How modern architects transform the messy mix of hybrid cloud into a force multiplier

The next BriefingsDirect cloud strategies insights interview focuses on how IT architecture and new breeds of service providers are helping enterprises manage complex cloud scenarios.

We’ll now learn how composable infrastructure and auto-scaling help improve client services, operations, and business goals attainment for a New York cloud services and architecture support provider.

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

Here to help us learn what’s needed to reach the potential of multiple — and often overlapping — cloud models is Arthur Reyenger, Cloud Practice Lead and Chief Cloud Architect at International Integrated Solutions (IIS) Ltd. in New York.

Here are some excerpts:

Gardner: How are IT architecture and new breeds of service providers coming together? What’s different now from just a few years ago for architecture when we have cloud, multi-cloud, and hybrid cloud services? 

Arthur Reyenger

Reyenger

Reyenger: Like the technology trends themselves, everything is accelerating. Before, you would have three-year or even five-year plans that were developed by the business. They were designed to reach certain business outcomes, they would design the technology to support that and it was then heads-down to build my rocket ship.

It’s changed now to where it’s a 12-month strategy that needs to be modular enough to be reevaluated at the end of those 12 months, and be re-architected — almost as if it were made of Lego blocks.

Gardner: More moving parts, less time.

Reyenger: Absolutely.

Gardner: How do you accomplish that? 

Reyenger: You leverage different cloud service providers, different managed services providers, and traditional value-added resellers, like International Integrated Solutions (IIS), in order to meet those business demands. We see a large push around automation, orchestration and auto-scaling. It’s becoming a way to achieve those business initiatives at that higher speed.

Gardner: There is a cloud continuum. You are choosing which workloads and what data should be on-premises, and what should be in a cloud, or multi-clouds. Trying to do this as a regular IT shop — buying it, specifying, integrating it — seems like it demands more than the traditional IT skills. How is the culture of IT adjusting? 

Reyenger: Every organization, including ours, has its own business transformation that they have to undergo. We think that we are extremely proactive. I see some companies that are developing in-house skill sets, and trying to add additional departments that would be more cloud-aware in order to meet those demands.

On the other side, you have folks that are leveraging partners like IIS, which has acumen within those spaces to supplement their bench, or they are building out a completely separate organization that will hopefully take them to the new frontier.

Gardner: Tell us about your company. What have you done to transform?

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Reyenger: IIS has spent 26 years building out an amazing book of business with amazing relationships with a lot of enterprise customers. But as times change, you need to be able to add additional practices like our cloud practice and our managed services practice. We have taken the knowledge we have around traditional IT services and then added in our internal developers and delivery consultants. They are very well-versed and aware of the new architecture. So we can marry the two together and help organizations reach that new end-state.

It’s very easy for startups to go 100 percent to the cloud and just run with it. It’s different when you have 2,000 existing applications and you want to move to the future as well. It’s nice to have someone who understands both of those worlds — and the appropriate way to integrate them. 

Gardner: I suppose there is no typical cloud engagement, but what is a common hurdle that organizations are facing as they go from that traditional IT mindset to the more cloud-centric thinking and hybrid deployment models?

The cloud answer

Reyenger: The concept of auto-scaling or bursting has become very, very prevalent. You see that within different lines of business. Ultimately, they are all asking for essentially the same thing — and the cloud is a pretty good answer.

At the same time, you really need to understand your business and the triggers. You need to be able to put the necessary intelligence together around those capabilities in order to make it really beneficial and align to the ebbs and flows of your business. So that’s been one of the very, very common requests across the board.

We’ve built out solutions that include intellectual property from IIS and our developers, as well as cloud management tools built around backup to the cloud to eliminate tape and modernize backup for customers. This builds out a dedicated object store that customers can own that also tiers to the different public cloud providers out there.

And we’ve done this in a repeatable fashion so that our customers get the cloud consumption look and feel, and we’ve leveraged innovative contractual arrangements to allow customers to consume against the scope of work rather than on lease. We’ve been able to marry that with the different standardized offerings out there to give someone the head start that they need in order to achieve their objectives. 

Gardner: You brought up the cloud consumption model. Organizations want the benefit of a public cloud environment and user experience for bursting, auto-scaling, and price efficiency. They might want to have workloads on-premises, to use a managed service, or take advantage of public clouds under certain circumstances.

How are you working with companies like Hewlett Packard Enterprise (HPE), for example, to provide composable auto-scaling capabilities with the look and feel of public cloud on their private cloud?

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Reyenger: Now it’s becoming a multi-cloud strategy. It’s one thing to say only on-premises and using one cloud. But using just one cloud has risk, and this is a problem.

We try to standardize everything through a single cloud management stack for our customers. We’re agnostic to a whole slew of toolsets around both orchestration and automation. We want to help them achieve that.

Intelligent platform performance

We looked at some of the very unique things that HPE has done, specifically around their Synergy platform, to allow for cloud management and cloud automation to deliver true composable infrastructure. That has huge value around energizing a company’s goals, strengthening their profitability, boosting productivity, and enhancing innovation. We’ve been able to extend that into the public cloud. So now we have customers that truly are getting the best of both worlds.

Composable infrastructure is having true infrastructure that you can deploy as code. It’s being able to standardize on a single RESTful API set.

Gardner: How do you define composable infrastructure? 

Reyenger: It’s having true infrastructure that you can deploy as code. You’ll hear a lot of folks say that and what it really means is being able to standardize on a single RESTful API set.

That allows your platform to have intelligence when you look at infrastructure as a service (IaaS), and then delivering things as either platform (PaaS) or software as a service (SaaS) — from either a DevOps approach, or from the lines of business directly to consumers. So it’s the ability to bridge those two worlds.

Traditionally, you may have underlying infrastructure that doesn’t have the intelligence or doesn’t have the visibility into the cloud automation. So I may be scaling, but I can’t scale into infinity. I really need an underlying infrastructure to be able to mold and adapt in order to meet those needs.

We’re finally reaching the point where we have that visibility and we have that capability, thanks to software-defined data center (SDDC) and a platform to ultimately be able to execute on. 

Gardner: When I think about composable infrastructure, I often wonder, “Who is the composer?” I know who composes the apps, that’s the developer — but who composes the infrastructure?  

Reyenger: This gets to a lot of the digital transformation that we talked about in seeking different resources, or cultivating your existing resources to gain more of a developer’s view.

But now you have IT operations and DevOps both able to come under a single management console. They are able to communicate effectively and then script on either side in order to compose based on the code requirements. Or they can put guardrails on different segments of their workloads in order to dictate importance or assign guidelines. The developers can ultimately make those requests or modify the environment. 

Gardner: When you get to composable infrastructure in a data center or private cloud, that’s fine. But that’s sort of like 2D Chess. When I think about multi-cloud or hybrid cloud — it’s more like 3D Chess. So how do I compose infrastructure, and who is the composer, when it comes to deciding where to support a workload in a certain way, and at what cost?

Consult before composing

Reyenger: We offer a series of consulting services around the delivery of managed services and the actual development to take an existing cloud management stack — whether that is Red Hat CloudForms, vRealize from VMware, or Terraform — it really doesn’t matter.

We are ultimately allowing that to be the single pane of glass, the single console. And then because it’s RESTful API integrations into those public cloud providers, we’re able to provide that transparency from that management interface, which mitigates risk and gives you control.

Then we deploy things like Puppet, Chef, and Ansible within those different virtual private clouds and within those public cloud fabrics. Then, using that cloud management stack, you can have uniformity and you can take that composition and that intelligence and bring it wherever you like — whether that’s based on geography or a particular cloud service provider preference.

There are many different ways to ultimately achieve that end-state. We just want to make sure that that standardization, to your point, doesn’t get lost the second you leave that firewall.

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Gardner: We are in the early days of composability of infrastructure in a multi-cloud world. But as the complexity and scale increases, it seems likely to me that we are going to need to bring things like machine learning and artificial intelligence (AI) because humans doing this manually will run out of runway.

Projecting into the future, do you see a role for an algorithmic, programmatic approach putting in certain variables, certain thresholds, and contextual learning to then make this composable infrastructure capability part of a machine process? 

Reyenger: The things that companies like HPE have done, and their new acquisition, Nimble, as well as at Red Hat, and several others in the industry, to leverage the intelligence they have from all of their different support calls and lifecycle management across applications allows them to provide feedback to the customer.

And in some cases, if you are tying it back from an automation engine that will actually give you the information as to how to solve your problem. A lot of the precursors to what you are talking about are already in the works and everyone is trying to be that data-cloud management company.

We will see more of that single pane of glass that they will leverage across multiple cloud providers.

It’s really early to ultimately pick favorites, but you are going to see more standardization. Rather than having 50 different RESTful APIs that everyone is standardizing on and that are constantly changing, so that I have to provide custom integrations. What we will see is more of that single pane of glass they will leverage across multiple cloud providers. That will leverage a lot of the same automation and orchestration toolsets that we talked about. 

Gardner: And HPE has their sights set on this with Project New Hybrid IT Stack? 

Reyenger: 100 percent. 

Gardner: Looking at composable infrastructure, auto-scaling, using things like HPE Synergy, if you’re an enterprise and you do this right, how do you take this up to the C-Suite and say, “Aha, we told you so. Now give us more so we can do more”? In other words, how does this improve business outcomes?

Fulfilling the promise

Reyenger: Every organization is different. I’ve spent a good chunk of my career being tactically deployed within very large organizations that are trying to achieve certain goals.

For me, I like to go to a customer’s 10-K SEC filing and look at the promises they’ve made to their investors. We want to ultimately be able to marry back what this IT investment will do for the short-term goals that they are all being judged against, as well as from both the key performance indicators (KPI) standpoint and from the health of the company.

It means meeting DevOps challenges and timelines, ruling out new green space workload issues, and taking data that sits within traditional business intelligence (BI) relational databases and giving access to some of that data to different departments. They should be able to run big data analytics against that data from those departments in real-time.

These are the types of testing methodologies that we like to set up so that we can help a customer actually rationalize what this means today in terms of dollars and cents and what it could mean in terms of that perceived value. 

Gardner: When you do this well, you get agility, and you get to choose your deployment models. It seems to me that there’s going to be a concept that arises of minimal viable cloud, or hybrid cloud.

Are we going to see IT costs at an operating level adjusted favorably? Is this something that ultimately will be so optimized — with higher utilization, leveraging the competitive market for cloud services — that meaningful decreases will occur in the total operating costs of IT in an organization?

An uphill road to lower IT costs

Reyenger: I definitely think that it’s quite possible. The way that most organizations are set up today, IT operations rolls back into finance. So if you sit underneath the CFO, like most organizations do, and a request gets made by marketing or sales or another line of business — it has to go up the chain, get translated, and then come back down.

A lot of times it’s difficult to push a rock up a hill. You don’t have all the visibility unless you can get back up to finance or back over to that line of business. If you are able to break down those silos, then I believe that your statement is 100 percent true.

But changing all of those internal controls for a lot of these organizations is very difficult, which is why some are deploying net-new teams to be ultimately the future of their internal IT service provider operations.

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Gardner: Arthur, I have been in this business long enough to know that every time we’ve gotten into the point where we think we are going to meaningfully decrease IT costs, some other new paradigm of IT comes up that requires a whole new round of investment. But it seems to me that this could be different this time, that we actually are getting to a standardized approach for supporting workloads and that traditional economics that impact any procurement service will become in effect here, too.

Mining to minimize risk

Reyenger: Absolutely. One of our big pushes has been around object storage. This still allows for traditional file- and block-level support. We are trying to help customers achieve that new economic view — of which cloud approach ultimately provides them that best price point, but still gives them low risk, visibility, and control over their data.

I will give you an example. There is a very large financial exchange that had a lot of intellectual property (IP) data that they traditionally mined internally, and then they provided it back to different, smaller financial institutions as a service, as financial reports. A few years back, they came to us and said, “I really want to leverage the agility of Amazon Web Services (AWS) in terms of being able to spin up a huge Hadoop form and mine this data very, very quickly — and leverage that without having to increase my overall cost. But I don’t feel comfortable providing that data into S3 within AWS, where now they have two extra copies of my data as part of the service level agreement. So what do I do?”

And we ultimately stood up the same object storage service next to AWS, so you wouldn’t have to pay any data eviction fees, and you could mine everything right there, leveraging the AWS Redshift, or Hadoop-as-a-service.

Then once these artifacts, or these reports, were created, they no longer had the IP. The reports came from the IP, but these are all roll-ups and comparisons, and now they are not sensitive to the company. We went ahead and put those into S3 and allowed Amazon to manage all of their customers’ identity and access management to go ahead and get access to that — and that all minimized risk for this exchange. We are able to prevent anyone outside of the organization to get behind the firewall to get at their data. You don’t have to worry about the SLAs associated with keeping this stuff up and available and it became a really nice hybrid story.

We help customers gain all the benefits associated with cloud – without taking on any of the additional risk.

These are the types of projects that we really like to work on with customers, to be able to help them gain all the benefits associated with cloud – without taking on any of the additional risk, or the negatives, associated with jumping into cloud with both feet. 

Gardner: You heard your customers, you saw a niche opportunity for object storage as a service, and you have put that together. I assume that you want a composable infrastructure to do that. So is this something on a HPE Synergy a future foundation? 

Reyenger: HPE Synergy doesn’t really have the disk density to get to the public cloud price point, but it does support object storage natively. So it’s great from a DevOps standpoint for object storage. We definitely think that as time progresses and HPE continues down the Synergy roadmap that that cloud role will eventually fix itself.

A lot of the cloud role is centered on hyper-converged infrastructure. And in this kind of mantra, I don’t see compute and storage growing at the same rates. I see storage growing considerably faster than the need for compute. So this is a way for us to be able to help supplement a Synergy deployment, or we can help our customers get the true ROI/TCO they are looking for out of the hyper-converged. 

Gardner: So maybe the question I should ask is what storage providers are you using in order to make this economically viable?

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Reyenger:  We are absolutely using the HPE Apollo storage line, and the different flavors of solid-state disks (SSD) down to SATA physical drives. And we are leveraging best-in-breed object storage software from Red Hat. We also have an OpenStack flavor as well.

We leverage things like automation and orchestration technologies, and our ServiceNow capabilities — all married with our RIP in order to give customers the choice of buying this, deploying it, and having us layer services on top if you want or if you want to consume a fully managed service for something that’s on-premises. I have a per-GB price and the same SLAs as those public cloud providers. So all of it’s coming together to allow customers to really have the true choice and flexibility that everyone claimed you could years ago.

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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As enterprises face hybrid IT complexity, new management solutions beckon

The next BriefingsDirect Voice of the Analyst interview examines how new machine learning and artificial intelligence (AI) capabilities are being applied to hybrid IT complexity challenges.

We’ll explore how mounting complexity and a lack of multi-cloud services management maturity must be solved in order for businesses to grow and thrive as digital enterprises.

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 companies and IT leaders are seeking new means to manage an increasingly complex transition to sustainable hybrid IT is Paul Teich, Principal Analyst at TIRIAS Research in Austin, Texas. The discussion is moderated by Dana Gardner, principal analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Paul, there’s a lot of evidence that businesses are adopting cloud models at a rapid pace. There is also lingering concern about the complexity of managing so many fast-moving parts. We have legacy IT, private cloud, public cloud, software as a service (SaaS) and, of course, multi-cloud. So as someone who tracks technology and its consumption, how much has technology itself been tapped to manage this sprawl, if you will, across hybrid IT?

Paul Teich

Teich

Teich: So far, not very much, mostly because of the early state of multi-cloud and the hybrid cloud business model. As you know, it takes a while for management technology to catch up with the actual compute technology and storage. So I think we are seeing that management is the tail of the dog, it’s getting wagged by the rest of it, and it just hasn’t caught up yet.

Gardner: Things have been moving so quickly with cloud computing that few organizations have had an opportunity to step back and examine what’s actually going on around them — never mind properly react to it. We really are playing catch up.

Teich: As we look at the options available, the cloud giants — the public cloud services — don’t have much incentive to work together. So you are looking at a market where there will be third parties stepping in to help manage multi-cloud environments, and there’s a lag time between having those services available and having the cloud services available and then seeing the third-party management solution step in.

Gardner: It’s natural to see that a specific cloud environment, whether it’s purely public like AWS or a hybrid like Microsoft Azure and Azure Stack, want to help their customers, but they want to help their customers all get to their solutions first and foremost. It’s a natural thing. We have seen this before in technology.

There are not that many organizations willing to step into the neutral position of being ecumenical, of saying they want to help the customer first, manage it all from the first.

As we look to how this might unfold, it seems to me that the previous models of IT management — agent-based, single-pane-of-glass, and unfortunately still in some cases spreadsheets and Post-It notes — have been brought to bear on this. But we might be in a different ball game, Paul, with hybrid IT, that there’s just too many moving parts, too much complexity, and that we might need to look at data-driven approaches. What is your take on that?

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Teich: I think that’s exactly correct. One of the jokes in the industry right now is if you want to find your stranded instances in the cloud, cancel your credit card and AWS or Microsoft will be happy to notify you of all of the instances that you are no longer paying for because your credit card expired. It’s hard to keep track of this, because we don’t have adequate tools yet.

When you are an IT manager and you have a lot of folks on public cloud services, you don’t have a full picture.

That single pane of glass, looking at a lot of data and information, is soon overloaded. When you are an IT manager, you are at a mid-sized or a large corporation, you have a lot of folks paying out-of-pocket right now, slapping a credit card down on public cloud services, so you don’t have a full picture. Where you do have a picture, there are so many moving parts.

I think we have to get past having a screen full of data, a screen full of information, and to a point where we have insight. And that is going to require a new generation of tools, probably borrowing from some of the machine learning evolution that’s happening now in pattern analytics.

Gardner: The timing in some respects couldn’t be better, right? Just as we are facing this massive problem of complexity of volume and velocity in managing IT across a hybrid environment, we have some of the most powerful and cost-effective means to deal with big data problems just like that.

Life in the infrastructure

Paul, before we go further let’s hear about you and your organization, and tell us, if you would, what a typical day is like in the life of Paul Teich?

Teich: At TIRIAS Research we are boutique industry analysts. By boutique we mean there are three of us — three principal analysts; we have just added a few senior analysts. We are close to the metal. We live in the infrastructure. We are all former engineers and/or product managers. We are very familiar with deep technology.

My day tends to be first, a lot of reading. We look at a lot of chips, we look at a lot of service-level information, and our job is to, at a very fundamental level, take very complex products and technologies and surface them to business decision-makers, IT decision-makers, folks who are trying to run lines of business (LOB) and make a profit. So we do the heavy lifting on why new technology is important, disruptive, and transformative.

Gardner: Thanks. Let’s go back to this idea of data-driven and analytical values as applied to hybrid IT management and complexity. If we can apply AI and machine learning to solve business problems outside of IT — in such verticals as retail, pharmaceutical, transportation — with the same characteristics of data volume, velocity, and variety, why not apply that to IT? Is this a case of the cobbler’s kids having no shoes? You would think that IT would be among the first to do this.

Dig deep, gain insight

Teich: The cloud giants have already implemented systems like this because of necessity. So they have been at the front-end of that big data mantra of volume, velocity — and all of that.

To successfully train for the new pattern recognition analytics, especially the deep learning stuff, you need a lot of data. You can’t actually train a system usefully without presenting it with a lot of use cases.

The public clouds have this data. They are operating social media services, large retail storefronts, and e-tail, for example. As the public clouds became available to enterprises, the IT management problem ballooned into a big data problem. I don’t think it was a big data problem five or 10 years ago, but it is now.

That’s a big transformation. We haven’t actually internalized what that means operationally when your internal IT department no longer runs all of your IT jobs anymore.

We are generating big data and that means we need big data tools to go analyze it and to get that relevant insight.

That’s the biggest sea change — we are generating big data in the course of managing our IT infrastructure now, and that means we need big data tools to go analyze it, and to get that relevant insight. It’s too much data flowing by for humans to comprehend in real time.

Gardner: And, of course, we are also talking about islands of such operational data. You might have a lot of data in your legacy operations. You might have tier 1 apps that you are running on older infrastructure, and you are probably happy to do that. It might be very difficult to transition those specific apps into newer operating environments.

You also have multiple SaaS and cloud data repositories and logs. There’s also not only the data within those apps, but there’s the metadata as to how those apps are running in clusters and what they are doing as a whole. It seems to me that not only would you benefit from having a comprehensive data and analytics approach for your IT operations, but you might also have a workflow and process business benefit by being an uber analyst, by being on top of all of these islands of operational data.

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To me, moving toward a comprehensive intelligence and data analysis capability for IT is the gift that keeps giving. You would then be able to also provide insight for an uber approach to processes across your entire organization — across the supply chains, across partner networks, and back to your customers. Paul, do you also see that there’s an ancillary business benefit to having that data analysis capability, and not ceding it to your cloud providers?

Manage data, improve workflow

Teich: I do. At one end of the spectrum it’s simply what do you need to do to keep the lights on, where is your data, all of it, in the various islands and collections and the data you are sharing with your supply chain as well. Where is the processing that you can apply to that data? Increasingly, I think, we are looking at a world in which the location of the stored data is more important than the processing power.

The management of all the data you have needs to segue into visible workflows.

We have processing power pretty much everywhere now. What’s key is moving data from place to place and setting up the connections to acquire it. It means that the management of all the data you have needs to segue into visible workflows.

Once I know what I have, and I am managing it at a baseline effectively, then I can start to improve my processes. Then I can start to get better workflows, internally as well as across my supply chain. But I think at first it’s simply, “What do I have going on right now?”

As an IT manager, how can I rein in some of these credit card instances, credit card storage on the public clouds, and put that all into the right mix. I have to know what I know first — then I can start to streamline. Then I can start to control my costs. Does that make sense?

Gardner: Yes, absolutely. And how can you know which people you want to give even more credit to on their credit cards – and let them do more of what they are doing? It might be very innovative, and it might be very cost-effective. There might also be those wasting money, spinning their wheels, repaving cow paths, over and over again.

If you don’t have the ability to make those decisions with insight, without the visibility, and then further analyze it as to how best to go about it – it seems to me a no-brainer.

It also comes at an auspicious time as IT is trying to re-factor its value to the organization. If in fact they are no longer running servers and networks and keeping the trains running on time, they have to start being more in the business of defining what trains should be running and then how to make them the best business engines, if you will.

If IT departments needs to rethink their role and step up their game, then they need to use technologies like advanced hybrid IT management from vendors with a neutral perspective. Then they become the overseers of operations at a fundamentally different level.

Data revelation, not revolution

Teich: I think that’s right. It’s evolutionary stuff. I don’t think it’s revolutionary. I think that in the same way you add servers to a virtual machine farm, as your demand increases, as your baseline demand increases, IT needs to keep a handle on costs — so you can understand which jobs are running where and how much more capacity you need.

One of the things they are missing with random access to the cloud is bulk purchasing. And so at a very fundamental level, helping your organization manage which clouds you are spending on by aggregating the purchase of storage, aggregating the purchase of compute instances to get just better buying power, doing price arbitrage when you can. To me, those are fundamental qualities of IT going forward in a multi-cloud environment.

They are extensions of where we are today; it just doesn’t seem like it yet. They have always added new servers to increasing internal capacity and this is just the next evolutionary step.

Gardner: It certainly makes sense that you would move as maturity occurs in any business function toward that orchestration, automation and optimization – rather than simply getting the parts in place. What you are describing is that IT is becoming more like a procurement function and less like a building, architecture, or construction function, which is just as powerful.

Not many people can make those hybrid IT procurement decisions without knowing a lot about the technology. Someone with just business acumen can’t walk in and make these decisions. I think this is an opportunity for IT to elevate itself and become even more essential to the businesses.

Teich: The opportunity is a lot like the Sabre airline scheduling system that nearly every airline uses now. That’s a fundamental capability for doing business, and it’s separate from the technology of Sabre. It’s the ability to schedule — people and airplanes – and it’s a lot like scheduling storage and jobs on compute instances. So I think there will be this step.

But to go back to the technology versus procurement, I think some element of that has always existed in IT in terms of dealing with vendors and doing the volume purchases on one side, but also having some architect know how to compose the hardware and the software infrastructure to serve those applications.

Connect the clouds

We’re simply translating that now into a multi-cloud architecture. How do I connect those pieces? What network capacity do I need to buy? What kind of storage architectures do I need? I don’t think that all goes away. It becomes far more important as you look at, for example, AWS as a very large bag of services. It’s very powerful. You can assemble it in any way you want, but in some respect, that’s like programming in C. You have all the power of assembly language and all the danger of assembly language, because you can walk up in the memory and delete stuff, and so, you have to have architects who know how to build a service that’s robust, that won’t go down, that serves your application most efficiently and all of those things are still hard to do.

So, architecture and purchasing are both still necessary. They don’t go away. I think the important part is that the orchestration part now becomes as important as deploying a service on the side of infrastructure because you’ve got multiple sets of infrastructure.

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Gardner: For hybrid IT, it really has to be an enlightened procurement, not just blind procurement. And the people in the trenches that are just buying these services — whether the developers or operations folks — they don’t have that oversight, that view of the big picture to make those larger decisions about optimization of purchasing and business processes.

That gets us back to some of our earlier points of, what are the tools, what are the management insights that these individuals need in order to make those decisions? Like with Sabre, where they are optimizing to fill every hotel room or every airplane seat, we’re going to want in hybrid IT to fill every socket, right? We’re going to want all that bare metal and all those virtualization instances to be fully optimized — whether it’s your cloud or somebody else’s.

It seems to me that there is an algorithmic approach eventually, right? Somebody is going to need to be the keeper of that algorithm as to how this all operates — but you can’t program that algorithm if you don’t have the uber insights into what’s going on, and what works and what doesn’t.

What’s the next step, Paul, in terms of the technology catching up to the management requirements in this new hybrid IT complex environment?

Teich: People can develop some of that experience on a small scale, but there are so many dimensions to managing a multi-cloud, hybrid IT infrastructure business model. It’s throwing off all of this metadata for performance and efficiency. It’s ripe for machine learning.

We’re moving so fast right now that if you are an organization of any size, machine learning has to come into play to help you get better economies of scale.

In a strong sense, we’re moving so fast right now that if you are an organization of any size, machine learning has to come into play to help you get better economies of scale. It’s just going to be looking at a bigger picture, it’s going to be managing more variables, and learning across a lot more data points than a human can possibly comprehend.

We are at this really interesting point in the industry where we are getting deep-learning approaches that are coming online cost effectively; they can help us do that. They have a little while to go before they are fully mature. But IT organizations that learn to take advantage of these systems now are going to have a head start, and they are going to be more efficient than their competitors.

Gardner: At the end of the day, if you’re all using similar cloud services then that differentiation between your company and your competitor is in how well you utilize and optimize those services. If the baseline technologies are becoming commoditized, then optimization — that algorithm-like approach to smartly moving workloads and data, and providing consumption models that are efficiency-driven — that’s going to be the difference between a 1 percent margin and a 5 percent margin over time.

The deep-learning difference

Teich: The important part to remember is that these machine-training algorithms are somewhat new, so there are several challenges with deploying them. First is the transparency issue. We don’t quite yet know how a deep-learning model makes specific decisions. We can’t point to one aspect and say that aspect is managing the quality of our AWS services, for example. It’s a black box model.

We can’t yet verify the results of these models. We know they are being efficient and fast but we can’t verify that the model is as efficient as it could possibly be. There is room for improvement over the next few years. As the models get better, they’ll leave less money on the table.

We’re also validating that when you build a machine-learning model that it’s covering all the situations you want it to cover. You need an audit trail for specific sets of decisions, especially with data that is subject to regulatory constraints. You need to know why you made decisions.

So the net is, once you are training a machine-learning model, you have to keep retraining it over time. Your model is not going to do the same thing as your competitor’s model. There is a lot of room for differentiation, a lot of room for learning. You just have to go into it with your eyes open that, yeah, occasionally things will go sideways. Your model might do something unexpected, and you just have to be prepared for that. We’re still in the early days of machine learning.

Gardner: You raise an interesting point, Paul, because even as the baseline technology services in the multi-cloud era become commoditized, you’re going to have specific, unique, and custom approaches to your own business’ management.

Your hybrid IT optimization is not going to be like that of any other company. I think getting that machine-learning capability attuned to your specific hybrid IT panoply of resources and assets is going to be a gift that keeps giving. Not only will you run your IT better, you will run your business better. You’ll be fleet and agile.

If some risk arises — whether it’s a cyber security risk, a natural disaster risk, a business risk of unintended or unexpected changes in your supply chain or in your business environment — you’re going to be in a better position to react. You’re going to have your eyes to the ground, you’re going to be well tuned to your specific global infrastructure, and you’ll be able to make good choices. So I am with you. I think machine learning is essential, and the sooner you get involved with it, the better.

Before we sign off, who are the vendors and some of the technologies that we will look to in order to fill this apparent vacuum on advanced hybrid IT management? It seems to me that traditional IT management vendors would be a likely place to start.

Who’s in?

Teich: They are a likely place to start. All of them are starting to say something about being in a multi-cloud environment, about being in a multi-cloud-vendor environment. They are already finding themselves there with virtualization, and the key is they have recognized that they are in a multi-vendor world.

There are some start-ups, and I can’t name them specifically right now. But a lot of folks are working on this problem of how do I manage hybrid IT: In-house IT, and multi-cloud orchestration, a lot of work going on there. We haven’t seen a lot of it publicly yet, but there is a lot of venture capital being placed.

I think this is the next step, just like PCs came in the office, smartphones came in the office as we move from server farms to the clouds, going from cloud to multi-cloud, it’s attracting a lot of attention. The hard part right now is nailing whom to place your faith in. The name brands that people are buying their internal IT from right now are probably good near-term bets. As the industry gets more mature, we’ll have to see what happens.

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Gardner: We did hear a vision described on this from Hewlett Packard Enterprise (HPE) back in June at their Discover event in Las Vegas. I’m expecting to hear quite a bit more on something they’ve been calling New Hybrid IT Stack that seems to possess some of the characteristics we’ve been describing, such as broad visibility and management.

So at least one of the long-term IT management vendors is looking in this direction. That’s a place I’m going to be focusing on, wondering what the competitive landscape is going to be, and if HPE is going to be in the leadership position on hybrid IT management.

Teich: Actually, I think HPE is the only company I’ve heard from so far talking at that level. Everybody is voicing some opinion about it, but from what I’ve heard, it does sound like a very interesting approach to the problem.

Microsoft actually constrained their view on Azure Stack to a very small set of problems, and is actively saying, “No, I don’t.” If you’re looking at doing virtual machine migration and taking advantage of multi-cloud for general-purpose solutions, it’s probably not something that you want to do yet. It was very interesting for me then to hear about the HPE Project New Hybrid IT Stack and what HPE is planning to do there.

Gardner: For Microsoft, the more automated and constrained they can make it, the more likely you’d be susceptible or tempted to want to just stay within an Azure and/or Azure Stack environment. So I can appreciate why they would do that.

Before we sign off, one other area I’m going to be keeping my eyes on is around orchestration of containers, Kubernetes, in particular. If you follow orchestration of containers and container usage in multi-cloud environments, that’s going to be a harbinger of how the larger hybrid IT management demands are going to go as well. So a canary in the coal mine, if you will, as to where things could get very interesting very quickly.

The place to be

Teich: Absolutely. And I point out that the Linux Foundation’s CloudNativeCon in early December 2017 looks like the place to be — with nearly everyone in the server infrastructure community and cloud infrastructure communities signing on. Part of the interest is in basically interchangeable container services. We’ll see that become much more important. So that sleepy little technical show is going to be invaded by “suits,” this year, and we’re paying a lot of attention to it.

Gardner: Yes, I agree. I’m afraid we’ll have to leave it there. Paul, how can our listeners and readers best follow you to gain more of your excellent insights?

Teich: You can follow us at www.tiriasresearch.com, and also we have a page on Forbes Tech, and you can find us there.

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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How mounting complexity, multi-cloud sprawl, and need for maturity hinder hybrid IT’s ability to grow and thrive

The next BriefingsDirect Voice of the Analyst interview examines how the economics and risk management elements of hybrid IT factor into effective cloud adoption and choice.

We’ll now explore how mounting complexity and a lack of multi-cloud services management maturity must be solved in order to have businesses grow and thrive as digital enterprises.

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

Tim Crawford, CIO Strategic Advisor at AVOA in Los Angeles joins us to report on how companies are managing an increasingly complex transition to sustainable hybrid IT. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Tim, there’s a lot of evidence that businesses are adopting cloud models at a rapid pace. But there is also lingering concern about how to best determine the right mix of cloud, what kinds of cloud, and how to mitigate the risks and manage change over time.

As someone who regularly advises chief information officers (CIOs), who or which group is surfacing that is tasked with managing this cloud adoption and its complexity within these businesses? Who will be managing this dynamic complexity?

Crawford: For the short-term, I would say everyone. It’s not as simple as it has been in the past where we look to the IT organization as the end-all, be-all for all things technology. As we begin talking about different consumption models — and cloud is a relatively new consumption model for technology — it changes the dynamics of it. It’s the combination of changing that consumption model — but then there’s another factor that comes into this. There is also the consumerization of technology, right? We are “democratizing” technology to the point where everyone can use it, and therefore everyone does use it, and they begin to get more comfortable with technology.

It’s not as it used to be, where we would say, “Okay, I’m not sure how to turn on a computer.” Now, businesses may be more familiar outside of the IT organization with certain technologies. Bringing that full-circle, the answer is that we have to look beyond just IT. Cloud is something that is consumed by IT organizations. It’s consumed by different lines of business, too. It’s consumed even by end-consumers of the products and services. I would say it’s all of the above.

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Gardner: The good news is that more and more people are able to — on their own – innovate, to acquire cloud services, and they can factor those into how they obtain business objectives. But do you expect that we will get to the point where that becomes disjointed? Will the goodness of innovation become something that spins out of control, or becomes a negative over time?

Crawford: To some degree, we’ve already hit that inflection-point where technology is being used in inappropriate ways. A great example of this — and it’s something that just kind of raises the hair on the back of my neck — is when I hear that boards of directors of publicly traded companies are giving mandates to their organization to “Go cloud.”

The board should be very business-focused and instead they’re dictating specific technology — whether it’s the right technology or not. That’s really what this comes down to.

What’s the right use of cloud – in all forms, public, private, software as a service (SaaS). What’s the right combination to use for any given application?

Another example is folks that try and go all-in on cloud but aren’t necessarily thinking about what’s the right use of cloud – in all forms, public, private, software as a service (SaaS). What’s the right combination to use for any given application? It’s not a one-size-fits-all answer.

We in the enterprise IT space haven’t really done enough work to truly understand how best to leverage these new sets of tools. We need to both wrap our head around it but also get in the right frame of mind and thought process around how to take advantage of them in the best way possible.

Another example that I’ve worked through from an economic standpoint is if you were to do the math, which I have done a number of times with clients — you do the math to figure out what’s the comparative between the IT you’re doing on-premises in your corporate data center with any given application — versus doing it in a public cloud.

Think differently

If you do the math, taking an application from a corporate data center and moving it to public cloud will cost you four times as much money. Four times as much money to go to cloud! Yet we hear the cloud is a lot cheaper. Why is that?

When you begin to tease apart the pieces, the bottom line is that we get that four-times-as-much number because we’re using the same traditional mindset where we think about cloud as a solution, the delivery mechanism, and a tool. The reality is it’s a different delivery mechanism, and it’s a different kind of tool.

When used appropriately, in some cases, yes, it can be less expensive. The challenge is you have to get yourself out of your traditional thinking and think differently about the how and why of leveraging cloud. And when you do that, then things begin to fall into place and make a lot more sense both organizationally — from a process standpoint, and from a delivery standpoint — and also economically.

Gardner: That “appropriate use of cloud” is the key. Of course, that could be a moving target. What’s appropriate today might not be appropriate in a month or a quarter. But before we delve into more … Tim, tell us about your organization. What’s a typical day in the life for Tim Crawford like?

It’s not tech for tech’s sake, rather it’s best to say, “How do we use technology for business advantage?”

Crawford: I love that question. AVOA stands for that position in which we sit between business and technology. If you think about the intersection of business and technology, of using technology for business advantage, that’s the space we spend our time thinking about. We think about how organizations across a myriad of different industries can leverage technology in a meaningful way. It’s not tech for tech’s sake, and I want to be really clear about that. But rather it’s best to say, “How do we use technology for business advantage?”

We spend a lot of time with large enterprises across the globe working through some of these challenges. It could be as simple as changing traditional mindsets to transformational, or it could be talking about tactical objectives. Most times, though, it’s strategic in nature. We spend quite a bit of time thinking about how to solve these big problems and to change the way that companies function, how they operate.

A day in a life of me could range from, if I’m lucky, being able to stay in my office and be on the phone with clients, working with folks and thinking through some of these big problems. But I do spend a lot of time on the road, on an airplane, getting out in the field, meeting with clients, understanding what people really are contending with.

I spent well over 20 years of my career before I began doing this within the IT organization, inside leading IT organizations. It’s incredibly important for me to stay relevant by being out with these folks and understanding what they’re challenged by — and then, of course, helping them through their challenges.

Any given day is something new and I love that diversity. I love hearing different ideas. I love hearing new ideas. I love people who challenge the way I think.

It’s an opportunity for me personally to learn and to grow, and I wish more of us would do that. So it does vary quite a bit, but I’m grateful that the opportunities that I’ve had to work with have been just fabulous, and the same goes for the people.

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Gardner: I’ve always enjoyed my conversations with you, Tim, because you always do challenge me to think a little bit differently — and I find that very valuable.

Okay, let’s get back to this idea of “appropriate use of cloud.” I wonder if we should also expand that to be “appropriate use of IT and cloud.” So including that notion of hybrid IT, which includes cloud and hybrid cloud and even multi-cloud. And let’s not forget about the legacy IT services.

How do we know if we’re appropriately using cloud in the context of hybrid IT? Are there measurements? Is there a methodology that’s been established yet? Or are we still in the opening innings of how to even measure and gain visibility into how we consume and use cloud in the context of all IT — to therefore know if we’re doing it appropriately?

The monkey-bread model

Crawford: The first thing we have to do is take a step back to provide the context of that visibility — or a compass, as I usually refer to these things. You need to provide a compass to help understand where we need to go.

If we look back for a minute, and look at how IT operates — traditionally, we did everything. We had our own data center, we built all the applications, we ran our own servers, our own storage, we had the network – we did it all. We did it all, because we had to. We, in IT, didn’t really have a reasonable alternative to running our own email systems, our own file storage systems. Those days have changed.

Fast-forward to today. Now, you have to pick apart the pieces and ask, “What is strategic?” When I say, “strategic,” it doesn’t mean critically important. Electrical power is an example. Is that strategic to your business? No. Is it important? Heck, yeah, because without it, we don’t run. But it’s not something where we’re going out and building power plants next to our office buildings just so we can have power, right? We rely on others to do it because there are mature infrastructures, mature solutions for that. The same is true with IT. We have now crossed the point where there are mature solutions at an enterprise level that we can capitalize on, or that we can leverage.

Part of the methodology I use is the monkey bread example. If you’re not familiar with monkey bread, it’s kind of a crazy thing where you have these balls of dough. When you bake it, the balls of dough congeal together and meld. What you’re essentially doing is using that as representative of, or an analogue to, your IT portfolio of services and applications. You have to pick apart the pieces of those balls of dough and figure out, “Okay. Well, these systems that support email, those could go off to Google or Microsoft 365. And these applications, well, they could go off to this SaaS-based offering. And these other applications, well, they could go off to this platform.”

And then, what you’re left with is this really squishy — but much smaller — footprint that you have to contend with. That problem in the center is much more specific — and arguably that’s what differentiates your company from your competition.

Whether you run email [on-premises] or in a cloud, that’s not differentiating to a business. It’s incredibly important, but not differentiating. When you get to that gooey center, that’s the core piece, that’s where you put your resources in, that’s what you focus on.

This example helps you work through determining what’s critical, and — more importantly — what’s strategic and differentiating to my business, and what is not. And when you start to pick apart these pieces, it actually is incredibly liberating. At first, it’s a little scary, but once you get the hang of it, you realize how liberating it is. It brings focus to the things that are most critical for your business.

Identify opportunities where cloud makes sense – and where it doesn’t. It definitely is one of the most significant opportunities for most IT organizations today.

That’s what we have to do more of. When we do that, we identify opportunities where cloud makes sense — and where it doesn’t. Cloud is not the end-all, be-all for everything. It definitely is one of the most significant opportunities for most IT organizations today.

So it’s important: Understand what is appropriate, how you leverage the right solutions for the right application or service.

Gardner: IT in many organizations is still responsible for everything around technology. And that now includes higher-level strategic undertakings of how all this technology and the businesses come together. It includes how we help our businesses transform to be more agile in new and competitive environments.

So is IT itself going to rise to this challenge, of not doing everything, but instead becoming more of that strategic broker between in IT functions and business outcomes? Or will those decisions get ceded over to another group? Maybe enterprise architects, business architects, business process management (BPM) analysts? Do you think it’s important for IT to both stay in and elevate to the bigger game?

Changing IT roles and responsibilities

Crawford: It’s a great question. For every organization, the answer is going to be different. IT needs to take on a very different role and sensibility. IT needs to look different than how it looks today. Instead of being a technology-centric organization, IT really needs to be a business organization that leverages technology.

The CIO of today and moving forward is not the tech-centric CIO. There are traditional CIOs and transformational CIOs. The transformational CIO is the business leader first who happens to have responsibility for technology. IT, as a whole, needs to follow the same vein.

For example, if you were to go into a traditional IT organization today and ask them what’s the nature of their business, ask them to tell you what they do as an administrator, as a developer, to help you understand how that’s going to impact the company and the business — unfortunately, most of them would have a really hard time doing that.

The IT organization of the future, will articulate clearly the work they’re doing and how that impacts their customers and their business, and how making different changes and tweaks will impact their business. They will have an intimate knowledge of how their business functions much more than how the technology functions. That’s a very different mindset, that’s the place we have to get to for IT on the whole. IT can’t just be this technology organization that sits in a room, separate from the rest of the company. It has to be integral, absolutely integral to the business.

Gardner: If we recognize that cloud is here to stay — but that the consumption of it needs to be appropriate, and if we’re at some sort of inflection point, we’re also at the risk of consuming cloud inappropriately. If IT and leadership within IT are elevating themselves, and upping their game to be that strategic player, isn’t IT then in the best position to be managing cloud, hybrid cloud and hybrid IT? What tools and what mechanisms will they need in order to make that possible?

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Crawford: Theoretically, the answer is that they really need to get to that level. We’re not there, on the whole, yet. Many organizations are not prepared to adopt cloud. I don’t want to be a naysayer of IT, but I think in terms of where IT needs to go on the whole, on the sum, we need to move into that position where we can manage the different types of delivery mechanisms — whether it’s public cloud, SaaS, private cloud, appropriate data centers — those are all just different levers we can pull depending on the business type.

Businesses change, customers change, demand changes and revenue comes from different places. IT needs to be able to shift gears just as fast and in anticipation of where the company goes.

As you mentioned earlier, businesses change, customers change, demand changes, and revenue comes from different places. In IT, we need to be able to shift gears just as fast and be prepared to shift those gears in anticipation of where the company goes. That’s a very different mindset. It’s a very different way of thinking, but it also means we have to think of clever ways to bring these tools together so that we’re well-prepared to leverage things like cloud.

The challenge is many folks are still in that classic mindset, which unfortunately holds back companies from being able to take advantage of some of these new technologies and methodologies. But getting there is key.

Gardner: Some boards of directors, as you mentioned, are saying, “Go cloud,” or be cloud-first. People are taking them at that, and so we are facing a sort of cloud sprawl. People are doing micro services and as developers spinning up cloud instances and object storage instances. Sometimes they’ll keep those running into production; sometimes they’ll shut them down. We have line of business (LOB) managers going out and acquiring services like SaaS applications, running them for a while, perhaps making them a part of their standard operating procedures. But, in many organizations, one hand doesn’t really know what the other is doing.

Are we at the inflection point now where it’s simply a matter of measurement? Would we stifle innovation if we required people to at least mention what it is that they’re doing with their credit cards or petty cash when it comes to IT and cloud services? How important is it to understand what’s going on in your organization so that you can begin a journey toward better management of this overall hybrid IT?

Why, oh why, oh why, cloud?

Crawford: It depends on how you approach it. If you’re doing it from an IT command-and-control perspective, where you want to control everything in cloud — full stop, that’s failure right out of the gate. But if you’re doing it from a position of — I’m trying to use it as an opportunity to understand why are these folks leveraging cloud, and why are they not coming to IT, and how can I as CIO be better positioned to be able to support them, then great! Go forth and conquer.

The reality is that different parts of the organization are consuming cloud-based services today. I think there’s an opportunity to bring those together where appropriate. But at the end of the day, you have to ask yourself a very important question. It’s a very simple question, but you have to ask it, and it has to do with each of the different ways that you might leverage cloud. Even when you go beyond cloud and talk about just traditional corporate data assets — especially as you start thinking about Internet of things (IoT) and start thinking about edge computing — you know that public cloud becomes problematic for some of those things.

The important question you have to ask yourself is, “Why?” A very simple question, but it can have a really complicated answer. Why are you using public cloud? Why are you using three different forms of public cloud? Why are you using private cloud and public cloud together?

Once you begin to ask yourself those questions, and you keep asking yourself that question … it’s like that old adage. Ask yourself why three times and you kind of get to the core as the true reason why. You’ll bring greater clarity as to the reasons, and typically the business reasons, of why you’re actually going down that path. When you start to understand that, it brings clarity to what decisions are smart decisions — and what decisions maybe you might want to think about doing differently.

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Gardner: Of course, you may begin doing something with cloud for a very good reason. It could be a business reason, a technology reason. You’ll recognize it, you gain value from it — but then over time you have to step back with maturity and ask, “Am I consuming this in such a way that I’m getting it at the best price-point?” You mentioned a little earlier that sometimes going to public cloud could be four times as expensive.

So even though you may have an organization where you want to foster innovation, you want people to spread their wings, try out proofs of concept, be agile and democratic in terms of their ability to use myriad IT services, at what point do you say, “Okay, we’re doing the business, but we’re not running it like a good business should be run.” How are the economic factors driven into cloud decision-making after you’ve done it for a period of time?

Cloud’s good, but is it good for business?

Crawford: That’s a tough question. You have to look at the services that you’re leveraging and how that ties into business outcomes. If you tie it back to a business outcome, it will provide greater clarity on the sourcing decisions you should make.

For example, if you’re spending $5 to make $6 in a specialty industry, that’s probably not a wise move. But if you’re spending $5 to make $500, okay, that’s a pretty good move, right? There is a trade-off that you have to understand from an economic standpoint. But you have to understand what the true cost is and whether there’s sufficient value. I don’t mean technological value, I mean business value, which is measured in dollars.

If you begin to understand the business value of the actions you take — how you leverage public cloud versus private cloud versus your corporate data center assets — and you match that against the strategic decisions of what is differentiating versus what’s not, then you get clarity around these decisions. You can properly leverage different resources and gain them at the price points that make sense. If that gets above a certain amount, well, you know that’s not necessarily the right decision to make.

Economics plays a very significant role — but let’s not kid ourselves. IT organizations haven’t exactly been the best at economics in the past. We need to be moving forward. And so it’s just one more thing on that overflowing plate that we call demand and requirements for IT, but we have to be prepared for that.

Gardner: There might be one other big item on that plate. We can allow people to pursue business outcomes using any technology that they can get their hands on — perhaps at any price – and we can then mature that process over time by looking at price, by finding the best options.

But the other item that we need to consider at all times is risk. Sometimes we need to consider whether getting too far into a model like a public cloud, for example, that we can’t get back out of, is part of that risk. Maybe we have to consider that being completely dependent on external cloud networks across a global supply chain, for example, has inherent cyber security risks. Isn’t it up to IT also to help organizations factor some of these risks — along with compliance, regulation, data sovereignty issues? It’s a big barrel of monkeys.

Before we sign off, as we’re almost out of time, please address for me, Tim, the idea of IT being a risk factor mitigator for a business.

Safety in numbers

Crawford: You bring up a great point, Dana. Risk — whether it is risk from a cyber security standpoint or it could be data sovereignty issues, as well as regulatory compliance — the reality is that nobody across the organization truly understands all of these pieces together.

It really is a team effort to bring it all together — where you have the privacy folks, the information security folks, and the compliance folks — that can become a united team.

It really is a team effort to bring it all together — where you have the privacy folks, the information security folks, and the compliance folks — that can become a united team. I don’t think IT is the only component of that. I really think this is a team sport. In any organization that I’ve worked with, across the industry it’s a team sport. It’s not just one group.

It’s complicated, and frankly, it’s getting more complicated every single day. When you have these huge breaches that sit on the front page of The Wall Street Journal and other publications, it’s really hard to get clarity around risk when you’re always trying to fight against the fear factor. So that’s another balancing act that these groups are going to have to contend with moving forward. You can’t ignore it. You absolutely shouldn’t. You should get proactive about it, but it is complicated and it is a team sport.

Gardner: Some take-aways for me today are that IT needs to raise its game. Yet again, they need to get more strategic, to develop some of the tools that they’ll need to address issues of sprawl, complexity, cost, and simply gaining visibility into what everyone in the organization is – or isn’t — doing appropriately with hybrid cloud and hybrid IT.

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Case study: How HCI-powered private clouds accelerate efficient digital transformation

The next BriefingsDirect cloud efficiency case study examines how a world-class private cloud project evolved in the financial sector.

We’ll now learn how public cloud-like experiences, agility, and cost structures are being delivered via a strictly on-premises model built on hyper-converged infrastructure for a risk-sensitive financial services company.

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

Jim McKittrick joins to help explore the potential for cloud benefits when retaining control over the data center is a critical requirement. He is Senior Account Manager at Applied Computer Solutions (ACS) in Huntington Beach, California. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Many enterprises want a private cloud for security and control reasons. They want an OpEx-like public cloud model, and that total on-premises control. Can you have it both ways?

McKittrick: We are showing that you can. People are learning that the public cloud isn’t necessarily all it has been hyped up to be, which is what happens with newer technologies as they come out.

Gardner: What are the drivers for keeping it all private?

McKittrick: Security, of course. But if somebody actually analyzes it, a lot of times it will be about cost and data access, and the ease of data egress because getting your data back can sometimes be a challenge.

Jim McKittrickAlso, there is a realization that even though I may have strict service-level agreements (SLAs), if something goes wrong they are not going to save my business. If that thing tanks, do I want to give that business away? I have some clients who absolutely will not.

Gardner: Control, and so being able to sleep well at night.

McKittrick: Absolutely. I have other clients that we can speak about who have HIPAA requirements, and they are privately held and privately owned. And literally the CEO says, “I am not doing it.” And he doesn’t care what it costs.

Gardner: If there were a huge delta between the price of going with a public cloud or staying private, sure. But that deltais closing. So you can have the best of both worlds — and not pay a very high penalty nowadays.

McKittrick: If done properly, certainly from my experience. We have been able to prove that you can run an agile, cloud-like infrastructure or private cloud as cost-effectively — or even more cost effectively — than you can in the public clouds. There are certainly places for both in the market.

Gardner: It’s going to vary, of course, from company to company — and even department to department within a company — but the fact is that that choice is there.

McKittrick: No doubt about it, it absolutely is.

Gardner: Tell us about ACS, your role there, and how the company is defining what you consider the best of hybrid cloud environments.

McKittrick: We are a relatively large reseller, about $600 million. We have specialized in data center practices for 27 years. So we have been in business quite some time and have had to evolve with the IT industry.

We have a head start on what’s really coming down the pipe — we are one to two years ahead of the general marketplace.

Structurally, we are fairly conventional from the standpoint that we are a typical reseller, but we pride ourselves on our technical acumen. Because we have some very, very large clients and have worked with them to get on their technology boards, we feel like we have a head start on what’s really coming down the pipe —  we are maybe one to two years ahead of the general marketplace. We feel that we have a thought leadership edge there, and we use that as well as very senior engineering leadership in our organization to tell us what we are supposed to be doing.

Gardner: I know you probably can’t mention the company by name, but tell us about a recent project that seems a harbinger of things to come.

Hyper-convergent control 

McKittrick: It began as a proof of concept (POC), but it’s in production, it’s live globally.

I have been with ACS for 18 years, and I have had this client for 17 of those years. We have been through multiple data center iterations.

When this last one came up, three things happened. Number one, they were under tremendous cost pressure — but public cloud was not an option for them.

The second thing was that they had grown by acquisition, and so they had dozens of IT fiefdoms. You can imagine culturally and technologically the challenges involved there. Nonetheless, we were told to consolidate and globalize all these operations.

Thirdly, I was brought in by a client who had run the US presence for this company. We had created a single IT infrastructure in the US for them. He said, “Do it again for the whole world, but save us a bunch of money.” The gauntlet was thrown down. The customer was put in the position of having to make some very aggressive choices. And so he effectively asked me bring them “cool stuff.”

You could give control to anybody in the organization across the globe and they would be able to manage it.

They asked, “What’s new out there? How can we do this?” Our senior engineering staff brought a couple of ideas to the table, and hyper-converged infrastructure (HCI) was central to that. HCI provided the ability to simplify the organization, as well as the IT management for the organization. You could give control of it to anybody in the organization across the globe and they would be able to manage it, working with partners in other parts of the world.

Gardner: Remote management being very important for this.

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McKittrick: Absolutely, yes. We also gained failover capabilities, and disaster recovery within these regional data centers. We ended going from — depending on whom you spoke to — somewhere between seven to 19 data centers globally, down to three. We were able to consolidate down to three. The data center footprint shrank massively. Just in the US, we went to one data center; we got rid of the other data center completely. We went from 34 racks down to 3.5.

Gardner: Hyper-convergence being a big part of that?

McKittrick: Correct, that was really the key, hyper-convergence and virtualization.

The other key enabling technology was data de-duplication, so the ability to shrink the data and then be able to move it from place to place without crushing bandwidth requirements, because you were only moving the changes, the change blocks.

Gardner: So more of a modern data lifecycle approach?

McKittrick: Absolutely. The backup and recovery approach was built in to the solution itself. So we also deployed a separate data archive, but that’s different than backup and recovery. Backup and recovery were essentially handled by VMware and the capability to have the same machine exist in multiple places at the same time.

Gardner: Now, there is more than just the physical approach to IT, as you described it, there is the budgetary financial approach. So how do they maybe get the benefit of the  OpEx approach that people are fond of with public cloud models and apply that in a private cloud setting?

Budget benefits 

McKittrick: They didn’t really take that approach. I mean we looked at it. We looked at essentially leasing. We looked at the pay-as-you-go models and it didn’t work for them. We ended up doing essentially a purchase of the equipment with a depreciation schedule and traditional support. It was analyzed, and they essentially said, “No, we are just going to buy it.”

Gardner: So total cost of ownership (TCO) is a better metric to look at. Did you have the ability to measure that? What were some of the metrics of success other than this massive consolidation of footprint and better control over management?

McKittrick: We had to justify TCO relative to what a traditional IT refresh would have cost. That’s what I was working on for the client until the cost pressure came to bear. We then needed to change our thinking. That’s when hyper-convergence came through.

What we would have spent on just hardware and infrastructure costs, not including network and bandwidth — would have been $55 million over five years, and we ended up doing it for $15 million.

The cost analysis was already done, because I was already costing it with a refresh, including compute and traditional SAN storage. The numbers I had over a five-year period – just what we would have spent on hardware and infrastructure costs, and not including network and bandwidth – would have been $55 million over five years, and we ended up doing it for $15 million.

Gardner: We have mentioned HCI several times, but you were specifically using SimpliVity, which is now part of Hewlett Packard Enterprise (HPE). Tell us about why SimpliVity was a proof-point for you, and why you think that’s going to strengthen HPE’s portfolio.

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McKittrick: This thing is now built and running, and it’s been two years since inception. So that’s a long time in technology, of course. The major factors involved were the cost savings.

As for HPE going forward, the way the client looked at it — and he is a very forward-thinking technologist — he always liked to say, “It’s just VMware.” So the beauty of it from their perspective – was that they could just deploy on VMware virtualization. Everyone in our organization knows how to work with VMware, we just deploy that, and they move things around. Everything is managed in that fashion, as virtual machines, as opposed to traditional storage, and all the other layers of things that have to be involved in traditional data centers.

The HCI-based data centers also included built-in WAN optimization, built-in backup and recovery, and were largely on solid-state disks (SSDs). All of the other pieces of the hardware stack that you would traditionally have — from the server on down — folded into a little box, so to speak, a physical box. With HCI, you get all of that functionality in a much simpler and much easier to manage fashion. It just makes everything easier.

Gardner: When you bring all those HCI elements together, it really creates a solution. Are there any other aspects of HPE’s portfolio, in addition now to SimpliVity, that would be of interest for future projects?

McKittrick: HPE is able to take this further. You have to remember, at the time, SimpliVity was a widget, and they would partner with the server vendors. That was really it, and with VMware.

Now with HPE, SimpliVity can really build out their roadmap. There is all kinds of innovation that’s going to come.

Now with HPE, SimpliVity has behind them one of the largest technology companies in the world. They can really build out their roadmap. There is all kinds of innovation that’s going to come. When you then pair that with things like Microsoft Azure Stack and HPE Synergy and its composable architecture — yes, all of that is going to be folded right in there.

I give HPE credit for having seen what HCI technology can bring to them and can help them springboard forward, and then also apply it back into things that they are already developing. Am I going to have more opportunity with this infrastructure now because of the SimpliVity acquisition? Yes.

Gardner:  For those organizations that want to take advantage of public cloud options, also having HCI-powered hybrid clouds, and composable and automated-bursting and scale-out — and soon combining that multi-cloud options via HPE New Stack – this gives them the best of all worlds.

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McKittrick: Exactly. There you are. You have your hybrid cloud right there. And certainly one could do that with traditional IT, and still have that capability that HPE has been working on. But now, [with SimpliVity HCI] you have just consolidated all of that down to a relatively simple hardware approach. You can now quickly deploy and gain all those hybrid capabilities along with it. And you have the mobility of your applications and workloads, and all of that goodness, so that you can decide where you want to put this stuff.

Gardner: Before we sign off, let’s revisit this notion of those organizations that have to have a private cloud. What words of advice might you give them as they pursue such dramatic re-architecting of their entire IT systems?

A people-first process

McKittrick: Great question. The technology was the easy part. This was my first global HCI roll out, and I have been in the business well over 20 years. The differences come when you are messing with people — moving their cheese, and messing with their rice bowl. It’s profound. It always comes back to people.

The people and process were the hardest things to deal with, and quite frankly, still are. Make sure that everybody is on-board. They must understand what’s happening, why it’s happening, and then you try to get all those people pulling in the same direction. Otherwise, you end up in a massive morass and things don’t get done, or they become almost unmanageable.

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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Inside story on HPC’s AI role in Bridges ‘strategic reasoning’ research at CMU

The next BriefingsDirect high performance computing (HPC) success interview examines how strategic reasoning is becoming more common and capable — even using imperfect information.

We’ll now learn how Carnegie Mellon University and a team of researchers there are producing amazing results with strategic reasoning thanks in part to powerful new memory-intense systems architectures.

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

To learn more about strategic reasoning advances, please join me in welcoming Tuomas Sandholm, Professor and Director of the Electronic Marketplaces Lab at Carnegie Mellon University in Pittsburgh. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Tell us about strategic reasoning and why imperfect information is often the reality that these systems face?

Sandholm: In strategic reasoning we take the word “strategic” very seriously. It means game theoretic, so in multi-agent settings where you have more than one player, you can’t just optimize as if you were the only actor — because the other players are going to act strategically. What you do affects how they should play, and what they do affects how you should play.

ts

Sandholm

That’s what game theory is about. In artificial intelligence (AI), there has been a long history of strategic reasoning. Most AI reasoning — not all of it, but most of it until about 12 years ago — was really about perfect information games like Othello, Checkers, Chess and Go.

And there has been tremendous progress. But these complete information, or perfect information, games don’t really model real business situations very well. Most business situations are of imperfect information.

So you don’t know the other guy’s resources, their goals and so on. You then need totally different algorithms for solving these games, or game-theoretic solutions that define what rational play is, or opponent exploitation techniques where you try to find out the opponent’s mistakes and learn to exploit them.

So totally different techniques are needed, and this has way more applications in reality than perfect information games have.

Gardner: In business, you don’t always know the rules. All the variables are dynamic, and we don’t know the rationale or the reasoning behind competitors’ actions. People sometimes are playing offense, defense, or a little of both.

Before we dig in to how is this being applied in business circumstances, explain your proof of concept involving poker. Is it Five-Card Draw?

Heads-Up No-Limit Texas Hold’em has become the leading benchmark in the AI community.

Sandholm: No, we’re working on a much harder poker game called Heads-Up No-Limit Texas Hold’em as the benchmark. This has become the leading benchmark in the AI community for testing these application-independent algorithms for reasoning under imperfect information.

The algorithms have really nothing to do with poker, but we needed a common benchmark, much like the IC chip makers have their benchmarks. We compare progress year-to-year and compare progress across the different research groups around the world. Heads-Up No-limit Texas Hold’em turned out to be great benchmark because it is a huge game of imperfect information.

It has 10 to the 161 different situations that a player can face. That is one followed by 161 zeros. And if you think about that, it’s not only more than the number of atoms in the universe, but even if, for every atom in the universe, you have a whole other universe and count all those atoms in those universes — it will still be more than that.

Gardner: This is as close to infinity as you can probably get, right?

Sandholm: Ha-ha, basically yes.

Gardner: Okay, so you have this massively complex potential data set. How do you winnow that down, and how rapidly does the algorithmic process and platform learn? I imagine that being reactive, creating a pattern that creates better learning is an important part of it. So tell me about the learning part.

Three part harmony

Sandholm: The learning part always interests people, but it’s not really the only part here — or not even the main part. We basically have three main modules in our architecture. One computes approximations of Nash equilibrium strategies using only the rules of the game as input. In other words, game-theoretic strategies.

That doesn’t take any data as input, just the rules of the game. The second part is during play, refining that strategy. We call that subgame solving.

Then the third part is the learning part, or the self-improvement part. And there, traditionally people have done what’s called opponent modeling and opponent exploitation, where you try to model the opponent or opponents and adjust your strategies so as to take advantage of their weaknesses.

However, when we go against these absolute best human strategies, the best human players in the world, I felt that they don’t have that many holes to exploit and they are experts at counter-exploiting. When you start to exploit opponents, you typically open yourself up for exploitation, and we didn’t want to take that risk. In the learning part, the third part, we took a totally different approach than traditionally is taken in AI.

We are letting the opponents tell us where the holes are in our strategy. Then, in the background, using supercomputing, we are fixing those holes.

We said, “Okay, we are going to play according to our approximate game-theoretic strategies. However, if we see that the opponents have been able to find some mistakes in our strategy, then we will actually fill those mistakes and compute an even closer approximation to game-theoretic play in those spots.”

One way to think about that is that we are letting the opponents tell us where the holes are in our strategy. Then, in the background, using supercomputing, we are fixing those holes.

All three of these modules run on the Bridges supercomputer at the Pittsburgh Supercomputing Center (PSC), for which the hardware was built by Hewlett Packard Enterprise (HPE).

HPC from HPE

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To Supercomputing and Deep Learning

Gardner: Is this being used in any business settings? It certainly seems like there’s potential there for a lot of use cases. Business competition and circumstances seem to have an affinity for what you’re describing in the poker use case. Where are you taking this next?

Sandholm: So far this, to my knowledge, has not been used in business. One of the reasons is that we have just reached the superhuman level in January 2017. And, of course, if you think about your strategic reasoning problems, many of them are very important, and you don’t want to delegate them to AI just to save time or something like that.

Now that the AI is better at strategic reasoning than humans, that completely shifts things. I believe that in the next few years it will be a necessity to have what I call strategic augmentation. So you can’t have just people doing business strategy, negotiation, strategic pricing, and product portfolio optimization.

You are going to have to have better strategic reasoning to support you, and so it becomes a kind of competition. So if your competitors have it, or even if they don’t, you better have it because it’s a competitive advantage.

Gardner: So a lot of what we’re seeing in AI and machine learning is to find the things that the machines do better and allow the humans to do what they can do even better than machines. Now that you have this new capability with strategic reasoning, where does that demarcation come in a business setting? Where do you think that humans will be still paramount, and where will the machines be a very powerful tool for them?

Human modeling, AI solving

Sandholm: At least in the foreseeable future, I see the demarcation as being modeling versus solving. I think that humans will continue to play a very important role in modeling their strategic situations, just to know everything that is pertinent and deciding what’s not pertinent in the model, and so forth. Then the AI is best at solving the model.

That’s the demarcation, at least for the foreseeable future. In the very long run, maybe the AI itself actually can start to do the modeling part as well as it builds a better understanding of the world — but that is far in the future.

Gardner: Looking back as to what is enabling this, clearly the software and the algorithms and finding the right benchmark, in this case the poker game are essential. But with that large of a data set potential — probabilities set like you mentioned — the underlying computersystems must need to keep up. Where are you in terms of the threshold that holds you back? Is this a price issue that holds you back? Is it a performance limit, the amount of time required? What are the limits, the governors to continuing?

Sandholm: It’s all of the above, and we are very fortunate that we had access to Bridges; otherwise this wouldn’t have been possible at all.  We spent more than a year and needed about 25 million core hours of computing and 2.6 petabytes of data storage.

This amount is necessary to conduct serious absolute superhuman research in this field — but it is something very hard for a professor to obtain. We were very fortunate to have that computing at our disposal.

Gardner: Let’s examine the commercialization potential of this. You’re not only a professor at Carnegie Mellon, you’re a founder and CEO of a few companies. Tell us about your companies and how the research is leading to business benefits.

Superhuman business strategies

Sandholm: Let’s start with Strategic Machine, a brand-new start-up company, all of two months old. It’s already profitable, and we are applying the strategic reasoning technology, which again is application independent, along with the Libratus technology, the Lengpudashi technology, and a host of other technologies that we have exclusively licensed to Strategic Machine. We are doing research and development at Strategic Machine as well, and we are taking these to any application that wants us.

 HPC from HPE

Overcomes Barriers 

To Supercomputing and Deep Learning

Such applications include business strategy optimization, automated negotiation, and strategic pricing. Typically when people do pricing optimization algorithmically, they assume that either their company is a monopolist or the competitors’ prices are fixed, but obviously neither is typically true.

We are looking at how do you price strategically where you are taking into account the opponent’s strategic response in advance. So you price into the future, instead of just pricing reactively. The same can be done for product portfolio optimization along with pricing.

Let’s say you’re a car manufacturer and you decide what product portfolio you will offer and at what prices. Well, what you should do depends on what your competitors do and vice versa, but you don’t know that in advance. So again, it’s an imperfect-information game.

Gardner: And these are some of the most difficult problems that businesses face. They have huge billion-dollar investments that they need to line up behind for these types of decisions. Because of that pipeline, by the time they get to a dynamic environment where they can assess — it’s often too late. So having the best strategic reasoning as far in advance as possible is a huge benefit.

If you think about machine learning traditionally, it’s about learning from the past. But strategic reasoning is all about figuring out what’s going to happen in the future.

Sandholm: Exactly! If you think about machine learning traditionally, it’s about learning from the past. But strategic reasoning is all about figuring out what’s going to happen in the future. And you can marry these up, of course, where the machine learning gives the strategic reasoning technology prior beliefs, and other information to put into the model.

There are also other applications. For example, cyber security has several applications, such as zero-day vulnerabilities. You can run your custom algorithms and standard algorithms to find them, and what algorithms you should run depends on what the other opposing governments run — so it is a game.

Similarly, once you find them, how do you play them? Do you report your vulnerabilities to Microsoft? Do you attack with them, or do you stockpile them? Again, your best strategy depends on what all the opponents do, and that’s also a very strategic application.

And in upstairs blocks trading, in finance, it’s the same thing: A few players, very big, very strategic.

Gaming your own immune system

The most radical application is something that we are working on currently in the lab where we are doing medical treatment planning using these types of sequential planning techniques. We’re actually testing how well one can steer a patient’s T-cell population to fight cancers, autoimmune diseases, and infections better by not just using one short treatment plan — but through sophisticated conditional treatment plans where the adversary is actually your own immune system.

Gardner: Or cancer is your opponent, and you need to beat it?

Sandholm: Yes, that’s right. There are actually two different ways to think about that, and they lead to different algorithms. We have looked at it where the actual disease is the opponent — but here we are actually looking at how do you steer your own T-cell population.

Gardner: Going back to the technology, we’ve heard quite a bit from HPE about more memory-driven and edge-driven computing, where the analysis can happen closer to where the data is gathered. Are these advances of any use to you in better strategic reasoning algorithmic processing?

Algorithms at the edge

Sandholm: Yes, absolutely! We actually started running at the PSC on an earlier supercomputer, maybe 10 years ago, which was a shared-memory architecture. And then with Bridges, which is mostly a distributed system, we used distributed algorithms. As we go into the future with shared memory, we could get a lot of speedups.

We have both types of algorithms, so we know that we can run on both architectures. But obviously, the shared-memory, if it can fit our models and the dynamic state of the algorithms, is much faster.

Gardner: So the HPE Machine must be of interest to you: HPE’s advanced concept demonstration model, with a memory-driven architecture, photonics for internal communications, and so forth. Is that a technology you’re keeping a keen eye on?

HPC from HPE

Overcomes Barriers 

To Supercomputing and Deep Learning

Sandholm: Yes. That would definitely be a desirable thing for us, but what we really focus on is the algorithms and the AI research. We have been very fortunate in that the PSC and HPE have been able to take care of the hardware side.

We really don’t get involved in the hardware side that much, and I’m looking at it from the outside. I’m trusting that they will continue to build the best hardware and maintain it in the best way — so that we can focus on the AI research.

Gardner: Of course, you could help supplement the cost of the hardware by playing superhuman poker in places like Las Vegas, and perhaps doing quite well.

Sandholm: Actually here in the live game in Las Vegas they don’t allow that type of computational support. On the Internet, AI has become a big problem on gaming sites, and it will become an increasing problem. We don’t put our AI in there; it’s against their site rules. Also, I think it’s unethical to pretend to be a human when you are not. The business opportunities, the monetary opportunities in the business applications, are much bigger than what you could hope to make in poker anyway.

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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Philips teams with HPE on ecosystem approach to improve healthcare informatics-driven outcomes

The next BriefingsDirect healthcare transformation use-case discussion focuses on how an ecosystem approach to big data solutions brings about improved healthcare informatics-driven outcomes.

We’ll now learn how a Philips Healthcare Informatics and Hewlett Packard Enterprise (HPE) partnership creates new solutions for the global healthcare market and provides better health outcomes for patients by managing data and intelligence better.

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

Joining us to explain how companies tackle the complexity of solutions delivery in healthcare by using advanced big data and analytics is Martijn Heemskerk, Healthcare Informatics Ecosystem Director for Philips, based in Eindhoven, the Netherlands. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Why are partnerships so important in healthcare informatics? Is it because there are clinical considerations combined with big data technology? Why are these types of solutions particularly dependent upon an ecosystem approach?

Heemskerk: It’s exactly as you say, Dana. At Philips we are very strong at developing clinical solutions for our customers. But nowadays those solutions also require an IT infrastructure layer underneath to solve the total equation. As such, we are looking for partners in the ecosystem because we at Philips recognize that we cannot do everything alone. We need partners in the ecosystem that can help address the total solution — or the total value proposition — for our customers.

Gardner: I’m sure it varies from region to region, but is there a cultural barrier in some regard to bringing cutting-edge IT in particular into healthcare organizations? Or have things progressed to where technology and healthcare converge?

Heemskerk: Of course, there are some countries that are more mature than others. Therefore the level of healthcare and the type of solutions that you offer to different countries may vary. But in principle, many of the challenges that hospitals everywhere are going through are similar.

Some of the not-so-mature markets are also trying to leapfrog so that they can deliver different solutions that are up to par with the mature markets.

Gardner: Because we are hearing a lot about big data and edge computing these days, we are seeing the need for analytics at a distributed architecture scale. Please explain how big data changes healthcare.

Big data value add

Heemskerk: What is very interesting for big data is what happens if you combine it with value-based care. It’s a very interesting topic. For example, nowadays, a hospital is not reimbursed for every procedure that it does in the hospital – the value is based more on the total outcome of how a patient recovers.

This means that more analytics need to be gathered across different elements of the process chain before reimbursement will take place. In that sense, analytics become very important for hospitals on how to measure on how things are being done efficiently, and determining if the costs are okay.

Gardner: The same data that can used to be more efficient can also be used for better healthcare outcomes and understanding the path of the disease, or for the efficacy of procedures, and so on. A great deal can be gained when data is gathered and used properly.

Heemskerk: That is correct. And you see, indeed, that there is much more data nowadays, and you can utilize it for all kind of different things.

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Gardner: Please help us understand the relationship between your organization and HPE. Where does your part of the value begin and end, and how does HPE fill their role on the technology side?

Healthy hardware relationships 

Heemskerk: HPE has been a highly valued supplier of Philips for quite a long time. We use their technologies for all kinds of different clinical solutions. For example, all of the hardware that we use for our back-end solutions or for advanced visualization is sourced by HPE. I am focusing very much on the commercial side of the game, so to speak, where we are really looking at how can we jointly go to market.

As I said, customers are really looking for one-stop shopping, a complete value proposition, for the challenges that they are facing. That’s why we partner with HPE on a holistic level.

Gardner: Does that involve bringing HPE into certain accounts and vice versa, and then going in to provide larger solutions together?

Heemskerk: Yes, that is exactly the case, indeed. We recognized that we are not so much focusing on problems related to just the clinical implications, and we are not just focusing on the problems that HPE is facing — the IT infrastructure and the connectivity side of the value chain. Instead, we are really looking at the problems that the C-suite-level healthcare executives are facing.

How do you align all of your processes so that there is a more optimized process flow within the hospitals?

You can think about healthcare industry consolidation, for example, as a big topic. Many hospitals are now moving into a cluster or into a network and that creates all kinds of challenges, both on the clinical application layer, but also on the IT infrastructure. How do you harmonize all of this? How do you standardize all of your different applications? How do you make sure that hospitals are going to be connected? How do you align all of your processes so that there is a more optimized process flow within the hospitals?

By addressing these kinds of questions and jointly going to our customers with HPE, we can improve user experiences for the customers, we can create better services, we have optimized these solutions, and then we can deliver a lot of time savings for the hospitals as well.

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Gardner: We have certainly seen in other industries that if you try IT modernization without including the larger organization — the people, the process, and the culture — the results just aren’t as good. It is important to go at modernization and transformation, consolidation of data centers, for example, with that full range of inputs and getting full buy-in.

Who else makes up the ecosystem? It takes more than two players to make an ecosystem.

Heemskerk: Yes, that’s very true, indeed. In this, system integrators also have a very important role. They can have an independent view on what would be the best solution to fit a specific hospital.

Of course, we think that the Philips healthcare solutions are quite often the best, jointly focused with the solutions from HPE, but from time to time you can be partnering with different vendors.

Besides that, we don’t have all of the clinical applications. By partnering with other vendors in the ecosystem, sometimes you can enhance the solutions that we have to think about; such as 3D solutions and 3D printing solutions.

Gardner: When you do this all correctly, when you leverage and exploit an ecosystem approach, when you cover the bases of technology, finance, culture, and clinical considerations, how much of an impressive improvement can we typically see?

Saving time, money, and people

Heemskerk: We try to look at it customer by customer, but generically what we see is that there are really a lot of savings.

First of all, addressing standardization across the clinical application layer means that a customer doesn’t have to spend a lot of money on training all of its hospital employees on different kinds of solutions. So that’s already a big savings.

Secondly, by harmonizing and making better effective use of the clinical applications, you can drive the total cost of ownership down.

Thirdly, it means that on the clinical applications layer, there are a lot of efficiency benefits possible. For example, advanced analytics make it possible to reduce the time that clinicians or radiologists are spending on analyzing different kinds of elements, which also creates time savings.

Gardner: Looking more to the future, as technologies improve, as costs go down, as they typically do, as hybrid IT models are utilized and understood better — where do you see things going next for the healthcare sector when it comes to utilizing technology, utilizing informatics, and improving their overall process and outcomes?

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Digital Solutions

That Drive Healthcare and Life Sciences

Heemskerk: What for me would be very interesting is to see is if we can create some kind of a patient-centric data file for each patient. You see that consumers are increasingly engaged in their own health, with all the different devices like Fitbit, Jawbone, Apple Watch, etc. coming up. This is creating a massive amount of data. But there is much more data that you can put into such a patient-centric file, with the chronic diseases information now that people are being monitored much more, and much more often.

If you can have a chronological view of all of the different touch points that the patient has in the hospital, combined with the drugs that the patient is using etc., and you have that all in this patient-centric file — it will be very interesting. And everything, of course, needs to be interconnected. Therefore, Internet of Things (IoT) technologies will become more important. And as the data is growing, you will have smarter algorithms that can also interpret that data – and so artificial intelligence (AI) will become much more important.

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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Posted in application transformation, big data, Cloud computing, data analysis, Enterprise architect, healthcare, Hewlett Packard Enterprise, machine learning, User experience | Tagged , , , , , , , , , | Leave a comment

Inside story: How Ormuco abstracts the concepts of private and public cloud across the globe

The next BriefingsDirect cloud ecosystem strategies interview explores how a Canadian software provider delivers a hybrid cloud platform for enterprises and service providers alike.

We’ll now learn how Ormuco has identified underserved regions and has crafted a standards-based hybrid cloud platform to allow its users to attain world-class cloud services just about anywhere.

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 how new breeds of hybrid cloud are coming to more providers around the globe thanks to the Cloud28+ consortium is Orlando Bayter, CEO and Founder of Ormuco in Montréal, and Xavier Poisson Gouyou Beachamps, Vice President of Worldwide Indirect Digital Services at Hewlett Packard Enterprise (HPE), based in Paris. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Let’s begin with this notion of underserved regions. Orlando, why is it that many people think that public cloud is everywhere for everyone when there are many places around the world where it is still immature? What is the opportunity to serve those markets?

Bayter: There are many countries underserved by the hyperscale cloud providers. If you look at Russia, United Arab Emirates (UAE), around the world, they want to comply with regulations on security, on data sovereignty, and they need to have the clouds locally to comply.

 

Orlando Bayter (1)

Bayter

Ormuco targets those countries that are underserved by the hyperscale providers and enables service providers and enterprises to consume cloud locally, in ways they can’t do today.

Gardner: Are you allowing them to have a private cloud on-premises as an enterprise? Or do local cloud providers offer a common platform, like yours, so that they get the best of both the private and public hybrid environment?

Bayter: That is an excellent question. There are many workloads that cannot leave the firewall of an enterprise. With that, you now need to deliver the economies, ease of use, flexibility, and orchestration of a public cloud experience in the enterprise. At Ormuco, we deliver a platform that provides the best of the two worlds. You are still leaving your data center and you don’t need to worry whether it’s on-premises or off-premises.

It’s a single pane of glass. You can move the workloads in that global network via established providers throughout the ecosystem of cloud services.

It’s a single pane of glass. You can move the workloads in that global network via established providers throughout the ecosystem of cloud services.

Gardner: What are the attributes of this platform that both your enterprise and service provider customers are looking for? What’s most important to them in this hybrid cloud platform?

Bayter: As I said, there are some workloads that cannot leave the data center. In the past, you couldn’t get the public cloud inside your data center. You could have built a private cloud, but you couldn’t get an Amazon Web Services (AWS)-like solution or a Microsoft Azure-like solution on-premises.

We have been running this now for two years and what we have noticed is that enterprises want to have the ease-of-use, sales, service, and orchestration on-premises. Now, they can connect to a public cloud based on the same platform and they don’t have to worry about how to connect it or how it will work. They just decide where to place this.

They have security, can comply with regulations, and gain control — plus 40 percent savings compared with VMware, and up to 50 percent to 60 percent compared with AWS.

Gardner: I’m also interested in the openness of the platform. Do they have certain requirements as to the cloud model, such as OpenStack?  What is it that enables this to be classified as a standard cloud?

Bayter: At Ormuco, we went out and checked what are the best solutions and the best platform that we can bring together to build this experience on-premises and off-premises.

We saw OpenStack, we saw Docker, and then we saw how to take, for example, OpenStack and make it like a public cloud solution. So if you look at OpenStack, the way I see it is as concrete, or a foundation. If you want to build a house or a condo on that, you also need the attic. Ormuco builds that software to be able to deliver that cloud look and feel, that self-service, all in open tools, with the same APIs both on private and public clouds.

Learn How Cloud 28+

Provides an Open Community

Of Cloud Service Providers

Gardner: What is it about the HPE platform beneath that that supports you? How has HPE been instrumental in allowing that platform to be built?

Community collaboration

Bayter: HPE has been a great partner. Through Cloud28+ we are able to go to markets in places that HPE has a presence. They basically generate that through marketing, through sales. They were able to bring deals to us and help us grow our business.

From a technology perspective, we are using HPE Synergy. With Synergy, we can provide composability, and we can combine storage and compute into a single platform. Now we go together into a market, we win deals, and we solve the enterprise challenges around security and data sovereignty.

Gardner: Xavier, how is Cloud28+ coming to market, for those who are not familiar with it? Tell us a bit about Cloud28+ and how an organization like Ormuco is a good example of how it works.

Poisson: Cloud28+ is a community of IT players — service providers, technology partners, independent software vendors (ISVs), value added resellers, and universities — that have decided to join forces to enable digital transformation through cloud computing. To do that, we pull our resources together to have a single platform. We are allowing the enterprise to discover and consume cloud services from the different members of Cloud28+.

We launched Cloud28+ officially to the market on December 15, 2016. Today, we have more than 570 members from across the world inside Cloud28+. Roughly 18,000 distributed services may be consumed and we also have system integrators that support the platform. We cover more than 300 data centers from our partners, so we can provide choice.

In fact, we believe our customers need to have that choice. They need to know what is available for them. As an analogy, if you have your smartphone, you can have an app store and do what you want as a consumer. We wanted to do the same and provide the same ease for an enterprise globally anywhere on the planet. We respect diversity and what is happening in every single region.

Ormuco has been one of the first technology partners. Docker is another one. And Intel is another. They have been working together with HPE to really understand the needs of the customer and how we can deliver very quickly a cloud infrastructure to a service provider and to an enterprise in record time. At the same time, they can leverage all the partners from the catalog of content and services, propelled by Cloud28+, from the ISVs.

Global ecosystem, by choice

Because we are bringing together a global ecosystem, including the resellers, if a service provider builds a project through Cloud28+, with a technology partner like Ormuco, then all the ISVs are included. They can push their services onto the platform, and all the resellers that are part of the ecosystem can convey onto the market what the service providers have been building.

We have a lot of collaboration with Ormuco to help them to design their solutions. Ormuco has been helping us to design what Cloud28+ should be, because it’s a continuous improvement approach on Cloud28+ and it’s via collaboration.

If you want to join Cloud28+ to take, don’t come. If you want to give, and take a lot afterward, yes, please come, because we all receive a lot.

As I like to say, “If you want to join Cloud28+ to take, don’t come. If you want to give, and take a lot afterward, yes, please come, because we all receive a lot.”

Gardner: Orlando, when this all works well, whatdo your end-users gain in terms of business benefits? You mentioned reduction in costs, that’s very important, of course. But is there more about your platform from a development perspective and an operational perspective that we can share to encourage people to explore it?

Bayter: So imagine yourself with an ecosystem like Cloud28+. They have 500 members. They have multiple countries, many data centers.

Now imagine that you can have the Ormuco solution on-premises in an enterprise and then be able to burst to a global network of service providers, across all those regions. You get the same performance, you get the same security, and you get the same compliance across all of that.

For an end-customer, you don’t need to think anymore where you’re going to put your applications. They will go to the public cloud, they will go to the private cloud. It is agnostic. You basically place it where you want it to go and decide the economies you want to get. You can compare with the hyperscale providers.

That is the key, you get one platform throughout our ecosystem of partners that can deliver to you that same functionality and experience locally. With a community such as Cloud28+, we can accomplish something that was not possible before.

Gardner: So, just hoping to delineate between the development and then the operations in production. Are you offering the developer an opportunity to develop there and seamlessly deploy, or are you more focused on the deployment after the applications are developed, or both?

Development to deployment 

Bayter: With our solution, same as AWS or Azure allows, a developer can develop their app via APIs, automated, use a database of choice (it could be MySQL, Oracle), and the load balancing and the different features we have in the cloud, whether it’s Kubernetes or Docker, build all that — and then when the application is ready, you can decide in which region you want to deploy the application.

So you go from development, to deployment technology of your choice, whether it’s Docker or Kubernetes, and then you can deploy to the global network that we’re building on Cloud28+. You can go to any region, and you don’t have to worry about how to get a service provider contract in Russia, or how do I get a contract in Brazil? Who is going to provide me with the service? Now you can get that service locally through a reseller, a distributor, or have an ISV deploythe software worldwide.

Gardner: Xavier, what other sorts of organizations should be aware of the Cloud28+ network?

Learn How Cloud 28+

Provides an Open Community

Of Cloud Service Providers

We accelerate go-to-market for startups, they gain immediate global reach with Cloud28+.

Poisson: We have the technology partners like Ormuco, and we are thankful for what they have brought to the community. We have service providers, of course, software vendors, because you can publish your software in Cloud28+ and provision it on-premises or off-premises. We accelerate go-to-market for startups, they gain immediate global reach with Cloud28+. So to all the ISVs, I say, “Come on, come on guys, we will help you reach out to the market.”

System integrators also, because we see this is an opportunity for the large enterprises and governments with a lot of multi-cloud projects taking care, having requirements for  security. And you know what is happening with security today, it’s a hot topic. So people are thinking about how they can have a multi-cloud strategy. System integrators are now turning to Cloud28+ because they find here a reservoir of all the capabilities to find the right solution to answer the right question.

Universities are another kind of member we are working with. Just to explain, we know that all the technologies are created first at the university and then they evolve. All the startups are starting at the university level. So we have some very good partnerships with some universities in several regions in Portugal, Germany, France, and the United States. These universities are designing new projects with members of Cloud28+, to answer questions of the governments, for example, or they are using Cloud28+ to propel the startups into the market.

Ormuco is also helping to change the business model of distribution. So distributors now also are joining Cloud28+. Why? Because a distributor has to make a choice for its consumers. In the past, a distributor had software inventory that they were pushing to the resellers. Now they need to have an inventory of cloud services.

There is more choice. They can purchase hyperscale services, resell, or maybe source to the different members of Cloud28+, according to the country they want to deliver to. Or they can own the platform using the technology of Ormuco, for example, and put that in a white-label model for the reseller to propel it into the market. This is what Azure is doing in Europe, typically. So new kinds of members and models are coming in.

Digital transformation

Lastly, an enterprise can use Cloud28+ to make their digital transformation. If they have services and software, they can become a supplier inside of Cloud28+. They source cloud services inside a platform, do digital transformation, and find a new go-to-market through the ecosystem to propel their offerings onto the global market.

Gardner: Orlando, do you have any examples that you could share with us of a service provider, ISV or enterprise that has white-labeled your software and your capabilities as Xavier has alluded to? That’s a really interesting model.

Bayter: We have been able to go-to-market to countries where Cloud28+ was a tremendous help. If you look at Western Europe, Xavier was just speaking about Microsoft Azure. They chose our platform and we are deploying it in Europe, making it available to the resellers to help them transform their consumption models.

They provide public cloud and they serve many markets. They provide a community cloud for governments and they provide private clouds for enterprises — all from a single platform.

If you look at the Europe, Middle East and Africa (EMEA) region, we have one of the largest managed service providers. They provide public cloud and they serve many markets. They provide a community cloud for governments and they provide private clouds for enterprises — all from a single platform.

We also have several of the largest telecoms in Latin America (LATAM) and EMEA. We have a US presence, where we have Managed.com as a provider. So things are going very well and it is largely thanks to what Cloud28+ has done for us.

Gardner: While this consortium is already very powerful, we are also seeing new technologies coming to the market that should further support the model. Such things as HPE New Stack, which is still in the works, HPE Synergy’s composability and auto-bursting, along with security now driven into the firmware and the silicon — it’s almost as if HPE’s technology roadmap is designed for this very model, or very much in alignment. Tell us how new technology and the Cloud28+ model come together.

Bayter: So HPE New Stack is becoming the control point of multi-cloud. Now what happens when you want to have that same experience off-premises and on-premises? New Stack could connect to Ormuco as a resource provider, even as it connects to other multi-clouds.

With an ecosystem like Cloud28+ all working together, we can connect those hybrid models with service providers to deliver that experience to enterprises across the world.

Learn How Cloud 28+

Provides an Open Community

Of Cloud Service Providers

Gardner: Xavier, anything more in terms of how HPE New Stack and Cloud28+ fit?

Partnership is top priority

Poisson: It’s a real collaboration. I am very happy with that because I have been working a long time at HPE, and New Stack is a project that has been driven by thinking about the go-to-market at the same time as the technology. It’s a big reward to all the Cloud28+ partners because they are now de facto considered as resource providers for our end-user customers – same as the hyperscale providers, maybe.

At HPE, we say we are in partnership first — with our partners, or ecosystem, or channel. I believe that what we are doing with Cloud28+, New Stack, and all the other projects that we are describing – this will be the reality around the world. We deliver on-premises for the channel partners.

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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