR data to quantify the state of AI spending in the enterprise and look at the positions of several key players in the space that offer AI tools and platforms. To do so we invite Andy Thurai, CUBE contributor, VP and principal analyst at Constellation Research. Andy will help us unpack the hits and misses from this past week’s Google IO conference and give us his perspectives on what it takes to catch the AI wave and avoid becoming driftwood.

Constellation research hits and misses from Google IO
https://www.constellationr.com/blog-news/google-s-generative-ai-strategy-google-io-2023-hits-and-misses

Recap of Google IO announcements:
https://t.co/yx6POoLRLG https://twitter.com/rowancheung/status/1656564347290746880?s=51&t=AqnHczjrru-dQaVNpPGp7w

Microsoft eyes search deal with Firefox as Bing search sputters:
https://www.theinformation.com/articles/microsoft-eyes-firefox-search-deal-as-bing-chatbot-gains-sputter?rc=nxigdx

Watson beats Ken Jennings
https://www.youtube.com/watch?v=Sp4q60BsHoY

IBM Watsonx
https://www.infoworld.com/article/3695951/ibm-takes-on-aws-google-and-microsoft-with-watsonx.html

AI will now add superpowers to every triggering buzzword, hence the title of this week’s post. Look past the buzz and you’ll find substance somewhere. The spring conference season is kicking into high gear, so it’s a time to get serious and extract the signal from the event noise. This week we’ll see Microsoft Build, which will no doubt volley shots back from the messaging at Google I/O.  Two other big events will take place this week, Red Hat Summit / Ansible Fest in Boston and the annual Dell Technologies World in Las Vegas. theCUBE will be covering both of these shows and we want to take this opportunity to update you on the state of hybrid multi-cloud…what we call supercloud. 

In this Breaking Analysis we examine some of the key infrastructure players in hybrid multi-cloud with a focus on Red Hat and Dell Technologies, two firms that increasingly are partnering with each other as VMware’s future evolves. We’ll share recent ETR survey data on the position of several other hybrid / cross-cloud players including Cloudflare, Equinix, HPE, IBM, Oracle, VMware and others. We’ll also share what we expect to hear at Red Hat Summit and Dell Technologies World this year. 

Fitzy’s cloud repatriation index:

https://www.platformonomics.com/2023/05/platformonomics-repatriation-index-q1-2023-surfs-up/

Percent of workloads in the cloud (Statistica): 

https://www.statista.com/statistics/1266602/workloads-cloud-organizations-worldwide/

Red Hat project Wisdom:

https://www.redhat.com/en/engage/project-wisdom

Nugget on reddit about Ansible Lightspeed

https://www.reddit.com/r/ansible/comments/12pnl2b/ansible_lightspeed/

GitHub clue on Ansible AI

https://github.com/ansible/vscode-ansible/releases

What to expect at Red Hat Summit 2023

https://siliconangle.com/2023/05/10/expect-red-hat-summit-join-thecube-may-23-24-rhsummit/

What to expect at Dell Tech World 2023:

https://siliconangle.com/2023/05/11/expect-thecubes-coverage-dell-technologies-world-join-thecube-may-22-24/

The era of AI everything continues to excite. But unlike the Internet era, where any company announcing a dotcom anything immediately rose in value, the AI gods appear to be more selective. Nvidia beat its top line whisper number by more than $300M and the company’s value is rapidly approaching one trillion dollars. Marvell narrowly beat expectations this week but cited future bandwidth demand driven by AI and the stock was up more than 20% on Friday. Broadcom was up nearly 10% on sympathy with the realization that connect-centricity beyond the CPU is what the company does really well. Meanwhile, other players like Snowflake, which also narrowly beat earnings Wednesday and touted AI as a future tailwind, got hammered as customers dial down cloud consumption. 

In this Breaking Analysis we look at the infrastructure of AI examining the action at the silicon layer specifically around Nvidia’s momentum. Since much of AI is about data, we’ll also look at the spending data on two top data platforms, Snowflake and Databricks to see what the survey data says and examine the future of real time data and automation as a catalyst for massive productivity growth in the economy. 

To do so we have a special Breaking Analysis panel with John Furrier and David Floyer. 

How Nvidia plans to own the data center

https://wikibon.com/breaking-analysis-how-nvidia-plans-to-own-the-datacenter-with-ai/

 What Pat Gelsinger has to do to save Intel

https://wikibon.com/breaking-analysis-pat-gelsinger-must-channel-andy-grove-recreate-intel/

Nvidia earnings: 

https://siliconangle.com/2023/05/24/nvidias-stock-soars-strong-sales-forecast-amid-surging-demand-ai-chips/

Snowflake earnings & Neeva acquisition

https://siliconangle.com/2023/05/24/snowflakes-stock-falls-guidance-miss-confirms-plans-acquire-neeva/

Databricks faces key strategic decisions…

https://wikibon.com/breaking-analysis-databricks-faces-critical-strategic-decisionsheres-why/

With a nearly $60B revenue run rate, growing at 14% and throwing off over $5B in operating cash last quarter, Cisco has an awesome business. But customers are vocal about the complexity of Cisco’s portfolio and if not addressed head on, the company risks encountering friction beyond just economic headwinds. We believe Cisco’s challenges are most decidedly not product breadth and depth, rather the company’s mandate is to integrate the piece parts of its intricate offerings to create more facile and seamless experiences for customers. 

In this Breaking Analysis and ahead of Cisco Live US, we dig deeper into Cisco’s business and double click on three key areas of its portfolio including: 1) Security; 2) Networking; and 3) Observability. With spending data from ETR and a guest appearance from SiliconANGLE contributor and market watcher Zeus Kerravala, principal at ZK Research. 

Is Cisco a buy? 

https://www.investors.com/news/technology/cisco-stock-buy-now/

Gartner MQ on observability & APM:

https://www.honeycomb.io/gartner-magic-quadrant-apm-observability-2022

Cisco’s most recent earnings transcript

https://www.fool.com/earnings/call-transcripts/2023/05/17/cisco-systems-csco-q3-2023-earnings-call-transcrip/

Cisco financial slide deck

https://seekingalpha.com/article/4605527-cisco-systems-inc-2023-q3-results-earnings-call-presentation

Databricks faces strategic decisions…here’s why
https://wikibon.com/breaking-analysis-databricks-faces-critical-strategic-decisionsheres-why/

Uber has one of the most amazing business models ever created. The company’s mission is underpinned by technology that helps people go anywhere and get anything. The results have been stunning. In just over a decade, Uber has become a firm with more than $30 billion in annual revenue, an annual bookings run rate of $126B and a market capitalization near $90 billion today.

Moreover, the company’s productivity metrics are 3-5 times greater than what you’d find at a typical technology company when, for example, measured by revenue per employee. In our view, Uber’s technology stack represents the future of enterprise data apps where organizations will essentially create real time digital twins of their businesses and in doing so, deliver enormous customer value. 

In this Breaking Analysis, we introduce you to one of the architects behind Uber’s groundbreaking fulfillment platform. We’ll explore their objectives, the challenges they had to overcome, how Uber has done it and why we believe their platform is a harbinger for the future. 

Uber’s fulfillment platform technical blog: 

https://www.uber.com/blog/fulfillment-platform-rearchitecture/

Using Google Cloud Spanner to support Uber’s data management mission:

https://www.uber.com/blog/building-ubers-fulfillment-platform/

Google Cloud Spanner technical paper:

https://static.googleusercontent.com/media/research.google.com/en//archive/spanner-osdi2012.pdf

HPE’s announcement of an AI cloud for large language models highlights a differentiated strategy that the company hopes will lead to sustained momentum in its high performance computing business. While we think HPE has some distinct advantages with respect to its supercomputing IP, the public cloud players have a substantial lead in AI with a point of view that generative AI is fully dependent on the cloud and its massive compute capabilities. The question is can HPE bring unique capabilities and a focus to the table that will yield competitive advantage and ultimately, profits in the space?

In this Breaking Analysis we unpack HPE’s LLM-as-a-service announcements from the company’s recent Discover conference and we’ll try to answer the question: Is HPEs strategy a viable alternative to today’s public and private cloud gen AI deployment models, or is it ultimately destined to be a niche player in the market? To do so we welcome to the program CUBE analyst Rob Strechay and Vice President / principal analyst from Constellation Research, Andy Thurai. 
World’s Top Performing Supercomputers: 

https://a16z.com/2023/06/20/emerging-architectures-for-llm-applications/

Over the past several months we’ve produced a number of in-depth analyses laying out our mental model for the future of data platforms. There are two core themes: 1) Data from people, places, things, and activities in the real world drives applications, not people typing into a UI; and 2) Informing and automating decisions means all data must be accessible. That drives a change from data locked in application silos to application logic being embedded in a platform that manages an end-to-end representation of an enterprise in its data.  

This week’s Snowflake Summit further confirmed our expectations with a strong top line message of “All Data / All Workloads” and a technical foundation that supports an expanded number of ways to access data. Squinting through the messaging and firehose of product announcements, we believe Snowflake’s core differentiation is its emerging ability to be a complete platform for data applications. Just about all competitors either analyze data or manage data. But no one vendor truly does both. To be precise, managing data doesn’t mean running pipelines or serving analytic queries or AI/ML models. It means managing operational data so that analytics can inform or automate operational activities captured in transactions. With data as the application foundation, the platform needs robust governance.

In this week’s Breaking Analysis, we try to connect the dots between Snowflake’s high level messaging and its technical foundation to better understand the core value it brings to customers and partners. As well, we’ll explore the ETR data with some initial input from the Databricks Data + AI Summit to assess the position and prospects of these two leaders along with the key public cloud players. 

The recent Databricks Data+AI Summit attracted a large audience and, like Snowflake Summit, featured a strong focus on large language models, unification and bringing AI to the data. While customers demand a unified platform to access all their data, Databricks and Snowflake are attacking the problem from different perspectives. In our view, the market size justifies the current enthusiasm seen around both platforms but it’s unlikely that either company has a knockout blow for the other. This is not a head on collision. Rather Snowflake is likely years ahead in terms of operationalizing data. Developers can build applications on one platform, like Oracle when it won the market, that perform analysis and take action. Databricks likely has a similar lead in terms of unifying all types of analytic data – e.g. BI, predictive analytics & generative AI. Developers can build analytic applications across heterogeneous data, like Palantir today. But they have to access external operational applications to take action. 

In this Breaking Analysis we follow up last week’s research by connecting the dots on the emerging tech stack we see forming from Databricks. With an emphasis on how the company is approaching generative AI, unification and governance…and what it means for customers.  To do so we tap the knowledge of three experts who attended the event, CUBE analysts Rob Strechay and George Gilbert and AI market maven Andy Thurai of Constellation Research. 

The AI heard ’round the world has put the machine intelligence sector back in the spotlight. But when you squint beyond the press hype, the data shows that artificial intelligence is now the number one sector in terms of relative spending velocity in the ETR taxonomy. Normally market hype leads deployments, but the data suggests that spending activity and market penetration for AI are coinciding with the hype. While hyperscale cloud players are reaping the rewards, we think this is a rising tide that’s going to lift all AI ships, those both plainly in sight and others that may not be so visible.

In this Breaking Analysis we dig deeper into the AI space with spending data from ETR and one of the best minds in tech generally, and AI specifically, Jeff Jonas, CEO, founder, and chief scientist at Senzing.

Cloud complexity, tools sprawl and the AI awakening further tip the balance in favor of cyber attackers. Combined with corporate inertia, AI-washing, LLM inconsistency and the pace of change, we believe for now anyway, adversaries have the advantage over defenders. Moreover, macro spending headwinds continue to force organizations to make budget tradeoffs, not the least of which is how to fund AI experiments and deployments. Notably, however, 45% of organizations are using LLMs in production for use cases that may very well improve the productivity of SecOps teams in the long run and accelerate the cat and mouse game back to a state of quasi-equilibrium. 

In this Breaking Analysis we share key takeaways from Supercloud 3 – AI meets cloud security – and put forth new spending data from the latest ETR survey that shows which security firms are best positioned in the AI race to capitalize on the wave. 

Cybersecurity in the AI age: The power, the promise, the peril

https://siliconangle.com/2023/07/03/cybersecurity-ai-age-power-promise-peril/

How organizations can combat AI-equipped attackers

https://siliconangle.com/2023/07/03/organizations-can-combat-ai-equipped-attackers/

Supercloud 3 - AI meets Cloud Security 

Supercloud.world

Recently leaked court documents during the Microsoft Activision hearing require us to revisit our cloud forecasts and market share data. The poorly redacted docs, which have since been removed from public viewing, suggest that Microsoft’s Azure revenue is at least 25% lower than our previous estimates. As a result, we’ve cut and revised our Azure revenue figures which in turn increases AWS’ big 4 hyperscale cloud market share. Our new estimates show that AWS maintains a greater than 50% share of revenue through 2023. While the change also helps Google Cloud, its market share is only modestly affected. 

In this Breaking Analysis we update our hyperscaler cloud revenue estimates and market share data. We’ll also explain how the ETR data on cloud should be interpreted in this context and look forward to potential catalysts for cloud growth, including acceleration in Q4 attributable to generative AI.

Microsoft annual 10K:

https://microsoft.gcs-web.com/static-files/e2931fdb-9823-4130-b2a8-f6b8db0b15a9

Wikibon repatriation report:

https://wikibon.com/breaking-analysis-desperately-seeking-cloud-repatriation/

SiliconANGLE article on leaked court documents with Azure revenue data:

https://siliconangle.com/2023/06/29/court-filing-shows-microsoft-azure-generated-lower-expected-34b-revenue-2022/

Constellation report on cloud optimization:

https://www.constellationr.com/blog-news/private-cloud-compelling-option-cios-insights-new-research

After a tough 2022, the first half of 2023 has shown impressive strength and many technology bets have paid off. For sure investors in the so-called Magnificent Seven, i.e. Apple, Alphabet, Amazon, Meta, Nvidia and Tesla have been rewarded. But sharp investors have sought alpha beyond these issues, riding the wave of secular trends in AI, cybersecurity, cloud infrastructure and software as well as other emerging spaces like cleantech and robotics. As we enter the second half of 2023, the runup in tech combined with macro uncertainty has many investors taking a cautious posture. But we believe the long term outlook for firms that can capitalize on the AI wave remains extremely attractive as an unstoppable force.   

Hello and welcome to this week’s Wikibon CUBE Insights, Powered by ETR. In this Breaking Analysis we’re pleased to have back, founder and Chief Investment Officer of Spear Invest, Ivana Delevska to assess the current state of the market and explore how this investor is playing AI’s rising tide.  

Spear Investment Deck

https://19544476.fs1.hubspotusercontent-na1.net/hubfs/19544476/Spear%20Alpha%20Investment%20Case%20Approved.pdf

Spear Advisors Fund Letter from its CIO

https://seekingalpha.com/article/4599648-spear-advisors-q1-2023-fund-letter

Platformonomics Repatriation Index

https://www.platformonomics.com/2023/05/platformonomics-repatriation-index-q1-2023-surfs-up/

Revised Wikibon Cloud Forecast

https://wikibon.com/breaking-analysis-what-leaked-court-docs-tell-us-about-aws-azure-google-cloud-market-shares/

The data from enterprise customers is clear but conflicted. While 94% of customers say they’re spending more on AI this year, they’re doing so with budget constraints that will steal from other initiatives. As well, the choice of where customers plan to run generative AI is split almost exactly down the middle in terms of public cloud vs. on-premises/edge. Further complicating matters, developers report the experiences in the public cloud with respect to feature richness and velocity of innovation has been outstanding. At the same time, organizations express valid concerns about IP leakage, compliance, legal risks and cost that will limit their use of the public cloud. 

In this Breaking Analysis we’ll share the most recent data and thinking around the adoption of large language models and address the factors to consider when thinking about how the market will evolve. As always, we’ll share the latest ETR data to shed new light on key issues customers face balancing risk with time to value.

Google memo - we have no moat and neither does OpenAI

https://www.semianalysis.com/p/google-we-have-no-moat-and-neither

Janelle Teng - AI in the Cloud article on Substack:

https://nextbigteng.substack.com/p/ai-model-layer-the-new-frontline-of-cloud-wars

A16z on the economics of AI:

https://a16z.com/2023/08/03/the-economic-case-for-generative-ai-and-foundation-models/

Wall St Journal Article citing AWS, Google, MSFT, Dell & HPE POV

https://www.wsj.com/articles/the-ai-boom-is-here-the-cloud-may-not-be-ready-1a51724d?reflink=mobilewebshare_permalink

Technalysis GenAI study of 1,000 ITDMS:

https://www.technalysisresearch.com/downloads/TECHnalysis%20Research%20Generative%20AI%20in%20Enterprise%20Survey%20Highlights.pdf

AWS Outposts at the edge with Sagemaker - Circa 2021

https://aws.amazon.com/blogs/machine-learning/machine-learning-at-the-edge-with-aws-outposts-and-amazon-sagemaker/

The FTC continues to drag its feet on approving Broadcom’s acquisition of VMware. Ironically, in our view, these delays only hurt the very competitive environment the FTC claims to be protecting. The AI era is accelerating at a breakneck pace and the big 3 hyperscale cloud vendors already have a sizable lead on legacy incumbents. If preserving competition is truly the agenda of the U.S. government, it should recognize that VMware, its enterprise ecosystem and market forces have the potential to neutralize cross cloud complexity and give customers a viable alternative to increasingly powerful public cloud players. 

In this Breaking Analysis and ahead of VMWare Explore 2023, we revisit our views on Broadcom’s rationale and likely actions post acquisition. We’ll share current ETR survey data to place VMware’s position in context to the major cloud players, speculate on its AI agenda and give a preview of next week’s VMware Explore. To do so we welcome CUBE analyst Rob Strechay and friend of theCUBE, Zeus Kerravala, principal of ZK Research. 

EU Commission approves Broadcom VMware

https://www.broadcom.com/company/news/financial-releases/61306#:~:text=SAN%20JOSE%2C%20Calif.%20%2C%20July,(NYSE%3A%20VMW)

Hock Tan blog post on VMware’s future:

https://www.broadcom.com/blog/keeping-customers-at-the-center-of-everything

Broadcom VMware Deck:

https://investors.broadcom.com/static-files/232c0cd2-02d9-4704-bb7b-5659cef67fae

Silverlingings article on VMware Broadcom’s slow progress:

https://www.silverliningsinfo.com/multi-cloud/broadcoms-61b-vmware-deal-slowly-makes-progress

Broadcom VMware merger will hatch a new Supercloud:

https://www.silverliningsinfo.com/multi-cloud/broadcom-vmware-merger-will-hatch-new-supercloud

FT interview with Hock Tan:

https://www.ft.com/content/0a4013b6-b3b9-49fd-87a9-bd0da5e229b1

Recent earnings prints from Amazon and Snowflake, along with new survey data, have provided additional context on top of the two events that Snowflake and Databricks each hosted last June. Specifically, we believe that the effects of cloud optimization are still being felt but are nearing the end of peak negative impact on cloud companies. Snowflake’s recent renewal with Microsoft better aligns sales incentives and should improve the company’s traction with Microsoft Azure, a platform that has long favored Databricks. Google however remains a different story as its agenda is to build out its own data cloud stack, rather than supporting Snowflake’s aspirations. 

In this Breaking Analysis, we clarify some of our previous assumptions around Snowflake economics. We’ll dig into the three U.S. based hyperscale platforms with ETR data to better understand the footprint that key data platforms have in those cloud accounts; and, ahead of Google Cloud Next, we’ll preview how we believe Google is evolving its cloud and data stacks to compete more effectively in the market.

Snowflake Investor Day Deck

https://investors.snowflake.com/events-and-presentations/event-details/2023/Snowflake-Investor-Day-2023/default.aspx

Snowflake proof points on Snowpark vs. Spark

https://www.snowflake.com/en/resources/report/snowpark-customer-results/

MP4 download of Snowpark data as narrated by CFO Scarpelli:

https://video-cube365-net-east.s3.amazonaws.com/uploads/clip-mp4/947379-hardsub.mp4

At Cloud Next, Google showcased its strong leadership position in data and AI. In our view, Google’s messaging, demos and tech-centric narrative have broad appeal for developers and next generation startups. As well, the company’s focus on solutions, contrasts its strategy to the typically disjointed services we’ve seen from AWS over the past decade. Google also showed off an expanded ecosystem of GSIs and smaller CSPs, encouraging the broad use of Google’s kit globally. While Google remains a distant third in the Iaas/PaaS race, with revenue one-fifth the size of AWS, it is playing the long game and betting the house on AI as a catalyst to its cloud future.

In this Breaking Analysis we unpack the key takeaways from Google Cloud Next with Rob Strechay and George Gilbert. We’ll share ETR data that positions Google’s AI relative to other leaders and we’ll contrast Google’s data-centric strategy with traditional architectural models. 

Google Cloud Next Keynotes:

https://cloud.withgoogle.com/next

AI shapes the narrative for Google Cloud Next

https://siliconangle.com/2023/08/29/old-new-ai-shapes-narrative-google-cloud-next/

AnalystANGLE on theCUBE:

https://www.youtube.com/watch?v=eHSOKi9yI50

Day 2 Keynote Analysis:

https://www.youtube.com/watch?v=mMw2Gv4UeAE

Analyst Angle:

https://www.youtube.com/watch?v=VCvTYHrWEKY

UiPath’s recent earnings beat and raise provides some evidence that thus far, Gen AI has not been diluitive for the company. As an early leader that is transforming beyond RPA toward end-to-end enterprise automation, UiPath, like all automation providers, has always faced adoption headwinds beyond isolated deployments. In this sense, Gen AI should bolster adoption and be a positive force. The flip side is that widely available tools like chatbots and generalized foundation models could eat away at the low end of the automation TAM, highlighting the urgency for companies like UiPath to move up market and accelerate innovation that brings differentiation from commoditized tools; and, importantly, create distance from embedded AI within mainstream enterprise SaaS platforms like Slack GPT and Salesforce Einstein. 

In this Breaking Analysis we briefly review the recent earnings print from UiPath. We’ll look at ETR survey data that shows Microsoft Power Automate’s impact on the automation market and how it is forcing UiPath to target larger accounts with a more functional product set. As well we’ll look at the impact that AI is having in these larger accounts and test UiPath management assertions that Gen AI will be a tailwind for the company. 

Q2 ‘24 $PATH Earnings Transcript

https://seekingalpha.com/article/4633537-uipath-inc-path-q2-2024-earnings-call-transcript?feed_item_type=news&utm_medium=referral&utm_source=msn.com

Gartner MQ for Robotic Process Automation 

https://www.gartner.com/doc/reprints?id=1-2EDXTGOY&ct=230705&st=sb

Barron’s article frames the quarter and the AI debate

https://www.barrons.com/articles/uipath-stock-earnings-artificial-intelligence-cfde9bcb

Automation Anywhere survey on GenAI adoption in automation use cases

https://www.prnewswire.com/news-releases/generative-ai-emerges-as-essential-tool-for-successful-process-automation-automation-anywhere-survey-finds-301895896.html

Motley Fool Bull/Bear case for UiPath

https://www.fool.com/investing/2023/09/07/uipath-stock-bear-vs-bull/

Power Laws have more power than you think

https://every.to/p/power-laws-have-more-power-than-you-think

theCUBE host Dave Vellante is joined by George Gilbert and Bob Muglia for this weeks Breaking Analysis

George Kurtz is pumped up…and why not? CrowdStrike’s business appears to be on a fast track and entering a new phase of growth, despite the difficult macro and elongated sales cycles. The company’s products are considered best in class, its business is growing steadily and an improved profitability and cash flow outlook had investors excited, at least up until this week. A still challenging environment and a rich 13X revenue multiple perhaps led to some profit taking, but Gen AI could be the next catalyst for the company. In the race to close the SecOps staffing gap, CrowdStrike has what appears to be a strong play with a natural language-based intelligent assistant known as Charlotte AI. 

In this Breaking Analysis we update our scenario on security leader CrowdStrike. We’ll review the company’s recent progress, share survey data that shows where it is strong and where there may be icebergs ahead. And we’ll preview Fal.Con 2023 which takes place next week in Las Vegas. 

We’re getting used to the phrase, “higher for longer,” referring to  the realization that interest rates are expected to remain elevated for a period of time. This trend is having an inverse effect on enterprise tech spending growth rates. Prior to the Fed’s tightening binge for example, IT decision makers (ITDMs) in aggregate expected annual technology spending to increase by 7.5%. Eleven fed interest rate hikes later, ITDMs estimate that their 2023 budgets will be up only 2.9%, with an expectation, or perhaps it’s a wishful hope, that their budgets will increase 3.8% in 2024. 

In this our 200th Breaking Analysis, we preview the current spending climate and where AI fits in relation to other sectors. We’ll also share with you a snapshot of the leaders in terms of spending velocity for their platforms; and how their performance compares to peers relative to earlier survey periods.

In this week’s CUBE Insights, Powered by ETR. George Gilbert and I welcome Ryan Blue to this, our 201st episode. Ryan is the co-creator and PMC chair of Apache Iceberg and a co-founder & the CEO of Tabular, a universal open table store that connects to any compute layer built by the creators of Iceberg.

MIT professor and economist Erik Brynjolfsson said recently that he’d be disappointed if AI didn’t lift the  current anemic 1.2% productivity growth rate to 3% or even 4%. This would be a good thing for business and government as it could potentially help with the labor shortage, drive earnings growth and increase tax revenues, which would ostensibly help address current debt levels. This is one of the promised impacts of AI. While the hype surrounding Gen AI has narrowly propped up certain sectors of the market, like AI startups and the magnificent seven, the macro effects have not been felt thus far as adoption remains largely experimental. 

In this Breaking Analysis and ahead of Supercloud 4, ETR’s Erik Bradley and Daren Brabham join the program to share the latest trends on AI adoption, how Gen AI is being used, some of the deployment models and the AI leaderboard based on spending momentum and presence in the market. 

Historical trends in the music industry:

https://open.lib.umn.edu/mediaandculture/chapter/6-4-current-popular-trends-in-the-music-industry/#:~:text=The%20Big%20Four%20control%20over,current%20distribution%20of%20market%20share.&text=Four%20major%20music%20labels%20control,the%20U.S.%20recording%20music%20industry.

Current trends in the music industry:

https://musicandcopyright.wordpress.com/2023/04/25/recorded-music-market-share-gains-for-sme-and-the-indies-publishing-share-growth-for-umpg-and-wcm/

IDC sponsored content on AI w/ some market data:

https://content.dataiku.com/idc-infobrief-2023

In 1987, Nobel Prize-winning economist Bob Solow famously observed, “You can see the computer age everywhere but in the productivity statistics.” This proclamation became known as the productivity paradox. Ironically, Solow’s statement preceded the greatest productivity boom since the dawn of the computer age which subsequently came to fruition in the 1990’s. It can be argued that a similar pattern is being seen today where AI is everywhere but generally not showing up in earnings numbers or productivity statistics…yet. 

In this Breaking Analysis we squint through the latest earnings reports from Microsoft, Alphabet and Amazon to understand what’s happening in cloud, evaluate the impact or lack thereof of AI on cloud earnings momentum and explain how we think about the future impact of generative AI and cloud. 

Power Law Explained Wikipedia

https://en.wikipedia.org/wiki/Power_law

Heavy tailed power laws:

Why are Power Law distributions called 'Heavy-tailed'?

Explainer video for power laws in statistics:

https://www.youtube.com/watch?v=JC71ZazlMR0

Power law in economics:

https://dash.harvard.edu/bitstream/handle/1/34651705/68262294.pdf

What is retrieval augmented generation (IBM Research)

https://research.ibm.com/blog/retrieval-augmented-generation-RAG

Llama2 technical paper from Meta:

https://scontent-dfw5-1.xx.fbcdn.net/v/t39.2365-6/10000000_662098952474184_2584067087619170692_n.pdf?_nc_cat=105&ccb=1-7&_nc_sid=3c67a6&_nc_ohc=o6bnSMYXMT8AX8QaArm&_nc_ht=scontent-dfw5-1.xx&oh=00_AfD4K2tm94KqZZ6vm0bmor-zmbJ5z5ENslOx60fJRmMO9A&oe=6548D47F

With Watson 1.0, IBM deviated from the silicon valley mantra, fail fast, as it took nearly a decade for the company to pivot off of its original vision. In our view, a different dynamic is in play today with Watson 2.0 – i.e. watsonx. IBM’s deep research in AI and learnings from its previous mistakes, have positioned the company to be a major player in the Generative AI era. Specifically, in our opinion, IBM has a leading technological foundation, a robust and rapidly advancing AI stack, a strong hybrid cloud position (thanks to Red Hat), an expanding ecosystem and a consulting organization with deep domain expertise to apply AI in industry-specific use cases.  

In this Breaking Analysis we share our takeaways and perspectives from a recent trip to IBM’s research headquarters. To do so we collaborate with analyst friends in theCUBE Collective, Sanjeev Mohan, Tony Baer and Merv Adrian. We’ll also share some relevant ETR spending data to frame the conversation. 

Conventional wisdom says Microsoft Corp. is the big winner in the recent OpenAI saga. We don’t quite see it that way.

Both Microsoft and OpenAI are in a worse position today than last Thursday, prior to the firing of OpenAI Chief Executive Sam Altman and the ongoing public drama that ensued. Microsoft and OpenAI had a huge lead in market momentum, artificial intelligence adoption and feature acceleration, and were setting the narrative in AI.

Our discussions with customers and industry insiders leads us to conclude that the duo has put its substantial lead at risk. Although Microsoft CEO Satya Nadella is making lemonade from lemons, the window was just cracked open for the competition and it’s more clear than ever that one large language model will not rule them all.

In this episode of Breaking Analysis, theCUBE analyst Dave Vellante focuses on the evolving landscape of enterprise tech, driven by generative AI, and its implications for AWS. The discussion emphasizes how AWS must adapt its powerful playbook, known for agility, developer choice, power, scale, reliability and security, to accommodate the growing demand for simplicity and coherence among mainstream customers.

Follow theCUBE's live event coverage https://www.thecube.net/

Vellante discusses the challenges that AWS must tackle in the face of changing customer preferences, market pressures and increased competition, particularly from Microsoft and Nvidia. Also, up for discussion, AWS's recent initiatives, such as its gen AI stack and partnership with Nvidia, as well as the technical challenges it faces in providing a unified data platform for developers.

Read the full article https://siliconangle.com/2023/12/02/reinvent-2023-underscores-new-simplicity-mandate-aws/

For daily news for CIOs, check out our parent publication at https://siliconangle.com/

Be sure to follow Dave's weekly Breaking Analysis podcast as well, for the deep data dives on enterprise computing trends, from spending patterns to Wall Street implications.
https://www.youtube.com/playlist?list=PLenh213llmcZMTRZKjnAwesSCiuLQT21E

We believe today’s so-called modern data stack, as currently envisioned, will be challenged by emerging use cases and AI-infused apps that begin to represent the real world, in real time, at massive data scale. To support these new applications, a change in underlying data and data center architectures will be necessary, particularly for exabyte scale workloads. Today’s generally accepted state of the art of separating compute from storage, must evolve in our view to separate compute from data and further enable compute to operate on a unified view of coherent and composable data elements. Moreover, our opinion is that AI will be used to enrich metadata to turn strings (i.e. ASCII code, files, objects, etc.) into things that represent real world capabilities of a business. 

In this Breaking Analysis we continue our quest to more deeply understand the emergence of a sixth data platform that can support intelligent applications in real time. To do so we are pleased to welcome two founders of VAST Data, CEO Renen Hallak and Jeff Denworth. VAST just closed a modest $118M financing round that included Fidelity at a valuation of ~$9B, which implies a quite minor change to the cap table.  

Artificial general intelligence, or AGI, has people both intrigued and fearful. As a leading researcher in the field, last July, OpenAI introduced the concept of superalignment via a team created to study scientific and technical breakthroughs to guide and ultimately control AI systems that are much more capable than humans. OpenAI refers to this level of AI as superintelligence. Last week, this team unveiled the first results of an effort to supervise more powerful AI with less powerful models. While promising, the effort showed mixed results and brings to light several more questions about the future of AI and the ability of humans to actually control such advanced machine intelligence.

In this Breaking Analysis we share the results of OpenAI’s superalignment research and what it means for the future of AI. We further probe ongoing questions about OpenAI’s unconventional structure which we continue to believe is misaligned with its conflicting objectives of both protecting humanity and making money. We’ll also poke at a nuanced change in OpenAI’s characterization of its relationship with Microsoft. Finally we’ll share some data that shows the magnitude of OpenAI’s lead in the market and propose some possible solutions to the structural problem faced by the industry.

Read the full article https://siliconangle.com/2023/12/18/david-versus-goliath-reimagined-openais-approach-ai-supervision/

In this Breaking Analysis we grade the 2023 predictions we made with ETR's Erik Bradley. We look back at what we said in January about the macro IT spending environment, cost optimization, security, generative AI, cloud, blockchain, data platforms, automation and tech events.

In this special Breaking Analysis we're pleased to host our third annual data predictions power panel with some of our collaborators in theCUBE Collective and members of the data gang. With us today are five of the top industry analysts focused on data platforms. Sanjeev Mohan of Sanjmo, Tony Baer of dbInsight, IDC's Carl Olofson, Dave Menninger who is with Ventana Research, now part of ISG and Doug Henschen with Constellation Research.

We believe the future of intelligent data apps will enable virtually all organizations to operate a platform that orchestrates an ecosystem similar to that of Amazon.com. By this we mean dynamically connecting and digitally representing an enterprise’s operations including its customers, partners, suppliers and even competitors. This vision includes the ability to rationalize top down plans with bottom up activities across the many dimensions of a business – e.g. demand, product availability, production capacity, geographies, etc. Unlike today’s data platforms, which generally are based on historical systems of truth, we envision a prescriptive model of a business’ operations enabled by an emerging layer that unifies the intelligence trapped within today’s application silos. 

In this Breaking Analysis, we explore in depth, the semantic layer we’ve been discussing since early last year. To do so we welcome Molham Aref, the CEO ofRelationalAI.

In this Breaking Analysis, theCUBE Research analyst Dave Vellante unpacks the Enterprise Technology Research January spending data and digs into those areas that are expected to show above average performance and those that are likely to lag.

Follow theCUBE's live event coverage https://www.thecube.net/