Learn ways a managed and orchestrated cloud lifecycle culture should be sought across enterprise IT organizations.
The next BriefingsDirect cloud deployment strategies interview explores how public cloud adoption is not reaching its potential due to outdated behaviors and persistent dissonance between what businesses can do and will do with cloud strengths.
Many of our ongoing hybrid IT and cloud computing discussions focus on infrastructure trends that support the evolving hybrid IT continuum. Today’s focus shifts to behavior -- how individuals and groups, both large and small, benefit from cloud adoption.
It turns out that a dark side to cloud points to a lackluster business outcome trend. A large part of the disappointment has to do with outdated behaviors and persistent dissonance between what line of business (LOB) practitioners can do and will do with their newfound cloud strengths.
We’ll now hear from an observer of worldwide cloud adoption patterns on why making cloud models a meaningful business benefit rests more with adjusting the wetware than any other variable.
Here to help explore why cloud failures and cost overruns are dogging many enterprises is Robert Christiansen, Vice President, Global Delivery, Cloud Professional Services and Innovation at Cloud Technology Partners (CTP), a Hewlett Packard Enterprise (HPE) company. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: What is happening now with the adoption of cloud that makes the issue of how people react such a pressing concern? What’s bringing this to a head now?
Christiansen: Enterprises are on a cloud journey. They have begun their investment, they recognize that agility is a mandate for them, and they want to get those teams rolling. They have already done that to some degree and extent. They may be moving a few applications, or they may be doing wholesale shutdowns of data centers. They are in lots of different phases in adoption situations.
What we are seeing is a lack of progress with regard to the speed and momentum of the adoption of applications into public clouds. It’s going a little slower than they’d like.
Gardner: We have been through many evolutions, generations, and even step-changes in technology. Most of them have been in a progressive direction. Why are we catching our heels now?
Christiansen: Cloud is a completely different modality, Dana. One of the things that we have learned here is that adoption of infrastructure that can be built from the ground-up using software is a whole other way of thinking that has never really been the core bread-and-butter of an infrastructure or a central IT team. So, the thinking and the process -- the ability to change things on the fly from an infrastructure point of view -- is just a brand new way of doing things.
And we have had various fits and starts around technology adoption throughout history, but nothing at this level. The tool kits available today have completely changed and redefined how we go about doing this stuff.
Gardner: We are not just changing a deployment pattern, we are reinventing the concept of an application. Instead of monolithic applications and systems of record that people get trained on and line up around, we are decomposing processes into services that require working across organizational boundaries. The users can also access data and insights in ways they never had before. So that really is something quite different. Even the concept of an application is up for grabs.
Christiansen: Well, think about this. Historically, an application team or a business unit, let’s say in a bank, said, “Hey, I see an opportunity to reinvent how we do funding for auto loans.”
We worked with a company that did this. And historically, they would have had to jump through a bunch of hoops. They would justify the investment of buying new infrastructure, set up the various components necessary, maybe landing new hardware in the organization, and going into the procurement process for all of that. Typically, in the financial world, it takes months to make that happen.
Today, that same team using a very small investment can stand up a highly available redundant data center in less than a day on a public cloud. In less than a day, using a software-defined framework. And now they can go iterate and test and have very low risk to see if the marketplace is willing to accept the kind of solution they want to offer.
And that just blows apart the procedural-based thinking that we have had up to this point; it just blows it apart. And that thinking, that way of looking at stuff is foreign to most central IT people. Because of that emotion, going to the cloud has come in fits and starts. Some people are doing it really well, but a majority of them are struggling because of the people issue.
Gardner: It seems ironic, Robert, because typically when you run into too much of a good thing, you slap on governance and put in central command and control, and you throttle it back. But that approach subverts the benefits, too.
How do you find a happy medium? Or is there such a thing as a happy medium when it comes to moderating and governing cloud adoption?
Christiansen: That’s where the real rub is, Dana. Let’s give it an analogy. At Cloud Technology Partners (CTP), we do cloud adoption workshops where we bring in all the various teams and try to knock down the silos. They get into these conversations to address exactly what you just said. “How do we put governance in place without getting in the way of innovation?”
It’s a huge, huge problem, because the central IT team’s whole job is to protect the brand of the company and keep the client data safe. They provide the infrastructure necessary for the teams to go out and do what they need to do.
When you have a structure like that but supplied by the public clouds like Amazon (AWS), Google, and Microsoft Azure, you still have the ability to put in a lot of those controls in the software. Before it was done either manually or at least semi-manually.
The central IT team's whole job is to protect the brand of the company and keep the client data safe. They provide the infrastructure necessary for the teams to go out and do what they need to do.
The challenge is that the central IT teams are not necessarily set up with the skills to make that happen. They are not by nature software development people. They are hardware people. They are rack and stack people. They are people who understand how to stitch this stuff together -- and they may use some automation. But as a whole it’s never been their core competency. So therein lies the rub: How do you convert these teams over to think in that new way?
At the same time, you have the pressing issue of, “Am I going to automate myself right out of a job?” That’s the other part, right? That’s the big, 800-pound gorilla sitting in the corner that no one wants to talk about. How do you deal with that?
Gardner: Are we talking about private cloud, public cloud, hybrid cloud, hybrid IT -- all the above when it comes to these trends?
Christiansen: It’s mostly public cloud that you see the perceived threats. The public cloud is perceived as a threat to the current way of doing IT today, if you are an internal IT person.
Let’s say that you are a classic compute and management person. You actually split across both storage and compute, and you are able to manage and handle a lot of those infrastructure servers and storage solutions for your organization. You may be part of a team of 50 in a data center or for a couple of data centers. Many of those classic roles literally go away with a public cloud implementation. You just don’t need them. So these folks need to pivot or change into new roles or reinvent themselves.
Let’s say you’re the director of that group and you happen to be five years away from retirement. This actually happened to me, by the way. There is no way these folks want to give up the range right before their retirement. They don’t want to reinvent their roles just before they’re going to go into their last years.
They literally said to me, “I am not changing my career this far into it for the sake of a public cloud reinvention.” They are hunkering down, building up the walls, and slowing the process. This seems to be an undercurrent in a number of areas where people just don’t want to change. They don’t want any differences.
Gardner: Just to play the devil’s advocate, when you hear things around serverless, when we see more operations automation, when we see artificial intelligence (AI)Ops use AI and machine learning (ML) -- it does get sort of scary.
You’re handing over big decisions within an IT environment on whether to use public or private, some combination, or multicloud in some combination. These capabilities are coming into fruition.
Maybe we do need to step back and ask, “Just because you can do something, should you?” Isn’t that more than just protecting my career? Isn’t there a need for careful consideration before we leap into some of these major new trends?
Transform fear into function
Christiansen: Of course, yeah. It’s a hybrid world. There are applications where it may not make sense to be in the public cloud. There are legacy applications. There are what I call centers of gravity that are database-centric; the business runs on them. Moving them and doing a big lift over to a public cloud platform may not make financial sense. There is no real benefit to it to make that happen. We are going to be living between an on-premises and a public cloud environment for quite some time.
The challenge is that people want to create a holistic view of all of that. How do I govern it in one view and under one strategy? And that requires a lot of what you are talking about, being more cautious going forward.
And that’s a big part of what we have done at CTP. We help people establish that governance framework, of how to put automation in place to pull these two worlds together, and to make it more seamless. How do you network between the two environments? How do you create low-latency communications between your sources of data and your sources of truth? Making that happen is what we have been doing for the last five or six years.
We help establish that governance framework, of how to put automation in place to pull these two worlds together, and to make it more seamless.
The challenge we have, Dana, is that once we have established that -- we call that methodology the Minimum Viable Cloud (MVC). And after you put all of that structure, rigor, and security in place -- we still run into the problems of motion and momentum. Those needed governance frameworks are well-established.
Gardner: Before we dig into why the cloud adoption inertia still exists, let’s hear more about CTP. You were acquired by HPE not that long ago. Tell us about your role and how that fits into HPE.
CTP: A cloud pioneer
Christiansen: CTP was established in 2010. Originally, we were doing mostly private cloud, OpenStack stuff, and we did that for about two to three years, up to 2013.
I am one of the first 20 employees. It’s a Boston-based company, and I came over with the intent to bring more public cloud into the practice. We were seeing a lot of uptick at the time. I had just come out of another company called Cloud Nation that I owned. I sold that company; it was an Amazon-based, Citrix-for-rent company. So imagine, if you would, you swipe a credit card and you get NetScaler, XenApp and XenDesktop running on top of AWS way back in 2012 and 2013.
I sold that company, and I joined CTP. We grew the practice of public cloud on Google, Azure, and AWS over those years and we became the leading cloud-enabled professional services organization in the world.
We were purchased by HPE in October 2017, and my role since that time is to educate, evangelize, and press deeply into the methodologies for adopting public cloud in a holistic way so it works well with what people have on-premises. That includes the technologies, economics, strategies, organizational change, people, security, and establishing a DevOps practice in the organization. These are all within our world.
We do consultancy and professional services advisory types of things, but on the same coin, we flip it over, and we have a very large group of engineers and architects who are excellent on keyboards. These are the people who actually write software code to help make a lot of this stuff automated to move people to the public clouds. That’s what we are doing to this day.
Gardner: We recognize that cloud adoption is a step-change, not an iteration in the evolution of computing. This is not going from client/server to web apps and then to N-Tier architectures. We are bringing services and processes into a company in a whole new way and refactoring that company. If you don’t, the competition or a new upstart unicorn company is going to eat your lunch. We certainly have seen plenty of examples of that.
So what prevents organizations from both seeing and realizing the cloud potential? Is this a matter of skills? Is it because everyone is on the cusp of retirement and politically holding back? What can we identify as the obstacles to overcome to break that inertia?
A whole new ball game
Christiansen: From my perspective, we are right in the thick of it. CTP has been involved with many Fortune 500 companies throughthis process.
The technology is ubiquitous, meaning that everybody in the marketplace now can own pretty much the same technology. Dana, this is a really interesting thought. If a team of 10 Stanford graduates can start up a company to disrupt the rental car industry, which somebody has done, by the way, and they have access to technologies that were only once reserved for those with hundreds of millions of dollars in IT budgets, you have all sorts of other issues to deal with, right?
So what’s your competitive advantage? It’s not access to the technologies. The true competitive advantage now for any company is the people and how they consume and use the technology to solve a problem. Before [the IT advantage] was reserved for those who had access to the technology. That’s gone away. We now have a level playing field. Anybody with a credit card can spin up a big data solution today – anybody. And that’s amazing, that’s truly amazing.
For an organization that had always fallen back on their big iron or infrastructure -- those processes they had as their competitive advantage -- that now has become a detriment. That’s now the thing that’s slowing them down. It’s the anchor holding them back, and the processes around it. That rigidity of people and process locks them into doing the same thing over and over again. It is a serious obstacle.
Untangle spaghetti systems
Another major issue came very much as a surprise, Dana. We observed it over the last couple of years of doing application inventory assessments for people considering shutting down data centers. They were looking at their applications, the ones holding the assets of data centers, as not competitive. And they asked, “Hey, can we shut down a data center and move a lot of it to the public cloud?”
We at CTP were hired to do what are called application assessments, economic evaluations. We determine if there is a cost validation for doing a lift-and-shift [to the public cloud]. And the number-one obstacle was inventory. The configuration management data bases (CMDBs), which hold the inventory of where all the servers are and what’s running on them for these organizations, were wholly out of date. Many of the CMDBs just didn’t give us an accurate view of it all.
When it came time to understand what applications were actually running inside the four walls of the data centers -- nobody really knew. As a matter of fact, nobody really knew what applications were talking to what applications, or how much data was being moved back and forth. They were so complex; we would be talking about hundreds, if not thousands, of applications intertwined with themselves, sharing data back and forth. And nobody inside organizations understood which applications were connected to which, how many there were, which ones were important, and how they worked.
When it came time to understand what applications were actually running inside of the four walls of the data centers -- no one really knew. Nobody knew what applications were talking to what applications, or how much data was being moved back and forth.
Years of managing that world has created such a spaghetti mess behind those walls that it’s been exceptionally difficult for organizations to get their hands around what can be moved and what can’t. There is great integration within the systems.
The third part of this trifecta of obstacles to moving to the cloud is, as we mentioned, people not wanting to change their behaviors. They are locked in to the day-to-day motion of maintaining those systems and are not really motivated to go beyond that.
Gardner: I can see why they would find lots of reasons to push off to another day, rather than get into solving that spaghetti maze of existing data centers. That’s hard work, it’s very difficult to synthesize that all into new apps and services.
Christiansen: It was hard enough just virtualizing these systems, never mind trying to pull it all apart.
Gardner: Virtualizing didn’t solve the larger problem, it just paved the cow paths, gained some efficiency, reduced poor server utilization -- but you still have that spaghetti, you still have those processes that can’t be lifted out. And if you can’t do that, then you are stuck.
Christiansen: Exactly right.
Gardner: Companies for many years have faced other issues of entrenchment and incumbency, which can have many downsides. Many of them have said, “Okay, we are going to create a Skunk Works, a new division within the company, and create a seed organization to reinvent ourselves.” And maybe they begin subsuming other elements of the older company along the way.
Is that what the cloud and public cloud utilization within IT is doing? Why wouldn’t that proof of concept (POC) and Skunk Works approach eventually overcome the digital transformation inertia?
Clandestine cloud strategists
Christiansen: That’s a great question, and I immediately thought of a client who we helped. They have a separate team that re-wrote or rebuilt an application using serverless on Amazon. It’s now a fairly significant revenue generator for them, and they did it almost two and-a-half years ago.
It uses a few cloud servers, but mostly they rely on the messaging backbones and non-server-based platform-as-a-service (PaaS) layers of AWS to solve their problem. They are a consumer credit company and have a lot of customer-facing applications that they generate revenue from on this new platform.
The team behind the solution educated themselves. They were forward-thinkers and saw the changes in public cloud. They received permission from the business unit to break away from the central IT team’s standard processes, and they completely redefined the whole thing.
The team really knocked it out of the park. So, high success. They were able to hold it up and tried to extend that success back into the broader IT group. The IT group, on the other hand, felt that they wanted more of a multicloud strategy. They weren’t going to have all their eggs in Amazon. They wanted to give the business units options, of either going to Amazon, Azure, or Google. They wanted to still have a uniform plane of compute for on-premises deployments. So they brought in Red Hat’s OpenShift, and they overlaid that, and built out a [hybrid cloud] platform.
Now, the Red Hat platform, I personally had had no direct experience, but I had heard good things about it. I had heard of people who adopted it and saw benefits. This particular environment though, Dana, the business units themselves rejected it.
The core Amazon team said, “We are not doing that because we’re skilled in Amazon. We understand it, we’re using AWS CloudFormation. We are going to write code to the applications, we are going to use Lambda whenever we can.” They said, “No, we are not doing that [hybrid and multicloud platform approach].”
Other groups then said, “Hey, we’re an Azure shop, and we’re not going to be tied up around Amazon because we don’t like the Amazon brand.” And all that political stuff arose, they just use Azure, and decided to go shooting off on their own and did not use the OpenShift platform because, at the time, the tool stacks were not quite what they needed to solve their problems.
The company ended up getting a fractured view. We recommended that they go on an education path, to bring the people up to speed on what OpenShift could do for them. Unfortunately, they opted not to do that -- and they are still wrestling with this problem.
CTP and I personally believe that this was an issue of education, not technology, and not opportunity. They needed to lean in, sponsor, and train their business units. They needed to teach the app builders and the app owners on why this was good, the advantages of doing it, but they never invested the time. They built it and hoped that the users would come. And now they are dealing with the challenges of the blowback from that.
Gardner: What you’re describing, Robert, sounds an awful lot like basic human nature, particularly with people in different or large groups. So, politics, right? The conundrum is that when you have a small group of people, you can often get them on board. But there is a certain cut-off point where the groups are too large, and you lose control, you lose synergy, and there is no common philosophy. It’s Balkanization; it’s Europe in 1916.
Christiansen: Yeah, that is exactly it.
Gardner:Very difficult hurdles. These are problems that humankind has been dealing with for tens of thousands of years, if not longer. So, tribalism, politics. How does a fleet organization learn from what software development has come up with to combat some of these political issues? I’m thinking of Agile methodologies, scrums, and having short bursts, lots of communication, and horizontal rather than command-and-control structures. Those sorts of things.
Find common ground first
Christiansen: Well, you nailed it. How you get this done is the question. How do you get some kind of agility throughout the organization to make this happen? And there are successes out there, whole organizations, 4,000 or 5,000 or 6,000 people, have been able to move. And we’ve been involved with them. The best practices that we see today, Dana, are around allowing the businesses themselves to select the platforms to go deep on, to get good at.
Let’s say you have a business unit generating $300 million a year with some service. They have money, they are paying the IT bill. But they want more control, they want more the “dev” from the DevOps process.
The best practices that we see today are around allowing the businesses themselves to select the cloud platforms to go deep on, to get good at. ... They want the "dev" from the DevOps process.
They are going to provide much of that on their own, but they still need core common services from central IT team. This is the most important part. They need the core services, such as identity and access management, key management, logging and monitoring, and they need networking. There is a set of core functions that the central team must provide.
And we help those central teams to find and govern those services. Then, the business units [have cloud model choice and freedom as long as they] consume those core services -- the access and identity process, the key management services, they encrypt what they are supposed to, and they use the networking functions. They set up separation of the services appropriately, based on standards. And they use automation to keep them safe. Automation prevents them from doing silly things, like leaving unencrypted AWS S3 buckets open to the public Internet, things like that.
You now have software that does all of that automation. You can turn those tools on and then it’s like a playground, a protected playground. You say, “Hey, you can come out into this playground and do whatever you want, whether it’s on Azure or Google, or on Amazon or on-premises.”
“Here are the services, and if you adopt them in this way, then you, as the team, can go deep, you can use Application programming interface (API) calls, you can use CloudFoundation or Python or whatever happens to be the scripting language you want to build your infrastructure with.”
Then you have the ability to let those teams do what they want. If you notice, what it doesn’t do is overlay a common PaaS layer, which isolates the hyperscale public cloud provider from your work. That’s a whole other food fight, religious battle, Dana, around lock-in and that kind of conversation.
Gardner: Imposing your will on everyone else doesn’t seem to go over very well.
So what you’re describing, Robert, is a right-sizing for agility, and fostering a separate-but-equal approach. As long as you can abstract to the services level, and as long as you conform to a certain level of compliance for security and governance -- let’s see who can do it better. And let the best approach to cloud computing win, as long as your processes end up in the right governance mix.
Development power surges
Christiansen: People have preferences, right? Come on! There’s been a Linux and .NET battle since I have been in business. We all have preferences, right? So, how you go about coding your applications is really about what you like and what you don’t like. Developers are quirky people. I was a C programmer for 14 years, I get it.
The last thing you want to do is completely blow up your routines by taking development back and starting over with a whole bunch of new languages and tools. Then they’re trying to figure out how to release code, test code, and build up a continuous integration/continuous delivery pipeline that is familiar and fast.
These are really powerful personal stories that have to be addressed. You have to understand that. You have to understand that the development community now has the power -- they have the power, not the central IT teams. That shift has occurred. That power shift is monumental across the ecosystem. You have to pay attention to that.
If the people don’t feel like they have a choice, they will go around you, which is where the problems are happening.
Gardner: I think the power has always been there with the developers inside of their organizations. But now it’s blown out of the development organization and has seeped up right into the line of business units.
Christiansen: Oh, that’s a good point.
Gardner: Your business strategy needs to consider all the software development issues, and not just leave them under the covers. We’re probably saying the same thing. I just see the power of development choice expanding, but I think it’s always been there.
But that leads to the question, Robert, of what kind of leadership person can be mindful of a development culture in an organization, and also understand the line of business concerns. They must appreciate the C-suite strategies. If you are a public company, keeping Wall Street happy, and keeping the customer expectations met because those are always going up nowadays.
It seems to me we are asking an awful lot of a person or small team that sits at the middle of all of this. It seems to me that there’s an organizational and a talent management deficit, or at least something that’s unprecedented.
Christiansen: It is. It really is. And this brings us to a key piece to our conversation. And that is the talent enablement. It is now well beyond how we’ve classically looked at it.
Some really good friends of mine run learning and development organizations and they have consulting companies that do talent and organizational change, et cetera. And they are literally baffled right now at the dramatic shift in what it takes to get teams to work together.
In the more flexible-thinking communities of up-and-coming business, a lot of the folks that start businesses today are technology people. They may end up in the coffee industry or in the restaurant industry, but these folks know technology. They are not unaware of what they need to do to use technology.
So, business knowledge and technology knowledge are mixing together. They are good when they get swirled together. You can’t live with one and not have the other.
For example, a developer needs to understand the implications of economics when they write something for cloud deployment. If they build an application that does not economically work inside the constructs of the new world, that’s a bad business decision, but it’s in the hands of the developer.
It’s an interesting thing. We’ve had that need for developer-empowerment before, but then you had a whole other IT group put restrictions on them, right? They’d say, “Hey, there’s only so much hardware you get. That’s it. Make it work.” That’s not the case anymore, right?
We have created a whole new training track category called Talent Enablement that CTP and HPE have put together around the actual consumers of cloud.
At the same time, you now have an operations person involved with figuring out how to architect for the cloud, and they may think that the developers do not understand what has to come together.
As a result, we have created a whole new training track category called Talent Enablement that CTP and HPE have put together around the actual consumers of cloud.
We have found that much of an organization’s delay in rolling this out is because the people who are consuming the cloud are not ready or knowledgeable enough on how to maximize their investment in cloud. This is not for the people building up those core services that I talked about, but for the consumers of the services, the business units.
We are rolling that out later this year, a full Talent Enablement track around those new roles.
Gardner: This targets the people in that line of business, decision-making, planning, and execution role. It brings them up to speed on what cloud really means, how to consume it. They can then be in a position of bringing teams together in ways that hadn’t been possible before. Is that what you are getting at?
Christiansen: That’s exactly right. Let me give you an example. We did this for a telecommunications company about a year ago. They recognized that they were not going to be able to roll out their common core services.
The central team had built out about 12 common core services, and they knew almost immediately that the rest of the organization, the 11 other lines of business, were not ready to consume them.
They had been asking for it, but they weren’t ready to actually drive this new Ferrari that they had asked for. There were more than 5,000 people who needed to be up-skilled on how to consume the services that a team of about 100 people had put together.
Now, these are not classic technical services like AWS architecture, security frameworks, or Access control list (ACL) and Network ACL (NACL) for networking traffic, or how you connect back and backhaul, that kind of stuff. None of that.
I’m talking about how to make sure you don’t get a cloud bill that’s out of whack. How do I make sure that my team is actually developing in the right way, in a safe way? How do I make sure my team understands the services we want them to consume so that we can support it?
It was probably 10 or 12 basic use domains. The teams simply didn’t understand how to consume the services. So we helped this organization build a training program to bring up the skills of these 4,000 to 5,000 people.
Now think about that. That has to happen in every global Fortune 2000 company where you may only have a central team of a 100, and maybe 50 cloud people. But they may need to turn over the services to 1,000 people.
We have a massive, massive, training, up-skilling, and enablement process that has to happen over the next several years.
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Many of the latest technologies -- such as Internet of Things (IoT) platforms, big data analytics, and cloud computing -- are making data-driven and efficiency-focused digital transformation more powerful. But exploiting these advances to improve municipal services for cities and urban government agencies face unique obstacles. Challenges range from a lack of common data sharing frameworks, to immature governance over multi-agency projects, to the need to find investment funding amid tight public sector budgets.
The good news is that architectural framework methods, extended enterprise knowledge sharing, and common specifying and purchasing approaches have solved many similar issues in other domains.
BriefingsDirect recently sat down with a panel to explore how The Open Group is ambitiously seeking to improve the impact of smart cities initiatives by implementing what works organizationally among the most complex projects.
The panel consists of Dr. Chris Harding, Chief Executive Officer atLacibus; Dr. Pallab Saha, Chief Architect at The Open Group; Don Brancato, Chief Strategy Architect at Boeing; Don Sunderland, Deputy Commissioner, Data Management and Integration, New York City Department of IT and Telecommunications, and Dr. Anders Lisdorf, Enterprise Architect for Data Services for the City of New York. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: Chris, why are urban and regional government projects different from other complex digital transformation initiatives?
Harding: Municipal projects have both differences and similarities compared with corporate enterprise projects. The most fundamental difference is in the motivation. If you are in a commercial enterprise, your bottom line motivation is money, to make a profit and a return on investment for the shareholders. If you are in a municipality, your chief driving force should be the good of the citizens -- and money is just a means to achieving that end.
This is bound to affect the ways one approaches problems and solves problems. A lot of the underlying issues are the same as corporate enterprises face.
Bottom-up blueprint approach
Brancato: Within big companies we expect that the chief executive officer (CEO) leads from the top of a hierarchy that looks like a triangle. This CEO can do a cause-and-effect analysis by looking at instrumentation, global markets, drivers, and so on to affect strategy. And what an organization will do is then top-down.
In a city, often it’s the voters, the masses of people, who empower the leaders. And the triangle goes upside down. The flat part of the triangle is now on the top. This is where the voters are. And so it’s not simply making the city a mirror of our big corporations. We have to deliver value differently.
There are three levels to that. One is instrumentation, so installing sensors and delivering data. Second is data crunching, the ability to turn the data into meaningful information. And lastly, urban informatics that tie back to the voters, who then keep the leaders in power. We have to observe these in order to understand the smart city.
Saha: Two things make smart city projects more complex. First, typically large countries have multilevel governments. One at the federal level, another at a provincial or state level, and then city-level government, too.
This creates complexity because cities have to align to the state they belong to, and also to the national level. Digital transformation initiatives and architecture-led initiatives need to help.
Secondly, in many countries around the world, cities are typically headed by mayors who have merely ceremonial positions. They have very little authority in how the city runs, because the city may belong to a state and the state might have a chief minister or a premier, for example. And at the national level, you could have a president or a prime minster. This overall governance hierarchy needs to be factored when smart city projects are undertaken.
These two factors bring in complexity and differentiation in how smart city projects are planned and implemented.
Sunderland: I agree with everything that’s been said so far. In the particular case of New York City -- and with a lot of cities in the US -- cities are fairly autonomous. They aren’t bound to the states. They have an opportunity to go in the direction they set.
The problem is, of course, the idea of long-term planning in a political context. Corporations can choose to create multiyear plans and depend on the scale of the products they procure. But within cities, there is a forced changeover of management every few years. Sometimes it’s difficult to implement a meaningful long-term approach. So, they have to be more reactive.
Create demand to drive demand
Driving greater continuity can nonetheless come by creating ongoing demand around the services that smart cities produce. Under [former New York City mayor] Michael Bloomberg, for example, when he launched 311 and nyc.gov, he had a basic philosophy which was, you should implement change that can’t be undone.
If you do something like offer people the ability to reduce 10,000 [city access] phone numbers to three digits, that’s going to be hard to reverse. And the same thing is true if you offer a simple URL, where citizens can go to begin the process of facilitating whatever city services they need.
In like-fashion, you have to come up with a killer app with which you habituate the residents. They then drive demand for further services on the basis of it. But trying to plan delivery of services in the abstract -- without somehow having demand developed by the user base -- is pretty difficult.
By definition, cities and governments have a captive audience. They don’t have to pander to learn their demands. But whereas the private sector goes out of business if they don’t respond to the demands of their client base, that’s not the case in the public sector.
The public sector has to focus on providing products and tools that generate demand, and keep it growing in order to create the political impetus to deliver yet more demand.
Gardner: Anders, it sounds like there is a chicken and an egg here. You want a killer app that draws attention and makes more people call for services. But you have to put in the infrastructure and data frameworks to create that killer app. How does one overcome that chicken-and-egg relationship between required technical resources and highly visible applications?
Lisdorf: The biggest challenge, especially when working in governments, is you don’t have one place to go. You have several different agencies with different agendas and separate preferences for how they like their data and how they like to share it.
This is a challenge for any Enterprise Architecture (EA) because you can’t work from the top-down, you can’t specify your architecture roadmap. You have to pick the ways that it’s convenient to do a project that fit into your larger picture, and so on.
It’s very different working in an enterprise and putting all these data structures in place than in a city government, especially in New York City.
Gardner: Dr. Harding, how can we move past that chicken and egg tension? What needs to change for increasing the capability for technology to be used to its potential early in smart cities initiatives?
Framework for a common foundation
Harding: As Anders brought up, there are lots of different parts of city government responsible for implementing IT systems. They are acting independently and autonomously -- and I suspect that this is actually a problem that cities share with corporate enterprises.
Very large corporate enterprises may have central functions, but often that is small in comparison with the large divisions that it has to coordinate with. Those divisions often act with autonomy. In both cases, the challenge is that you have a set of independent governance domains -- and they need to share data. What’s needed is some kind of framework to allow data sharing to happen.
This framework has to be at two levels. It has to be at a policy level -- and that is going to vary from city to city or from enterprise to enterprise. It also has to be at a technical level. There should be a supporting technical framework that helps the enterprises, or the cities, achieve data sharing between their independent governance domains.
Gardner: Dr. Saha, do you agree that a common data framework approach is a necessary step to improve things?
Saha: Yes, definitely. Having common data standards across different agencies and having a framework to support that interoperability between agencies is a first step. But as Dr. Anders mentioned, it’s not easy to get agencies to collaborate with one another or share data. This is not a technical problem. Obviously, as Chris was saying, we need policy-level integration both vertically and horizontally across different agencies.
Some cities set up urban labs as a proof of concept. You can make assessment on how the demand and supply are aligned.
One way I have seen that work in cities is they set up urban labs. If the city architect thinks they are important for citizens, those services are launched as a proof of concept (POC) in these urban labs. You can then make an assessment on whether the demand and supply are aligned.
Obviously, it is a chicken-and-egg problem. We need to go beyond frameworks and policies to get to where citizens can try out certain services. When I use the word “services” I am looking at integrated services across different agencies or service providers.
The fundamental principle here for the citizens of the city is that there is no wrong door, he or she can approach any department or any agency of the city and get a service. The citizen, in my view, is approaching the city as a singular authority -- not a specific agency or department of the city.
Gardner: Don Brancato, if citizens in their private lives can, at an e-commerce cloud, order almost anything and have it show up in two days, there might be higher expectations for better city services.
Is that a way for us to get to improvement in smart cities, that people start calling for city and municipal services to be on par with what they can do in the private sector?
Public- and private-sector parity
Brancato: You are exactly right, Dana. That’s what’s driven the do it yourself (DIY) movement. If you use a cell phone at home, for example, you expect that you should be able to integrate that same cell phone in a secure way at work. And so that transitivity is expected. If I can go to Amazon and get a service, why can’t I go to my office or to the city and get a service?
This forms some of the tactical reasons for better using frameworks, to be able to deliver such value. A citizen is going to exercise their displeasure by their vote, or by moving to some other place, and is then no longer working or living there.
Traceability is also important. If I use some service, it’s then traceable to some city strategy, it’s traceable to some data that goes with it. So the traceability model, in its abstract form, is the idea that if I collect data it should trace back to some service. And it allows me to build a body of metrics that show continuously how services are getting better. Because data, after all, is the enablement of the city, and it proves that by demonstrating metrics that show that value.
So, in your e-commerce catalog idea, absolutely, citizens should be able to exercise the catalog. There should be data that shows its value, repeatability, and the reuse of that service for all the participants in the city.
Gardner: Don Sunderland, if citizens perceive a gap between what they can do in the private sector and public -- and if we know a common data framework is important -- why don’t we just legislate a common data framework? Why don’t we just put in place common approaches to IT?
Sunderland: There have been some fairly successful legislative actions vis-à-vis making data available and more common. The Open Data Law, which New York City passed back in 2012, is an excellent example. However, the ability to pass a law does not guarantee the ability to solve the problems to actually execute it.
In the case of the service levels you get on Amazon, that implies a uniformity not only of standards but oftentimes of [hyperscale] platform. And that just doesn’t exist [in the public sector]. In New York City, you have 100 different entities, 50 to 60 of them are agencies providing services. They have built vast legacy IT systems that don’t interoperate. It would take a massive investment to make them interoperate. You still have to have a strategy going forward.
The idea of adopting standards and frameworks is one approach. The idea is you will then grow from there. The idea of creating a law that tries to implement uniformity -- like an Amazon or Facebook can -- would be doomed to failure, because nobody could actually afford to implement it.
Since you can’t do top-down solutions -- even if you pass a law -- the other way is via bottom-up opportunities. Build standards and governance opportunistically around specific centers of interest that arise. You can identify city agencies that begin to understand that they need each other’s data to get their jobs done effectively in this new age. They can then build interconnectivity, governance, and standards from the bottom-up -- as opposed to the top-down.
Gardner: Dr. Harding, when other organizations are siloed, when we can’t force everyone into a common framework or platform, loosely coupled interoperability has come to the rescue. Usually that’s a standardized methodological approach to interoperability. So where are we in terms of gaining increased interoperability in any fashion? And is that part of what The Open Group hopes to accomplish?
Not something to legislate
Harding: It’s certainly part of what The Open Group hopes to accomplish. But Don was absolutely right. It’s not something that you can legislate. Top-down standards have not been very successful, whereas encouraging organic growth and building on opportunities have been successful.
The prime example is the Internet that we all love. It grew organically at a time when governments around the world were trying to legislate for a different technical solution; the Open Systems Interconnection (OSI) model for those that remember it. And that is a fairly common experience. They attempted to say, “Well, we know what the standard has to be. We will legislate, and everyone will do it this way.”
That often falls on its face. But to pick up on something that is demonstrably working and say, “Okay, well, let’s all do it like that,” can become a huge success, as indeed the Internet obviously has. And I hope that we can build on that in the sphere of data management.
It’s interesting that Tim Berners-Lee, who is the inventor of the World Wide Web, is now turning his attention to Solid, a personal online datastore, which may represent a solution or standardization in the data area that we need if we are going to have frameworks to help governments and cities organize.
A prime example is the Internet. It grew organically when governments were trying to legislate a solution. That often falls on its face. Better to pick up on something that is working in practice.
Gardner: Dr. Lisdorf, do you agree that the organic approach is the way to go, a thousand roof gardens, and then let the best fruit win the day?
Lisdorf: I think that is the only way to go because, as I said earlier, any top-down sort of way of controlling data initiatives in the city are bound to fail.
Gardner: Let’s look at the cost issues that impact smart cities initiatives. In the private sector, you can rely on an operating expenditure budget (OPEX) and also gain capital expenditures (CAPEX). But what is it about the funding process for governments and smart cities initiatives that can be an added challenge?
How to pay for IT?
Brancato: To echo what Dr. Harding suggested, cost and legacy will drive a funnel to our digital world and force us -- and the vendors -- into a world of interoperability and a common data approach.
Cost and legacy are what compete with transformation within the cities that we work with. What improves that is more interoperability and adoption of data standards. But Don Sunderland has some interesting thoughts on this.
Sunderland: One of the great educations you receive when you work in the public sector, after having worked in the private sector, is that the terms CAPEX and OPEX have quite different meanings in the public sector.
Governments, especially local governments, raise money through the sale of bonds. And within the local government context, CAPEX implies anything that can be funded through the sale of bonds. Usually there is specific legislation around what you are allowed to do with that bond. This is one of those places where we interact strongly with the state, which stipulates specific requirements around what that kind of money can be used for. Traditionally it was for things like building bridges, schools, and fixing highways. Technology infrastructure had been reflected in that, too.
What’s happened is that the CAPEX model has become less usable as we’ve moved to the cloud approach because capital expenditures disappear when you buy services, instead of licenses, on the data center servers that you procure and own.
This creates tension between the new cloud architectures, where most modern data architectures are moving to, and the traditional data center, server-centric licenses, which are more easily funded as capital expenditures.
The rules around CAPEX in the public sector have to evolve to embrace data as an easily identifiable asset [regardless of where it resides]. You can’t say it has no value when there are whole business models being built around the valuation of the data that’s being collected.
There is great hope for us being able to evolve. But for the time being, there is tension between creating the newer beneficial architectures and figuring out how to pay for them. And that comes down to paying for [cloud-based operating models] with bonds, which is politically volatile. What you pay for through operating expenses comes out of the taxes to the people, and that tax is extremely hard to come by and contentious.
So traditionally it’s been a lot easier to build new IT infrastructure and create new projects using capital assets rather than via ongoing expenses directly through taxes.
Gardner: If you can outsource the infrastructure and find a way to pay for it, why won’t municipalities just simply go with the cloud entirely?
Cities in the cloud, but services grounded
Saha: Across the world, many governments -- not just local governments but even state and central governments -- are moving to the cloud. But one thing we have to keep in mind is that at the city level, it is not necessary that all the services be provided by an agency of the city.
It could be a public/private partnership model where the city agency collaborates with a private party who provides part of the service or process. And therefore, the private party is funded, or allowed to raise money, in terms of only what part of service it provides.
Many cities are addressing the problem of funding by taking the ecosystem approach because many cities have realized it is not essential that all services be provided by a government entity. This is one way that cities are trying to address the constraint of limited funding.
Gardner: Dr. Lisdorf, in a city like New York, is a public cloud model a silver bullet, or is the devil in the details? Or is there a hybrid or private cloud model that should be considered?
Lisdorf: I don’t think it’s a silver bullet. It’s certainly convenient, but since this is new technology there are lot of things we need to clear up. This is a transition, and there are a lot of issues surrounding that.
One is the funding. The city still runs in a certain way, where you buy the IT infrastructure yourself. If it is to change, they must reprioritize the budgets to allow new types of funding for different initiatives. But you also have issues like the culture because it’s different working in a cloud environment. The way of thinking has to change. There is a cultural inertia in how you design and implement IT solutions that does not work in the cloud.
There is still the perception that the cloud is considered something dangerous or not safe. Another view is that the cloud is a lot safer in terms of having resilient solutions and the data is safe.
This is all a big thing to turn around. It’s not a simple silver bullet. For the foreseeable future, we will look at hybrid architectures, for sure. We will offload some use cases to the cloud, and we will gradually build on those successes to move more into the cloud.
Gardner: We’ve talked about the public sector digital transformation challenges, but let’s now look at what The Open Group brings to the table.
Dr. Saha, what can The Open Group do? Is it similar to past initiatives around TOGAFas an architectural framework? Or looking at DoDAF, in the defense sector, when they had similar problems, are there solutions there to learn from?
Smart city success strategies
Saha: At The Open Group, as part of the architecture forum, we recently set up a Government Enterprise Architecture Work Group. This working group may develop a reference architecture for smart cities. That would be essential to establish a standardization journey around smart cities.
One of the reasons smart city projects don’t succeed is because they are typically taken on as an IT initiative, which they are not. We all know that digital technology is an important element of smart cities, but it is also about bringing in policy-level intervention. It means having a framework, bringing cultural change, and enabling a change management across the whole ecosystem.
At The Open Group work group level, we would like to develop a reference architecture. At a more practical level, we would like to support that reference architecture with implementation use cases. We all agree that we are not going to look at a top-down approach; no city will have the resources or even the political will to do a top-down approach.
Given that we are looking at a bottom-up, or a middle-out, approach we need to identify use cases that are more relevant and successful for smart cities within the Government Enterprise Architecture Work Group. But this thinking will also evolve as the work group develops a reference architecture under a framework.
Gardner: Dr. Harding, how will work extend from other activities of The Open Group to smart cities initiatives?
Collective, crystal-clear standards
Harding: For many years, I was a staff member, but I left The Open Group staff at the end of last year. In terms of how The Open Group can contribute, it’s an excellent body for developing and understanding complex situations. It has participants from many vendors, as well as IT users, and from the academic side, too.
Such a mix of participants, backgrounds, and experience creates a great place to develop an understanding of what is needed and what is possible. As that understanding develops, it becomes possible to define standards. Personally, I see standardization as kind of a crystallization process in which something solid and structured appears from a liquid with no structure. I think that the key role The Open Group plays in this process is as a catalyst, and I think we can do that in this area, too.
Gardner: Don Brancato, same question; where do you see The Open Group initiatives benefitting a positive evolution for smart cities?
Brancato: Tactically, we have a data exchange model, the Open Data Element Framework that continues to grow within a number of IoT and industrial IoT patterns. That all ties together with an open platform, and into Enterprise Architecture in general, and specifically with models like DODAF, MODAF, and TOGAF.
Data catalogs provide proof of the activities of human systems, machines, and sensors to the fulfillment of their capabilities and are traceable up to the strategy.
We have a really nice collection of patterns that recognize that the data is the mechanism that ties it together. I would have a look at the open platform and the work they are doing to tie-in the service catalog, which is a collection of activities that human systems or machines need in order to fulfill their roles and capabilities.
The notion of data catalogs, which are the children of these service catalogs, provides the proof of the activities of human systems, machines, and sensors to the fulfillment of their capabilities and then are traceable up to the strategy.
I think we have a nice collection of standards and a global collection of folks who are delivering on that idea today.
Gardner: What would you like to see as a consumer, on the receiving end, if you will, of organizations like The Open Group when it comes to improving your ability to deliver smart city initiatives?
Use-case consumer value
Sunderland: I like the idea of reference architectures attached to use cases because -- for better or worse -- when folks engage around these issues -- even in large entities like New York City -- they are going to be engaging for specific needs.
Reference architectures are really great because they give you an intuitive view of how things fit. But the real meat is the use case, which is applied against the reference architecture. I like the idea of developing workgroups around a handful of reference architectures that address specific use cases. That then allows a catalog of use cases for those who facilitate solutions against those reference architectures. They can look for cases similar to ones that they are attempting to resolve. It’s a good, consumer-friendly way to provide value for the work you are doing.
Gardner: I’m sure there will be a lot more information available along those lines at www.opengroup.org.
When you improve frameworks, interoperability, and standardization of data frameworks, what success factors emerge that help propel the efforts forward? Let’s identify attractive drivers of future smart city initiatives. Let’s start with Dr. Lisdorf. What do you see as a potential use case, application, or service that could be a catalyst to drive even more smart cities activities?
Lisdorf: Right now, smart cities initiatives are out of control. They are usually done on an ad-hoc basis. One important way to get standardization enforced -- or at least considered for new implementations – is to integrate the effort as a necessary step in the established procurement and security governance processes.
Whenever new smart cities initiatives are implemented, you would run them through governance tied to the funding and the security clearance of a solution. That’s the only way we can gain some sort of control.
This approach would also push standardization toward vendors because today they don’t care about standards; they all have their own. If we included in our procurement and our security requirements that they need to comply with certain standards, they would have to build according to those standards. That would increase the overall interoperability of smart cities technologies. I think that is the only way we can begin to gain control.
Gardner: Dr. Harding, what do you see driving further improvement in smart cities undertakings?
Prioritize policy and people
Harding: The focus should be on the policy around data sharing. As I mentioned, I see two layers of a framework: A policy layer and a technical layer. The understanding of the policy layer has to come first because the technical layer supports it.
The development of policy around data sharing -- or specifically on personal data sharing because this is a hot topic. Everyone is concerned with what happens to their personal data. It’s something that cities are particularly concerned with because they hold a lot of data about their citizens.
Gardner: Dr. Saha, same question to you.
Saha: I look at it in two ways. One is for cities to adopt smart city approaches. Identify very-high-demand use cases that pertain to environmental mobility, or the economy, or health -- or whatever the priority is for that city.
Identifying such high-demand use cases is important because the impact is directly seen by the people, which is very important because the benefits of having a smarter city are something that need to be visible to the people using those services, number one.
The other part, that we have not spoken about, is we are assuming that the city already exists, and we are retrofitting it to become a smart city. There are places where countries are building entirely new cities. And these brand-new cities are perfect examples of where these technologies can be tried out. They don’t yet have the complexities of existing cities.
It becomes a very good lab, if you will, a real-life lab. It’s not a controlled lab, it’s a real-life lab where the services can be rolled out as the new city is built and developed. These are the two things I think will improve the adoption of smart city technology across the globe.
Gardner: Don Brancato, any ideas on catalysts to gain standardization and improved smart city approaches?
City smarts and safety first
Brancato: I like Dr. Harding’s idea on focusing on personal data. That’s a good way to take a group of people and build a tactical pattern, and then grow and reuse that.
In terms of the broader city, I’ve seen a number of cities successfully introduce programs that use the notion of a safe city as a subset of other smart city initiatives. This plays out well with the public. There’s a lot of reuse involved. It enables the city to reuse a lot of their capabilities and demonstrate they can deliver value to average citizens.
In order to keep cities involved and energetic, we should not lose track of the fact that people move to cities because of all of the cultural things they can be involved with. That comes from education, safety, and the commoditization of price and value benefits. Being able to deliver safety is critical. And I suggest the idea of traceability of personal data patterns has a connection to a safe city.
Traceability in the Enterprise Architecture world should be a standard artifact for assuring that the programs we have trace to citizen value and to business value. Such traceability and a model link those initiatives and strategies through to the service -- all the way down to the data, so that eventually data can be tied back to the roles.
For example, if I am an individual, data can be assigned to me. If I am in some role within the city, data can be assigned to me. The beauty of that is we automate the role of the human. It is even compounded to the notion that the capabilities are done in the city by humans, systems, machines, and sensors that are getting increasingly smarter. So all of the data can be traceable to these sensors.
Gardner: Don Sunderland, what have you seen that works, and what should we doing more of?
Sunderland: I am still fixated on the idea of creating direct demand. We can’t generate it. It’s there on many levels, but a kind of guerrilla tactic would be to tap into that demand to create location-aware applications, mobile apps, that are freely available to citizens.
The apps can use existing data rather than trying to go out and solve all the data sharing problems for a municipality. Instead, create a value-added app that feeds people location-aware information about where they are -- whether it comes from within the city or without. They can then become habituated to the idea that they can avail themselves of information and services directly, from their pocket, when they need to. You then begin adding layers of additional information as it becomes available. But creating the demand is what’s key.
When 311 was created in New York, it became apparent that it was a brand. The idea of getting all those services by just dialing those three digits was not going to go away. Everybody wanted to add their services to 311. This kind of guerrilla approach to a location-aware app made available to the citizens is a way to drive more demand for even more people.
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According to a recent Forrester Research survey of IT decision makers, two-thirds of those pursuing hybrid IT in their digital transformation quest did so without a comprehensive plan. The result? A chaotic hybrid cloud deployment model that can be costly – not only economically, but also in terms agility and governance.
What causes this haphazard cloud use, and what new tools, processes, and methods are available that help IT leaders reign in their hybrid IT sprawl?
Dana Gardner, Principal Analyst at Interarbor Solutions, discusses these issues in a recent BriefingsDirect, Voice of the Analyst hybrid IT management strategies. In this podcast, Gardner talks with Rhett Dillingham, Vice President and Senior Analyst at Moor Insights and Strategy, to get his take on multi-cloud sprawl and what can be done to contain it.
Jerry-rigged, multi-cloud management tools aren’t working
Gardner and Dillingham describe how enterprises today are using at least one public cloud and many are using multiple public clouds—in addition to their private infrastructure. Although public cloud deployment has matured over the years, the typical enterprise doesn’t have the tools needed to understand the optimal cloud mix in terms of purchase and consumption options. When you combine that challenge with determining an accurate cost model for private infrastructure, the task can become overwhelming very quickly.
The challenge is how to manage these infrastructures in terms of costs, security, and governance. Commonly available management tools only work on a cloud-by-cloud basis; a single tool that consolidates the management of all resources is hard to find. Although many organizations already have management tools for solving a variety of issues relating to heterogeneous systems, existing toolsets don’t extend to the public cloud.
The enterprise clearly needs better cloud management tools and services. These tools should encompass the entire hybrid infrastructure (aka hybrid estate) – from multiple off-premises, public clouds to numerous on-premises, private clouds. Until these tools or services are deployed, the problem of cloud sprawl will continue to grow.
What’s available now to better manage multi-cloud sprawl?
According to Dillingham, private infrastructure vendors are delivering new management capabilities, but actually managing clouds isn’t where most of them started. The rush to adopt public cloud – and the focus on agility over cost-efficiency – promoted a culture of visibility and reporting, but not governance. Therefore, many of the tools available are better at delivering visibility, instead of the management. Yet both visibility and governance are needed for enterprises to be able to get the most out of their hybrid IT infrastructure.
A number of vendors are innovating in this space. Dillingham gives the example of HPE OneSphere from Hewlett Packard Enterprise (HPE). HPE OneSphere is a multi-cloud management solution that delivers visibility and governance capabilities along with the analytics enterprises need to make better cloud decisions.
Managed services are also starting to appear—the next logical step in helping the enterprise gain better management of their multi-cloud chaos. This type of service analyzes and optimizes the enterprise’s footprint across various cloud infrastructures on the basis of agility and cost comparisons.
Managing hybrid IT with tools or services?
Gardner wonders if enterprises should think of cloud management oversight and optimization as a set of services, rather than a product or a tool. He mentions, HPE GreenLake Hybrid Cloud, a new service that delivers cloud-native operations, compliance, financial control, and more for public clouds. “Is that the way to go?” Gardner asks? “Should we think of cloud management oversight and optimization as a set of services, rather than a product or a tool? It seems to me that a set of services, with an ecosystem behind them, is pretty powerful.”
Dillingham explains that he believes in a three layer approach. The first is the multi-cloud infrastructure management tool, whether it is consumed as software or as a service. The second is the professional consultative services around the tool, which helps the enterprise take full advantage of the tool. And the third is a decision on whether you need an operational partner from a managed service provider perspective.
Dillingham explains, this is where “HPE is stepping up and saying we will handle all three of these. We will deliver your tools in various consumption models through a software-as-a-service (SaaS) delivery model with HPE OneSphere. And we will operate the services for you beyond that SaaS control portal – into your infrastructure management, across a hybrid footprint with the HPE GreenLake Hybrid Cloud offering. It is very compelling.”
Lots of moving parts. Choose carefully—with a long term view in mind.
Gardner concludes the podcast by asking Dillingham what the end user needs to consider to be successful in a cloud-first organization. With so many moving parts, what things should be top of mind?
Dillingham explains that it’s a complex process – and the enterprise needs a plan that includes many aspects. And that’s where you may want to enlist a professional services partner, to help walk you through the decision-making process. This discussion should include where you want to be in three, five, or even 10 years. The most important aspect to consider, according to Dillingham, is the goal. And this goal needs to be considered with a long term view in mind.
To listen to the complete podcast, click here. To learn more from HPE about managing your multi-cloud environment, check out this link. Read more from Rhett Dillingham on controlling hybrid cloud costs in a recent Forbes article.
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For thousands of companies, the evaluation of their cloud choices also impacts how they on can help conquer the “VMware tax” by moving beyond a traditional server virtualization legacy.
The next BriefingsDirect panel discussion focuses on improving performance and cost monitoring of various IT workloads in a multi-cloud world.
We will now explore how multi-cloud adoption is forcing cloud monitoring and cost management to work in new ways for enterprises.
Our panel of Micro Focus experts will unpack new Dimensional Research survey findings gleaned from more than 500 enterprise cloud specifiers. You will learn about their concerns, requirements and demands for improving the monitoring, management and cost control over hybrid and multi-cloud deployments.
To share more about interesting new cloud trends, we are joined by Harald Burose, Director of Product Management at Micro Focus, and he is based in Stuttgart; Ian Bromehead, Direct of Product Marketing at Micro Focus, and he is based in Grenoble, France, and Gary Brandt, Product Manager at Micro Focus, based in Sacramento. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: Let's begin with setting the stage for how cloud computing complexity is rapidly advancing to include multi-cloud computing -- and how traditional monitoring and management approaches are falling short in this new hybrid IT environment.
Enterprise IT leaders tasked with the management of apps, data, and business processes amid this new level of complexity are primarily grounded in the IT management and monitoring models from their on-premises data centers.
They are used to being able to gain agent-based data sets and generate analysis on their own, using their own IT assets that they control, that they own, and that they can impose their will over.
Yet virtually overnight, a majority of companies share infrastructure for their workloads across public clouds and on-premises systems. The ability to manage these disparate environments is often all or nothing.
The cart is in front of the horse. IT managers do not own the performance data generated from their cloud infrastructure.
In many ways, the ability to manage in a hybrid fashion has been overtaken by the actual hybrid deployment models. The cart is in front of the horse. IT managers do not own the performance data generated from their cloud infrastructure. Their management agents can’t go there. They have insights from their own systems, but far less from their clouds, and they can’t join these. They therefore have hybrid computing -- but without commensurate hybrid management and monitoring.
They can’t assure security or compliance and they cannot determine true and comparative costs -- never mind gain optimization for efficiency across the cloud computing spectrum.
Old management into the cloud
But there’s more to fixing the equation of multi-cloud complexity than extending yesterday’s management means into the cloud. IT executives today recognize that IT operations’ divisions and adjustments must be handled in a much different way.
Even with the best data assets and access and analysis, manual methods will not do for making the right performance adjustments and adequately reacting to security and compliance needs.
Automation, in synergy with big data analytics, is absolutely the key to effective and ongoing multi-cloud management and optimization.
Fortunately, just as the need for automation across hybrid IT management has become critical, the means to provide ML-enabled analysis and remediation have matured -- and at compelling prices.
Great strides have been made in big data analysis of such vast data sets as IT infrastructure logs from a variety of sources, including from across the hybrid IT continuum.
Many analysts, in addition to myself, are now envisioning how automated bots leveraging IT systems and cloud performance data can begin to deliver more value to IT operations, management, and optimization. Whether you call it BotOps, or AIOps, the idea is the same: The rapid concurrent use of multiple data sources, data collection methods and real-time top-line analytic technologies to make IT operations work the best at the least cost.
IT leaders are seeking the next generation of monitoring, management and optimizing solutions. We are now on the cusp of being able to take advantage of advanced ML to tackle the complexity of multi-cloud deployments and to keep business services safe, performant, and highly cost efficient.
We are on the cusp of being able to take advantage of ML to tackle the complexity of multi-cloud deployments and keep business services safe.
Similar in concept to self-driving cars, wouldn’t you rather have self-driving IT operations? So far, a majority of you surveyed say yes; and we are going to now learn more about that survey information.
Ian, please tell us more about the survey findings.
IT leaders respond to their needs
Ian Bromehead: Thanks, Dana. The first element of the survey that we wanted to share describes the extent to which cloud is so prevalent today.
More than 92 percent of the 500 or so executives are indicating that we are already in a world of significant multi-cloud adoption.
The lion’s share, or nearly two-thirds, of this population that we surveyed are using between two to five different cloud vendors. But more than 12 percent of respondents are using more than 10 vendors. So, the world is becoming increasingly complex. Of course, this strains a lot of the different aspects [of management].
What are people doing with those multiple cloud instances? As to be expected, people are using them to extend their IT landscape, interconnecting application logic and their own corporate data sources with the infrastructure and the apps in their cloud-based deployments -- whether they’re Infrastructure as a Service (IaaS) or Platform as a Service (PaaS). Some 88 percent of the respondents are indeed connecting their corporate logic and data sources to those cloud instances.
What’s more interesting is that a good two-thirds of the respondents are sharing data and integrating that logic across heterogeneous cloud instances, which may or may not be a surprise to you. It’s nevertheless a facet of many people’s architectures today. It’s a result of the need for agility and cost reduction, but it’s obviously creating a pretty high degree of complexity as people share data across multiple cloud instances.
The next aspect that we saw in the survey is that 96 percent of the respondents indicate that these public cloud application issues are resolved too slowly, and they are impacting the business in many cases.
Some of the business impacts range from resources tied up by collaborating with the cloud vendor to trying to solve these issues, and the extra time required to resolve issues impacting service level agreements (SLAs) and contractual agreements, and prolonged down time.
What we regularly see is that the adoption of cloud often translates into a loss in transparency of what’s deployed and the health of what’s being deployed, and how that’s capable of impacting the business. This insight is a strong bias on our investment and some of the solutions we will talk to you about. Their primary concern is on the visibility of what’s being deployed -- and what depends on the internal, on-premise as well as private and public cloud instances.
People need to see what is impacting the delivery of services as a provider, and if that’s due to issues with local or remote resources, or the connectivity between them. It’s just compounded by the fact that people are interconnecting services, as we just saw in the survey, from multiple cloud providers. Sothe weak part could be anywhere, could be anyone of those links. The ability for people to know where those issues are isnot happening fast enough for many people, with some 96 percent indicating that the issues are being resolved too slowly.
How to gain better visibility?
What are the key changes that need to be addressed when monitoring hybrid IT absent environments? People have challenges with discovery, understanding, and visualizing what has actually been deployed, and how it is impacting the end-to-end business.
They have limited access to the cloud infrastructure, and things like inadequate security monitoring or traditional monitoring agent difficulties, as well as monitoring lack of real-time metrics to be able to properly understand what’s happening.
It shows some of the real challenges that people are facing. And as the world shifts to being more dependent on the services that they consume, then traditional methods are not going to be properly adapted to the new environment. Newer solutions are needed. New ways of gaining visibility – and the measuring availability and performance are going to be needed.
I think what’s interesting in this part of the survey is the indication that the cloud vendors themselves are not providing this visibility. They are not providing enough information for people to be able to properly understand how service delivery might be impacting their own businesses. For instance, you might think that IT is actually flying blind in the clouds as it were.
The cloud vendors are not providing the visibility. They are not providing enough information for people to be able to understand service delivery impacts.
So, one of my next questions was, Across the different monitoring ideas or types, what’s needed for the hybrid IT environment? What should people be focusing on? Security infrastructure, getting better visibility, and end-user experience monitoring, service delivery monitoring and cloud costs – all had high ranking on what people believe they need to be able to monitor. Whether you are a provider or a consumer, most people end up being both. Monitoring is really key.
People say they really need to span infrastructure monitoring, metric that monitoring, and gain end-user security and compliance. But even that’s not enough because to properly govern the service delivery, you are going to have to have an eye on the costs -- the cost of what’s being deployed -- and how can you optimize the resources according to those costs. You need that analysis whether you are a consumer or the provider.
The last of our survey results shows the need for comprehensive enterprise monitoring. Now, people need things such as high-availability, automation, the ability to cover all types of data to find issues like root causes and issues, even from a predictive perspective. Clearly, here people expect scalability, they expect to be able to use a big data platform.
For consumers of cloud services, they should be measuring what they are receiving, and capable of seeing what’s impacting the service delivery. No one is really so naive as to say that infrastructure is somebody else’s problem. When it’s part of this service, equally impacting the service that you are paying for, and that you are delivering to your business users -- then you better have the means to be able to see where the weak links are. It should be the minimum to seek, but there’s still happenings to prove to your providers that they’re underperforming and renegotiate what you pay for.
Ultimately, when you are sticking such composite services together, IT needs to become more of a service broker. We should be able to govern the aspects of detecting when the service is degrading.
So when their service is more PaaS, then workers’ productivity is going to suffer and the business will expect IT to have the means to reverse that quickly.
So that, Dana, is the set of the different results that we got out of this survey.
A new need for analytics
Gardner: Thank you, Ian. We’ll now go to Gary Brandt to learn about the need for analytics and how cloud monitoring solutions can be cobbled together anew to address these challenges.
Gary Brandt: Thanks, Dana. As the survey results were outlined and as Ian described, there are many challenges and numerous types of monitoring for enterprise hybrid IT environments. With such variety and volume of data from these different types of environments that gets generated in the complex hybrid environments, humans simply can’t look at dashboards or use traditional tools and make sense of the data efficiently. Nor can they take necessary actions required in a timely manner, given the volume and the complexity of these environments.
So how do we deal with all of this? It’s where analytics, advanced analytics via ML, really brings in value. What’s needed is a set of automated capabilities such as those described in Gartner’s definition of AIOps and these include traditional and streaming data management, log and wire metrics, and document ingestion from many different types of sources in these complex hybrid environments.
Dealing with all this, trying to, when you are not quite sure where to look, when you have all this information coming in, it requires some advanced analytics and some clever artificial intelligence (AI)-driven algorithms just to make sense of it. This is what Gartner is really trying to guide the market toward and show where the industry is moving. The key capabilities that they speak about are analytics that allow for predictive capabilities and the capability to find anomalies in vast amounts of data, and then try to pinpoint where your root cause is, or at least eliminate the noise and get to focus on those areas.
We are making this Gartner report available for a limited time. What we have found also is that people don’t have the time or often the skill set to deal with activities and they focus on -- they need to focus on the business user and the target and the different issues that come up in these hybrid environments and these AIOpscapabilities that Gartner speaks about are great.
But, without the automation to drive out the activities or the response that needs to occur, it becomes a missing piece. So, we look at a survey -- some of our survey results and what our respondents said, it was clear that upward of the high-90 percent are clearly telling us that automation is considered highly critical. You need to see which event or metric trend so clearly impacts on a business service and whether that service pertains to a local, on-prem type of solution, or a remote solution in a cloud at some place.
Automation is key, and that requires a degree of that service definition, dependency mapping, which really should be automated. And to be declared more – just more easily or more importantly to be kept up to date, you don’t need complex environments, things are changing so rapidly and so quickly.
Sense and significance of all that data?
Micro Focus’ approach uses analytics to make sense of this vast amount of data that’s coming in from these hybrid environments to drive automation. The automation of discovery, monitoring, service analytics, they are really critical -- and must be applied across hybrid IT against your resources and map them to your services that you define.
Those are the vast amounts of data that we just described. They come in the form of logs and events and metrics, generated from lots of different sources in a hybrid environment across cloud and on-prem. You have to begin to use analytics as Gartner describes to make sense of that, and we do that in a variety of ways, where we use ML to learn behavior, basically of your environment, in this hybrid world.
And we need to be able to suggest what the most significant data is, what the significant information is in your messages, to really try to help find the needle in a haystack. When you are trying to solve problems, we have capabilities through analytics to provide predictive learning to operators to give them the chance to anticipate and to remediate issues before they disrupt the services in a company’s environment.
When you are trying to solve problems, we have capabilities through analytics to provide predictive learning to operators to remediate issues before they disrupt.
And then we take this further because we have the analytics capability that’s described by Gartner and others. We couple that with the ability to execute different types of automation as a means to let the operator, the operations team, have more time to spend on what’s really impacting the business and getting to the issues quicker than trying to spend time searching and sorting through that vast amount of data.
And we built this on different platforms. One of the key things that’s critical when you have this hybrid environment is to have a common way, or an efficient way, to collect information and to store information, and then use that data to provide access to different functionality in your system. And we do that in the form of microservices in this complex environment.
We like to refer to this as autonomous operations and it’spart of our OpsBridge solution, which embodies a lot of different patented capabilities around AIOps. Harald is going to speak to our OpsBridgesolution in more detail.
Operations Bridge in more detail
Gardner: Thank you, Gary. Now that we know more about what users need and consider essential, let’s explore a high-level look at where the solutions are going, how to access and assemble the data, and what new analytics platforms can do.
We’ll now hear from Harald Burose, Director of Product Management at Micro Focus.
Harald Burose: When we listen carefully to the different problems that Ian was highlighting, we actually have a lot of those problems addressed in the Operations Bridge solution that we are currently bringing to market.
All core use cases for Operations Bridge tie it to the underpinning of the Vertica big data analytics platform. We’re consolidating all the different types of data that we are getting; whether business transactions, IT infrastructure, application infrastructure, or business services data -- all of that is actually moved into a single data repository and then reduced in order to basically understand what the original root cause is.
And from there, these tools like the analytics that Gary described, not only identify the root cause, but move to remediation, to fixing the problem using automation.
This all makes it easy for the stakeholders to understand what the status is and provide the right dashboarding, reporting via the right interface to the right user across the full hybrid cloud infrastructure.
As we saw, some 88 percent of our customers are connecting their cloud infrastructure to their on-premises infrastructure. We are providing the ability to understand that connectivity through a dynamically updated model, and to show how these services are interconnecting -- independent of the technology -- whether deployed in the public cloud, a private cloud, or even in a classical, non-cloud infrastructure. They can then understand how they are connecting, and they can use the toolset to navigate through it all, a modern HTML5-based interface, to look at all the data in one place.
They are able to consolidate more than 250 different technologies and information into a single place: their log files, the events, metrics, topology -- everything together to understand the health of their infrastructure. That is the key element that we drive with the Operations Bridge.
Now, we have extended the capabilities further, specifically for the cloud. We basically took the generic capability and made it work specifically for the different cloud stacks, whether private cloud, your own stack implementations, a hyperconverged (HCI) stack, like Nutanix, or a Docker container infrastructure that you bring up on a public cloud like Azure, Amazon, or Google Cloud.
We are now automatically discovering and placing that all into the context of your business service application by using the Automated Service Modeling part of the Operations Bridge.
Now, once we actually integrate those toolsets, we tightly integrate them for native tools on Amazon or for Docker tools, for example. You can include these tools, so you can then automate processes from within our console.
Customers vote a top choice
And, best of all, we have been getting positive feedback from the cloud monitoring community, by the customers. And the feedback has helped earn us a Readers’ Choice Award by the Cloud Computing Insider in 2017, by being ahead of the competition.
This success is not just about getting the data together, using ML to understand the problem, and using our capabilities to connect these things together. At the end of the day, you need to act on the activity.
Having a full-blown orchestration compatibility within OpsBridgeprovides more than 5,000 automated workflows, so you can automate different remediation tasks -- or potentially point to future provisioning tasks that solve the problems of whatever you can imagine. You can use this to not only identify the root cause, but you can automatically kick off a workflow to address the specific problems.
If you don’t want to address a problem through the workflow, or cannot automatically address it, you still have a rich set of integrated tools to manually address a problem.
Having a full-blown orchestration capability with OpsBridge provides more than 5,000 automated workflows to automate many different remediation tasks.
Last, but not least, you need to keep your stakeholders up to date. They need to know, anywhere that they go, that the services are working. Our real-time dashboard is very open and can integrate with any type of data -- not just the operational data that we collect and manage with the Operations Bridge, but also third-party data, such as business data, video feeds, and sentiment data. This gets presented on a single visual dashboard that quickly gives the stakeholders the information: Is my business service actually running? Is it okay? Can I feel good about the business services that I am offering to my internal as well as external customer-users?
And you can have this on a network operations center (NOC) wall, on your tablet, or your phone -- wherever you’d like to have that type of dashboard. You can easily you create those dashboards using Microsoft Office toolsets, and create graphical, very appealing dashboards for your different stakeholders.
Gardner: Thank you, Harald. We are now going to go beyond just the telling, we are going to do some showing. We have heard a lot about what’s possible. But now let’s hear from an example in the field.
Multicloud monitoring in action
David Herrera: Banco Sabadell is fourth largest Spanish banking group. We had a big project to migrate several systems into the cloud and we realized that we didn’t have any kind of visibility about what was happening in the cloud.
We are working with private and public clouds and it’s quite difficult to correlate the information in events and incidents. We need to aggregate this information in just one dashboard. And for that, OpsBridgeis a perfect solution for us.
We started to develop new functionalities on OpsBridge, to customize for our needs. We had to cooperate with a project development team in order to achieve this.
The main benefit is that we have a detailed view about what is happening in the cloud. In the dashboard we are able to show availability, number of resources that we are using -- almost in real time. Also, we are able to show what the cost is in real time of every resource, and we can do even the projection of the cost of the items.
The main benefit is we have a detailed view about what is happening in the cloud. We are able to show what the cost is in real time of every resource.
[And that’s for] every single item that we have in the cloud now, even across the private and public cloud. The bank has invested a lot of money in this solution and we need to show them that it’s really a good choice in economical terms to migrate several systems to the cloud, and this tool will help us with this.
Our response time will be reduced dramatically because we are able to filter and find what is happening, andcall the right people to fix the problem quickly. The business department will understand better what we are doing because they will be able to see all the information, and also select information that we haven’t gathered. They will be more aligned with our work and we can develop and deliver better solutions because also we will understand them.
We were able to build a new monitoring system from scratch that doesn’t exist on the market. Now, we are able to aggregate a lot of detailing information from different clouds.
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The next BriefingsDirect hybrid IT management success story examines how the nonprofit research institute HudsonAlpha improves how it harnesses and leverages a spectrum of IT deployment environments.
Here to help explore the benefits of improved levels of multi-cloud visibility and process automation is Katreena Mullican, Senior Architect and Cloud Whisperer at HudsonAlpha Institute for Biotechnology in Huntsville, Alabama. The discussion is moderated by Dana Gardner, principal analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: What’s driving the need to solve hybrid IT complexity at HudsonAlpha?
Mullican: The big drivers at HudsonAlpha are the requirements for data locality and ease-of-adoption. We produce about 6 petabytes of new data every year, and that rate is increasing with every project that we do.
We support hundreds of research programs with data and trend analysis. Our infrastructure requires quickly iterating to identify the approaches that are both cost-effective and the best fit for the needs of our users.
Gardner: Do you find that having multiple types of IT platforms, environments, and architectures creates a level of complexity that’s increasingly difficult to manage?
Mullican: Gaining a competitive edge requires adopting new approaches to hybrid IT. Even carefully contained shadow IT is a great way to develop new approaches and attain breakthroughs.
Gardner: You want to give people enough leash where they can go and roam and experiment, but perhaps not so much that you don’t know where they are, what they are doing.
Mullican: Right. “Software-defined everything” is our mantra. That’s what we aim to do at HudsonAlpha for gaining rapid innovation.
Gardner: How do you gain balance from too hard-to-manage complexity, with a potential of chaos, to the point where you can harness and optimize -- yet allow for experimentation, too?
Mullican: IT is ultimately responsible for the security and the up-time of the infrastructure. So it’s important to have a good framework on which the developers and the researchers can compute. It’s about finding a balance between letting them have provisioning access to those resources versus being able to keep an eye on what they are doing. And not only from a usage perspective, but from a cost perspective, too.
Gardner: Tell us about HudsonAlpha and its fairly extreme IT requirements.
Mullican: HudsonAlpha is a nonprofit organization of entrepreneurs, scientists, and educators who apply the benefits of genomics to everyday life. We also provide IT services and support for about 40 affiliate companies on our 150-acre campus in Huntsville, Alabama.
Gardner: What about the IT requirements? How you fulfill that mandate using technology?
Mullican: We produce 6 petabytes of new data every year. We have millions of hours of compute processing time running on our infrastructure. We have hardware acceleration. We have direct connections to clouds. We have collaboration for our researchers that extends throughout the world to external organizations. We use containers, and we use multiple cloud providers.
Gardner: So you have been doing multi-cloud before there was even a word for multi-cloud?
Mullican: We are the hybrid-scale and hybrid IT organization that no one has ever heard of.
Gardner: Let’s unpack some of the hurdles you need to overcome to keep all of your scientists and researchers happy. How do you avoid lock-in? How do you keep it so that you can remain open and competitive?
Agnostic arrangements of clouds
Mullican: It’s important for us to keep our local datacenters agnostic, as well as our private and public clouds. So we strive to communicate with all of our resources through application programming interfaces (APIs), and we use open-source technologies at HudsonAlpha. We are proud of that. Yet there are a lot of possibilities for arranging all of those pieces.
There are a lot [of services] that you can combine with the right toolsets, not only in your local datacenter but also in the clouds. If you put in the effort to write the code with that in mind -- so you don’t lock into any one solution necessarily -- then you can optimize and put everything together.
Gardner: Because you are a nonprofit institute, you often seek grants. But those grants can come with unique requirements, even IT use benefits and cloud choice considerations.
Cloud cost control, granted
Mullican: Right. Researchers are applying for grants throughout the year, and now with the National Institutes of Health (NIH), when grants are awarded, they come with community cloud credits, which is an exciting idea for the researchers. It means they can immediately begin consuming resources in the cloud -- from storage to compute -- and that cost is covered by the grant.
So they are anxious to get started on that, which brings challenges to IT. We certainly don’t want to be the holdup for that innovation. We want the projects to progress as rapidly as possible. At the same time, we need to be aware of what is happening in a cloud and not lose control over usage and cost.
Gardner: Certainly HudsonAlpha is an extreme test bed for multi-cloud management, with lots of different systems, changing requirements, and the need to provide the flexibility to innovate to your clientele. When you wanted a better management capability, to gain an overview into that full hybrid IT environment, how did you come together with HPE and test what they are doing?
Variety is the spice of IT
Mullican: We’ve invested in composable infrastructure and hyperconverged infrastructure (HCI) in our datacenter, as well as blade server technology. We have a wide variety of compute, networking, and storage resources available to us.
The key is: How do we rapidly provision those resources in an automated fashion? I think the key there is not only for IT to be aware of those resources, but for developers to be as well. We have groups of developers dealing with bioinformatics at HudsonAlpha. They can benefit from all of the different types of infrastructure in our datacenter. What HPE OneSphere does is enable them to access -- through a common API -- that infrastructure. So it’s very exciting.
Gardner: What did HPE OneSphere bring to the table for you in order to be able to rationalize, visualize, and even prioritize this very large mixture of hybrid IT assets?
Mullican: We have been beta testing HPE OneSphere since October 2017, and we have tied it into our VMware ESX Server environment, as well as our Amazon Web Services (AWS) environment successfully -- and that’s at an IT level. So our next step is to give that to researchers as a single pane of glass where they can go and provision the resources themselves.
Gardner: What this might capability bring to you and your organization?
Cross-training the clouds
Mullican: We want to do more with cross-cloud. Right now we are very adept at provisioning within our datacenters, provisioning within each individual cloud. HudsonAlpha has a presence in all the major public clouds -- AWS, Google, Microsoft Azure. But the next step would be to go cross-cloud, to provision applications across them all.
For example, you might have an application that runs as a series of microservices. So you can have one microservice take advantage of your on-premises datacenter, such as for local storage. And then another piece could take advantage of object storage in the cloud. And even another piece could be in another separate public cloud.
But the key here is that our developer and researchers -- the end users of OneSphere – they don’t need to know all of the specifics of provisioning in each of those environments. That is not a level of expertise in their wheelhouse. In this new OneSphere way, all they know is that they are provisioning the application in the pipeline -- and that’s what the researchers will use. Then it’s up to us in IT to come along and keep an eye on what they are doing through the analytics that HPE OneSphere provides.
Gardner: Because OneSphere gives you the visibility to see what the end users are doing, potentially, for cost optimization and remaining competitive, you may be able to play one cloud off another. You may even be able to automate and orchestrate that.
Mullican: Right, and that will be an ongoing effort to always optimize cost -- but not at the risk of slowing the research. We want the research to happen, and to innovate as quickly as possible. We don’t want to be the holdup for that. But we definitely do need to loop back around and keep an eye on how the different clouds are being used and make decisions going forward based on the analytics.
Gardner: There may be other organizations that are going to be more cost-focused, and they will probably want to dial back to get the best deals. It’s nice that we have the flexibility to choose an algorithmic approach to business, if you will.
Mullican: Right. The research that we do at HudsonAlpha saves lives and the utmost importance is to be able to conduct that research at the fastest speed.
Gardner: HPE OneSphere seems geared toward being cloud-agnostic. They are beginning on AWS, yet they are going to be adding more clouds. And they are supporting more internal private cloud infrastructures, and using an API-driven approach to microservices and containers.
The research that we do at HudsonAlpha saves lives, and the utmost importance is to be able to conduct the research at the fastest speed.
As an early tester, and someone who has been a long-time user of HPE infrastructure, is there anything about the combination of HPE Synergy, HPE SimpliVity HCI, and HPE 3PAR intelligent storage -- in conjunction with OneSphere -- that’s given you a "whole greater than the sum of the parts" effect?
Mullican: HPE Synergy and composable infrastructure is something that is very near and dear to me. I have a lot of hours invested with HPE Synergy Image Streamer and customizing open-source applications on Image Streamer -– open-source operating systems and applications.
The ability to utilize that in the mix that I have architected natively with OneSphere -- in addition to the public clouds -- is very powerful, and I am excited to see where that goes.
Gardner: Any words of wisdom to others who may be have not yet gone down this road? What do you advise others to consider as they are seeking to better compose, automate, and optimize their infrastructure?
Get adept at DevOps
Mullican: It needs to start with IT. IT needs to take on more of a DevOps approach.
As far as putting an emphasis on automation -- and being able to provision infrastructure in the datacenter and the cloud through automated APIs -- a lot of companies probably are still slow to adopt that. They are still provisioning in older methods, and I think it’s important that they do that. But then, once your IT department is adept with DevOps, your developers can begin feeding from that and using what IT has laid down as a foundation. So it needs to start with IT.
It involves a skill set change for some of the traditional system administrators and network administrators. But now, with software-defined networking (SDN) and with automated deployments and provisioning of resources -- that’s a skill set that IT really needs to step up and master. That’s because they are going to need to set the example for the developers who are going to come along and be able to then use those same tools.
That’s the partnership that companies really need to foster -- and it’s between IT and developers. And something like HPE OneSphere is a good fit for that, because it provides a unified API.
On one hand, your IT department can be busy mastering how to communicate with their infrastructure through that tool. And at the same time, they can be refactoring applications as microservices, and that’s up to the developer teams. So both can be working on all of this at the same time.
Then when it all comes together with a service catalog of options, in the end it’s just a simple interface. That’s what we want, to provide a simple interface for the researchers. They don’t have to think about all the work that went into the infrastructure, they are just choosing the proper workflow and pipeline for future projects.
We want to provide a simple interface to the researchers. They don't have to think about all the work that went into the infrastructure.
Gardner: It also sounds, Katreena, like you are able to elevate IT to a solutions-level abstraction, and that OneSphere is an accelerant to elevating IT. At the same time, OneSphere is an accelerant to the adoption of DevOps, which means it’s also elevating the developers. So are we really finally bringing people to that higher plane of business-focus and digital transformation?
HCI advances across the globe
Mullican: Yes. HPE OneSphere is an advantage to both of those departments, which in some companies can be still quite disparate. Now at HudsonAlpha, we are DevOps in IT. It’s not a distinguished department, but in some companies that’s not the case.
And I think we have a lot of advantages because we think in terms of automation, and we think in terms of APIs from the infrastructure standpoint. And the tools that we have invested in, the types of composable and hyperconverged infrastructure, are helping accomplish that.
Gardner: I speak with a number of organizations that are global, and they have some data sovereignty concerns. I’d like to explore, before we close out, how OneSphere also might be powerful in helping to decide where data sets reside in different clouds, private and public, for various regulatory reasons.
Is there something about having that visibility into hybrid IT that extends into hybrid data environments?
Mullican: Data locality is one of our driving factors in IT, and we do have on-premises storage as well as cloud storage. There is a time and a place for both of those, and they do not always mix, but we have requirements for our data to be available worldwide for collaboration.
So, the services that HPE OneSphere makes available are designed to use the appropriate data connections, whether that would be back to your object storage on-premises, or AWS Simple Storage Service (S3), for example, in the cloud.
Gardner: Now we can think of HPE OneSphere as also elevating data scientists -- and even the people in charge of governance, risk management, and compliance (GRC) around adhering to regulations. It seems like it’s a gift that keeps giving.
Hybrid hard work pays off
Mullican: It is a good fit for hybrid IT and what we do at HudsonAlpha. It’s a natural addition to all of the preparation work that we have done in IT around automated provisioning with HPE Synergy and Image Streamer.
HPE OneSphere is a way to showcase to the end user all of the efforts that have been, and are being, done by IT. That’s why it’s a satisfying tool to implement, because, in the end, you want what you have worked on so hard to be available to the researchers and be put to use easily and quickly.
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