How Containers are Becoming the New Basic Currency for Pay as You Go Hybrid IT

A discussion on how IT operators are now looking to increased automation, orchestration, and compatibility benefits to further exploit containers as a mainstay across their next-generation hybrid IT estate.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Hewlett Packard Enterprise.

Dana Gardner: Hello, and welcome to the next edition of the BriefingsDirect Voice of the Innovator podcast series. I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator for this ongoing discussion on the latest insights into container disruption trends and optimal use strategies.

Gardner

Container-based deployment models have rapidly gained popularity across a full spectrum of hybrid IT architectures -- from edge, to cloud, to data center. IT operators are now looking to increased automation, orchestration, and compatibility benefits to further exploit containers as a mainstay across their next-generation hybrid IT estate.

Stay with us as we examine innovative container use cases and the escalating benefits that come from broad container use with Robert Christiansen, Evangelist in the Office of the Chief Technology Officer at Hewlett Packard Enterprise (HPE). Welcome back, Robert.

Robert Christiansen: Thank you for having me, Dana.

Gardner: Containers are being used in more ways and in more places. What was not that long ago a fringe favorite for certain developer use cases is becoming broadly disruptive. How disruptive has the container model become?

Christiansen: Well, it’s the new change in the paradigm. We are looking to accelerate software releases. This is the Agile motion. At the end of the day, software is consuming the world, and if you don’t release software quicker -- with more features more often -- you are being left behind.

Christiansen

The mechanism to do that is to break them out into smaller consumable segments that we can manage. Typically that motion has been adopted at the public cloud level on containers, and that is spreading into the broader ecosystem of the enterprises and private data centers. That is the fundamental piece -- and containers have that purpose.

Gardner: Robert, users are interested in that development and deployment advantage, but are there also operational advantages, particularly in terms of being able to move workloads more freely across multiple clouds and hybrid clouds?

Christiansen: Yes, the idea is twofold. First off was to gain agility and motion, and then people started to ask themselves, “Well, I want to have choice, too.” So as we start abstracting away the dependencies of what runs a container, such as a very focused one that might be on a particular cloud provider, I can actually start saying, “Hey, can I write my container platform services and APIs compatible across multiple platforms? How do I go between platforms; how do I go between on-prem or in the public cloud?

Gardner: And because containers can be tailored to specific requirements needed to run a particular service, can they also extend down to the edge and in resource-constrained environments?

Adjustable containers add flexibility 

Christiansen: Yes, and more importantly, they can adjust to sizing issues, too. So think about pushing a container that’s very lightweight into a host that needs to have high availability of compute but may be limited on storage.

There are lots of different use cases. As you collapse the virtualization of an app -- that’s what a container really does, it virtualizes app components, it virtualizes app parts and dependencies. You only deploy the smallest bit of code needed to execute that one thing. That works in niche uses like a hospital, telecommunications on a cell tower, on an automobile, on the manufacturing floor, or if you want to do multiple pieces inside a cloud platform that services a large telco. However you structure it, that’s the type of flexibility containers provide.

Gardner: And we know this is becoming a very popular model, because the likes of VMware, the leader in virtualization, is putting a lot of emphasis on containers. They don’t want to lose their market share, they want to be in the next game, too. And then Microsoft with Azure Stack is now also talking about containers -- more than I would have expected. So that’s a proof-point, when you have VMware and Microsoft agreeing on something.

Christiansen: Yes, that was really interesting actually. I just saw this little blurb that came up in the news about Azure Stack switching over to a container platform, and I went, “Wow!” Didn’t they just put in three- or five-years’ worth of R and D? They are basically saying, “We might be switching this over to another platform.” It’s the right thing to do.

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And no one saw Kubernetes coming, or maybe OpenShift did. But the reality now is containers suddenly came out of nowhere. Adoption has been there for a while, but it’s never been adopted like it has been now.

Gardner: And Kubernetes is an important part because it helps to prevent complexity and sprawl from getting out of hand. It allows you to have a view over these different disparate deployment environments. Tell us why Kubernetes is in an accelerant to containers adoption.

Christiansen: Kubernetes fundamentally is an orchestration platform that allows you to take containers and put them in the right place, manage them, shut them down when they are not working or having behavior problems. We need a place to orchestrate, and that’s what Kubernetes is meant to be.

It basically displaced a number of other private, what we call opinionated, orchestrators. There was a number of them out there that were being worked on. And then Google released Kubernetes, which was fundamentally their platform that they had been running their world on for 10 years. They are doing for this ecosystem what the Android system did for cell phones. They were releasing and open sourcing the operating model, which is an interesting move.

Gardner: It’s very rapidly become the orchestration mechanism to rule them all. Has Kubernetes become a de facto industry standard?

Christiansen: It really has. We have not seen a technology platform gain acceptance in the ecosystem as fast as this. I personally in all my years or decades have not seen something come up this fast.

Gardner: I agree, and the fact that everyone is all-in is very powerful. How far will this orchestration model will go? Beyond containers, perhaps into other aspects of deployment infrastructure management?

Christiansen: Let’s examine the next step. It could be a code snippet. Or if you are familiar with functions, or with Amazon Web Services (AWS) Lambda [serverless functions], you are talking about that. That would be the next step of how orchestration – it allows anyone to just run code only. I don’t care about a container. I don’t care about the networking. I don’t care about any of that stuff -- just execute my code.

Gardner: So functions-as-a-service (FaaS) and serverless get people used to that idea. Maybe you don’t want to buy into one particular serverless approach versus another, but we are starting to see that idea of much more flexibility in how services can be configured and deployed -- not based on a platform, an OS, or even a cloud.

Containers’ tipping point 

Christiansen: Yes, you nailed it. If you think about the stepping stones to get across this space, it’s a dynamic fluid space. Containers are becoming, I bet, the next level of abstraction and virtualization that’s necessary for the evolution of application development to go faster. That’s a given, I think, right now.

Malcolm Gladwell talked about tipping points. Well, I think we have hit the tipping point on containers. This is going to happen. It may take a while before the ecosystem changes over. If you put the strategy together, if you are a decision-maker, you are making decisions about what to do. Now your container strategy matters. It matters now, not a year from now, not two years from now. It matters now.

Gardner: The flexibility that containers and Kubernetes give us refocuses the emphasis of how to do IT. It means that you are going to be thinking about management and you are going to be thinking about economics and automation. As such, you are thinking at a higher abstraction than just developing and deploying applications and then attaching and integrating data points to them.

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How does this higher abstraction of managing a hybrid estate benefit organizations when they are released from the earlier dependencies?

Christiansen: That’s a great question. I believe we are moving into a state where you cannot run platforms with manual systems, or ticketing-based systems. That type of thing. You cannot do that, right? We have so many systems and so much interoperability between the systems, that there has to be some sort of anatomic or artificial intelligence (AI)-based platforms that are going to make the workflow move for you.

There will still be someone to make a decision. Let’s say a ticket goes through, and it says, “Hey, there is the problem.” Someone approves it, and then a workflow will naturally happen behind that. These are the evolutions, and containers allow you to continue to remove the pieces that cause you problems.

Right now we have big, hairy IT operations problems. We have a hard time nailing down where they are. The more you can start breaking these apart and start looking at your hotspots of areas that have problems, you can be more specifically focused on solving those. Then you can start using some intelligence behind it, some actual workload intelligence, to make that happen.

Gardner: The good news is we have lots of new flexibility, with microservices, very discrete approaches to combining them into services, workflows, and processes. The bad news is we have all that flexibility across all of those variables.

Auspiciously we are also seeing a lot of interest and emphasis in what’s called AIOps, AI-driven IT operations. How do we now rationalize what containers do, but keep that from getting out of hand? Can we start using programmatic and algorithmic approaches? What you are seeing when we combine AIOps and containers?

Simplify your stack 

Christiansen: That’s like what happens when I mix oranges with apples. It’s kind of an interesting dilemma. But I can see why people want to say, “Hey, how does my container strategy help me manage my asset base? How do I get to a better outcome?”

One reason is because these approaches enable you to collapse the stack. When you take complexity out of your stack -- meaning, what are the layers in your stack that are necessary to operate in a given outcome -- you then have the ability to remove complexity.

We are talking about dropping the containers all the way to bare metal. And if you drop to bare metal, you have taken not only cost out of the equation, you have taken some complexity out of the equation. You have taken operational dependencies out of the equation, and you start reducing those. So that’s number one.

Number two is you have to have some sort of service mesh across this thing. So with containers comes a whole bunch of little hotspots all over the place and a service manager must know where those little hotspots are. If you don’t have an operating model that’s intelligent enough to know where those are (that’s called a service mesh, where they are connected to all these things) you are not going to have autonomous behaviors over the top of that that will help you.

So yes, you can connect the dots now between your containers to get autonomous, but you have got to have that layer in between that’s telling where the problems are -- and then you have intelligence above that that says how do I handle it.

Gardner: We have been talking, Robert, at an abstract level. Let’s go a bit more to the concrete. Are there use cases examples that HPE is working through with customers that illustrate the points we have been making around containers and Kubernetes?

Practice, not permanence 

Christiansen: I just met with the team, and they are working with a client right now, a very large Fortune 500 company, where they are applying the exact functions that I just talked to you about.

First thing that needed to happen is a development environment where they are actually developing code in a solid continuous integration, continuous development, and DevOps practice. We use the word “practice,” it’s like medicine and law. It’s a practice, nothing is permanent.

So we put that in place for them. The second thing is they’re trying to release code at speed. This is the first goal. Once you start releasing code at speed, with containers as the mechanism by which you are doing it, then you start saying, “Okay, now my platform on which I’m dropping on is going through development, quality assurance, integration, and then finally into production.

By the time you get to production, you need to know how you’re managing your platform. So it’s a client evolution. We are in that process right now -- from end-to-end -- to take one of their applications that is net new and another application that’s a refactor and run them both through this channel.

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Now, most clients we engage with are in that early stage. They’re doing proof of concepts. There are a couple of companies out there that have very large Kubernetes installations, that are in production, but they are born-in-the-cloud companies. And those companies have an advantage. They can build that whole thing I just talked about from scratch. But 90 percent of the people out there today, what I call the crown jewels of applications, have to deal with legacy IT. They have to deal with what’s going on today, their data sources have gravity, they still have to deal with that existing infrastructure.

Those are the people I really care about. I want to give them a solution that goes to that agile place. That’s what we’re doing with our clients today, getting them off the ground, getting them into a container environment that works.

Gardner: How can we take legacy applications and deployments and then use containers as a way of giving them new life -- but not lifting and shifting?

Improve past, future investments 

Christiansen: Organizations have to make some key decisions on investment. This is all about where the organization is in its investment lifecycle. Which ones are they going to make bets on, and which ones are they going to build new?

We are involved with clients going through that process. What we say to them is, “Hey, there is a set of applications you are just not going to touch. They are done. The best we can hope for is put the whole darn thing in a container, leave it alone, and then we can manage it better.” That’s about cost, about economics, about performance, that’s it. There are no release cycles, nothing like that.

The best we can hope for is put the whole darn thing in a container and we can manage it better. That's about cost, economics, and performance.

The next set are legacy applications where I can do something to help. Maybe I can take a big, beefy application and break it into four parts, make a service group out of it. That’s called a refactor. That will give them a little bit of agility because they can only release code pieces for each segment.

And then there are the applications that we are going to rewrite. These are dependent on what we call app entanglement. They may have multiple dependencies on other applications to give them data feeds, to give them connections that are probably services. They have API calls, or direct calls right into them that allow them to do this and that. There is all sorts of middleware, and it’s just a gnarly mess.

If you try to move those applications to public cloud and try to refactor them there, you introduce what I call data gravity issues or latency issues. You have to replicate data. Now you have all sorts of cost problems and governance problems. It just doesn’t work.

You have to keep those applications in the datacenters. You have to give them a platform to do it there. And if you can’t give it to them there, you have a real problem. What we try to do is break those applications into part in ways where the teams can work in cloud-native methodologies -- like they are doing in public cloud -- but they are doing it on-premises. That’s the best way to get it done.

Gardner: And so the decision about on-premises or in a cloud, or to what degree a hybrid relationship exists, isn’t so much dependent upon cost or ease of development. We are now rationalizing this on the best way to leverage services, use them together, and in doing so, we attain backward compatibility – and future-proof it, too.

Christiansen: Yes, you are really nailing it, Dana. The key is thinking about where the app appropriately needs to live. And you have laws of physics to deal with, you have legacy issues to deal with, and you have cultural issues to deal with. And then you have all sorts of data, what we call data nationalization. That means dealing with GDPR and where is all of this stuff going to live? And then you have edge issues. And this goes on and on, and on, and on.

So getting that right -- or at least having the flexibility to get it right -- is a super important aspect. It’s not the same for every company.

Gardner: We have been addressing containers mostly through an applications discussion. Is there a parallel discussion about data? Can we begin thinking about data as a service, and not necessarily in a large traditional silo database, but perhaps more granular, more as a call, as an API? What is the data lifecycle and DataOps implications of containers?

Everything as a service 

Christiansen: Well, here is what I call the Achilles heel of the container world. It doesn’t handle persistent data well at all. One of the things that HPE has been focused on is providing stateful, legacy, highly dependent persistent data stores that live in containers. Okay, that is a unique intellectual property that we offer. I think is really groundbreaking for the industry.

Kubernetes is a stateless container platform, which is appropriate for cloud-native microservices and those fast and agile motions. But the legacy IT world in stateful, with highly persistent data stores. They don’t work well in that stateless environment.

Through the work we’ve been doing over the last several years, specifically with an HPE-acquired company called BlueData, we’ve been able to solve that legacy problem. We put that platform into the AI, machine learning (ML), and big data areas first to really flesh that all out. We are joining those two systems together and offering a platform that is going to be really useful out in marketplace.

Gardner: Another aspect of this is the economics. So one of the big pushes from HPE these days is everything as a service, of being able to consume and pay for things as you want regardless of the deployment model -- whether it’s on premises, hybrid, in public clouds, or multi-clouds. How does the container model we have been describing align well with the idea of as a service from an economic perspective?

Christiansen: As-a-service is really how I want to get my services when I need them. And I only want to pay for what I need at the time I need it. I don’t want to overpay for it when I don’t use it. I don’t want to be stuck without something when I do need it.

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Solving that problem inside various places in the ecosystem is a different equation, it comes up differently. Some clients want to buy stuff, they want to capitalize it and just put it on the books. So we have to deal with that.

You have other people who say, “Hey, I’m willing to take on this hardware burden as a financer, and you can rent it from me.” You can consume all the pieces you need and then you’ve got the cloud providers as a service. But more importantly, let’s go back to how the containers allow you to have much finer granularity about what it is you’re buying. And if you want to deploy an app, maybe you are paying for that app to be deployed as opposed to the container. But the containers are the encapsulation of it and where you want to have it.

So you still have to get to what I call the basic currency. The basic currency is a container. Where does that container run? It has to run either on premises, in the public cloud, or on the edge. If people are going to agree on that basic currency model, then we can agree on an economic model.

Gardner: Even if people are risk averse, I don’t think they’re in trouble by making some big bets on containers as their new currency and to attain capabilities and skills around both containers and Kubernetes. Recognizing that this is not a big leap of faith, what do you advise people to do right now to get ready?

Christiansen: Get your arms around the Kubernetes installations you already have, because you know they’re happening. This is just like when the public cloud was arriving and there was shadow IT going on. You know it’s happening; you know people are writing code, and they’re pushing it into a Kubernetes cluster. They’re not talking to the central IT people about how to manage or run it -- or even if it’s going to be something they can handle. So you’ve got to get a hold of them first.

Teamwork works 

Go find your hand raisers. That’s what I always say. Who are the volunteers? Who has their hands in the air? Openly say, “Hey, come in. I’m forming a containers, Kubernetes, and new development model team.” Give it a name. Call it the Michael Jordan team of containers. I don’t care. But go get them. Go find out who they are, right?

And then form and coalesce that team around that knowledge base. Learn how they think, and what is the best that’s going on inside of your own culture. This is about culture, culture, culture, right? And do it in public so people can see it. This is why people got such black eyes when they were doing their first stuff around public cloud because they snuck off and did it, and then they were really reluctant not to say anything. Bring it out in the open. Let’s start talking about it.

Next thing is looking for instantiations of applications that you either are going to build net new or you are going to refactor. And then decide on your container strategy around that Kubernetes platform, and then work it as a program. Be open about transparency about what you’re doing. Make sure you’re funded.

If your data lives on-premises and an application is going to need data, you're going to need to have an on-premises solution for containers that can handle legacy and cloud at the same time. If that data goes to the cloud, you can always move the container there, too.

And most importantly, above all things, know where your data lives. If your data lives on-premises and that application you’re talking about is going to need data, you’re going to need to have an on-premises solution for containers, specifically those that handle legacy and public cloud at the same time. If that data decides it needs to go to public cloud, you can always move it there.

Gardner: I’m afraid we’ll have to leave it there. We’ve been exploring containers as a new currency and how that’s a disruptive force as well as an opportunity for improving the way IT operations works. And we’ve learned how IT operators are innovating around more automation and orchestration in order to take full advantage of what containers and Kubernetes offer. We’ve also heard about how intelligence and AIOps can be brought to bear when things start to get scale intensive.

Please join me in thanking our guest, Robert Christensen, Evangelist in the Office of the Chief Technology Officer at HPE. Thank you, Robert.

Christensen: Thank you so much, Dana.

Gardner: And a big thank you as well to our audience for joining us for this sponsored BriefingsDirect Voice of the Innovator containers trends and use strategies interview. I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host for this series of Hewlett Packard Enterprise-supported discussions.

Thanks again for listening. Please pass this along to your community, and do come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Hewlett Packard Enterprise.

A discussion on how IT operators are now looking to increased automation, orchestration, and compatibility benefits to further exploit containers as a mainstay across their next-generation hybrid IT estate. Copyright Interarbor Solutions, LLC, 2005-2019. All rights reserved.

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HPE Strategist Mark Linesch on the Surging Role of Containers in Advancing the Hybrid IT Estate

A discussion on containers innovation and next developments in automated and extensible IT infrastructure container solutions for hybrid IT and multicloud.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Hewlett Packard Enterprise.

Dana Gardner: Hello, and welcome to the next edition of the BriefingsDirect Voice of the Innovator podcast series. I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator for this ongoing discussion on the latest insights into hybrid cloud and composability strategies.

Gardner

Openness, flexibility, and speed to distributed deployments have been top drivers of the steady growth of container-based solutions. Now, IT operators are looking to increase automation, built-in intelligence, and robust management as they seek container-enabled hybrid cloud and multicloud approaches for data and workloads.

Stay with us now as we examine the rapidly evolving containers innovation landscape and learn about the next chapter of automated and extensible IT infrastructure solutions with Mark Linesch, Vice President of Technology Strategy in the CTO Office and Hewlett Packard Labs at Hewlett Packard Enterprise (HPE).

 

Welcome to BriefingsDirect, Mark.

Mark Linesch: Thanks, Dana. It’s great to be here.

Gardner: Let’s look at the state of the industry around containers. What are the top drivers for containers adoption now that the technology has matured?

Containers catch on

Linesch: The history of computing, as far back as I can remember, has been about abstraction; abstraction of the infrastructure and then a separation of concern between the infrastructure and the applications.

Linesch

It used to be it was all bare metal, and then about a decade ago, we went on the journey to virtualization. And virtualization is great, it’s an abstraction that allows for certain amount of agility. But it’s fairly expensive because you are virtualizing the entire infrastructure, if you will, and dragging along a unique operating system (OS) each time you do that.

So the industry for the last few years has been saying, “Well, what’s next, what’s after virtualization?” And clearly things like containerization are starting to catch hold.

Why now? Well, because we are living in a hybrid cloud world, and we are moving pretty aggressively toward a more distributed edge-to-cloud world. We are going to be computing, analyzing, and driving intelligence in all of our edges -- and all of our clouds.

Things such as performance- and developer-aware capabilities, DevOps, the ability to run an application in a private cloud and then move it to a public cloud, and being able to drive applications to edge environments on a harsh factory floor -- these are all aspects of this new distributed computing environment that we are entering into. It’s a hybrid estate, if you will.

Containers have advantages for a lot of different constituents in this hybrid estate world. First and foremost are the developers. If you think about development and developers in general, they have moved from the older, monolithic and waterfall-oriented approaches to much more agile and continuous integration and continuous delivery models.

And containers give developers a predictable environment wherein they can couple not only the application but the application dependencies, the libraries, and all that they need to run an application throughout the DevOps lifecycle. That means from development through test, production, and delivery.

Containers carry and encapsulate all of the app’s requirements to develop, run, test, and scale. With bare metal or virtualization, as the app moved through the DevOps cycle, I had to worry about the OS dependencies and the type of platforms I was running that pipeline on.

Developers’ package deal 

A key thing for developers is they can package the application and all the dependencies together into a distinct manifest. It can be version-controlled and easily replicated. And so the developer can debug and diagnose across different environments and save an enormous amount of time. So developers are the first beneficiaries, if you will, of this maturing containerized environment.

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But next are the IT operations folks because they now have a good separation of concern. They don’t have to worry about reconfiguring and patching all these kinds of things when they get a hand-off from developers into a production environment. That capability is fundamentally encapsulated for them, and so they have an easier time operating.

And increasingly in this more hybrid distributed edge-to-cloud world, I can run those containers virtually anywhere. I can run them at the edge, in a public cloud, in a private cloud, and I can move those applications quickly without all of these prior dependencies that virtualization or bare metal required. It contains an entire runtime environment and application, plus all the dependencies, all the libraries, and the like.

The third area that’s interesting for containers is around isolation. Containers virtualize the CPU, the memory, storage network resources – and they do that at the OS level. So they use resources much more efficiently for that reason.

Unlike virtualization, which includes your entire OS as well as the application, containers run on a single OS. Each container shares the OS kernel with other containers so it's lightweight, uses less resources, and spins up instantly.

Unlike virtualization, which includes your entire OS as well as the application, containers run on a single OS. Each container shares the OS kernel with other containers, so it’s lightweight, uses much fewer resources, and spins up almost instantly -- in seconds versus virtual machines (VMs) that spin up in minutes.

When you think about this fast-paced, DevOps world we live in -- this increasingly distributed hybrid estate from the many edges and many clouds we compute and analyze data in -- that’s why containers are showing quite a bit of popularity. It’s because of the business benefits, the technical benefits, the development benefits, and the operations benefits.

Gardner: It’s been fascinating for me to see the portability and fit-for-purpose containerization benefits, and being able to pass those along a DevOps continuum. But one of the things that we saw with virtualization was that too much of a good thing spun out of control. There was sprawl, lack of insight and management, and eventually waste.

How do we head that off with containers? How do containers become manageable across that entire hybrid estate?

Setting the standard 

Linesch: One way is standardizing the container formats, and that’s been coming along fairly nicely. There is an initiative called The Open Container Initiative, part of the Linux Foundation, that develops to the industry standard so that these containers, formats, and runtime software associated with them are standardized across the different platforms. That helps a lot.

Number two is using a standard deployment option. And the one that seems to be gripping the industry is Kubernetes. Kubernetes is an open source capability that provides mechanisms for deploying, maintaining, and scaling containerized applications. Now, the combination of the standard formats from a runtime perspective with the ability to manage that with capabilities like Mesosphere or Kubernetes has provided the tooling and the capabilities to move this forward.

Gardner: And the timing couldn’t be better, because as people are now focused on as-a-service for so much -- whether it’s an application, infrastructure, and increasingly, entire data centers -- we can focus on the business benefits and not the underlying technology. No one really cares whether it’s running in a virtualized environment, on bare metal, or in a container -- as long as you are getting the business benefits.

Linesch: You mentioned that nobody really cares what they are running on, and I would postulate that they shouldn’t care. In other words, developers should develop, operators should operate. The first business benefit is the enormous agility that developers get and that IT operators get in utilizing standard containerized environments.

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Not only do they get an operations benefit, faster development, lower cost to operate, and those types of things, but they take less resources. So containers, because of their shared and abstracted environment, really take a lot fewer resources out of a server and storage complex, out of a cluster, so you can run your applications faster, with less resources, and at lower total cost.

This is very important when you think about IT composability in general because the combination of containerized environments with things like composable infrastructure provides the flexibility and agility to meet the needs of customers in a very time sensitive and very agile way.

Gardner: How are IT operators making a tag team of composability and containerization? Are they forming a whole greater than the sum of the parts? How do you see these two spurring innovation?

Linesch: I have managed some of our R and D centers. These are usually 50,000-square-foot data centers where all of our developers and hardware and software writers are off doing great work.

And we did some interesting things a few years ago. We were fully virtualized, a kind of private cloud environment, so we could deliver infrastructure-as-a-service (IaaS) resources to these developers. But as hybrid cloud hit and became more of a mature and known pattern, our developers were saying, “Look, I need to spin this stuff up more quickly. I need to be able to run through my development-test pipeline more effectively.”

And containers-as-a-service was just a super hit for these guys. They are under pressure every day to develop, build, and run these applications with the right security, portability, performance, and stability. The containerized systems -- and being able to quickly spin up a container, to do work, package that all, and then move it through their pipelines -- became very, very important.

From an infrastructure operations perspective, it provides a perfect marriage between the developers and the operators. The operators can use composition and things like our HPE Synergy platform and our HPE OneView tooling to quickly build container image templates. These then allow those developers to populate that containers-as-a-service infrastructure with the work that they do -- and do that very quickly.

Gardner: Another hot topic these days is understanding how a continuum will evolve between the edge deployments and a core cloud, or hybrid cloud environment. How do containers help in that regard? How is there a core-to-cloud and/or core-to-cloud-to-edge benefit when containers are used?

Gaining an edge 

Linesch: I mentioned that we are moving to a much more distributed computing environment, where we are going to be injecting intelligence and processing through all of our places, people, and things. And so when you think about that type of an environment, you are saying, “Well, I’m going to develop an application. That application may require more microservices or more modular architecture. It may require that I have some machine learning (ML) or some deep learning analytics as part of that application. And it may then need to be provisioned to 40 -- or 400 -- different sites from a geographic perspective.”

When you think about edge-to-cloud, you might have a set of factories in different parts of the United States. For example, you may have 10 factories all seeking to develop inferencing and analyzed actions on some type of an industrial process. It might be video cameras attached to an assembly line looking for defects and ingesting data and analyzing that data right there, and then taking some type of a remediation action.

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And so as we think about this edge-to-cloud dance, one of the things that’s critical there is continuous integration and continuous delivery -- of being able to develop these applications and the artificial intelligence (AI) models associated with analyzing the data on an ongoing basis. The AI models, quite frankly, drift and they need to be updated periodically. And so continuous integration and continuous delivery types of methodologies are becoming very important.

Then, how do I package up all of those application bits, analytics bits, and ML bits? How do I provision that to those 10 factories? How do I do that in a very fast and fluid way?

That’s where containers really shine. They will give you bare-metal performance. They are packaged and portable – and that really lends itself to the fast-paced delivery and delivery cycles required for these kinds of intelligent edge and Internet of Things (IoT) operations.

Gardner: We have heard a lot about AIOps and injecting more intelligence into more aspects of IT infrastructure, particularly at the June HPE Discover conference. But we seem to be focusing on the gathering of the data and the analysis of the data, and not so much on the what do you do with that analysis – the execution based on the inferences.

It seems to me that containers provide a strong means when it comes to being able to exploit recommendations from an AI engine and then doing something -- whether to deploy, to migrate, to port.

Am I off on some rough tangent? Or is there something about containers -- and being able to deftly execute on what the intelligence provides -- that might also be of benefit?

Linesch: At the edge, you are talking about many applications where a large amount of data needs to be ingested. It needs to be analyzed, and then take a real-time action from a predictive maintenance, classification, or remediation perspective.

We are seeing the benefits of containers really shine in these more distributed edge-to-cloud environments. At the edge, many apps need a large amount of data ingested. The whole cycle time of ingesting data, analyzing it, and taking some action back is highly performant with containers.

And so containers spin up very quickly. They use very few resources. The whole cycle-time of ingesting data, analyzing that data through a container framework, taking some action back to the thing that you are analyzing is made a whole lot easier and a whole lot performant with less resources when you use containers.

Now, virtualization still has a very solid set of constituents, both at the hybrid cloud and at the intelligent edge. But we are seeing the benefits of containers really shine in these more distributed edge-to-cloud environments.

Gardner: Mark, we have chunked this out among the developer to operations and deployment, or DevOps implications. And we have talked about the edge and cloud.

But what about at the larger abstraction of impacting the IT organization? Is there a benefit for containerization where IT is resource-constrained when it comes to labor and skills? Is there a people, skills, and talent side of this that we haven’t yet tapped into?

Customer microservices support 

Linesch: There definitely is. One of the things that we do at HPE is try to help customers move into these new models like containers, DevOps, and continuous integration and delivery. We offer a set of services that help customers, whether they are medium-sized customers or large customers, to think differently about development of applications. As a result, they are able to become more agile and microservices-oriented.

Microservice-oriented development really lends itself to this idea of containers, and the ability of containers to interact with each other as a full-set application. What you see happening is that you have to have a reason not to use containers now.

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That’s pretty exciting, quite frankly. It gives us an opportunity to help customers to engage from an education perspective, and from a consulting, integration, and support perspective as they journey through microservices and how to re-architect their applications.

Our customers are moving to a more continuous integration-continuous development approach. And we can show them how to manage and operate these types of environments with high automation and low operational cost.

Gardner: A lot of the innovation we see along the lines of digital transformation at a business level requires taking services and microservices from different deployment models -- oftentimes multi-cloud, hybrid cloud, software-as-a-service (SaaS) services, on-premises, bare metal, databases, and so forth.

Are you seeing innovation percolating in that way? If you have any examples, I would love to hear them.

Linesch: I am seeing that. You see that every day when you look at the Internet. It’s a collaboration of different services based on APIs. You collect a set of services for a variety of different things from around these Internet endpoints, and that’s really as-a-service. That’s what it’s all about -- the ability to orchestrate all of your applications and collections of service endpoints.

Furthermore, beyond containers, there are new as-a-function-based, or serverless, types of computing. These innovators basically say, “Hey, I want to consume a service from someplace, from an HTTP endpoint, and I want to do that very quickly.” They very effectively are using service-oriented methodologies and the model of containers.

We are seeing a lot of innovation in these function-as-a-service (FaaS) capabilities that some of the public clouds are now providing. And we are seeing a lot of innovation in the overall operations at scale of these hybrid cloud environments, given the portability of containers.

At HPE, we believe the cloud isn’t a place -- it’s an experience. The utilization of containers provides a great experience for both the development community and the IT operations community. It truly helps better support the business objectives of the company.

Investing in intelligent innovation 

Gardner: Mark, for you personally, as you are looking for technology strategy, how do you approach innovation? Is this something that comes organically, that bubbles up? Or is there a solid process or workflow that gets you to innovation? How do you foster innovation in your own particular way that works?

Linesch: At HPE, we have three big levers that we pull on when we think about innovation.

The first is we can do a lot of organic development -- and that’s very important. It involves understanding where we think the industry is going, and trying to get ahead of that. We can then prove that out with proof of concepts and incubation kinds of opportunities with lead customers.

We also, of course, have a lever around inorganic innovation. For example, you saw recently an acquisition by HPE of Cray to turbocharge the next generation of high-performance computing (HPC) and to drive the next generation of exascale computing.

The third area is our partnerships and investments. We have deep collaboration with companies like Docker, for example. They have been a great partner for a number of years, and we have, quite frankly, helped to mature some of that container management technology.

We are an active member of the standards organizations around the containers. Being able to mature the technology with partners like Docker, to get at the business value of some of these big advancements is important. So those are just three ways we innovate.

Longer term, with other HPE core innovations, such as composability and memory-driven computing, we believe that containers are going to be even more important. You will be able to hold the containers in memory-driven computing systems, in either Dynamic random-access memory (DRAM) or storage-class memory (SCM).

You will be able to spin them up instantly or spin them down instantly. The composition capabilities that we have will increasingly automate a very significant part of bringing up such systems, of bringing up applications, and really scaling and moving those applications to where they need to be.

One of the principles that we are focused on is moving the compute to the data -- as opposed to moving the data to the compute. And the reason for that is when you move the compute to the data, it's a lot easier, simpler, and faster with less resources.

One of the principles that we are focused on is moving the compute to the data -- as opposed to moving the data to the compute. And the reason for that is when you move the compute to the data, it’s a lot easier, simpler, and faster -- with less resources.

This next generation of distributed computing, memory-driven computing, and composability is really ripe for what we call containers in microseconds. And we will be able to do that all with the composability tooling we already have.

Gardner: When you get to that point, you’re not just talking about serverless. You’re talking about cloudless. It doesn’t matter where the FaaS is being generated as long as it’s at the right performance level that you require, when you require it. It’s very exciting.

Before we break, I wonder what guidance you have for organizations to become better prepared to exploit containers, particularly in the context of composability and leveraging a hybrid continuum of deployments? What should companies be doing now in order to be getting better prepared to take advantage of containers?

Be prepared, get busy

Linesch: If you are developing applications, then think deeply about agile development principles, and developing applications with a microservice-bent is very, very important.

If you are in IT operations, it’s all about being able to offer bare metal, virtualization, and containers-as-a-service options -- depending on the workload and the requirements of the business.

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Hybrid Cloud More Effectively

I recommend that companies not stand on the sidelines but to get busy, get to a proof of concept with containers-as-a-service. We have a lot of expertise here at HPE. We have a lot of great partners, such as Docker, and so we are happy to help and engage.

We have quite a bit of on-boarding and helpful services along the journey. And so jump in and crawl, walk, and run through it. There are always some sharp corners on advanced technology, but containers are maturing very quickly. We are here to help our customers on that journey.

Gardner: I’m afraid we’ll have to leave it there. We have been exploring how openness, flexibility, and speed to distributed deployments have been top drivers for the steady growth of container-based solutions. And we have learned how IT operators now are looking to increase automation, built-in intelligence, and robust management as they seek to take advantage of container-enabled hybrid cloud models.

So please join me in thanking Mark Linesch, Vice President of Technology Strategy in the CTO Office and Hewlett Packard Labs at HPE. Thank you so much, Mark,

Linesch: Thank you, Dana. I really enjoyed the conversation.

Gardner: And a big thank you as well to our audience for joining this BriefingsDirect Voice of the Innovator interview. I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host for this ongoing series of Hewlett Packard Enterprise-sponsored discussions.

Thanks again for listening. Please pass this along to your IT community, and do come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Hewlett Packard Enterprise.

A discussion on containers innovation and next developments in automated and extensible IT infrastructure container solutions for hybrid IT and multicloud. Copyright Interarbor Solutions, LLC, 2005-2019. All rights reserved.

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