Tuesday, November 21, 2017

Inside story on HPC's role in the Bridges Research Project at Pittsburgh Supercomputing Center

The next BriefingsDirect Voice of the Customer high-performance computing (HPC) success story interview examines how Pittsburgh Supercomputing Center (PSC) has developed a research computing capability, Bridges, and how that's providing new levels of analytics, insights, and efficiencies.

We'll now learn how advances in IT infrastructure and memory-driven architectures are combining to meet the new requirements for artificial intelligence (AI), big data analytics, and deep machine learning.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy.

Here to describe the inside story on building AI Bridges are Dr. Nick Nystrom, Interim Director of Research, and Paola Buitrago, Director of AI and Big Data, both at Pittsburgh Supercomputing Center. The discussion is moderated by Dana Gardner, principal analyst, at Interarbor Solutions.

Here are some excerpts:

Gardner: Let's begin with what makes Bridges unique. What is it about Bridges that is possible now that wasn't possible a year or two ago?

Nystrom: Bridges allows people who have never used HPC before to use it for the first time. These are people in business, social sciences, different kinds of biology and other physical sciences, and people who are applying machine learning to traditional fields. They're using the same languages and frameworks that they've been using on their laptops and now that is scaling up to a supercomputer. They are bringing big data and AI together in ways that they just haven't done before.

Gardner: It almost sounds like the democratization of HPC. Is that one way to think about it?

Nystrom: It very much is. We have users who are applying tools like R and Python and scaling them up to very large memory -- up to 12 terabytes of random access memory (RAM) -- and that enables them to gain answers to problems they've never been able to answer before.

Gardner: There is a user experience aspect, but I have to imagine there are also underlying infrastructure improvements that also contribute to user democratization.
We stay in touch with the user community and we look at this from their perspective. What are the applications that they need to run? What we came up with is a very heterogeneous system.

Nystrom: Yes, democratization comes from two things. First, we stay closely in touch with the user community and we look at this opportunity from their perspective first. What are the applications that they need to run? What do they need to do? And from there, we began to work with hardware vendors to understand what we had to build, and, what we came up with is a very heterogeneous system.

We have three tiers of nodes having memories ranging from 128 gigabytes to 3 terabytes, to 12 terabytes of RAM. That's all coupled on the same very-high-performance fabric. We were the first installation in the world with the Intel Omni-Path interconnect, and we designed that in a custom topology that we developed at PSC expressly to make big data available as a service to all of the compute nodes with equally high bandwidth, low latency, and to let these new things become possible.

Gardner: What other big data analytics benefits have you gained from this platform?

Buitrago: A platform like Bridges enables that which was not available before. There's a use case that was recently described by Tuomas Sandholm, [Professor and Director of the Electronic Marketplaces Lab at Carnegie Mellon University. It involves strategic machine learning using Bridges HPC to play and win at Heads-Up, No-limit Texas Hold'em poker as a capabilities benchmark.]

This is a perfect example of something that could not have been done without a supercomputer. A supercomputer enables massive and complex models that can actually give an accurate answer.

Right now, we are collecting a lot of data. There's a convergence of having great capabilities right in the compute and storage -- and also having the big data to answer really important questions. Having a system like Bridges allows us to, for example, analyze all that there is on the Internet, and put the right pieces together to answer big societal or healthcare-related questions.

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Gardner: The Bridges platform has been operating for some months now. Tell us some other examples or use cases that demonstrate its potential.

Dissecting disease through data

Nystrom: Paola mentioned use cases for healthcare. One example is a National Institutes of Health (NIH) Center of Excellence in the Big Data to Knowledge program called the Center for Causal Discovery.

They are using Bridges to combine very large data in genomics, such as lung-imaging data and brain magnetic resonance imaging (MRI) data, to come up with real cause-and-effect relationships among those very large data sets. That was never possible before because the algorithms were not scaled. Such scaling is now possible thanks very large memory architectures and because the data is available.

At CMU and the University of Pittsburgh, we have those resources now and people are making discoveries that will improve health. There are many others. One of these is on the Common Crawl data set, which is a very large web-scale data set that Paola has been working with.

Buitrago: Common Crawl is a data set that collects all the information on the Internet. The data is currently available on the Amazon Web Services (AWS) cloud in S3. They host these data sets for free. But, if you want to actually analyze the data, to search or create any index, you have to use their computing capabilities, which is a good option. However, given the scale and the size of the data, this is something that requires a huge investment.

So we are working on actually offering the same data set, putting it together with the computing capabilities of Bridges. This would allow the academic community at large to do such things as build natural language processing models, or better analyze the data -- and they can do it fast, and they can do it free of charge. So that's an important example of what we are doing and how we want to support big data as a whole.

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Computing Solutions

Gardner: So far we’ve spoken about technical requirements in HPC, but economics plays a role here. Many times we've seen in the evolution of technology that as things become commercially available off-the-shelf technologies, they can be deployed in new ways that just weren’t economically feasible before. Is there an economics story here to Bridges?

Low-cost access to research

Nystrom: Yes, with Bridges we have designed the system to be extremely cost-effective. That's part of why we designed the interconnect topology the way we did. It was the most cost-effective way to build that for the size of data analytics we had to do on Bridges. That is a win that has been emulated in other places.

So, what we offer is available to research communities at no charge -- and that's for anyone doing open research. It's also available to the industrial sector at essentially a very attractive rate because it’s a cost-recovery rate. So, we do work with the private sector. We are looking to do even more of that in future.

We're always looking at the best available technology for performance, for price, and then architecting that into a solution that will serve research.
Also, the future systems we are looking at will leverage lots of developing technologies. We're always looking at the best available technology for performance, for price, and then architecting that into a solution that will serve research.

Gardner: We’ve heard a lot recently from Hewlett Packard Enterprise (HPE) recently about their advances in large-scale memory processing and memory-driven architectures. How does that fit into your plans?

Nystrom: Large, memory-intensive architectures are a cornerstone of Bridges. We're doing a tremendous amount of large-scale genome sequence assembly on Bridges. That's individual genomes, and it’s also metagenomes with important applications such as looking at the gut microbiome of diabetic patients versus normal patients -- and understanding how the different bacteria are affected by and may affect the progression of diabetes. That has tremendous medical implications. We’ve been following memory technology for a very long time, and we’ve also been following various kinds of accelerators for AI and deep learning.

Gardner: Can you tell us about the underlying platforms that support Bridges that are currently commercially available? What might be coming next in terms of HPE Gen10 servers, for example, or with other HPE advances in the efficiency and cost reduction in storage? What are you using now and what do you expect to be using in the future?

Ever-expanding memory, storage

Nystrom: First of all, I think the acquisition of SGI by HPE was very strategic. Prior to Bridges, we had a system called Blacklight, which was the world’s largest shared-memory resource. It’s what taught us, and we learned how productive that can be for new communities in terms of human productivity. We can’t scale smart humans, and so that’s essential.

In terms of storage, there are tremendous opportunities now for integrating storage-class memory, increasing degrees of flash solid-state drives (SSDs), and other stages. We’ve always architected our own storage systems, but now we are working with HPE to think about what we might do for our next round of this.

Gardner: For those out there listening and reading this information, if they hadn’t thought that HPC and big data analytics had a role in their businesses, why should they think otherwise?

Nystrom: From my perspective, AI is permeating all aspects of computing. The way we see AI as important in an HPC machine is that it is being applied to applications that were traditionally HPC only -- things like weather and protein folding. Those were apps that people used to run on just big iron.

These will be enterprise workloads where AI has a key impact. They will use AI as an empowering tool to make what they already do, better.
Now, they are integrating AI to help them find rare events, to do longer-term simulations in less time. And they’ll be doing this across other industries as well. These will be enterprise workloads where AI has a key impact. It won’t necessarily turn companies into AI companies, but they will use AI as an empowering tool to make what they already do, better.

Gardner: An example, Nick?

Nystrom: A good example of the way AI is permeating other fields is what people are doing at the Institute for Precision Medicine, [a joint effort between the University of Pittsburgh and the University of Pittsburgh Medical Center], and the Carnegie Mellon University Machine Learning and Computational Biology Departments.

They are working together on a project called Big Data for Better Health. Their objective is to apply state of the art machine learning techniques, including deep learning, to integrated genomic patient medical records, imaging data, and other things, and to really move toward realizing true personalized medicine.

Gardner: We’ve also heard a lot recently about hybrid IT. Traditionally HPC required an on-premises approach. Now, to what degree does HPC-as-a-service make sense in order to take advantage of various cloud models?

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Nystrom: That’s a very good question. One of the things that Bridges makes available through the democratizing of HPC is big data-as-a-service and HPC-as-a-service. And it does that in many cases by what we call gateways. These are web portals for specific domains.

At the Center for Causal Discovery, which I mentioned, they have the Causal Web. It’s a portal, it can run in any browser, and it lets people who are not experts with supercomputers access Bridges without even knowing they are doing it. They run applications with a supercomputer as the back-end.

Another example is Galaxy Project and Community Hub, which are primarily for bioinformatic workflows, but also other things. The main Galaxy instance is hosted elsewhere, but people can run very large memory genome assemblies on Bridges transparently -- again without even knowing. They don’t have to log in, they don’t have to understand Linux; they just run it through a web browser, and they can use HPC-as-a-service. It becomes very cloud-like at that point.

Super-cloud supercomputing

Cloud and traditional HPC are complimentary among different use cases, for what's called for in different environments and across different solutions.
Buitrago: Depending on the use case, an environment like the cloud can make sense. HPC can be used for an initial stage, if you want to explore different AI models, for example. You can fine-tune your AI and benefit from having the data close. You can reduce the time to start by having a supercomputer available for only a week or two. You can find the right parameters, you get the model, and then when you are actually generating inferences you can go to the cloud and scale there. It supports high peaks in user demand. So, cloud and traditional HPC are complimentary among different use cases, for what’s called for in different environments and across different solutions.

Gardner: Before we sign off, a quick look to the future. Bridges has been here for over a year, let's look to a year out. What do you expect to come next?

Nystrom: Bridges has been a great success. It's very heavily subscribed, fully subscribed, in fact. It seems to work; people like it. So we are looking to build on that. We're looking to extend that to a much more powerful engine where we’ve taken all of the lessons we've learned improving Bridges. We’d like to extend that by orders of magnitude, to deliver a lot more capability -- and that would be across both the research community and industry.

Gardner: And using cloud models, what should look for in the future when it comes to a richer portfolio of big data-as-a-service offerings?

Buitrago: We are currently working on a project to make data more available to the general public and to researchers. We are trying to democratize data and let people do searches and inquiries and processing that they wouldn’t be able to do without us.

We are integrating big data sets that go from web crawls to genomic data. We want to offer them paired with the tools to properly process them. And we want to provide this to people who haven’t done this in the past, so they can explore their questions and try to answer them. That’s something we are really interested in and we look forward to moving into a production stage.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy. Sponsor: Hewlett Packard Enterprise.

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Monday, November 20, 2017

How UBC gained TCO advantage via flash for its EduCloud cloud storage service

The next BriefingsDirect cloud efficiency case study explores how a storage-as-a-service offering in a university setting gains performance and lower total cost benefits by a move to all-flash storage.

We’ll now learn how the University of British Columbia (UBC) has modernized its EduCloud storage service and attained both efficiency as well as better service levels for its diverse user base.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or  download a copy.

Here to help us explore new breeds of SaaS solutions is Brent Dunington, System Architect at UBC in Vancouver. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: How is satisfying the storage demands at a large and diverse university setting a challenge? Is there something about your users and the diverse nature of their needs that provides you with a complex requirements list? 

Dunington: A university setting isn't much different than any other business. The demands are the same. UBC has about 65,000 students and about 15,000 staff. The students these days are younger kids, they all have iPhones and iPads, and they just want to push buttons and get instant results and instant gratification. And that boils down to the services that we offer.

We have to be able to offer those services, because as most people know, there are choices -- and they can go somewhere else and choose those other products.

Our team is a rather small team. There are 15 members in our team, so we have to be agile, we have to be able to automate things, and we need tools that can work and fulfill those needs. So it's just like any other business, even though it’s a university setting.

Flash Performance

Gardner: Can you give us a sense of the scale that describes your storage requirements?

Dunington: We do SaaS, we also do infrastructure-as-a-service (IaaS). EduCloud is a self-service IaaS product that we deliver to UBC, but we also deliver it to 25 other higher institutions in the Province of British Columbia.

We have been doing IaaS for five years, and we have been very, very successful. So more people are looking to us for guidance.

Because we are not just delivering to UBC, we have to be up running and always able to deliver, because each school has different requirements. At different times of the year -- because there is registration, there are exam times -- these things have to be up. You can’t not be functioning during an exam and have 600 students not able to take the tests that they have been studying for. So it impacts their life and we want to make sure that we are there and can provide the services for what they need.

Gardner: In order to maintain your service levels within those peak times, do you in your IaaS and storage services employ hybrid-cloud capabilities so that you can burst? Or are you doing this all through your own data center and your own private cloud?

On-Campus Cloud

Dunington: We do it all on-campus. British Columbia has a law that says all the data has to stay in Canada. It’s a data-sovereignty law, the data can't leave the borders.

That's why EduCloud has been so successful, in my opinion, because of that option. They can just go and throw things out in the private cloud.

The public cloud providers are providing more services in Canada: Amazon Web Services (AWS) and Microsoft Azure cloud are putting data centers in Canada, which is good and it gives people an option. Our team’s goal is to provide the services, whether it's a hybrid model or all on-campus. We just want to be able to fulfill those needs.

Gardner: It sounds like the best of all worlds. You are able to give that elasticity benefit, a lot of instant service requirements met for your consumers. But you are starting to use cloud pay-as-you-go types of models and get the benefit of the public cloud model -- but with the security, control and manageability of the private clouds.

What decisions have you made about your storage underpinnings, the infrastructure that supports your SaaS cloud?

Dunington: We have a large storage footprint. For our site, it’s about 12 petabytes of storage. We realized that we weren’t meeting the needs with spinning disks. One of the problems was that we had runaway virtual workloads that would cause problems, and they would impact other services. We needed some mechanism to fix that.

We wanted to make sure that we had the ability to attain quality of service levels and control those runaway virtual machines in our footprint.
We went through the whole request for proposal (RFP) process, and all the IT infrastructure vendors responded, but we did have some guidelines that we wanted to go through. One of the things we did is present our problems and make sure that they understood what the problems were and what they were trying to solve.

And there were some minimum requirements. We do have a backup vendor of choice that they needed to merge with. And quality of service is a big thing. We wanted to make sure that we had the ability to attain quality of service levels and control those runaway virtual machines in our footprint.

Gardner: You gained more than just flash benefits when you got to flash storage, right?

Streamlined, safe, flash storage

Dunington: Yes, for sure. With an entire data center full of spinning disks, it gets to the point where the disks start to manage you; you are no longer managing the disks. And the teams out there changing drives, removing volumes around it, it becomes unwieldy. I mean, the power, the footprint, and all that starts to grow.

Also, Vancouver is in a seismic zone, we are right up against the Pacific plate and it's a very active seismic area. Heaven forbid anything happens, but one of the requirements we had was to move the data center into the interior of the province. So that was what we did.

When we brought this new data center online, one of the decisions the team made was to move to an all-flash storage environment. We wanted to be sure that it made financial sense because it's publicly funded, and also improved the user experience, across the province.

Gardner: As you were going about your decision-making process, you had choices, what made you choose what you did? What were the deciding factors?

Dunington: There were a lot of deciding factors. There’s the technology, of being able to meet the performance and to manage the performance. One of the things was to lock down runaway virtual machines and to put performance tiers on others.

But it’s not just the technology; it's also the business part, too. The financial part had to make sense. When you are buying any storage platform, you are also buying the support team and the sales team that come with it.

Our team believes that technology is a certain piece of the pie, and the rest of it is relationship. If that relationship part doesn't work, it doesn’t matter how well the technology part works -- the whole thing is going to break down.

Because software is software, hardware is hardware -- it breaks, it has problems, there are limitations. And when you have to call someone, you have to depend on him or her. Even though you bought the best technology and got the best price -- if it doesn't work, it doesn’t work, and you need someone to call.

So those service and support issues were all wrapped up into the decision.

Flash Performance

We chose the Hewlett Packard Enterprise (HPE) 3PAR all-flash storage platform. We have been very happy with it. We knew the HPE team well. They came and worked with us on the server blade infrastructure, so we knew the team. The team knew how to support all of it. 

We also use the HPE OneView product for provisioning, and it integrated into that all. It also supported the performance optimization tool (IT Operations Management for HPE OneView) to let us set those values, because one of the things in EduCloud is customers choose their own storage tier, and we mark the price on it. So basically all we would do is present that new tier as new data storage within VMware and then they would just move their workloads across non-disruptively. So it has worked really well.

The 3PAR storage piece also integrates with VMware vRealize Operations Manager. We offer that to all our clients as a portal so they can see how everything is working and they can do their own diagnostics. Because that’s the one goal we have with EduCloud, it has to be self-service. We can let the customers do it, that's what they want.

Gardner: Not that long ago people had the idea that flash was always more expensive and that they would use it for just certain use-cases rather than pervasively. You have been talking in terms of a total cost of ownership reduction. So how does that work? How does the economics of this over a period of time, taking everything into consideration, benefit you all?

Economic sense at scale

Dunington: Our IT team and our management team are really good with that part. They were able to break it all down, and they found that this model would work at scale. I don’t know the numbers per se, but it made economic sense.

Spinning disks will still have a place in the data center. I don't know a year from now if an all-flash data center will make sense, because there are some records that people will throw in and never touch. But right now with the numbers on how we worked it out, it makes sense, because we are using the standard bronze, the gold, the silver tiers, and with the tiers it makes sense.

The 3PAR solution also has dedupe functionality and the compression that they just released. We are hoping to see how well that trends. Compression has only been around for a short period of time, so I can’t really say, but the dedupe has done really well for us.

Gardner: The technology overcomes some of the other baseline economic costs and issues, for sure.

We have talked about the technology and performance requirements. Have you been able to qualify how, from a user experience, this has been a benefit?

Dunington: The best benchmark is the adoption rate. People are using it, and there are no help desk tickets, so no one is complaining. People are using it, and we can see that everything is ramping up, and we are not getting tickets. No one is complaining about the price, the availability. Our operational team isn't complaining about it being harder to manage or that the backups aren’t working. That makes me happy.

The big picture

Gardner: Brent, maybe a word of advice to other organizations that are thinking about a similar move to private cloud SaaS. Now that you have done this, what might you advise them to do as they prepare for or evaluate a similar activity?

Not everybody needs that speed, not everybody needs that performance, but it is the future and things will move there.
Dunington: Look at the full picture, look at the total cost of ownership. There’s the buying of the hardware, and there's also supporting the hardware, too. Make sure that you understand your requirements and what your customers are looking for first before you go out and buy it. Not everybody needs that speed, not everybody needs that performance, but it is the future and things will move there. We will see in a couple of years how it went.

Look at the big picture, step back. It’s just not the new shiny toy, and you might have to take a stepped approach into buying, but for us it worked. I mean, it’s a solid platform, our team sleeps well at night, and I think our customers are really happy with it.

Gardner: This might be a little bit of a pun in the education field, but do your homework and you will benefit.

Flash Performance

Dunington: Yes, for sure.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or  download a copy. Sponsor: Hewlett Packard Enterprise.

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Friday, November 17, 2017

How modern storage provides hints on optimizing and best managing hybrid IT and multi-cloud resources

The next BriefingsDirect Voice of the Analyst interview examines the growing need for proper rationalizing of which apps, workloads, services and data should go where across a hybrid IT continuum.

Managing hybrid IT necessitates not only a choice between public cloud and private cloud, but a more granular approach to picking and choosing which assets go where based on performance, costs, compliance, and business agility.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy.

Here to report on how to begin to better assess what IT variables should be managed and thoughtfully applied to any cloud model is Mark Peters, Practice Director and Senior Analyst at Enterprise Strategy Group (ESG). The discussion is moderated by Dana Gardner, principal analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Now that cloud adoption is gaining steam, it may be time to step back and assess what works and what doesn’t. In past IT adoption patterns, we’ve seen a rapid embrace that sometimes ends with at least a temporary hangover. Sometimes, it’s complexity or runaway or unmanaged costs, or even usage patterns that can’t be controlled. Mark, is it too soon to begin assessing best practices in identifying ways to hedge against any ill effects from runaway adoption of cloud? 

Peters: The short answer, Dana, is no. It’s not that the IT world is that different. It’s just that we have more and different tools. And that is really what hybrid comes down to -- available tools.

It’s not that those tools themselves demand a new way of doing things. They offer the opportunity to continue to think about what you want. But if I have one repeated statement as we go through this, it will be that it’s not about focusing on the tools, it’s about focusing on what you’re trying to get done. You just happen to have more and different tools now.
Gardner: We hear sometimes that at as high as board of director levels, they are telling people to go cloud-first, or just dump IT all together. That strikes me as an overreaction. If we’re looking at tools and to what they do best, is cloud so good that we can actually just go cloud-first or cloud-only?

Cloudy cloud adoption

Peters: Assuming you’re speaking about management by objectives (MBO), doing cloud or cloud-only because that’s what someone with a C-level title saw on a Microsoft cloud ad on TV and decided that is right, well -- that clouds everything.

You do see increasingly different people outside of IT becoming involved in the decision. When I say outside of IT, I mean outside of the operational side of IT.

You get other functions involved in making demands. And because the cloud can be so easy to consume, you see people just running off and deploying some software-as-a-service (SaaS) or infrastructure-as-a-service (IaaS) model because it looked easy to do, and they didn’t want to wait for the internal IT to make the change.
All of the research we do shows that the world is hybrid for as far ahead as we can see.

Running away from internal IT and on-premises IT is not going to be a good idea for most organizations -- at least for a considerable chunk of their workloads. All of the research we do shows that the world is hybrid for as far ahead as we can see. 

Gardner: I certainly agree with that. If it’s all then about a mix of things, how do I determine the correct mix? And if it’s a correct mix between just a public cloud and private cloud, how do I then properly adjust to considerations about applications as opposed to data, as opposed to bringing in microservices and Application Programming Interfaces (APIs) when they’re the best fit?

How do we begin to rationalize all of this better? Because I think we’ve gotten to the point where we need to gain some maturity in terms of the consumption of hybrid IT.
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Peters: I often talk about what I call the assumption gap. And the assumption gap is just that moment where we move from one side where it’s okay to have lots of questions about something, in this case, in IT. And then on the other side of this gap or chasm, to use a well-worn phrase, is where it’s not okay to ask anything because you’ll see you don’t know what you’re talking about. And that assumption gap seems to happen imperceptibly and very fast at some moment.

So, what is hybrid IT? I think we fall into the trap of allowing ourselves to believe that having some on-premises workloads and applications and some off-premises workloads and applications is hybrid IT. I do not think it is. It’s using a couple of tools for different things.

It’s like having a Prius and a big diesel and/or gas F-150 pickup truck in your garage and saying, “I have two hybrid vehicles.” No, you have one of each, or some of each. Just because someone has put an application or a backup off into the cloud, “Oh, yeah. Well, I’m hybrid.” No, you’re not really.

The cloud approach

The cloud is an approach. It’s not a thing per se. It’s another way. As I said earlier, it’s another tool that you have in the IT arsenal. So how do you start figuring what goes where?

I don’t think there are simple answers, because it would be just as sensible a question to say, “Well, what should go on flash or what should go on disk, or what should go on tape, or what should go on paper?” My point being, such decisions are situational to individual companies, to the stage of that company’s life, and to the budgets they have. And they’re not only situational -- they’re also dynamic.

I want to give a couple of examples because I think they will stick with people. Number one is you take something like email, a pretty popular application; everyone runs email. In some organizations, that is the crucial application. They cannot run without it. Probably, what you and I do would fall into that category. But there are other businesses where it’s far less important than the factory running or the delivery vans getting out on time. So, they could have different applications that are way more important than email.

When instant messaging (IM) first came out, Yahoo IM text came out, to be precise. They used to do the maintenance between 9 am and 5 pm because it was just a tool to chat to your friends with at night. And now you have businesses that rely on that. So, clearly, the ability to instant message and text between us is now crucial. The stock exchange in Chicago runs on it. IM is a very important tool.

The answer is not that you or I have the ability to tell any given company, “Well, x application should go onsite and Y application should go offsite or into a cloud,” because it will vary between businesses and vary across time.

If something is or becomes mission-critical or high-risk, it is more likely that you’ll want the feeling of security, I’m picking my words very carefully, of having it … onsite.

You have to figure out what you're trying to get done before you figure out what you're going to do with it.
But the extent to which full-production apps are being moved to the cloud is growing every day. That’s what our research shows us. The quick answer is you have to figure out what you’re trying to get done before you figure out what you’re going to do it with. 

Gardner: Before we go into learning more about how organizations can better know themselves and therefore understand the right mix, let’s learn more about you, Mark. 
Tell us about yourself, your organization at ESG. How long have you been an IT industry analyst? 

Peters: I grew up in my working life in the UK and then in Europe, working on the vendor side of IT. I grew up in storage, and I haven’t really escaped it. These days I run ESG’s infrastructure practice. The integration and the interoperability between the various elements of infrastructure have become more important than the individual components. I stayed on the vendor side for many years working in the UK, then in Europe, and now in Colorado. I joined ESG 10 years ago.

Lessons learned from storage

Gardner: It’s interesting that you mentioned storage, and the example of whether it should be flash or spinning media, or tape. It seems to me that maybe we can learn from what we’ve seen happen in a hybrid environment within storage and extrapolate to how that pertains to a larger IT hybrid undertaking.

Is there something about the way we’ve had to adjust to different types of storage -- and do that intelligently with the goals of performance, cost, and the business objectives in mind? I’ll give you a chance to perhaps go along with my analogy or shoot it down. Can we learn from what’s happened in storage and apply that to a larger hybrid IT model?
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Peters: The quick answer to your question is, absolutely, we can. Again, the cloud is a different approach. It is a very beguiling and useful business model, but it’s not a panacea. I really don’t believe it ever will become a panacea.

Now, that doesn’t mean to say it won’t grow. It is growing. It’s huge. It’s significant. You look at the recent announcements from the big cloud providers. They are at tens of billions of dollars in run rates.

But to your point, it should be viewed as part of a hierarchy, or a tiering, of IT. I don’t want to suggest that cloud sits at the bottom of some hierarchy or tiering. That’s not my intent. But it is another choice of another tool.

Let’s be very, very clear about this. There isn’t “a” cloud out there. People talk about the cloud as if it exists as one thing. It does not. Part of the reason hybrid IT is so challenging is you’re not just choosing between on-prem and the cloud, you’re choosing between on-prem and many clouds -- and you might want to have a multi-cloud approach as well. We see that increasingly.

What we should be looking for are not bright, shiny objects -- but bright, shiny outcomes.
Those various clouds have various attributes; some are better than others in different things. It is exactly parallel to what you were talking about in terms of which server you use, what storage you use, what speed you use for your networking. It’s exactly parallel to the decisions you should make about which cloud and to what extent you deploy to which cloud. In other words, all the things you said at the beginning: cost, risk, requirements, and performance.

People get so distracted by bright, shiny objects. Like they are the answer to everything. What we should be looking for are not bright, shiny objects -- but bright, shiny outcomes. That’s all we should be looking for.

Focus on the outcome that you want, and then you figure out how to get it. You should not be sitting down IT managers and saying, “How do I get to 50 percent of my data in the cloud?” I don’t think that’s a sensible approach to business. 

Gardner: Lessons learned in how to best utilize a hybrid storage environment, rationalizing that, bringing in more intelligence, software-defined, making the network through hyper-convergence more of a consideration than an afterthought -- all these illustrate where we’re going on a larger scale, or at a higher abstraction.

Going back to the idea that each organization is particular -- their specific business goals, their specific legacy and history of IT use, their specific way of using applications and pursuing business processes and fulfilling their obligations. How do you know in your organization enough to then begin rationalizing the choices? How do you make business choices and IT choices in conjunction? Have we lost sufficient visibility, given that there are so many different tools for doing IT?

Get down to specifics

Peters: The answer is yes. If you can’t see it, you don’t know about it. So to some degree, we are assuming that we don’t know everything that’s going on. But I think anecdotally what you propose is absolutely true.

I’ve beaten home the point about starting with the outcomes, not the tools that you use to achieve those outcomes. But how do you know what you’ve even got -- because it’s become so easy to consume in different ways? A lot of people talk about shadow IT. You have this sprawl of a different way of doing things. And so, this leads to two requirements.

Number one is gaining visibility. It’s a challenge with shadow IT because you have to know what’s in the shadows. You can’t, by definition, see into that, so that’s a tough thing to do. Even once you find out what’s going on, the second step is how do you gain control? Control -- not for control’s sake -- only by knowing all the things you were trying to do and how you’re trying to do them across an organization. And only then can you hope to optimize them.

You can't manage what you can't measure. You also can't improve things that can't be managed or measured.
Again, it’s an old, old adage. You can’t manage what you can’t measure. You also can’t improve things that can’t be managed or measured. And so, number one, you have to find out what’s in the shadows, what it is you’re trying to do. And this is assuming that you know what you are aiming toward.

This is the next battleground for sophisticated IT use and for vendors. It’s not a battleground for the users. It’s a choice for users -- but a battleground for vendors. They must find a way to help their customers manage everything, to control everything, and then to optimize everything. Because just doing the first and finding out what you have -- and finding out that you’re in a mess -- doesn’t help you.
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Visibility is not the same as solving. The point is not just finding out what you have – but of actually being able to do something about it. The level of complexity, the range of applications that most people are running these days, the extremely high levels of expectations both in the speed and flexibility and performance, and so on, mean that you cannot, even with visibility, fix things by hand.

You and I grew up in the era where a lot of things were done on whiteboards and Excel spreadsheets. That doesn’t cut it anymore. We have to find a way to manage what is automated. Manual management just will not cut it -- even if you know everything that you’re doing wrong. 

Gardner: Yes, I agree 100 percent that the automation -- in order to deal with the scale of complexity, the requirements for speed, the fact that you’re going to be dealing with workloads and IT assets that are off of your premises -- means you’re going to be doing this programmatically. Therefore, you’re in a better position to use automation.

I’d like to go back again to storage. When I first took a briefing with Nimble Storage, which is now a part of Hewlett Packard Enterprise (HPE), I was really impressed with the degree to which they used intelligence to solve the economic and performance problems of hybrid storage.

Given the fact that we can apply more intelligence nowadays -- that the cost of gathering and harnessing data, the speed at which it can be analyzed, the degree to which that analysis can be shared -- it’s all very fortuitous that just as we need greater visibility and that we have bigger problems to solve across hybrid IT, we also have some very powerful analysis tools.

Mark, is what worked for hybrid storage intelligence able to work for a hybrid IT intelligence? To what degree should we expect more and more, dare I say, artificial intelligence (AI) and machine learning to be brought to bear on this hybrid IT management problem?

Intelligent automation a must

Peters: I think it is a very straightforward and good parallel. Storage has become increasingly sophisticated. I’ve been in and around the storage business now for more than three decades. The joke has always been, I remember when a megabyte was a lot, let alone a gigabyte, a terabyte, and an exabyte.

And I’d go for a whole day class, when I was on the sales side of the business, just to learn something like dual parsing or about cache. It was so exciting 30 years ago. And yet, these days, it’s a bit like cars. I mean, you and I used to use a choke, or we’d have to really go and check everything on the car before we went on 100-mile journey. Now, we press the button and it better work in any temperature and at any speed. Now, we just demand so much from cars.

To stretch that analogy, I’m mixing cars and storage -- and we’ll make it all come together with hybrid IT in that it’s better to do things in an automated fashion. There’s always one person in every crowd I talk to who still believes that a stick shift is more economic and faster than an automatic transmission. It might be true for one in 1,000 people, and they probably drive cars for a living. But for most people, 99 percent of the people, 99.9 percent of the time, an automatic transmission will both get you there faster and be more efficient in doing so. The same became true of storage.

We used to talk about how much storage someone could capacity-plan or manage. That’s just become old hat now because you don’t talk about it in those terms. Storage has moved to be -- how do we serve applications? How do we serve up the right place in the right time, get the data to the right person at the right time at the right price, and so on?

We don’t just choose what goes where or who gets what, we set the parameters -- and we then allow the machine to operate in an automated fashion. These days, increasingly, if you talk to 10 storage companies, 10 of them will talk to you about machine learning and AI because they know they’ve got to be in that in order to make that execution of change ever more efficient and ever faster. They’re just dealing with tremendous scale, and you could not do it even with simple automation that still involves humans.

It will be self-managing and self-optimizing. It will not be a “recommending tool,” it will be an “executing tool.”
We have used cars as a social analogy. We used storage as an IT analogy, and absolutely, that’s where hybrid IT is going. It will be self-managing and self-optimizing. Just to make it crystal clear, it will not be a “recommending tool,” it will be an “executing tool.” There is no time to wait for you and me to finish our coffee, think about it, and realize we have to do something, because then it’s too late. So, it’s not just about the knowledge and the visibility. It’s about the execution and the automated change. But, yes, I think your analogy is a very good one for how the IT world will change.
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Gardner: How you execute, optimize and exploit intelligence capabilities can be how you better compete, even if other things are equal. If everyone is using AWS, and everyone is using the same services for storage, servers, and development, then how do you differentiate?

How you optimize the way in which you gain the visibility, know your own business, and apply the lessons of optimization, will become a deciding factor in your success, no matter what business you’re in. The tools that you pick for such visibility, execution, optimization and intelligence will be the new real differentiators among major businesses.

So, Mark, where do we look to find those tools? Are they yet in development? Do we know the ones we should expect? How will organizations know where to look for the next differentiating tier of technology when it comes to optimizing hybrid IT?

What’s in the mix?

Peters: We’re talking years ahead for us to be in the nirvana that you’re discussing.

I just want to push back slightly on what you said. This would only apply if everyone were using exactly the same tools and services from AWS, to use your example. The expectation, assuming we have a hybrid world, is they will have kept some applications on-premises, or they might be using some specialist, regional or vertical industry cloud. So, I think that’s another way for differentiation. It’s how to get the balance. So, that’s one important thing.

And then, back to what you were talking about, where are those tools? How do you make the right move?

We have to get from here to there. It’s all very well talking about the future. It doesn’t sound great and perfect, but you have to get there. We do quite a lot of research in ESG. I will throw just a couple of numbers, which I think help to explain how you might do this.

We already find that the multi-cloud deployment or option is a significant element within a hybrid IT world. So, asking people about this in the last few months, we found that about 75 percent of the respondents already have more than one cloud provider, and about 40 percent have three or more.

You’re getting diversity -- whether by default or design. It really doesn’t matter at this point. We hope it’s by design. But nonetheless, you’re certainly getting people using different cloud providers to take advantage of the specific capabilities of each.

This is a real mix. You can’t just plunk down some new magic piece of software, and everything is okay, because it might not work with what you already have -- the legacy systems, and the applications you already have. One of the other questions we need to ask is how does improved management embrace legacy systems?

Some 75 percent of our respondents want hybrid management to be from the infrastructure up, which means that it’s got to be based on managing their existing infrastructure, and then extending that management up or out into the cloud. That’s opposed to starting with some cloud management approach and then extending it back down to their infrastructure.

People want to enhance what they currently have so that it can embrace the cloud. It’s enhancing your choice of tiers so you can embrace change.
People want to enhance what they currently have so that it can embrace the cloud. It's enhancing your choice of tiers so you can embrace change. Rather than just deploying something and hoping that all of your current infrastructure -- not just your physical infrastructure but your applications, too -- can use that, we see a lot of people going to a multi-cloud, hybrid deployment model. That entirely makes sense. You're not just going to pick one cloud model and hope that it  will come backward and make everything else work. You start with what you have and you gradually embrace these alternative tools. 

Gardner: We’re creating quite a list of requirements for what we’d like to see develop in terms of this management, optimization, and automation capability that’s maybe two or three years out. Vendors like Microsoft are just now coming out with the ability to manage between their own hybrid infrastructures, their own cloud offerings like Azure Stack and their public cloud Azure.
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Where will we look for that breed of fully inclusive, fully intelligent tools that will allow us to get to where we want to be in a couple of years? I’ve heard of one from HPE, it’s called Project New Hybrid IT Stack. I’m thinking that HPE can’t be the only company. We can’t be the only analysts that are seeing what to me is a market opportunity that you could drive a truck through. This should be a big problem to solve.

Who’s driving?

Peters: There are many organizations, frankly, for which this would not be a good commercial decision, because they don’t play in multiple IT areas or they are not systems providers. That’s why HPE is interested, capable, and focused on doing this. 

Many vendor organizations are either focused on the cloud side of the business -- and there are some very big names -- or on the on-premises side of the business. Embracing both is something that is not as difficult for them to do, but really not top of their want-to-do list before they’re absolutely forced to.

From that perspective, the ones that we see doing this fall into two categories. There are the trendy new startups, and there are some of those around. The problem is, it’s really tough imagining that particularly large enterprises are going to risk [standardizing on them]. They probably even will start to try and write it themselves, which is possible – unlikely, but possible.

Where I think we will get the list for the other side is some of the other big organizations --- Oracle and IBM spring to mind in terms of being able to embrace both on-premises and off-premises.  But, at the end of the day, the commonality among those that we’ve mentioned is that they are systems companies. At the end of the day, they win by delivering the best overall solution and package to their clients, not individual components within it.
If you’re going to look for a successful hybrid IT deployment took, you probably have to look at a hybrid IT vendor.

And by individual components, I include cloud, on-premises, and applications. If you’re going to look for a successful hybrid IT deployment tool, you probably have to look at a hybrid IT vendor. That last part I think is self-descriptive. 

Gardner: Clearly, not a big group. We’re not going to be seeking suppliers for hybrid IT management from request for proposals (RFPs) from 50 or 60 different companies to find some solutions. 

Peters: Well, you won’t need to. Looking not that many years ahead, there will not be that many choices when it comes to full IT provisioning. 

Gardner: Mark, any thoughts about what IT organizations should be thinking about in terms of how to become proactive rather than reactive to the hybrid IT environment and the complexity, and to me the obvious need for better management going forward?

Management ends, not means

Peters: Gaining visibility into not just hybrid IT but the on-premise and the off-premise and how you manage these things. Those are all parts of the solution, or the answer. The real thing, and it’s absolutely crucial, is that you don’t start with those bright shiny objects. You don’t start with, “How can I deploy more cloud? How can I do hybrid IT?” Those are not good questions to ask. Good questions to ask are, “What do I need to do as an organization? How do I make my business more successful? How does anything in IT become a part of answering those questions?”

In other words, drum roll, it’s the thinking about ends, not means.

Gardner:  If our listeners and readers want to follow you and gain more of your excellent insight, how should they do that? 

Peters: The best way is to go to our website, www.esg-global.com. You can find not just me and all my contact details and materials but those of all my colleagues and the many areas we cover and study in this wonderful world of IT.