In this episode of the Infrastructure Matters podcast, hosts Steven Dickens and Krista Macomber discuss common themes discussed during recent visits with clients in the data protection marketplace – notably, generative artificial intelligence (AI), and protection of cloud-hosted, software-as-a-service (SaaS) applications. This includes the utilization of AI to streamline the application and oversight of protection policies, to uncover security vulnerabilities, and to democratize conversations around security between IT Operations teams and the C-Suite. They also touch on Tesla as a use case for utilizing AI for business model innovation, and the market-wide implications of the most recent financial performance from Oracle’s cloud business unit.
Topics include:
- HYCU’s new book launch – Averting the SaaS Data Apocalypse – and the general state of the market for protecting SaaS applications.
- The implications of generative AI for data protection solutions.
- Tesla’s Dojo Supercomputer and how the company is capturing the wave of interest in, and demand for, AI.
- Oracle’s overall and cloud business unit earnings.
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Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this webcast. The author does not hold any equity positions with any company mentioned in this webcast.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Transcript:
Steven Dickens: Hello and welcome to another episode of Infrastructure Matters. My name’s Steven Dickens and I’m joined this week by Krista Macomber. Hey Krista, welcome to the show.
Krista Macomber: Hi, Steven. Thanks so much. How are you doing?
Steven Dickens: Yeah, good. This is the third day in a row we’ve been hanging out, two days in person.
Krista Macomber: It’s been lovely. I know. How do we miss an opportunity to record in person?
Steven Dickens: I know, I know. Why we’re recording down the screen from our two respective houses when we’ve been together all week? But hey, it is what it is.
Krista Macomber: It happens. Plenty to catch up on.
Steven Dickens: Yes. As always, a busy week in tech. We’ll go through a few news items. We’ll talk about something that we had the pleasure of being involved in yesterday, and then, we’ll go into the deep dives topic, which I’ve been kind of in your world for the last couple of days so I think it’s going to be a fantastic topic to go through here. I mean, we’re there, so maybe let’s start with some of the stuff we got involved in yesterday with the team at HYCU. Krista, take us away and this is your domain, give us sort of overview of HYCU and really what we were involved in yesterday.
Krista Macomber: Sure, sure. Yeah. Steven, as you’re alluding to, so we were in the Boston area over the last couple of days for a handful of client meetings and one of them happened to be, as you mentioned, HYCU. They’re a really cool data protection vendor. They’ve always had this very niche focus of providing a data protection service that is very specifically designed for whatever the resource it is protecting. They actually got their start working with Nutanix hyperconverged infrastructure, but they’ve since really brought into focus on cloud infrastructure as a service and more recently actually SaaS applications.
What’s really interesting, Steven, is it’s not just the heavy hitter that we tend to think about being Microsoft 365, but what HYCU is doing is they’re bringing a platform to be able to develop data protection services that are tailored for the myriad of other applications that we are seeing enterprises are using. It was really cool energy in the HYCU offices because actually, their CEO, Simon Taylor, he just actually launched a book called Averting the SaaS Apocalypse. Haven’t had a chance to read it yet, but really looking forward to dig in. As you know, we got a very fantastic opportunity to sit in on their internal all hands sort of book launch type event. That was really great.
Steven Dickens: Yeah, I came away from the event super pumped. Simon’s big energy, I think. Then we had a chance to sit down with the product team and really dig in on where they’re going. I think the interesting thing I took away from the whole conversation is it’s a congested market in data resilience backup and the whole space that they’re in, but I think HYCU’s found a niche focusing on SaaS, focusing on how you back up some of those applications.
The Major League Baseball example they talked us through with the Red Sox, that’s part of the book. Just fascinating for me, the criticality of some of the data that supports some of the Major League Baseball sort of in-game operations and how crucial it is and how it would literally stop baseball game in its tracks if there was an outage and how they’re able to mitigate that, so I think some fantastic things. I’ve not read the book either. Neither of us. I got back at 9:30 last night. That’s why you’ll see me drinking from a bucket of tea today, but I’m looking forward to digging in. I think it’s going to be fascinating to hear that story.
Krista Macomber: 100%, and Steven, I think you hit on something that’s really important, which is the fact that a data loss or kind of outage incident really can stop whether it be an organization like a baseball team in the form of the Red Sox or a healthcare industry, any sort of organization. In the data protection market, it just unfortunately, tends to be an afterthought. Unfortunately, we do tend to think about, okay, what are the applications and the infrastructures that we need either to migrate to on or to build out? Then, once we’re up and running on them, then we tend to think, oh, well, how are we going to protect them? What’s interesting about this space is, so you mentioned, obviously it’s a competitive market in the form of the vendors that are providing services and solutions, but also, just the number of SaaS applications that we’re seeing enterprises are already beginning to use. I think that that kind of ecosystem will just continue to become larger and more fragmented.
It’s just so easy for, for example, a line of business to just go ahead and swipe a credit card and spin up a SaaS application without much if any oversight from IT. I think from my perspective, that’s really part of the pain point that HYCU is really looking to hit on, is how do we allow for these organizations to establish data protection services that are again, specifically tailored to all of these unique needs? There might be some legacy applications in healthcare, for example, without causing a lot of friction to that process. Again, ton of energy, looking forward to reading the book and just in general, it’s a space that I know we’re going to be looking at.
In our meeting with HYCU, I actually pulled up some data from our enterprise data protection study that we fielded late last year. We’re gearing up to field it again. At that time, we found that over 55% of the respondents in that study indicated around this time last year that they were already making some moves to protect Microsoft 365 and then more than 25% said that they were already in the works for protecting another SaaS application, so it’ll be really interesting to see how maybe we’re continuing to shift in that direction, what are some of the critical applications that really bubble up to the surface? I’m definitely very excited to continue to watch this space, for sure.
Steven Dickens: We’ll put details of the book that Simon’s wrote in the show notes and a link to that research. Exciting. I think we’re going to be tracking those guys more closely.
I’ve got a couple of news topics for this week. It’s been really a tale of two cities and I’ll talk about Tesla and Oracle. Both of those have had wild swings on the stock market this week. I wrote a Forbes article, which we’ll put in the show notes that describes how Tesla caught the wave of AI that’s sweeping the market and was vocal about what it’s been doing with its Dojo Supercomputer. It’s custom silicon that it’s developed with its D1 chip and how the business has accumulated over 10,000 A100 GPUs from Nvidia to build out a real, I want to say single purpose, maybe that’s too strong, but certainly very focused AI-driven backend to capture the data that comes from 4 million vehicles that they’ve got on the road.
I did some research and looking and all of those 4 million plus vehicles have continually got their cameras turned on and are providing that data back into Tesla, regardless of whether you’ve got the paid features for things like full autonomous driving turned on or not, and that gives Tesla a huge competitive advantage here, I think and that was what I was drilling into and the market started to realize this. There was a Morgan Stanley report. I’m yet to digest all 66 pages of it, but there’s a Morgan Stanley report, which I’ll be reading this week that talks about how Tesla’s not only leveraging some of the tailwinds that are going on in the automotive market, but is also positioned to take advantage of the huge tsunami of interest that’s going on with AI. As I say, I’ll put a link to the Forbes article that I wrote, a bit of a deep dive looking at Tesla, the car manufacturers, a supercomputer company, so more in my swim lane of being able to talk about them as a high-performance computing environment rather than a car company.
Krista Macomber: Yeah, and it’s going to be interesting to see. We had some of these conversations this week, Steven, around, okay, each organization looking to utilize AI in a way that is most meaningful for their business. It’s obviously, as we know, a huge buzzword, but how do organizations look to catch onto that wave, so to speak, in a way that is again, going to really move the needle? I think the Tesla use case is definitely an interesting one.
Steven Dickens: Yeah, and it’s interesting, as I say, that Tesla caught the wave and got a 10% bump intraday on Monday. I’ve yet to see where they are since Monday, but they had a wild swing on Monday. The flip side of that was Oracle announcing earnings and getting slammed by the market, and I’ll talk about why I think unjustly in a moment, but their share price went down by I think just over 12% intraday were recording just before the market’s open here. I haven’t seen where they are yet this morning, but what really was surprising for me was that 12% represents the largest drop since the end of the dotcom bust in the early 2000s. I think the markets are maybe being a little overzealous in their sort of folks and I’ll tell you why, and I’ve got the numbers here, so just let me read them.
Oracle said total revenue rose by 9%. Oracle’s a bellwether of the industry. We’re not seeing them as a high-growth rule of 40 company any longer, although parts of their business are. But I think at the size and scale, they reported 12.45 billion and the market narrative around that is that’s a miss. But when you do the analysis, the estimates were 12.47 billion, so let’s put this in perspective. Oracle on an over $12 billion number missed by 20 million. Let’s put some perspective around this and say, yes, they did miss. It’s either a miss it or a beat or a hit, and it’s only one of those three that you can do and yes, they missed, but it’s consensus estimates and they missed by 20K. If you know Oracle like we do, that’s one deal didn’t happen out of probably thousands that happened in the quarter.
Krista Macomber: Before we even dissected it like that, Steven, even just thinking about that 9% number understanding, like you say, just their position in the industry, their scale. To me that certainly doesn’t sound like a miss, so it’s-
Steven Dickens: Yeah. When you dig into the numbers, growth was driven by a 30% increase in cloud, which included a 66% growth in cloud infrastructure, taking them north of 1.5 billion for the quarter, a 17% growth in cloud applications to 3.1 billion. Those are some big numbers. They’re growing bigger than some of their peer group with those with a 66% growth. That’s faster than we’re seeing from our AWS Azure and GCP.
I think what spooked the market a little bit was the miss, the headline, not a lot of nuanced analysis there, but also some of the headwinds that they’re seeing around the Cerner acquisition. That’s a big long-term strategic play. The Cerner application base is largely on-prem. I’ve been involved in that in the past. That’s a classic on-prem, HIPAA-regulated workload, and it’s going to take some time to get those hospitals and practices and doctor’s offices to move to the cloud, to highly regulated workload. It’s going to be a multi-year exercise and Safra Catz talked about that in earnings.
I think the other thing that spooked the market was a little bit around some of the forecast for top-line growth. People were expecting higher guidance… 5 to 7% is probably a little bit less than the 8% that people are expecting, but again, we’re talking, if they hit the high end of their guidance at 7% growth versus 8% growth. Bit of an overreaction here by the markets. Certainly not giving any equity advice here, but I think overreaction for sure, for me, of the strength and health of the Oracle business.
Krista Macomber: The context needs to be factored in for sure.
Steven Dickens: Yes. 20 million miss on a 12.45 billion number needs to have some nuance.
Krista Macomber: Yeah.
Steven Dickens: Yeah, the stock markets world, we’re tech analysts, not equity analysts, so don’t take anything we say as equities advice, but we are here to provide some context and I think what we see in our position is strength in cloud, strength in database, new Exadata versions coming on a regular cadence, cloud customer from an on-prem, hybrid cloud, strong strategy, strong execution. We’ll be out to Oracle cloud world as a team, so expect a lot of announcements and good news coming from that. I think that’s the news for this week. Some fantastic things we’ve managed to be involved in and some wild swings on the stock market.
One of the things that I’ve been living in Krista’s world for the last couple of days, so we decided to do the deep dive and really had conversations with three or four vendors for the layman that I am in the data resilience and backup space was we’re seeing cyber resilience and data backup come together and we’re seeing AI infused in that discussion, so I’ll maybe hand over to you and let you take the stage here. What are you seeing in this space? You talked about some research and some other things. Maybe give us your perspective.
Krista Macomber: Sure. Yeah. As you mentioned, Steven, I think the data protection market is not immune by any means to just kind of the tidal wave of AI and the interest in it that we’re seeing. It’s interesting in the data protection space because we can think about it from a few different angles. The first angle I would say is thinking about how do we make sure that any data that’s being fed into large language models and things of that nature is protected, is secure, and really that it’s handled ethically, for lack of a better way to put it. We’re not necessarily feeding in information that we aren’t supposed to have access to, things of that nature.
That one, I think right now, there’s not necessarily a ton of concern and I think it’s in part because we are seeing that especially for large enterprises, which are what we tend to work with quite a bit. They are looking at potentially standing up their own infrastructure and creating their own natural language models and AI training engines. By and large, the data that’s being fed into it may already be protected, though I will say it will be important as an industry to be aware of some of these guardrails in terms of how this information is being accessed and used as it’s being fed into these models and really because at the end of the day, that helps to make sure that the insights that we’re getting out of these AI models is really the most effective that it can be.
Steven Dickens: I think one of the interesting takeaways from me, and I’ll let you comment on this because you are certainly the expert in this space, was as people back up their data, using that backup as the corpus to present to an AI large language model. Instead of using, I don’t know, live data where it sits maybe on tier one or two storage or maybe even tier zero storage, but using the backup as the source of reference for the large language model. That was something I’d not thought of that came out of a couple of our conversations whilst we’re on the road this week.,So maybe you can elaborate for the listeners there.
Krista Macomber: Yeah. That would definitely be I think maybe the second perspective in terms of how the impact of AI on the data protection space, and I see that there’s opportunity there. One example that we’ve already seen when we think about not necessarily AI but analytics and scanning for cyber resiliency is potentially the opportunity to have maybe clones or scanning backup data to uncover that malware attack, for example, has occurred. I bring this up because I think these AI use cases you’re bringing up is not all that different. I do think that there’s opportunity there, especially if we are thinking about the initial training of a model and maybe getting some of these AI engines off the ground so to speak. You can have potentially a very, very rich history of data and trending and things of that nature and then at the same time, you’re not worried about having any type of potential performance impact or things of that nature on the production side, if you are using your backup data and potentially feeding from that backup infrastructure.
I wouldn’t be surprised if it was a trend that we do see. I think a lot of what we’re discussing in this space is still very early days and honestly, to a degree, hypothetical because I think we’re still seeing and you probably see a little bit more on the production side, Steven, than I do, but I think we’re still a little bit in the early days of these use cases for AI and natural large language learning and things of that nature. Again, I think we’ll continue to see, but that’s definitely a use case that I would expect that we would see moving forward.
Steven Dickens: Yeah. You mentioned briefly one of the other things, and I’ll take you there, that you were talking about AI being applied during the backup process to spot anomalies and look for as a sort of ransomware security kind of, and that came through in a couple of our conversations, even from an encrypted backup point of view, the ability to insert a capability to look at that backup data feed and look for anomalies that might be inserted. I came away super fascinated with that. I mean, I know you track the space better than I do. Do you see that as a specific use case for AI that we’re going to see more of?
Krista Macomber: I think possibly. I would say right now what we’ve seen it’s been a little bit more on the machine learning side of things as opposed to true what we consider to be generative AI. However, I think potentially the seeds are planted, so to speak. We are already seeing that looking at this trending from a machine learning basis is helping companies to not only spot that attack has occurred and has penetrated the backup environment, but also to do things like uncover how far it has spread, what systems or databases for example, specifically have been impacted. Also, one big issue is the ability to identify what we call the last known good. Where is the point in time that is not corrupted, that is as close to the point of the attack as we can to minimize that data loss. That’s something that is very unique when we think about needing to recover from a cyber attack versus a natural disaster or one of these more traditional, for lack of a better way to put it, disaster events, so certainly I could see some use cases there.
Also, a little bit more forward-thinking as well, the ability to maybe uncover vulnerabilities. Of course, I’m thinking a little bit more on the protection side of things. Of course, we could potentially think about use cases on the production side as well, but really looking at the data estate, the infrastructure and uncovering again, what are some of those top vulnerabilities and helping to prioritize them as well. Not only where are they, but what are the biggest risks that IT operations maybe needs to respond to to make sure that they’re using their time most effectively, so certainly a couple of potentially use cases that you could think about there.
Steven Dickens: Yeah, I think it’s going to be fascinating. I think, as you rightly mentioned, we’re at the early days specifically around AI. I think it’s the convergence that was interesting for me over the last couple of days to live more in your world around cyber resilience and ransomware being merged with data protection and data backup and then infusing gen AI into that as a enabling technology to make both of those worlds more advanced and feature-rich.
Krista Macomber: Exactly. I think potentially, facilitate the collaboration between these two teams, right? IT operations and security teams. Typically, I would say they’ve maybe had their more distinct swim lanes, but as you’re mentioning, Steven, certainly they’re beginning to converge and having to collaborate more closely, especially when it comes to potentially preventing a cyber attack from occurring, but also certainly on the recovery side.
One thing that I know we had some discussions about this past week was the concept of maybe kind of a chatbot-type front end and maybe using that to maybe do some forensics as well. So okay, we had an incident back in May, for example, and can we have a report output that utilized AI to maybe give not only a recap of what happened, but maybe a little bit deeper context as well to help to maybe facilitate some of those conversations. Okay, let’s look at what happened here. How can we prevent this from occurring moving forward? That’s certainly, I think-
Steven Dickens: I think an interesting piece for me on that one was the democratizing what is quite detailed information and quite techy speaking, gets nerdy pretty quickly from an operational team, up to a C-suite level executive. I think the generative AI models are going to give us a platform to be able to, I don’t want to say dumb it down, but certainly contextualize it and democratize what’s been in those tools for those senior leaders. Provide me the top three incidents we’ve had in the last three months and give me a short report on what happened and what we did to resolve them is a kind of natural language search that generative AI is perfectly suited for.
Krista Macomber: A hundred percent because it’s all about the context and so what at the end of the day, more than just the data output, so the more we can expedite that process and as you mentioned, make it consumable for all of the stakeholders that need to sit at the table able for preventing, recovering from ransomware, things of that nature. Certainly important.
Steven Dickens: Well, that’s a fantastic conversation. As I say, it’s been a fantastic week to spend some time in your world and go deep on data protection and cyber resiliency and some of the ransomware stuff. You’ve been listening to the Infrastructure Matters podcast where every week, we bring you some news and then deep dive on a topic. Thank you very much for watching. Do all those things you do on all of your subscription services, like and subscribe because that’s good for us and we’ll see you next week. Thank you very much for watching.
Author Information
Regarded as a luminary at the intersection of technology and business transformation, Steven Dickens is the Vice President and Practice Leader for Hybrid Cloud, Infrastructure, and Operations at The Futurum Group. With a distinguished track record as a Forbes contributor and a ranking among the Top 10 Analysts by ARInsights, Steven's unique vantage point enables him to chart the nexus between emergent technologies and disruptive innovation, offering unparalleled insights for global enterprises.
Steven's expertise spans a broad spectrum of technologies that drive modern enterprises. Notable among these are open source, hybrid cloud, mission-critical infrastructure, cryptocurrencies, blockchain, and FinTech innovation. His work is foundational in aligning the strategic imperatives of C-suite executives with the practical needs of end users and technology practitioners, serving as a catalyst for optimizing the return on technology investments.
Over the years, Steven has been an integral part of industry behemoths including Broadcom, Hewlett Packard Enterprise (HPE), and IBM. His exceptional ability to pioneer multi-hundred-million-dollar products and to lead global sales teams with revenues in the same echelon has consistently demonstrated his capability for high-impact leadership.
Steven serves as a thought leader in various technology consortiums. He was a founding board member and former Chairperson of the Open Mainframe Project, under the aegis of the Linux Foundation. His role as a Board Advisor continues to shape the advocacy for open source implementations of mainframe technologies.
With a focus on data security, protection, and management, Krista has a particular focus on how these strategies play out in multi-cloud environments. She brings approximately a decade of experience providing research and advisory services and creating thought leadership content, with a focus on IT infrastructure and data management and protection. Her vantage point spans technology and vendor portfolio developments; customer buying behavior trends; and vendor ecosystems, go-to-market positioning, and business models. Her work has appeared in major publications including eWeek, TechTarget and The Register.
Prior to joining The Futurum Group, Krista led the data center practice for Evaluator Group and the data center practice of analyst firm Technology Business Research. She also created articles, product analyses, and blogs on all things storage and data protection and management for analyst firm Storage Switzerland and led market intelligence initiatives for media company TechTarget.
Krista holds a Bachelor of Arts in English Journalism with a minor in Business Administration from the University of New Hampshire.
