By Tech Barometer – From The Forecast by Nutanix
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In this Tech Barometer podcast segment, McDowell shares insights from his report Taming the AI-enabled Edge with HCI-based Cloud Architectures and explores the impact of extending IT resources to the edge and the driving force of AI.
Find more enterprise cloud news, features stories and profiles at The Forecast.
Transcription:
Steve McDowell: The reason we push AI to the edge is because that’s where the data is, you know, we want to do the processing close to where the data is so that we don’t have latency. And in a lot of environments, if we’re ever disconnected, it’s going to shut down my business.
Jason Lopez: The question is, how do you deploy edge resources in real time? In this Tech Barometer podcast, Steve McDowell, Chief analyst at NAND research talks about his paper “Taming the AI-Enabled Edge with HCI-Based Cloud Architectures.” I’m Jason Lopez. Our aim in the next several minutes is to discuss how AI impacts edge computing.
Steve McDowell: We’ve always defined edge as any resources that live outside the confines of your data center. And there’s some definitions that say the extension of data center resources to a location where there are no data center personnel. It’s remote.
Jason Lopez: But AI, of course, adds complexity. One example McDowell cites is automated train car switching. The sides of train cars have bar codes which are scanned, and a local stack of servers processes where the cars are and where they need to be.
Steve McDowell: I can do this in real time. I can partition my workloads so that, you know, computationally expensive stuff or maybe batch stuff can still live in the core. And I don’t have to do that at the edge all the time. So I can really fine tune what it is I’m deploying and managing.
[Related: Slew of Changes Drive VMware Customers to Consider Alternatives]
Jason Lopez: This is important when you consider that AI at the edge differs from traditional edge deployments primarily due to its need for greater computational power.
Steve McDowell: Once we start putting AI in, then suddenly we have to have the ability to process that AI, which often means the use of GPUs or other kinds of AI accelerators. Ten years ago, if we talked about edge, we’re talking largely about embedded systems or compute systems that we treat as embedded. Embedded is a special word in IT. It means it’s fairly locked down. It doesn’t get updated very often. When we look at things like AI, on the other hand, that’s a very living workflow. If I’m doing image processing for manufacturing, for example, for quality assurance, I want to update those models continuously to make sure I’ve got the latest and the greatest.
Jason Lopez: And along with managing fleets of hardware and software in AI deployments at the edge, there’s also the issue of security.
Steve McDowell: By treating edge systems as connected and part of my infrastructure, and not as we historically have treating them as kind of embedded systems, if you will, it also allows me to, in real time, manage patches, look at vulnerabilities, surface alerts back up to my security operations center, my SOC. It makes the edge look like it’s part of my data center.
Jason Lopez: Tools like Nutanix allow for this approach, applying a consistent management practice across both core and edge environments. This involves deciding what tasks to perform at the edge versus the core due to constraints like cost, security, and physical space.
Steve McDowell: A key part of the conversation becomes what lives where? And that’s not a tool problem, right? That’s kind of a system architecture problem. But once you start partitioning your workloads and say, this certain kind of AI really needs to be done in the core, Nutanix gives me that ability and cloud native technologies give me that ability to say, well, I’ll just put this kind of inference in the cloud and I’ll keep this part local.
[Related: Pivot Past the Enterprise AI and Cloud Native Hype]
Jason Lopez: McDowell’s thinking springs from the flexibility afforded by hyper-converged infrastructure. The idea of AI at the edge is part of the whole architecture of storage, network and compute.
Steve McDowell: That can be as disaggregated as it needs to be. So if I need a whole lot of compute in the cloud, I can do that and then put the little bit at the edge and I can manage all of that through that single pane of glass, very, very powerful.
Jason Lopez: Treating edge computing as a part of the data center becomes so interesting because of how the data center itself is being transformed by AI and machine learning.
Steve McDowell: Once we abstract the workload away from the hardware, I’ve broken a key dependency. I don’t have to physically touch a machine to manage it, to update it, to do whatever.
Jason Lopez: The point McDowell makes is how management, not just of the configuration of a node, but across a fleet, is simplified. It enhances efficiency and scalability.
Steve McDowell: We’re taking technology that evolved to solve problems in cloud, but they apply equally to the edge, I think. It turns out, it’s a fantastic way to manage edge.
[Related: More Reasons for HCI at the Edge]
Jason Lopez: AI at the edge is increasingly adopting cloud-native technologies like virtualization and containers. The shift is to container-based deployments for AI models, sharing GPUs and managing them remotely.
Steve McDowell: If you look at how, you know, NVIDIA, for example, suggests pushing out models and managing workloads on GPUs, it’s very container-driven.
Jason Lopez: And McDowell explains why this simplifies edge management.
Steve McDowell: A GPU in a training environment is a very expensive piece of hardware. And giving users bare metal access to that, you know, requires managing that as a separate box. Using Cloud-native technologies, I can now share that GPU among multiple users, very, very simply. That same flexibility now allows me to manage GPUs at the edge with the level of abstraction that works. So I can sit in my data center, push a button and manage that box without actually worrying about what that box looks like necessarily. So I don’t need that expertise kind of onsite, right? Which is a key enabler for edge. If you have to have trained IT specialists wherever you’re deploying, that doesn’t scale. And edge is all about scalability.
[Related: The Future of AI Computing Resides at the Edge]
Jason Lopez: GPUs are typically what power AI, but are are not commonly found at the edge. But inference is a facet of AI that many technologists see value in at the edge. GPUs would be the right fit if at the edge, generative AI is needed. But what’s needed now are inference engines, especially around vision and natural language processing.
Steve McDowell: Take, for example, a retail environment where they have intelligent cameras that are positioned all up and down the aisles of the grocery store. And the only job that these cameras have is to monitor the inventory on the shelf across from the camera. And when they’ve sold out of Chex mix and there’s a gap there, it sends an alert, come restock. I mean, it’s very kind of data intensive and you don’t want to send that to the cloud necessarily.
Jason Lopez: Technology is moving toward managing infrastructure environments seamlessly, such as edge, data centers, and cloud, without changing tools or management models.
Steve McDowell: Nutanix has capabilities for managing AI in your workflow, kind of period, full stop. A good example of this is GPT in a box. Where it’s a technology stack and I plug a GPU in and I can do natural language processing. If I want to push that out to the edge. I don’t have to change my tools. I mean, the beautiful thing, and the reason that we use tools like Nutanix is that it gives me kind of a consistent control plane across my infrastructure. Now, infrastructure used to mean data center, and then it meant data center and cloud. And now with edge, it means data center and cloud and edge. The power of Nutanix though, is it allows me to extend outside of my traditional kind of infrastructure into the edge without changing my management models. So, as AI goes to the edge, I think the things that already make Nutanix great for AI in the data center are equally applicable at the edge.
Jason Lopez: Steve McDowell is founder and chief analyst at NAND research. This is the Tech Barometer podcast, I’m Jason Lopez. Tech Barometer is a production of The Forecast, where you can find more articles, podcasts and video on tech and the people behind the innovations. It’s at theforecastbynutanix dot com.
In this Tech Barometer podcast, Nick Mahlitz, digital infrastructure manager at Forestry and Land Scotland, takes listeners to his homeland, where he helps the government use data and cloud technologies to manage natural resources and meet sustainability goals.
Find more enterprise cloud news, features stories and profiles at The Forecast.
Transcript:
Nick Mahlitz: I learn new things every day as I talk to our staff members. Just recently, we’re using drones with lasers to map out the land. So the drone footage stuff is really, really, really good. They can then tailor what they do with the land around what they found with these drones and with the lasers, they can go through forest layers, they can analyze the types of land that is, and oh, there’s a ridge there that we perhaps need to avoid, and just making better decisions.
Jason Lopez: We’re starting this podcast interview by parachuting right into the heart of the work of Forestry and Land Scotland, the federal organization that manages the country’s public land and wilderness. A year ago we talked with the manager of the organization’s data centers, Nick Mahlitz and posed the question:
Ken Kaplan: The forest needs technology?
Nick Mahlitz: Yes. The forests do, yes, to manage your forests well and good, to use technology in a challenging environment like Scotland, where it’s very remote and the weather can be quite extreme sometimes. Technology and exploring all realms of technology will only help us better manage Scotland’s forests and our land.
[Related: Forestry and Land Scotland Trailblazes Private-Public Shift to Cloud]
Jason Lopez: So, we circled back to follow up on that interview. Forestry and Land Scotland is utilizing technologies like drones with laser mapping capabilities. As we’ll learn, it gets very data intensive which is Nick’s job to oversee. He supports the organization’s mission to balance natural resources. One of those balancing acts is to better track wildlife, particularly deer, to protect young trees.
Nick Mahlitz: Scotland has a lot of deer, so we have to cull a fair amount of them. And the challenges around Scotland being a very remote piece of land and identifying and culling enough deer in a small frame of time can be very challenging. So with technology of tagging deer and using drones to manage where they are, a ranger can go from culling a couple of deer and say half a day or a day to 8, 9, 10 deer within the same timeframe.
Jason Lopez: Scotland’s public land serves many interests. Trees enhance carbon sequestration. Some of its forests are grown for timber, and some of its land is used for renewable energy projects — such as wind and hydroelectric power. Scotland’s goal is to be net zero by 2045. One of the most important uses of the land is for the public’s enjoyment of the outdoors. He takes note: it’s good for people behind the scenes of his own organization to experience the places their work supports.
Nick Mahlitz: You know, I don’t want to be the person in the basement. You know, the data is there, but it’s also good out and enjoy it. And we try and do that. We encourage non-forester staff to go out with a forester for the day. Pick what you want to do. Do you want to go and see a piece of bog peatland be restored? Do you want to go and plant a tree? Do you want to go and uplift trees? You know, we offer these activities to people like myself or back office staff, HR procurement, except anybody who wants an interest in it, because it’s so important. If you understand that you’ll understand your role in the organization and how better you can play a part.
[Related: How a Top University in Scotland Expanded Remote Teaching Tech During a Crisis]
Jason Lopez: This is why the forest needs technology. The earth’s landscape has been so altered by human development for the past 30,000 years, it requires human conservation to prevent further decline or restore land to a balanced state. Intervention is critical.
Nick Mahlitz: Peatland restorations, the soil gets degraded, you know, so we’re trying to restore the balance in the soil so that it can keep more carbon, et cetera, et cetera. So there’s that ongoing. We’ve got big plans for a big nursery that’s coming up where we can plant 19 million trees a year. We’re planting the trees in a special way. The seeds are planted into biodegradable paper that can just be streamlined, planted, and we can plant far more than we could normally. And then as we cultivate them in a nursery, we have to plant them outside in fields. And we’ve re-engineered equipment to then do that planting for us rather than manually. And, you know, just that kind of approach just means far more efficiencies meeting our targets and making our staff more efficient, which is fantastic.
Jason Lopez: What scientists are learning today about the natural world and what technologists are innovating is accelerating.
Nick Mahlitz: And that is unlocked by cloud, by edge, by modern approach. Lots to be done though. Lots to be done still.
Jason Lopez: Nick’s current goal, managing the data centers of Forestry and Land Scotland, is on integrating AI and automation to improve their operations to better understand their data.
Nick Mahlitz: And that’s what we’re actively working on now. And the reality is I can know about AI and automation, me and my team and others in the digital landscape. We know about that for ourselves, but to translate that into somebody with a chainsaw who’s cutting down trees or somebody who’s managing wildlife management as in deer or our nurseries where we’re planting our seedlings to then grow, what does AI and automation do for these ones? And that’s the core of our business.
[Related: Do Forests Really Need Technology?]
Jason Lopez: He reminds us that AI is not the core of the business. AI is a tool. His team’s core business is about data.
Nick Mahlitz: How much data do we have? How can we better understand it? How can it better help us make more informed decisions on our future for sustainability, for a net zero, for generating revenue, et cetera, that we do? So there is now a big piece to understand how we capture data, how we store that data, how we report on that data, how we integrate that data, how we use AI and automation with that data. So that really is a big focus for our organisation over the next year or two.
Jason Lopez: And this exemplifies how Forestry and Land’s data centers operate, with a passion for sustainability. Migrating to the cloud improved efficiency and prompted a shift towards reducing energy and CPU usage ,as well as modernizing.
Nick Mahlitz: So, you know, we have, we have legacy systems and they have legacy interactions and, but they’re now in the cloud. So we can replace some of those interactions with more modern solutions, which gets rid of, you know, having to spend so much energy or CPU, I get rid of that inefficiency, even in code, even right down to the lower levels. And that really can make a big difference as well. And that’s something that’s, FLS is passionate about sustainability, but even, you know, filtering that down to our digital teams, they appreciate that too. So that’s where we can look at and make those changes that just makes everything run better in a more sustainable way.
Jason Lopez: The transition to a full public cloud makes management easier and has simplified data center operations. And it’s allowed for easy integration of other cloud products and solutions.
Nick Mahlitz: So we have no on-prem environment to administer or manage. So that is quite a unique position that we find ourselves in. And we could not be more delighted with the results. The actual transition to the cloud using Nutanix was an experience that made our journey so much simpler and has bought us the time that we need to modernise and transform our solutions into that next-gen approach. So what we did with Nutanix really was, we saw it as groundbreaking. It’s delivered what we aspire to and it had benefits that perhaps we never really realised at the time that we now enjoy.
Jason Lopez: Nick says the migration has resulted in something else they didn’t originally factor in: time savings. He and his colleagues have the time resources to invest in new technologies, which help in the goal of reaching that net zero target by 2045.
Nick Mahlitz: And comparing our footprint of our on-prem environment compared to what we have now through the metrics that we receive from Microsoft, given that we’re in the Azure platform, it’s really heartening to see that that sustainability piece and net zero is being reached in some way or added to our targets that we have as an organization. And then equally that full cloud integration means that we can now tap into other cloud products, cloud solutions, and very easily integrate them into what we have, which before we didn’t fully appreciate that we could do that. And as Nutanix expand their products and services in the cloud, we’re only going to enjoy that more and more.
[Related: Easy Alternative for Migrating or Extending to Public Cloud]
Jason Lopez: The transition to the cloud, again, enabled the organization to adopt other cloud technologies.
Nick Mahlitz: And now that we’re in there on NC2 in the cloud, what we had to do as part of that journey was unlock other cloud technologies to help us realize that. So for instance, identity management, access management, VPN, et cetera, et cetera. We’re now using all the cloud variants of such so that we have no dependency on really local on-prem infrastructure. So what that entails is a very much a kind of zero trust model that’s highly secure within line with modern approach. So that really can then unlock capabilities that we’re just starting to tap into. But given my team, the ability to now manage that in a completely different way to what we had. But it unlocks really future capabilities at which the IT person’s appetite and desire and helps for recruitment and retain of staff and investment and development on staff when what we’ve done can excite people. It can excite the IT people for sure and other people in the organization. So that’s been really, really a good thing for FLS.
Jason Lopez: Astrophysicists remind us what it is to look back, from space, at planet earth, and viscerally understand how vital earth is to life as we know it, yet how small and fragile. People across political boundaries, economies and cultures are galvanizing efforts to preserve oceans, land and forests… and doing this whether its reducing pollution, conserving farmland topsoil, or establishing more efficient data centers.
Nick Mahlitz: And it really just lines up to understanding where we are in technology and our timelines and our lives, working in that agile manner, having the growth mindset, embracing technology, all the attitudes that really permeate behind a good digital team. We took that novel approach. We did our due diligence, but we did something new and exciting. And really that’s the refreshment I have from working for 20 years in this career, so to speak, that still there’s the ability to do novel, new things. We Scots are a passionate people. And as I meet other digital and IT teams in other government areas, there’s a similar aspiration and enthusiasm for understanding technology in their, in their areas too.
Jason Lopez: Nick Mahlitz is the senior digital infrastructure manager for Forestry and Land, Scotland. This is the check barometer podcast, I’m Jason Lopez. You might want to check out the original video we did with Nick entitled “Do the forests really need technology?” You can find that and more stories and podcasts at the forecastbynutanix dot com.
In this Tech Barometer podcast segment, NAND Research Chief Analyst Steve McDowell describes how CIOs manage change and mitigate risk in the first year after Broadcom acquired VMware.
Find more enterprise cloud news, features stories and profiles at The Forecast.
Transcript:
Steve McDowell: I think this year is a lot of, you know, resetting how we think about VMware and I think a little bit of resetting everything about Broadcom and what they do. There’s a lot of uncertainty. I don’t think my position is changed.
Jason Lopez: Steve McDowell is the chief analyst of NAND Research. Welcome to another Tech Barometer podcast from The Forecast, I’m Jason Lopez. When McDowell talks about the Broadcom purchase of VMware these days, he’s quick to point out how the discussion has shifted from what’s Broadcom going to do to what customers are going to do.
[Related: Slew of Changes Drive VMware Customers to Consider Alternatives]
Steve McDowell: IT is all about managing risk. As long as there’s uncertainty, as an IT guy, I need a plan. I need to know how to mitigate against that uncertainty. Even if it’s not wholesale replacement, have a plan B. And a big part of this is second source. Start mixing in as new projects come up, other technologies and balance the risk, right? You mitigate risk by balancing the options.
Jason Lopez: He says the way to look at next steps from an IT perspective is that customers have a lot of unplanned stuff on their plates. There’s a challenge to ensure there are no hiccups in the data center, especially if IT has to find alternatives to VMware.
Steve McDowell: There’s nothing that is a hundred percent drop in replacement for all the overlap Nutanix has with VMware, for example. It’s still a big effort. It’s still a big effort. And you’re asking me to do this effort, well, if I’m going to switch, right, while I’m also trying to figure out this AI thing and solve all my cybersecurity problems. If I’m doing a new project, I’m going to look at cloud native, I’m going to look at Nutanix. And it’s really the only two alternatives. I’m either going OpenShift or I’m going AHV.
Jason Lopez: What IT wants is predictability and consistency.
Steve McDowell: That’s all any IT guy wants. He wants not to have to think about this. IT plans way ahead, and there’s so many digital transformation products on their plates. And this is a distraction. And that’s what they hate.
Jason Lopez: And McDowell’s advice to the players who make IT solutions.
Steve McDowell: You know where that pain threshold is, and you need to build your programs around that. You got to make the switching costs come down, whatever that means, rebates, technical assistance, training, whatever, professional services. There’s ways for competitors to come in there and leverage the situation that does bring relief to these IT guys.
Jason Lopez: Steve McDowell is Chief Analyst for NAND Research. This is the Tech Barometer podcast. I’m Jason Lopez. Tech Barometer is produced by The Forecast. You can find us and more tech stories at theforecastbynutanix.com. All one word, theforecastbynutanix.com.
In this Tech Barometer podcast, Tobi Knaup, general manager for Cloud Native at Nutanix, explains what’s accelerating cloud native application development and how enterprises run these apps across hybrid multicloud IT environments.
Find more enterprise cloud news, features stories and profiles at The Forecast.
Transcript (AI generated):
Tobi Knaup: Cloud Native really is a concept that describes how to build and run modern applications. Those applications are typically microservice-oriented, they run in containers, and they’re dynamically managed. On top of a container platform, typically that’s Kubernetes, that’s really become the industry standard. Kubernetes runs anywhere. You can run it on the public cloud. You can run it on a private cloud. You can run it on the edge. So if you’re building applications on top of Kubernetes in containers, that makes them truly portable so you can run them anywhere, hybrid multicloud.
Jason Lopez: That’s the voice of Tobi Knaup, the general manager for Cloud Native at Nutanix. In this short podcast, the editor of The Forecast, Ken Kaplan, chats with Tobi about the integration of cloud-native applications and hybrid multi-cloud environments. In this discussion they touch on cloud-native applications across various cloud environments; the synergy between AI and Kubernetes; and the shift to Kubernetes for consistency and portability.
[Related: Flattening the Cloud Native Learning Curve]
Ken Kaplan: What was the limitation that’s been unlocked with Kubernetes?
Tobi Knaup: The limitation that was there before is there wasn’t a consistent sort of packaging format for applications that made them really easily portable. And containers kind of provide that abstraction. In computer science, we sometimes call it a layer of indirection. So it abstracts applications away from the underlying infrastructure. And containers are a very lightweight way to package an application, so it’s very easy to ship them all around, all over the place.
Ken Kaplan: And their connection to managing data in different ways, is that something that you have to think about?
Tobi Knaup: Yeah, absolutely. So containers, or Kubernetes when it was first launched, actually did not have support for data. It purely ran stateless applications. So only a few years later, the community, it was actually our engineers at Data2IQ together with Google, created what’s called the container storage interface. And so that became the industry standard for attaching storage to containers. But that was still very bare bones, just simple volumes attached to containers. And so what we did here at Nutanix recently with NDK (application-level services for Kubernetes), really takes that to the next level. Really adds capabilities for disaster recovery and resilience. So makes it really, really easy to run these kind of sensitive stateful applications on Kubernetes.
Ken Kaplan: Awesome, and we’ve been hearing the word resilience and it sounds like the hybrid multicloud, building your apps in containers, these kinds of things are bringing some more control and flexibility for things that you need to keep your business running. Talk about hybrid multicloud in the sense that it’s a choice or it’s where people are today. How did we get here?
Tobi Knaup: Yeah, so I think there are many reasons for why people choose hybrid or multicloud. It’s typically not what a lot of people think at first. I think when hybrid cloud or multicloud first became a concept, people thought, people are going to look for the cheapest compute all over the world and that’s where things are running. I talked to some customers that are doing that actually, but they’re kind of rare and they’re typically hedge funds. So of course they look at market prices. But for most people, the constraints are different. It could be regulatory constraints, right? Data needs to reside in a certain geography or frankly just what an organization is comfortable with, where they’re comfortable putting their most sensitive data. Some don’t want to put it on the public cloud, right? But they appreciate the flexibility and the dynamicism of a public cloud for new developments. So they’re sort of running their steady state production workloads on prem, but they’re giving cloud environments to the development teams for building the next generation of apps, which then may move on prem later when they go to production. So I think a lot of organizations are looking at what’s the best environment for each app and that’s how they’re choosing. And now in large organizations, what we see too is that’s where the multicloud strategy is very common. Sometimes also for regulatory reasons, they have to go with a dual vendor strategy. But also large companies, they tend to acquire a lot of other companies and so the cloud that the company uses that they bought may be different from the cloud that corporate uses and so now they have to manage multiple.
[Related: Containers Progress in a World of Data Center Virtualization]
Ken Kaplan: That’s a lot of complexity. Yes. I guess we could finish here with what are some of the things that you’re seeing, you’re excited about, they’re grabbing your attention, are rising, they’re coming up, everyone’s talking about AI. AI and containers and Kubernetes, they are going together, what’s on your mind?
Tobi Knaup: Yeah, 100% they’re going together. So AI is my other passion besides cloud native. Been doing a lot of work there over the years actually. And it’s worth mentioning that Kubernetes came out of Google. It’s sort of built on the same ideas on which Google runs and they’ve been running their own AI workloads on that platform internally for years. And today, the leading AI companies in the world, like OpenAI, they’re running in Kubernetes. So if you’re using chat GPT, that’s running on Kubernetes. And so it’s a really great fit for these AI workloads because AI workloads, they tend to be very dynamic. They need to share resources, very expensive resources in this case. GPUs are very expensive and in short supply. So it’s a great fit. Also organizations want to iterate on AI very quickly. So Kubernetes really enables that, enables people to ship software fast. So with GPT in a box, which runs on Kubernetes, we’re really making it easy for organizations to put these models into production. And we’re also putting AI into our Kubernetes product, into NKP to assist Kubernetes platform engineers. So there’s a co-pilot type chat bot that’s built in that answers their questions, both sort of generic knowledge questions as well as questions about the environment. They can use it to troubleshoot. So, you know, really simplifies their lives.
[Related: Cloud Native Architecture Critical to 5G Success]
Ken Kaplan: Everything’s coming together.
Tobi Knaup: It is indeed.
Jason Lopez: Tobi Knaup is the general manager for Cloud Native at Nutanix. Ken Kaplan is the editor in chief of The Forecast. They spoke in Barcelona, Spain at .NEXT 2024. This is the Tech Barometer podcast, a production of The Forecast. For more podcasts, video and articles about technology and the people in tech, check it out at www.theforecastbynutanix.com.
In this Tech Barometer podcast, Rene van den Bedem of Microsoft’s Cloud and AI division discusses the future of AI and how cloud computing is evolving to power more aspects of life.
Find more enterprise cloud news, features stories and profiles at The Forecast.
Transcript (AI generated):
Rene van de Bedem: When I started, the personal computer was becoming more miniaturized.
Jason Lopez: Rene van den Bedem says when he started his career in computing it was 1994. The trend was smaller and more compact machines. Windows 3, with a more user-friendly, graphical interface was the dominant OS. It was a period of diversification in personal computing. This is the Tech Barometer podcast. Rene van de Bedem is Principal Technical Program Manager at Microsoft, where he does a lot of work in cloud and digital transformation. We asked him about the state of enterprise computing and he ushered us into a sort of timeline, that ends up at AI… but starts in the 90s with computers becoming more miniaturized.
Rene van de Bedem: And then the networking constructs had just come out.
[Related: Focus Shifts to Migration in Wake of Broadcom’s VMware Acquisition}
Jason Lopez: The emergence of ethernet, token ring technology, and TCP/IP, ithelped establish the building blocks for the interconnected world we live in today. It was the beginning of the transition from military and academic use to the public.
Rene van de Bedem: Jump 10 years later, we went from narrowband in telco, so you know, like PSTN, dial-up modems, 64k data circuits.
Jason Lopez: This shift from slow to faster connectivity, laid the groundwork for the high speed internet technologies that would make cloud possible.
Rene van de Bedem: Jump to let’s say 2001-2002, you had the explosion of the internet. The internet really became this mainstream thing.
[Related: IT Leaders Get AI-Ready and Go]
Jason Lopez: This was the dot-com era, with faster chips, advances in hardware. It moved us from dial-up to broadband, It was a time marked by the spread of wi-fi. Mobility was becoming a big deal.
Rene van de Bedem: So you had all of these building blocks coming together to where we are now, with the invention of the cloud back in 2006, I think it was, with AWS.
Jason Lopez: There was a fundamental transformation in information technology, where physical infrastructure was being replaced by the cloud. It gave users unprecedented levels of accessibility, efficiency, and scalability.
Rene van de Bedem: And now in 2024 with AI, we’re now on this cusp of this next rocket launch that’s coming.
Jason Lopez: AI is becoming a tool with a wide range of uses, much the way calculators did back in the 80s and 90s. Microsoft, Rene says, is integrating AI into all its products. That’s called “co-pilot.” This change signals a transformation to the era we’re entering, where AI is a must have technology.
[Related: Creating AI to Give People Superpowers]
Rene van de Bedem: People who work in an industry, if they don’t adopt these new tools, they’re going to be left behind. So in 10 years time, all jobs around the world, most of them will have some type of AI-based co-pilot that you’ll need to use to do your job, and those that don’t, they’ll just be left behind.
Jason Lopez: It’s a continual evolution. And it especially applies to tech companies which must adapt to the changing needs and challenges of storing and processing an ever-increasing volume of data.
Rene van de Bedem: Obviously, having very, very fast, expensive storage, you need that for a part of the workloads, but then the ability to archive petabytes of data so that you can derive business value from your data sets, that’s a necessity. So storage is always evolving. I’m sure it’s similar is going to be true for quantum computing. We’re going to see a shift in the way that we build our traditional computing models so that that can harness and integrate with AI as well as quantum computing.
Jason Lopez: Cloud service providers are beginning to offer quantum products in a limited way, though scalable quantum computers are not yet a reality. Right now, it’s in the realm of researchers and developers to experiment with quantum principles and algorithms.
Rene van de Bedem: Most of the cloud providers have a service that allows customers to play with quantum computing.
Jason Lopez: Unlike traditional computing, quantum computing stores information in a more complex way, with an exponential increase in processing power for certain types of problems. Rene says the future looks like a hybrid.
Rene van de Bedem: Quantum computing is not going to replace traditional computing. Every technology has got pros and cons. Quantum computing, even though the processing is happening, is not really able to maintain its state once the problem is solved. So what happens is you’ll have your quantum computing model that’s running, and then you’ll have traditional computing services wrapped around that, and all of the data, once it’s solved, goes into traditional computing software constructs, I suppose you would say, to maintain the results of that data and the history and the archives and all the reporting and everything. It’s a hybrid technology where the two need to work together.
Jason Lopez: With the rise of the cloud, many businesses rushed in. There were and are all sorts of very good reasons: reduced IT costs, scalability and flexibility and agility, access to big data analytics, access to AI. And then, simply, it was a trend. There was a sort of peer pressure to move to the cloud.
Rene van de Bedem: When they got there, they realized, “Oh, the business goals that we’ve been trying to achieve are actually not being met,” or they weren’t considered. Typically, cost and operational complexity, because there’s a level of skill that you need to have to work in a hyperscaler correctly, regardless of whether it’s Google, Azure, or AWS. It may turn out that the laws of the land, the laws of physics, or the laws of economics are very, very important to them. So they’re constrained as part of their business goals that they’re trying to achieve. And it turns out, “Okay, running in the cloud is not such a good idea. And then they’re forced to go back. So I have seen that a few times. Because obviously, you’ve got people, process, technology, and financials are the four major domains. And if one of those is weak, then you’re probably not going to be successful.
Jason Lopez: This is what hyperconverged infrastructure was born to do: to consolidate storage, compute, and networking resources into a single, easily managed platform which is software defined, and helps reduce capital and operational expenditures. Nutanix launched its first HCI product in 2011, focusing on making data center infrastructure invisible. Rene says that when it comes to virtualization he’s seen a variety of platforms such as VMware and HyperV, though the Nutanix platform offers a more user-friendly experience. Nutanix Cloud Clusters, also known as NC2, is aimed at more easily managing workloads on hybrid clouds. Rene’s job is to make sure these platforms work inside Azure.
Rene van de Bedem: The beauty of running NC2 on Azure or Azure VMWare solution, to use Microsoft as an example, because that’s all being extrapolated in the back end and the customer doesn’t see it, it’s a lot more easy for them to consume, because really the main requirement is “do you have an Azure landing zone” and then you can build whatever service that you want on it.
Jason Lopez: Rene van den Bedem is Principal Technical Program Manager at Microsoft. This is the Tech Barometer podcast, thanks for listening, I’m Jason Lopez. Tech Barometer is produced by The Forecast, where you can find more stories on technology. Check out Jason Johnson’s article which profile’s Rene, entitled, “Simplifying Hybrid Cloud and Migrations to Azure Public Cloud.” Just go to theforecastbynutanix.com. That’s theforecastbynutanix, all one word, dot com.
Editor’s note: Learn about Nutanix’s hybrid multicloud capabilities, compare offerings from VMware by Broadcom and Nutanix, see how to migrate to Nutanix then explore the VMware to Nutanix Migration Promotion.
In this Tech Barometer podcast, Red Hat’s Bev Gunn and Richard Harmon take listeners into the collaborative world of open source software and explain why it can lead to responsible AI.
Find more enterprise cloud news, features stories and profiles at The Forecast.
Transcript (AI generated):
Richard Harmon: The fundamental principle that’s first is around a global community trying to innovate. So it’s not a single firm, but the global community collaborating. You have people with very different backgrounds, different experiences that are heavily driving innovation overall, and much of the innovation is coming from the open source world.
Bev Gunn: We have strong partnerships with Intel, a lot of the hardware manufacturers as well from the IBM systems groups to NetApp and Dell and HP, and all of the main hardware firms, plus the APIs and chip organizations. So again, just in terms of how open source and our technologies can actually enhance what they’re doing, aligned to what Richard has said is very key to moving forward.
[Related: Can Open Source Software Help Resolve AI Trust Issues?]
Jason Lopez: This is the Tech Barometer podcast. I’m Jason Lopez on today’s edition of Tech Barometer, a look at open Source. Open Source was in the headlines quite a bit during the.com boom. And rather than develop things in the seclusion of their organizations, the idea was to collaborate across company boundaries. This model has evolved over the past two decades. There’s still a bit of controversy over it versus building software in proprietary ways, but open source proponents like the speakers you’re about to hear from Red Hat, see open source as a crucial factor in developing AI in a responsible way In this era of virtualization, hybrid multi-cloud ai, edge quantum computing, it has a vital role to enable new capabilities and engineering business and governance.
[Relate: Open Source Software Powering Business Application Boom]
Richard Harmon: The open source community also has, in some cases, it’s not always profit focused. It’s about building something that’s completely new or different. It’s also about making it accessible to the global community.
Jason Lopez: Richard Harmon is the vice president for the Global Financial Services Industry at Red Hat.
Richard Harmon: But I think, for example, AI governance, there’s a lot of effort about how to evaluate the accuracy of whatever algo that you want to utilize. It’s important not to have black boxes so you can explain what the model is doing, why is it doing and what the answers are. It’s also making sure that things are done in a fair way so that you can monitor that. There’s no bias in other things that could come from the data, come from the algo, come from all different sources.
Jason Lopez: Harmon adds that the ability to audit as well as the security and privacy of applications for consumers, businesses, and governments, is paramount. This is where open source plays a role in accountability, such as in AI responsibility.
Richard Harmon: And I think that that’s something we see with many, many of the projects, the AI based projects in the open source space. Now, I’m not saying if you go into a project that’s done by a single firm, they would also require to instill those principles, but there’s also in many cases, a profit motive behind it. So sometimes when it has a wider open source view, you have people in the community that really focus on these types of things that make AI responsible versus just making AI work.
[Relate: The Race to Hybrid Multicloud Interoperability]
Jason Lopez: Companies like Red Hat provide open source tools that enable developers to innovate across various platforms while ensuring code security and privacy, including practices like confidential computing. We
Richard Harmon: Allow developers to build and innovate on any platform they want to run on basically. So it’s that kind of enablement.
Bev Gunn: It allows those developers with different skill sets, with different experiences and backgrounds and what have you to help to contribute around new technologies linked into AI.
Jason Lopez: Bev Gunn, who works in Red Hat’s global financial services, refers to what’s happening with the rise of AI in terms of speed and momentum. It’s a matter of how to develop and deploy technology smarter, quicker, and doing more with less.
Bev Gunn: In the old days, there was a certain way and methodology of working and partnering and what have you now, I said every day of the week where we have organizations who want to be part of that cultural movements of open source, of transparency, of contribution.
Jason Lopez: Open source tools like Python make advanced algorithms accessible through freely available libraries and development tools. As Richard points out, these are provided not just by Red Hat, but other companies in the space.
[Relate: IT Leaders Get AI-Ready and Go]
Richard Harmon: And eventually we’re going to have more and more of things like generative AI that will actually make learning of how to code much easier and quicker and make things much more efficient. But I think the secret, which you hit on precisely, is that this ability of democratizing access, and I think that’s the most compelling part about open source, is that it’s accessible to anyone. And I think that also is a lot about the culture of Red Hat and the culture of any company that’s in open source. It’s really a culture of sharing. It’s a culture of openness and transparency, but it’s also a culture of trying to strive to really build something and develop something that people can use and benefit from.
Jason Lopez: There’s a role for open source AI and transforming enterprise operations within the hybrid cloud environment. It allows for experimentation and it benefits from improving hardware performance, especially in automation, which is foundational to AI and makes processes smarter and more efficient.
Richard Harmon: I’ll give one example Swift right? It’s the global payment system. It’s owned by more than 11,000 banks globally, and it is really largely the global international payment rails for almost all countries. And what Swift has done is they’ve taken an open source approach, and they’re focused on building out sort of the next generation of AI platform with particular focus on trying to build out what they call financial transaction intelligence at scale. And their initial focus has been in financial crime. They’re building out a high performance AI environment, leveraging the unique data set they have, which is pretty much a very, very large percentage of all transactions around the world. That’s unique. No individual institution, or bank commercial provider has that kind of data set. They’re in a unique position to potentially build tools that the 11,000 plus members can utilize to help address financial crime aspects.
[Related: Birth of a Hypervisor That Unleashed the Hybrid Multicloud Era]
Jason Lopez: This is where AI is being enabled to allow Swift to securely innovate and information and insights can be shared with other institutions, which can build whatever models they want.
Bev Gunn: And so banks had to become very innovative in terms of the service offerings they had and have today because a lot of the new and neo banks or digital banks are spinning up with a lot of innovation. A lot of our banks are now offering almost concierge services with different capabilities and innovations. And so how do you differentiate yourself in the market, but stay ahead of the competition by still being profitable? Coming up with the example that Richard gave in one of the big banks, saving costs is going to be imperative because those costs can then be diverted and redistributed to create more innovation and more differentiated services to your customers and to the public.
[Relate: IT Team Modifies Open Source NetBox to Help Manage Hybrid Multicloud]
Jason Lopez: When we began this story, one of the facets of open source was about its effect on creating responsible ai. Open source is an enabler of transparency. It helps to maintain flexibility, allowing organizations to switch platforms. The approach enhances resiliency by mitigating risks associated with over-reliance on a single provider.
Richard Harmon: Yeah, I mean, in Europe we have the DORA, the Digital Operation Resiliency Act, and it’s around mission-critical applications, but it’s around third-party dependencies for, it’s mostly in financial service for banks. In this case DORA was the first time that the cloud providers are included in this because they are a critical third-party platform. And so the regulators are concerned that there is a concentration risk about that, and at the same time, they want to ensure that firms are doing the right things to ensure that they have an exit strategy. At Red Hat, we like to talk about portability, about moving across, basically running your application anywhere on a hybrid multi-cloud environment. But it doesn’t mean that you have to run on many clouds. It means if you’re running in one cloud and you need to demonstrate that you can run an application like core banking or payments or something in another cloud, you can demonstrate that, but it doesn’t mean you have to be running in many, many clouds. It’s the ability that allows you to avoid that lock-in effect,
Jason Lopez: Regulators aren’t just concerned about one bank, but about the entire system of banks. It’s one thing for one bank to go down, but the platform issue it’s entirely another. When you’re talking about five or six major banks,
Richard Harmon: The analogy I always make is if you look at Lehman Brothers, Lehman Brothers went down, the problem is no one knew who else was impacted, and there’s spillover effects. And so we had the commercial paper market crash. We had financial a disaster that many, many governments had to bail out the financial system to put it back into a stable environment. And it’s that kind of systemic risk that regulators are really, really worried about. So obviously they don’t want any individual bank to get into trouble or have big issues, but their big picture is the overall financial system.
[Related: Unlocking Benefits of Hybrid Multicloud IT Automation]
Jason Lopez: Today, there are millions of open source projects which reflect contributions from a diverse global community, including government, corporate sectors, academia, and students. In the last decade, global adoption of open source has significantly increased, and Red Hat has played a major role as a leading open source company.
Richard Harmon: It’s a global community from government entities, corporate, academics, and students of all walks of life that in some cases contribute to these projects. So it’s typically projects people are passionate about. Obviously at Red Hat, we have a lot of very passionate engineers, but it’s also very focused on addressing challenges that various industries have, society has. So it’s not just about building a piece of software, it’s typically about trying to make something. And even when you get into, for example, climate, there’s a project called OS Climate. I’m on the governing board of it, and Red Hat is a major participant with many other institutions, but that’s an example of a good number of institutions getting together to try to help the wider industry efforts and make things like data and analytics available to anyone who wants to access it.
Bev Gunn: And just on that collaborative piece, when we think about what we’re doing with Microsoft and AWS around managed OpenShift that’s taken place over the last five years because they’ve understood as well from an open source perspective, the strength of open source capabilities, even though they’re contributors to community as well, but actually building out managed service offerings within their own organizations with our technologies is kudos to the value that they see that this brings to the markets and to their own customers and prospects. So feeding of what Richard said and then looping in some of that activity definitely showcases that collaboration piece in the market with some of the big cloud providers, which there’s a lot.
Jason Lopez: Bev Gunn is an executive in Red Hat’s Global Financial Services. Richard Harmon is the Vice President for Global Financial Services Industry at Red Hat. This is the Tech Barometer podcast. I’m Jason Lopez. Thanks for listening. For more stories and more insights into technology and the people in tech, check out the forecast which produces this podcast. You can find the forecast at the forecast by nutanix.com.
In this video, Harmail Chatha shares how he helped build a state-of-the-art, efficient data center using software-defined capabilities from Nutanix.
Find more enterprise cloud news, features stories and profiles at The Forecast.
Transcript:
Ken Kaplan: When you started building these early on, sustainability was definitely a part of it. You want to make them efficient, but it’s shifted.
Harmail Chatha: So when I first started, sustainability wasn’t even a thing in the industry, right? You heard about sustainability farms and food production and stuff like that, but you didn’t hear about it too much in the tech sector. And of course, larger companies like HPE, and Cisco, have been at it for a long time, but customers really, really never understood it and it wasn’t very top of mind. The way that I got involved in sustainability really started in 2018, not knowing that I was trying to build a sustainable data center, but I’ve actually built one of the most sustainable data centers. And what the premise of that build-out, the architecture then was, we wanted it optimized. We wanted to ensure the amount of power coming into a rack was exactly the amount of power we’re using within the rack, and that the rack wasn’t under provision.
So we’re only using half of the rack, but we’re maximizing full utilization of the rack itself. As I started getting more involved with ESG and specifically the E portion of it, IT consumes a major part of total power in any organization and IT manages the data centers. And we started to realize, wow, we have some really efficient data centers that we architected back in 2018, and we got some not-so-efficient data centers around the world that are more colo retail, a couple of racks here and there.
[Related: Building Scalable, Sustainable Data Centers]
So for us, our multi-megawatt data centers are the most sustainable data centers. We sought out partners that were focused on minimizing their environmental impact by having a lower PUE, and by having innovative strategies around water reclamation. And that really offered us solutions and options around renewable energy as well. So that baseline with that premise set, and now we’re in 2023 and sustainability is top of mind for everybody. For example, we conducted an annual ECI, Enterprise Cloud Index, survey with 1500 global IT leaders, and 92% of the respondents said that sustainability is more top of mind this year than it was last year. With that sustainability starts at the data center. I mean, there are obviously different scopes of sustainability, but IT being the largest consumer makes the biggest impact and can have the most impact on reductions as well.
Ken Kaplan: And this experience that you’re gaining, you’ve done the work that was very successful.
Harmail Chatha: So it was an epiphany to be involved in ESG, specifically the E, and to understand that data centers I built in 2018 are a core part of Nutanix’s environmental impact and the fact that they’re so sustainable. We don’t have to go back and reinvent the wheel because our data centers are already hyper-dense. We’re already maximizing the utilization of power and real estate within the data center. On top of that, we’re already gaining more impact by having renewable energy options and being able to offset or be carbon neutral in our data centers as well. So we got lucky. We’re ahead of the game. It was very smart and intuitive for us to kind of have that focus of optimization, which has ultimately led to more efficiency in the environmental impact.
[Related: Experts Discuss Top IT Sustainability Challenges]
Ken Kaplan: Tell me about your journey, Nutanix’s journey towards sustainable IT.
Harmail Chatha: So Nutanix’s journey really started when the company started itself, right? A step in the right direction, whether they knew it then or not, with hybrid converged infrastructure was this very sustainable approach. So from the get-go we’ve always been a sustainable company per se. But really in 2018 when we revamped our data center strategy, when we went to hyperdense rack design, we even got more sustainable. We only got the amount of power that we needed for our consumption. We only got the right amount of real estate that we needed for our hyperdense racks as well. So those two steps were key in our sustainability journey. But ultimately what we focus on is reducing our infrastructure footprint. We try to consolidate as much as we can. Our standard architecture in the data center is a four-node block, so that way we’re maximizing the power in the space within the rack in itself.
So that was really the third step we took is the consolidation. And then within our platform, we ensured that we weren’t over-provisioning and underutilizing, meaning that we only provisioned infrastructure that we needed for a specific workload or a data set without an overkill of infrastructure in itself as well. We avoided VM sprawl problems as well, ensuring that we’re only running the VMs that we need to run and then hibernating or deleting the rest of the VMs as well. And then ultimately what that led to is a carbon reduction on the back end of it, right? Because our environment is so highly efficient from the data center provider to our power consumption and real estate utilization to our consolidation of infrastructure, eliminating waste of over provisioning, and underutilizing has really led to a much more sustainable carbon-neutral footprint for us in the data center environment.
Experts in modern data center technologies and sustainability provide valuable insights for building IT sustainability strategies.
Find more enterprise cloud news, features stories and profiles at The Forecast.
Transcript:
Mat Brown: There is a lot of regulation coming, a lot of legislation.
Andrea Osika: Between 2021 and 2022 there was an 80% increase in regs that encompass ESG.
Harmail Chatha: If you’re going to build a sustainability strategy, budget should be the starting point. By consolidating the hardware, you’re reducing your power footprint by 35%.
Jason Lopez: What you’re about to hear are the highlights from a breakout session for IT pros who attended the Nutanix .NEXT conference in Chicago. The speakers are from Nutanix, Andrea Osika, who is laser-focused on sustainability in ESG, Mat Brown, technical marketing manager, along with Harmel Chatha, who leads global hybrid multi-cloud operations. They work on sustainability issues, which are reported in Nutanix’s annual Environmental, Social, and Governance report. This is the Tech Barometer Podcast. If your IT organization is trying to navigate ESG, this segment sheds light on IT sustainability trends and insights Nutanix has gained from evolving its own sustainability efforts. They reveal their experiences in adapting to various waves of change, including uptime and costs, security and regulations, particularly around carbon compliance and the management of greenhouse emissions through FinOps and AIOps. Andrea Osika starts off with this: as sustainability becomes increasingly central to business operations and strategy, IT professionals and executives will be expected to adapt to, in fact, their performance often measured by, a focus on ESG.
[Related: Data Center Decisions Draw on Sustainability Strategies]
Andrea Osika: When I started in this space, a lot of very large companies mostly had initiatives around this. And it was kind of seen as a nice-to-have. But if you think about the definition of sustainability and balancing today versus tomorrow, there’s business value that’s involved. And it turns out that companies who set short-term goals and balance those with sustainability metrics have actually outperformed the market in the last 10 years. So this has made investors take notice. Depending on what app you use to look at your publicly traded stocks, you might see now a sustainability tab. And we’re going to add on top of that an energy crisis and more environmentally-minded customers and even talent that your organization wants to attract and hire and then even retain. They’re all paying attention to what different organizations are doing in this space, particularly in Europe, in the UK, over in Asia. There are all kinds of pending and imposed regulations that are coming. I have been attending so many webinars and working with consultants to try and keep up. It seems like the goalpost is almost moving as we try to find a way to standardize and communicate all of these metrics. And one way is through an ESG report. I know I throw acronyms around. I’ve said it a couple of times, but environmental, social, and governance.
Jason Lopez: The 2022 Enterprise Cloud Index Report, or ECI, showed that 95% of IT professionals saw sustainability becoming more crucial in business decisions. The more recent 2024 ECI report shows IT pros are actively integrating sustainability strategies with their IT modernization efforts. Many organizations have become more data-driven about sustainability. 51% of organizations say they improved their ability to identify areas for reducing waste. 44% indicate they improved their ability to monitor and measure greenhouse gas emissions, as well as their carbon footprint. In the breakout session, Nutanix experts explained how the environmental impact of technology goes deeper than power usage and metrics. There’s the lifecycle of IT hardware, starting with the mining of metals and minerals, the manufacturing process, packaging, shipping, the management of devices in an IT setting, and the eventual disposal of the devices. Mat Brown identified a starting point for a business case. Dive into getting educated about sustainability facts, build relationships with like-minded individuals and organizations, plan and implement, identify the metrics relevant to the organization’s operations, and automate the measurement of those metrics.
[Related: 4 Steps for Building an IT Sustainability Strategy]
Mat Brown: IT is both a big part of the problem, particularly for companies that aren’t involved in manufacturing. They are often emitting the most carbon emissions through the use of their data center and other IT services. But technology is also, of course, a massive part of the solution, potentially. Whether it’s digital transformation, removing paper processes, automating lots of operations, smart building management to be more energy efficient, improving logistics and mapping out routes and things like that. On the one hand, we’re this big consumer of energy that’s being asked to consume less. And on the other hand, we’re also the platform where they want to do all of this smart, intelligent AI and ML stuff to improve the world around us. And what we’re starting to learn is that everything has a footprint and everything adds up.
Jason Lopez: As Andrea Osika talks about frameworks used for measuring power consumption and measuring carbon emissions, she introduces the concept of scope. Each scope, from Scope 1 to Scope 3, classifies emissions based on their source and whether emissions are direct or indirect.
Andrea Osika: Scope comes from the greenhouse gas protocol, which is the basis for all carbon emissions reporting worldwide. It’s essentially the gold standard for how companies report their emissions. And it’s broken down into three categories. They are in the order of descending control of the reporting organization. So if we start at the top, those are the direct emissions. That’s scope 1. And these are the emissions that are released into the air, typically from combustion, from burning something. And if you think about what that means in real terms, that’s like if your organization has a fleet of vehicles or the natural gas that’s used to heat your facilities. Those are two kinds of concrete examples. Scope 2 are indirect emissions. And they are a result of energy that is used to produce power. So typically this is in the form of steam or electricity. So electricity in your organization’s facilities and your data centers. And then scope 3 is the easiest one for me to explain. But it’s the most challenging. Even the greenhouse gas protocol tells us that this is something that they need to continue to work on. But it is literally everything else. This is your value chain. This is your hardware, your OPEX, your CAPEX. This all falls into scope 3. This is how your organization will report your emissions. And if you need an easy way to remember scopes 1, 2, and 3, here’s how I’ve learned. The energy that you burn. The energy that you buy. Everything else.
[Related: Experts Discuss Top IT Sustainability Challenges]
Jason Lopez: Focusing on scope 2 and scope 3 emissions is where Nutanix and other tech companies see the most opportunity to influence their overall carbon footprint, either through improving energy efficiency or by addressing the broader impacts of their products and services on the environment.
Mat Brown: How far does the rabbit hole go? Well, it certainly goes to embedded emissions in the hardware that are built and shipped to a facility. That’s one thing. Any cables you buy to plug in. It also includes any cloud services you may use, SAS services, bare metal services, and things like that. Those are probably a lot more tangible that you can get a feel of. Some providers also will be able to feed back to you the emissions associated with those services provided. Others less so. How their methodologies work probably are on an ongoing basis, but often they’re estimated using monetary values or something like that. Scope 2 is really where we talk a lot more to our customers about. So when a customer has their own data center, the electricity used to power that IT in the rack, that is a scope 2 emission. Somebody somewhere is burning fuel, gas, coal, or even renewable energy comes with a carbon footprint. That all adds up to power the IT equipment that we have running in our data centers.
Jason Lopez: This is where Harmel Chatha comes in. He’s responsible for running Nutanix’s hybrid multi-cloud IT operations. He explains how Nutanix and its customers leverage software-defined hyper-converged infrastructure, which brings operational efficiencies and helps manage and scale resources wisely. Chatha talks about using fewer resources, generating less waste, and avoiding unnecessary complexity by relying on modern IT solutions.
Harmail Chatha: We reduced our infrastructure footprint. We consolidated where we could. We got away, not that we ever had, three-tier architecture as well. We only deploy hardware that’s required. It’s not deployed in a safe manner on the over-provision just to be safe that I have enough capacity. Step two of it is really eliminating waste and over-provisioning. You only buy what you need, you only deploy what you need to deploy, and you only run the services that need to be run. And step three is really the benefits of step one and two, which leads to carbon reduction. That means you can deploy your applications anywhere you like across any region, wherever the power is cheapest at that given point in time. Now that we’ve got some context around what can be done, let’s apply to what we have done. So Nutanix is about 12 years old. We inherently are sustainable from the HCI perspective because we integrate, converge, compute, storage, and networking into our stack. Since 2010 when Nutanix started, we already had a sustainable footprint, whether we knew it or we didn’t. Nobody was really measuring sustainability at that point. But then in 2018, we took a bigger step. We revamped our data center strategy from our data center where we initially started to a new strategy where we consolidated our racks. We’re populating our racks with 92 nodes. That is 23 blocks in a single rack. And what we gain from that is 68% more efficiency from an OpEx, CapEx perspective, and consolidation perspective. If we are already an HCI stack, we’re already 100% virtualized in our environments. There is no bare metal one-to-one environment in any of our data centers. The last couple of years, we voluntarily started reporting our ESG reporting. And this is so complex. So for us, sustainability has been and will continue to be a journey, not just a one-off set destination that we can check off now that we’ve done our ESG report. We’re super sustainable. We’re not by any means. That first year, we only focused on Scope One, Scope Two, and Scope Three related to our data centers and related to our offices’ total power consumption.
[Related: Building Scalable, Sustainable Data Centers]
Jason Lopez: Understanding what to measure means identifying the relevant metrics that would accurately reflect the company’s impact on the environment. Then it’s determining how to measure. No small feat given the number of locations and data centers. To manage and analyze this vast amount of data, his team consolidated the information into Google Sheets as a starting point. Partners with the expertise to measure emissions helped. Chatha says it seemed they had a baseline.
Harmail Chatha: But no, we didn’t. The second year, we learned more. We gained a better understanding of how to measure. The data was more accurate, so hence our emission reporting was much more accurate. But in year three of our ESG report, we implemented a SaaS platform that actually aggregates in real time all of our power consumption from our leased offices and our data centers. So we can go to the platform and actually check it out in real time which location is utilizing how much power and what the footprint of that is. We got away from the Google Sheets. We’ve got a platform now. Data is more accurate. Our emissions calculation is more accurate.
Jason Lopez: A strategic approach to sustainable IT begins with the optimization of the infrastructure platform. As Mat Brown describes, it offers the potential for significant environmental benefits and supports things like the deployment of sustainable applications and better management of hardware life cycles.
Mat Brown: If you can use less hardware, then that obviously is a good thing for embodied emissions. There’s less power supply potentially in that hardware. That’s another good thing for reducing power consumption. But if you think about how you can reuse or repurpose IT equipment, there’s recycling programs in place. You have the choice of hardware vendor, even down to choice of components, whether that’s an Intel CPU or an AMD CPU. You can look at their various properties, features, et cetera, and see what fits your business requirements around your hardware life cycle and circularity the best. So take up that choice where you can.
[Related: Green Data Centers: Designing a Sustainable IT Future]
Jason Lopez: Different electricity grids in different countries or regions have different carbon intensity. Carbon intensity refers to the amount of CO2 produced per unit of electricity generated. Grids that rely heavily on coal or oil have a much higher carbon intensity compared to renewable sources like wind, solar, or hydro.
Mat Brown: For example, if you had a data center in Poland and you were able to magically shift it up to Sweden where there’s a lot more renewable energy with a lot lower carbon intensity, that could be a 30 times drop in the use phase emissions for that platform. In order to work out how much IT platforms emit or are responsible for in terms of carbon emissions, you’ll need to know that carbon intensity grid factor, which you can get from a variety of sources. And you’ll also want to know something called the power usage effectiveness of your facility. Those tend down towards one, the lower being the more efficient. But it’s not just all about the PUE. Reducing power at the rack can be much more effective than just shrinking a few percentage points on the power usage effectiveness of the data center. But being able to place your workload potentially where it’s going to run in the most efficient way is very key to this whole physical location, power, and environment.
Jason Lopez: He said Nutanix emphasizes the critical dynamic between infrastructure and power usage. Modernizing data centers increases flexibility, scalability, and encourages more innovation in IT while consuming less power.
Mat Brown: Because that platform’s all integrated in a single pane of glass, you can then start working on your operational efficiency more and more, optimizing the actual demand, optimizing what consumers of IT are asking for, doing right sizing, using AIOps for improvement, reducing waste, oversized VM everywhere, implementing show back, charge back, or even recently I heard the term at a FinOps discussion, shame back, to shame people who weren’t implementing their optimizations effectively. You can put the impact in front of the user, the application owner, and show them what they’re responsible for and feed back to them, then they can take on more responsibility for driving optimization.Jason Lopez: Mat Brown is Senior Technical Marketing Engineer at Nutanix. Harmail Chatha is Nutanix’s Senior Director of Global Cloud Operations. Andrea Osika is Marketing Manager of Sustainability at Nutanix. What you heard were the highlights from a stage presentation on sustainability given during the .NEXT conference in Chicago in 2023. This is the Tech Barometer podcast. I’m Jason Lopez. Tech Barometer is produced by The Forecast. For more podcasts and stories about technology and the people in tech, you can find it at theforecastbynutanix.com.
In this video, learn how a cloud operations expert thinks about power efficiency, software-defined infrastructure and how to get more with less from data center innovation.
Find more enterprise cloud news, features stories and profiles at The Forecast.
Transcript:
Ken Kaplan: What does the data center signify to you? What’s the role?
Harmail Chatha: So whether people know it or not, data centers are a very crucial part of everyone’s daily lives, right? All the applications that we have on our mobile phones and our desktops, all the websites that we visit come from a data center. A public cloud is actually a large scale data center in itself as well. So anything that’s tech related goes back to a data house where it’s hosted and hence the services are provided.
Ken Kaplan: Everything we do from health to going to the grocery store increasingly touches the data center.
Harmail Chatha: Absolutely. Health for sure. All the images, all the applications that are used within the hospitals as well. The POS systems and restaurants and grocery stores for sure. Airline industry, when you’re booking your tickets online, that’s all being served by a data center. So really just about anything digital has something to do with the data center.
Ken Kaplan: Part of building the data centers that you’ve helped build: a critical part is the hardware that needs to go in and the power consumption that needs to run it. How is that changing?
Harmail Chatha: So I’ve been in the data center industry since 2005. Back in the day it was small, 42 U racks, maybe three to four kilowatts per rack of power utilization. Maybe you half fill those racks and you had multiple power coming into the rack from a redundancy perspective. But to the point we’re at now, we’re pushing multi kilowatts into a rack. Specifically at Nutanix, we’re between 17.3 to 34 kilowatts per rack. Racks have gone very high density in the sense that we’re able to deploy a lot more compute, especially with hyperconverged infrastructure where you’re able to consolidate storage, networking, and compute into a single server. You’re able to really impact and pack these racks up with compute, which ultimately requires a lot of power and therefore requires a lot of cooling from the data center provider as well. So we call it a hyperdense rack design.
Ken Kaplan: You’re talking a lot about hardware, but software’s playing a key role here, just capabilities you’re being able to take on because of the advancements in software.
Harmail Chatha: Yeah, so software obviously is a huge part of it. One, starting at the lower tier infrastructure consolidation is a first step in the right direction, but ultimately it comes down to the software. Our data centers are software defined from a networking perspective. It’s all white box switches and we control the entire network through software itself. Our infrastructure is all controlled through clusters that are provisioned through AOS, AHV and Prism Central. And what that’s leading us to is infrastructure has a three to five year lifecycle, but we’re actually pushing that lifecycle longer now through our software. Because the software is getting more efficient, it’s better able to utilize the underlying hardware, therefore we’re able to use that hardware on a five to seven, eight year cycle in itself. So software really is becoming the core. Infrastructure is agnostic at the lower tier and software is dictating the lifecycle.
Ken Kaplan: How did you connect with your data center most recently to check on it and see how it’s doing?
Harmail Chatha: Yeah, so our data centers are lights out data centers for the most part. Our bigger data centers, we do have some folks in them, but because they’re so software defined, we don’t have to go to the data center every day. The ones that are lights out through hardware and making sure we have enough redundancy. Then the software being able to manage the VMs. If we do have a hardware failure, there’s really no need for us to go to the data center. And because we got a blueprint for scaling out our data center when we are at a capacity that’s really simple for us to expand. Example would be during the pandemic, we expanded one of our data centers by two megawatts during the pandemic. And that’s no easy feat, right? That’s a lot of physical build out. But because I’ve got such a great team, we got such amazing architecture that was ahead of its time, we’re able to leverage that in addition to the partnerships that we built as well. So there really isn’t a need for me to go to the data center anymore. I think ever since the pandemic started, I’ve probably been once and that was more to check in on the team, make sure they’re doing good in our larger data center. But the remote ones I haven’t been to in several years.
Ken Kaplan: Now, how about virtually? Are you checking it two or three times a day? Are you looking at through your laptop on your phone? What is that part like?
Harmail Chatha: So virtually, we’ve got a lot of alerts set up for the data center as well. So if something does go wrong, a power PDU goes out, cooling is inefficient, we’ve got systems in place where we get alerts that’s at the infrastructure tier from a data center perspective. But for our infrastructure of Nutanix and the cluster that we manage, they’re all software defined as well. We get alerts through Prism Central. We’re able to act on those alerts remotely. Even if there’s a failure of a hard drive or a power supply, we’re able to call some people in and just get that fixed. But the data center interaction is really mostly at the software level now and not at the physical level.
In this video interview, Mat Brown, senior technical marketing engineer at Nutanix, discusses the increasing importance of data center sustainability strategies and the challenges of managing carbon emissions from IT operations.
Find more enterprise cloud news, features stories and profiles at The Forecast.
Transcription:
Mat Brown: Increasingly, our customers are asking us about sustainability issues and about ESG. They want to know about the carbon emissions related to their IT solutions, whether they’re running them in their own data center at a co-location or in public cloud. These are becoming top of mind for more and more customers all the time.
It’s especially grown up over the last couple of years. What’s really kicked that on has been the energy crisis that’s built up in Europe especially. But then more and more regulation is coming out of the EU and in other places around the world, and that’s driving these sustainability challenges for businesses everywhere.
[Related: Three Trends Defining IT Sustainability in 2024]
Eventually it’s going to be have to embedded into every part of the business they do. I’d expect people will be doing sustainability training, like they do security training, and I expect that people will be reporting on their organization’s and missions like they currently report on their financial practice.
Yeah, so we’ve kind of mapped out four steps on the road to progress, as it were for organizations. Of course, the fundamental basis for everything is a better understanding of impact, but also an understanding of what your business goals are. Who are your allies? Who can you talk to and what resources are at your disposal? From there, you can understand what you need to measure, start implementing the processes to make those measurements, and then on that basis you can then plan and transform and build a business case for future activity as well.
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