Posted By Dana L Gardner,
1 hour ago
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Our BriefingsDirect discussion today focuses on an essential aspect of helping businesses make the best use of cloud computing.
We're examining the role and value of cloud services brokers with an emphasis on small to medium-sized businesses (SMBs), regional businesses, and government, and looking for attaining the best results from a specialist cloud service brokerage role within these different types of organizations.
No two businesses have identical needs, and so specialized requirements need to be factored into the use of often commodity-type cloud services. An intermediary brokerage can help companies and government agencies make the best use of commodity and targeted IaaS clouds, and not fall prey to replacing an on-premises integration problem with a cloud complexity problem.
To learn more about the role and value of the specialist cloud services brokerage, we're joined by Todd Lyle, President of Duncan, LLC, a cloud services brokerage in Ohio, and Kevin Jackson, the Founder and CEO of GovCloud Network in Northern Virginia. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: How do we get regular companies to effectively start using these new cloud services?
Lyle: Through education. That’s our first step. The technology is clearly here, the three of us will agree. It's been here for quite some time now. The beauty of it is that we're able to extract bits and pieces for bundles, much like you get from your cell phone or your cable TV folks. You can pull those together through a cloud services brokerage.
So brokerage firms will go out and deal with the cloud services providers like Amazon, Rackspace, Dell, and those types of organizations. They bring the strengths of each of those organizations together and bundle them. Then, the consumer gets that on a monthly basis. It's non-CAPEX, meaning there is no capital expenditure.
You're renting these services. So you can expand and contract as necessary. To liken this to a utility environment, utility organizations that do electric and do power, you flip the switch on or turn the faucet on and off. It’s a metered service.
That's where you're going to get the largest return on your collective investment when you switch from a traditional IT environment on-premises, or even a private cloud, to the public cloud and the utility that this brings.
Gardner: Kevin you're involved more with government agencies. They've been using IT for an awfully long time. How is the adjustment to cloud models for them? Is it easier, is it better, or is it just a different type of approach, and therefore requires only adjustment?
Jackson: Thank you for bringing that up. Yes, I've been focused on providing advanced IT to the federal market and Fortune 500 businesses for quite a while. The advent of cloud computing and cloud services brokerages is a double-edged sword. At once, it provides a much greater agility with respect to the ability to leverage information technology.
But, at the same time, it brings a much greater amount of responsibility, because cloud service providers have a broad range of capabilities. That broad range has to be matched against the range of requirements within an enterprise, and that drives a change in the management style of IT professionals.
You're going more from your implementation skills to a management of IT skills. This is a great transition across IT, and is something that cloud services brokerages can really aid. [See Jackson's recent blog on brokerages.]
Gardner: Todd, it sounds as if we're moving this from an implementation and a technology skill set into more of a procurement, governance, contracts, and creating the right service-level agreements (SLAs). These are, I think, new skills for many businesses. How is that coaching aspect of a cloud service’s brokerage coming out in the market? Is that something you are seeing a lot of demand for?
Lyle: It’s customer service, plain and simple. We hear about it all the time, but we also pass it off all the time. You have to be accessible. If you're a 69-year-old business owner and embracing a technology from that demographic, it’s going to be different than if you are 23 years old, different in the approach that you take with that person.
As we all get more tenured, we'll see more adaptability to new technologies in a workplace, but that’s a while out. That's the 35-and-younger crowd. If you go to 35-and-above, it's what Kevin mentioned -- changing the culture, changing the way things are procured within those cultures, and also centralizing command. That’s where the brokerage or the exchange comes into place for this. [See Lyle's video on cloud brokerages.]
Change management is a key aspect of being able to have an organization take on change as a normal aspect of their business.
Gardner: One of the things that’s interesting to me is that a lot of companies are now looking at this as not just as a way of switching from one type of IT, say a server under a desk, to another type of IT, a server in a cloud.
It’s forcing companies to reevaluate how they do business and think of themselves as a new process-management function, regardless of where the services reside. This also requires more than just how to write a contract. It's really how to do business transformation.
Does that play into the cloud services brokerage? Do you find yourselves coaching companies on business management?
Jackson: Absolutely. One of the things cloud services is bringing to the forefront is the rapidity of change. We're going from an environment where organizations expect a homogenous IT platform to where hybrid IT is really the norm. Change management is a key aspect of being able to have an organization take on change as a normal aspect of their business.
This is also driving business models. The more effective business models today are taking advantage of the parallel and global nature of cloud computing. This requires experience, and cloud services brokerages have the experience of dealing with different providers, different technologies, and different business models. This is where they provide a tremendous amount of value.
Different types of services
Gardner: Todd, this notion of being a change agent also raises the notion that we're not just talking about one type of cloud service. We're talking about software as a service (SaaS), bringing communications applications like e-mail and calendar into a web or mobile environment. We're talking about platform as a service (PaaS), if you're doing development and DevOps. We're talking about even some analytics nowadays, as people try to think about how to use big data and business intelligence (BI) in the cloud.
Tell me a bit more about why being a change agent across these different models -- and not just a cloud implementer or integrator -- raises the value of this cloud service brokerage role?
Lyle: It’s a holistic approach. I've been talking to my team lately about being the Dale Carnegie of the cloud, hence the specialist cloud services brokerage, because it really does come down to personalities.
In a book that I've recently written called Grounding the Cloud, Basics and Brokerages, I talk about the human element. That's the personalities, expectations, and abilities of your workforce, not only your present workforce but your future workforce, which we discussed just a moment ago, as far as demographics were concerned.
It's constant change. Kevin said it, using a different term, but that's the world we live in. Some schools are doing this, where they're adding this to their MBA programs. It is a common set of skills that you must have, and it's managing personalities more than you're managing technology, in my opinion.
It's about the human element, our personalities, and how to make these changes so that the companies actually can speed up.
Gardner: Tell me a bit more about this book, Todd, it’s called Grounding the Cloud. When is it available and how can people learn more about it?
Lyle: It’s available now on Amazon, and they can find out more at www.groundingthecloud.org. This is a layman’s introduction to cloud computing, and so it helps business men and women get a better understanding of the cloud -- and how they could best maximize their time and their money, as it associates to their IT needs.
Gardner: Does the book get into this concept of the specialist cloud services brokerage (SCSB), as opposed to just a general brokerage, and getting at what's the difference?
Lyle: That’s an excellent question, Dana. There are a lot of perceptions, you have one as well, of what a cloud services brokerage is. But, at the end of the day -- and we've been talking about this in the entire discussion -- it's about the human element, our personalities, and how to make these changes so that the companies actually can speed up.
We discuss it here in the "flyover country," in Ohio. We meet in the book with Cleveland State University. We meet with Allen Black Enterprises, and then even with a small landscaping company to demonstrate how the cloud is being applied from six and seven users, all the way up to 25,000 users. And we're doing it here in the Midwest, where things tend to take a couple of years to change.
Gardner: How is a cloud services brokerage different from a systems integrator? It seems there's some commonality. But you are not just a channel, or reseller, you are really as much an advocate for the user.
Lyle: A specialist cloud services brokerage is going to be more like Underwriters Laboratories (UL). It’s going to go out, fielding all the different cloud flavors that are available, pick what they feel is best, and bring it together in a bundle. Then, the SCSB works with the entity to adapt to the culture and the change that's going to have to occur and the education within their particular businesses, as opposed to a very high-level vertical, where some things are just pushed out at an enterprise level.
Jackson: I see this cloud services brokerage and specialist cloud services brokerage as the new-age system integrator, because there are additional capabilities that are offered.
For example, you need a trusted third-party to monitor and report on adherence to SLAs. The provider is not going to do that. That’s a role for your cloud services brokerage. Also you need to maintain viable options for alternative cloud-service providers. The cloud services brokerage will identify your options and give you choices, should you need the change. A specialist cloud services brokerage also helps to ensure portability of your business process and data from one cloud service provider to another.
Management of change is more than a single aspect within the organization. It’s how to adapt with constant change and make sure that your enterprise has options and doesn't get locked into a single vendor.
Lyle: It comes to the point, Kevin, of building for constant change. You're exactly right.
Learn more about Todd D. Lyle's book,
Grounding the Cloud: Basics and Brokerages,
Gardner: You raise an interesting point too, Kevin, that one shouldn’t get lulled into thinking that they can just make a move to the cloud, and it will all be done. This is going to be a constant set of moves, a journey, and you're going to want to avail yourself of the cloud services marketplace that’s emerging.
We're seeing prices driven down. We're seeing competition among commodity-level cloud services. I expect we'll see other kinds of market forces at work. You want to be agile and be able to take advantage of that in your total cost of computing.
Jackson: There's a broad range of providers in the marketplace, and that range expands daily. Similarly, there's a large range of requirements within any enterprise of any size. Brokers act as matchmakers, avoiding common mistakes, and also help the organizations, the SMBs in particular, implement best practices in their adoption of this new model.
Gardner: Also, when you have a brokerage as your advocate, they're keeping their eye on the cloud marketplace, so that you can keep your eye on your business and your vertical, too. Therefore, you're going to have somebody to tip you off when things change and they will be on the vanguard for deals. Is that something that comes up in your book, Todd, of the public service brokerage being an educated expert in a field where the business really wants to stick to its knitting?
Lyle: Absolutely. That’s the primary goal, both at a strategic level, when you're deciding what products to use -- the Rackspaces, the Microsofts, the RightSignatures, etc. -- all the way down to the tactical one of the daily operation. When I leave the company, how soon can we lock Todd out? How soon can we lock him down or lock him out? It becomes a security issue at a very granular level. Because it's metered, you turn it off, you turn Todd off, you save his data, and put it someplace else.
That’s a role that, requires command and control and oversight, and that's a responsibility. You're part butler. You're looking out for the day-to-day, the minute issues. Then you get up to a very high level. You're like UL. You're keeping an eye on everything that’s occurring. UL comes to mind because they do things that are tactile and those things that you can't touch, and definitely the cloud is something you can’t touch.
Jackson: Actually, I believe it represents the embracing of a cooperative model of my consumers of this information technology, but embracing with open eyes. This is particularly of interest within the federal marketplace, because federal procurement executives have to stop their adversarial attitude toward industry. Cloud services brokerages and specialist cloud services brokerages sit at the same the table with these consumers.
This is particularly of interest within the federal marketplace, because federal procurement executives have to stop their adversarial attitude towards industry.
Lyle: Kevin, your point is very well taken. I'll go one step further. We were talking up and down the scales, strategic down to the daily operations. One of the challenges that we have to overcome is the signatories, the senior executives, that make these decisions. They're in a different age group and they're used to doing things a certain way.
That being said, getting legislation to be changed at the federal level, directives being pushed down, will make the difference, because they do know how to take orders. I know I'm speaking frankly, but what's going to have to occur for us to see some significant change within the next five years is being told how the procurement process is going to happen.
You're taking the feather; I'm taking the stick, but it’s going to take both of those to accomplish that task at the federal level.
Gardner: We know that Duncan, LLC is a specialized cloud services brokerage. Kevin, tell us a little bit about the GovCloud Network. What is your organization, and how do you align with cloud brokerages?
Jackson: GovCloud Network is a specialty consultancy that helps organizations modify or change their mission and business processes in order to take advantage of this new style of system integrator.
Earlier, I said that the key to transition in a cloud is adopting and adapting to the parallel nature and a global nature of cloud computing. This requires a second look at your existing business processes and your existing mission processes to do things in different ways. That's what GovCloud Network allows. It helps you redesign your business and mission processes for this constant change and this new model.
Notion of governance
Gardner: I'd like to go back to this notion of governance. It seems to me, Todd, that when you have different parts of your company procuring cloud services, sometimes this is referred to as shadow IT. They're not doing it in concert, through a gatekeeper like a cloud broker. Not only is there a potential redundancy of efforts in labor and work in process, but there is this governance and security risk, because one hand doesn’t know what the other hand is doing.
Let's address this issue about better security from better governance by having a common brokerage gatekeeper, rather than having different aspects of your company out buying and using cloud services independently.
Lyle: We're your trusted adviser. We’re also very much a trusted member of your team when you bring us into the fold. We provide oversight. We're big brother, if you want to look at it that way, but big brother is important when you are dealing with your business and your business resources. You don’t want to leave a window open at night. You certainly don't want to leave your network open.
There's a lot going on in today's world, a lot of transition, the NSA and everything we worry about. It's important to have somebody providing command and control. We don’t sit there and stare at a monitor all day. We use systems that watch this, but we can tell when there's an increase or decrease out of the norm of activities within your organization.
We're big brother, if you want to look at it that way, but big brother is important when you are dealing with your business and your business resources.
It really doesn't matter how big or how small, there are systems that allow us to monitor this and give a heads up. If you're part of a leadership team, you’d be notified that again Todd Lyle has left an open window. But if you don't know that Todd even has the window, then that’s even a bigger concern. That comes down to the leadership again -- how you want to manage your entity.
We all want to feel free to make decisions, but there are too many benefits available to us, transparent benefits, as Kevin put it, to using the cloud and hiding in plain sight, maximizing e-mail at 100,000 plus users. Those are all good things but they require oversight.
It's almost like an aviation model, where you have your ground control and your flight crew. Everybody on that team is providing oversight to the other. Ultimately, you have your control tower that's watching that, and the control tower, both in the air and on the ground, is your cloud services brokerage.
Jackson: It’s important to understand that cloud computing is the industrialization of information technology. You're going from an age where the IT infrastructure is a hand-designed and built work of art to where your IT infrastructure is a highly automated assembly-line platform that requires real-time monitoring and metering. Your specialist cloud services brokerage actually helps you in that transition and operations within this highly automated environment.
Gardner: Todd, we spoke earlier about how we're moving from implementation to procurement. We've also talked about governance being important, SLAs, and managing a contract across variety of different organizations that are providing cloud type services. It seems to me that we're talking about financial types of relations.
So even the Federal Government can adopt cloud services brokerage and respond in a very quick and efficient and effective manner.
How does the cloud services brokerage help the financial people in a company. Maybe it's an individual who wears many hats, but you could think of them as akin to a chief financial officer, even though that might not be their title?
What is it that we are doing with the cloud services brokerage that is of a special interest and value to the financial people? Is it unified billing or is it one throat to choke? How does that work?
Lyle: Both, and then some. Ultimately it's unified billing and unified management from daily operations. It's helping people understand that we're moving from a capitalized expense, the server, the software, things that are tactile that we are used to touching. We're used to being able to count them and we like to see our stuff.
So it's transitioning and letting go, especially for the people who watch the money. We have a fiduciary responsibility to the organizations that we work for. Part of that is communicating, educating, and helping the CFO-type person understand the transition not only from the CAPEX to the OPEX, because they get that, but also how you're going to correlate it to productivity.
It's letting them know to be patient. It's going to take a couple months for your metering to level up. We have some statistics and we can read into that. It's holding their hand, helping them out. That's a very big deal as far as that's concerned.
Gardner: Let's start to think about how to get started. Obviously, every company is different. They're going to be at a different place in terms of maturity, in their own IT, never mind the transition to cloud types of activities. Would you recommend the book as a starting point? Do you have some other materials or references? How do you help that education process get going. I'm thinking about organizations that are really at the very beginning?
Lyle: We've created a gateway cloud in our book, not to confuse the cloud story. Ultimately, we have to take in consideration our economy, the world economy today. We're still very slow to move forward.
There are some activities occurring that are forcing us to make change. Our contracts may be running out. Software like XP is no longer supported. So we may be forced into making a change. That's when it's time to engage a cloud services brokerage or a specialist cloud services brokerage.
Go out and buy the book. It's available on Amazon. It gives you a breakdown, and you can do an assessment of your organization as it currently is and it will help you map your network. Then, it will help you reach out to a cloud services brokerage, if you are so inclined, through points of interest for request for proposal or request for information.
The fun part is, it gives you a recipe using Rackspace, Jungle Disk, and gotomeeting.com, where you get to build a baby cloud. Then, you can go out and play with it.
This is written for the layperson. I've been told it’s entertaining, which is the most important part, because you’re going to read it then.
You want to begin with three points: file sharing, remote access, and email. You can be the lighthouse or you can be a dry-cleaners, but every organization needs file sharing, remote access, and email. We open-sourced this recipe or what we call the industrial bundle for small businesses.
It's not daunting. We’ve got some time yet, but I would encourage you to get a handle on where your infrastructure is today, digest that information, go out and play with the gateway cloud that we've created, and reach out to us if you are so inclined.
Learn more about Todd D. Lyle's book,
Grounding the Cloud: Basics and Brokerages,
We’d love for you to use one of our organizations, but ultimately know that there are people out there to help you. This book was written for us, not for the technical person. It is not in geek speak. This is written for the layperson. I've been told it’s entertaining, which is the most important part, because you’re going to read it then.
Jackson: I would urge SMBs to take the plunge. Cloud can be scary to some, but there is very little risk and there is much to gain for any SMB. The using, leveraging, taking advantage of the cloud gateway that Todd mentioned is a very good, low risk, and high reward path towards the cloud.
Gardner: I would agree with both of what you all said. The notion of a proof of concept and dipping your toe in. You don't have to buy it all at once, but find an area of your company where you’re going to be forced to make a change anyway and then to your point, Kevin, do it now. Take the plunge earlier rather than later.
Jackson: Before you're forced.
Gardner: Before you’re forced, but you want to look at a tactical benefit and where to work toward strategic benefit, but there is going to be some really large changes happening in what these cloud providers can do in a fairly short amount of time.
We're moving from discrete apps into the entire desktop, so a full PC experience as a service. That’s going to be very attractive to people. They're going to need to make some changes to get there. But rather than thinking about services discreetly, more and more of what they're looking for is going to be coming as the entire IT services experience, and more analytics capabilities mixed into that. So I am glad to hear you both explaining how to do it, managed at a proof-of-concept level. But I would say do it sooner rather than later.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: Duncan, LLC.
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Posted By Dana L Gardner,
Monday, September 29, 2014
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The next BriefingsDirect innovator case study interview focuses on financial services giant TIAA-CREF restructured its IT organization processes and technology to further their overall business agility.
At the recent VMworld 2014 Conference in San Francisco, our moderator, Dana Gardner, Principal Analyst at Interarbor Solutions, interviewed Kevin Murphy, Chief Technology Officer at TIAA-CREF, and Matt Santos, Senior Director of Production Services at TIAA-CREF, to learn how the New York-based large financial organization moved from virtualization to private cloud computing and on to software-defined data center (SDDC) benefits.
Here are some excerpts:
Murphy: TIAA-CREF is a very interesting company. It was founded by Andrew Carnegie. We service the academic, medical, and non-profit sector. Part of our mission is financial services for the greater good. The firm has done an amazing job sticking to that mission very carefully. We’ve obviously started to expand over the years, but it’s a unique firm, passionate about providing services to our customers.
Gardner: As we know, these days, financial services is a lot about IT. It’s about data, applications, processes, and streamlining. Tell us about where you’ve been in terms of your IT organization. Where were you five years ago and what’s different now?
Murphy: It’s a very interesting story. In 2009 to 2010, we were underfunded, under-invested, and almost a clumsy IT organization. In the last four or five years, there’s been a significant investment by the firm. There's been a lot of focus on changing our process and policies, and also providing a much higher level of service to our customers.
We haven't completed that, because that never ends, but certainly we’ve done a full infrastructure refresh. We’ve moved our development organization to agile. We’re delivering new products to our customers on an ongoing basis and we have best-in-class availability and performance. So it’s a really good story, and now we’re embarking on the next leg of the journey.
Gardner: Matt, what were some of the major challenges that you faced? I think a lot of organizations can relate to the fact that IT has had difficulty keeping up with the speed of business, but what challenges did you face in terms of making a substantial change?
Santos: I can point back to what Kevin was talking about doing the major infrastructure refresh. As part of that, we had built over a thousand virtual machines (VMs) in a very short period of time just to stand up the new infrastructure. We learned back then how quickly we could do it if we got out of our own way.
After that infrastructure refresh was over, we went back to business as usual. Deployments for development teams were taking anywhere from six to eight weeks. At that point, we started to understand that the problem was not with the technology. The problem was with a lot of the process, the people, and the way that we were structured organizationally.
As we started to look at the organization, a lot of the tools started to mature around orchestration and automation. At that point, we realized that it was time to take another look, not only at that technology, but also the way we structured the teams. We talked a lot about converging infrastructure. We’ve actually also started to look at the convergence of the people.
Gardner: Is it fair to say that the services orientation across the board, not just technically but in that larger realm of culture and organization, has been a big part of it?
Today, we have a good portion of our organization that understands, at finite details, our business functions, and it’s made us so much more effective.
Murphy: It was important for IT people to understand the business that they supported. Years back, we didn’t have that intimate business knowledge. Today, we have a good portion of our organization that understands, at finite details, our business functions, and it’s made us so much more effective.
Gardner: Given that you have a bit of a track record here, a multi-year effort showing some significant success, is it fair to say that you really had to change wholesale that IT mentality to be aligned with the business?
What I’m getting at here is a lot of organizations go at this at a crawl-walk-run level or they’re looking at individual sets of applications to try to change or modernize, or a proof of concept level approach to IT. Is there something in this that required you to do it all at once, and what are the benefits or drawbacks for doing it that way?
Murphy: I don’t think it’s a requirement. I’ll give credit to Annabelle Bexiga, our CIO, who started to drive the culture change across IT. Driving that culture change and our starting to think more and more about the way we do business has really opened up a whole new avenue for us to look at.
We have reached best in class. We're on parity. Now, we’re going to what you call that bold step, which is that we have created a program we call Project Everest. We actually have a little bit of fun with it, but we’ve created a program that is looking at fundamentally changing how we deliver services in IT, particularly in the infrastructure organization.
Gardner: Now, understanding how the technology is also evolving, we can dwell on the people and the process, of course, but the technology is still important. We’ve seen a lot of uptake in virtualization and we’ve seen a maturation toward cloud and services orientation.
Now, we’re hearing more about SDDC, software-defined networking (SDN), and software-defined storage (SDS) being more fleet and agile with these workloads. How has that dovetailed with your organizational shift as a services-oriented company?
Santos: Going back again to 2011, and some of the large refresh projects, it’s interesting how you can have the right idea, but have it at the wrong time. We started as part of that infrastructure refresh. We talked about stabilizing which was number one, when we talked about why we did what we did. There were reasons, and there were stability and availability issues that we needed to fix.
Job number one was to stabilize, but at the same time, we started playing around with automation and orchestration back then. From our vantage point, the tools weren't there. The promises were, and so we worked with a lot of different vendors outside of VMware, trying to showcase a lot those technologies, and to be quite honest, it didn’t work.
Once we started watching what our engineers were able to do in the cloud space, we realized that that’s where the future was.
At that point, we decided that we weren't able to stabilize and revolutionize at the same time and we focused on stabilization. About three or four years later, here we are again, but this time, the landscape has changed. VMware is back in the mix very largely in regards to orchestration and automation. So we started focusing on that again. Luckily, it’s a night-and-day difference in the ability to use these tools to be able to accomplish a lot.
Now, what we’re trying to understand is operationally how we hand them to somebody. Do we give them to the development teams? How do we structure our operational models so we don’t have silos?
Once we started watching what our engineers were able to do in the cloud space, we realized that that’s where the future was and we needed to be able to do that both internally and externally. Externally, there are a lot of options, but also internally. How do we structure the teams differently around the technology? It’s the biggest question that we’re struggling with right now, but hopefully we’ll make some strides.
Murphy: Also, there has been a convergence of philosophies. We have a big push now on continuous improvement. We’re marrying our continuous improving initiatives with the automation initiatives and that is what I call the Four Pillars of Everest.
By taking that view of how we do our operations and how we deliver our services, we're questioning every single facet of our organization and we’re pushing those continuous improvement methodologies. Marrying that with technology and automation to some of the tools from VMware, I think, is going to bring us to a totally different delivery model for our clients internally and our participants externally.
Gardner: We’ve mentioned a little bit about development and agile, making that aligned with operations, and streamlining the ability to outsource and take advantage of the right types of sourcing models, but you’ve also got an internal private cloud project that perhaps is a binding agent or even an accelerant to some of these larger issues around DevOps and hybrid clouds. Tell us a little bit about your private cloud initiative.
Murphy: This is one of the areas where Matt and his team and others have done an amazing job. It’s a true partnership between our organization and development as to how we deliver services. It’s a really important portion of what we’re doing.
Santos: We’ve had a lot of teams rally around the tools. One of the interesting management techniques that we’ve used during this is letting our smart people run, and they’ve done that around the tools. They’ve created what we are affectionately calling the Carnegie Compute Cloud. As Kevin stated, Andrew Carnegie was the founder of the company. So now, we’re having a little fun with the play on the past and the future.
The Carnegie Compute Cloud, if you were to log into it, is actually a picture of Andrew Carnegie wearing a Google Glass, which allows you to step into the future. But the way we look at it is that it’s a bunch of different things.
We believe that there are workloads that should be outside of the premises and we believe that there are workloads that should absolutely be within the premises.
So organizationally, yes, we can hand the keys over to development but at that point, a lot of things change. We do a lot of things differently. If you think about things like capacity management, instead of looking at it at a server-by-server level, we can look at it by a departmental level where they only have so much to provision.
Also from a standards perspective, that’s a big one. We've been trying to develop standards and enforce some with PowerPoint slides. We've found PowerPoint slides to be a very ineffective tool for enforcement.
If we give them a server-build option that can happen in a period of a couple of hours, people would choose the fast path. So we’re looking at the technology to do a lot around that as well, but then also behind the scenes, we're looking at it the same ways. How do we converge the teams around this type of technology?
Essentially, this Carnegie Compute Cloud is our central portal for everything. We have endpoint neutrality. We believe that there are workloads that should be outside of the premises and we believe that there are workloads that should absolutely be within the premises.
The Carnegie Compute Cloud is going to be the central landing spot for everything that we do, or the starting point for everything that we do with infrastructure, all the way down to how we run the business.
We're starting up new roles around product management, working with the development team, as Kevin said, making sure that the products we build are built with them, and then we’re going to monitor the products in regards to how they’re selling.
If my team is developing products and spending development hours on application suites that we are not rolling out, then we’re making a bad product. We call it the business of production services, and so we’re rallying around the Carnegie Compute Cloud.
Murphy: That’s the evolution that's happening across the industry where we’re moving from one-off engineered solutions to how do we manage the organization as an entity? That that’s one of the things that we now have the capability of doing with Carnegie Compute. VMware tools have helped a lot and I think the transition for skills and people is going to be pretty dramatic over the next few years.
Santos: It’s not about the bringing in an engineer that can do the skill. It’s bringing in an engineer who can automate the skill. There’s a lot of work being done and it’s how we’re looking at the individuals that we’re bringing in.
Gardner: I’ve spoken to a number of organizations that, when they’ve attained that scale, when they’ve attained that automation, when it becomes a fabric and they can then focus on the business process issues, they also realize some additional benefits.
A common fabric and infrastructure in a standardized approach allows them to do better data life cycle management and better disaster recovery (DR) operations. There are trade-offs and benefits for the next generation of applications, perhaps a mobile-first approach. Do you see yet, or do you forecast, the ability for you to leverage what you’ve already done in ways that are additional benefits in terms of these other IT necessities?
VMware tools have helped a lot and I think the transition for skills and people is going to be pretty dramatic over the next few years.
Murphy: We’re already starting to see some of the benefit. We’re rolling out the tools, and as Matt said, delivering to our AD partners without the lengthy requirements and documenting. It's effectively right from the menu. So it gives them total transparency and control.
Gardner: Another important aspect of IT today, of course, is to try to reduce total costs over time. Is it too soon to look at your return on investment (ROI) or your total cost of ownership (TCO)? What are some of the economic impacts?
Murphy: It is too soon at this point, but we have a very aggressive schedule for efficiencies. That’s what we’re calling it. We're going after efficiencies in our operation over the next two to three years. We have a definitive business case and we have established targets in areas that we’re going to go within the organization. What’s key is that we’ve started to see the benefit of it, and again, we’re going to continue to push this over the next two to three years.
Gardner: I don’t think we could address an IT discussion in the financial services sector without looking at risk, security, governance, compliance, and audits. What is there about what you’ve done that impacts that?
Murphy: A lot of those discussions are happening now. Matt and his team have done a great job building those bridges, and a lot of that work is happening with all of our partners. I mentioned AD but certainly, security, compliance and all the others are also in those discussions, and we are looking forward to build those bridges worldwide.
Santos: We started the conversations with them. Anytime you’re talking about automation or anytime you’re talking about moving workloads inside and outside the campus, you understand that those are going to be conversations that you’re going to have to have at some point.
Very early on, we formed that partnership with our security, compliance, and risk departments to make them part of the decision-making process, versus being somebody who provides a sign-off at the end.
We understood that that was a recipe for failure and to be honest with you, they have been very progressive and open-minded in regards to understanding the direction of the wind. They understand that this is where the world is going to and they’re going to have to figure out a way to have a secure model that goes along with it. They’ve been fabulous partners from day one, I think because they feel part of it. They were not asked to provide the risk acceptance at the end while we had to explain it to them. We started conversations with them from day one.
Obviously, one the things that’s more important to us than anything else is the protection of our participants’ data. That’s a foundational item.
Murphy: Not just in IT. We're very plugged into it, but across our firm. Obviously, one the things that’s more important to us than anything else is the protection of our participants’ data. That’s a foundational item that we have to do with all of these programs. Our firm is incredibly focused on doing that and so are we in IT. It almost comes naturally that we engage with all those other parties.
Gardner: So even while you’ve been very bold and looked at your IT organization in total in terms of trying to bring it to a modern level and more sophisticated services delivery capabilities, are there any specific milestones along the way that you can point out as examples that allowed you to sell this better at that cultural level?
Even though you go about this holistically, it’s nice to have short-term goals that you can then point to, get that buy-in, and then move forward. Any examples of an important milestone that helps you make this really part of a business transition, too?
Murphy: I’ll talk at a very high level. We’re looking at what I call the Four Pillars of Everest. It’s really going after all parts of our organization. It’s not just using VMware tools for automation. It’s also looking at how we do problem and change management, how do we do monitoring, and how do we do participant notification.
Gardner: Let’s close out on that look into tomorrow. Matt, as somebody involved with IT operations, it seems to me there’s a very exciting two, three, five years coming up.
There will be some real improvements in the quality of the technology that supports workloads, commodity hardware, price of storage going down, the ability to move workloads and be fleet across not only the DevOps divide, but across the cloud and hybrid divide. How optimistic are you about where you can take your organization, based on some of these technology trends over the next couple of years?
Role of technology
Santos: Very optimistic. It’s a great time to be in the industry, especially walking around the streets of San Francisco. You very quickly learn that technology plays a huge part in society. Within the financials arena, we have the wonderful opportunity to be leaders in this space. It’s exciting to watch.
Within our company, I always use the term "I feel like we have an athletic posture." For years, we were playing defense. We were kind of having our arms up. This has been the first time that we’ve been able to be forward looking and playing offense, if you will, versus defense.
So it’s an exciting time for us. There's a buzz in the air. We feel as if we’re delivering, and people are asking a lot of questions. Even to use it as a barometer, we’ve been having large-scale meetings, off-sites, with our development teams where the developers actually outnumber the infrastructure representatives. This was was the first time we’ve seen that much interest in the way that we deliver our platforms.
This has been the first time that we’ve been able to be forward looking and playing offense, if you will, versus defense.
We’re truly looking at the DevOps model, making sure we understand our customers’ expectations. It’s been a very, very exciting time to be at TIAA-CREF and to work with VMware.
Murphy: We had one of these meetings just recently, it talks to the passion within that room. The meeting ended and we said, "Okay, development can go. We’re going to continue on our own infrastructure." Not one person left the room. They’re that highly engaged in what we’re doing so it really is a one-IT theme and I think it’s critical to the success of going forward.
Gardner: Just to tie this back to TIAA-CREF as an organization, being involved with the financial resources that drive a retirement phase, or of course, coming into the baby-boom generation where more and more people are going to be going into retirement, these are going to be services that would be mission critical to their lives.
Murphy: Our function within IT and within the firm is mission critical. And we owe it to the firm and to our participants to do everything we can to deliver the highest level of service at the lowest cost possible, and that’s what this is all about. It’s a model we’re driving. It allows our AD partners in the firm to invest more in building new functionality for that population, and I think that that’s the reason we’re in this business.
Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: VMware.
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Posted By Dana L Gardner,
Wednesday, September 24, 2014
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The latest BriefingsDirect discussion focuses on one of the toughest balancing acts in seeking the best of cloud computing benefits. This balance comes from obtaining the proper degree of centralization or "common good" for infrastructure efficiency, while preserving a sufficient culture of decentralization for agility, innovation, and departmental-level control.
The requirement for empowering centralization is no more evident than in a large university setting, where support and consensus must be preserved among such constituencies as faculty, staff, students, and researchers -- across an expansive educational community.
But the typical IT model does not support localized agility when it takes weeks to spin up a server, if online services lack automation, or if manual processes hold back efficient ongoing IT operations. Too much IT infrastructure redundancy also means weak security, high costs, lack of agility, and slow upgrades.
We're joined by an IT executive from the University of New Mexico (UNM) to learn more about moving to a streamlined and automated private cloud model to gain a common good benefit, while maintaining a vibrant and reassured culture of innovation. We're also joined by a VMware executive to learn more about the latest ways to manage cloud architectures and processes to attain the best of cloud efficiencies, while empowering improved services delivery and process agility.
They are: Brian Pietrewicz, Director of Computing Platforms at the University of New Mexico in Albuquerque, and Kurt Milne, Director of Product Marketing in the Management Business Unit at VMware. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: Tell us about your IT organization at the university and how you've been able to do change, but at the same time not alienate your users, who are, I imagine, used to having things their way.
Pietrewicz: At the University of New Mexico, it's a highly decentralized organization. In most cases, the departments are responsible for their own IT. In most cases, that means they don't have the resources to effectively run IT, in particular, things like data centers, servers, storage, disaster recovery (DR), and backups.
What we're doing to improve the process is providing infrastructure as a service (IaaS) to those groups so that they don’t have to worry about the heavy lifting of the infrastructure pieces that I mentioned before. They can stay focused on their core mission, whether that’s physics, or psychology, or who knows what.
So we offer IaaS. We're running a VMware stack, and we're also running vCloud Automation Center (vCAC). We've deployed the Self-Service Portal. We give departments, faculty members, or departmental IT folks the ability to go into the portal and deploy their own machines at will.
Then, they are administrators of that machine. They also have additional management features through the vCAC console so that they can effectively do whatever they need to do with the server, but not have to worry about any of the underlying infrastructure.
Gardner: That sounds like the best of both worlds. In a sense, you're a service provider in the organization, getting the benefits of centralization and efficiency, but allowing them to still have a lot of hands-on control, which I assume that they want.
Pietrewicz: Correct. The other part is the agility, the ability for them to be able to react quickly, to consume infrastructure on demand as they need it, and have the benefit of all the things that virtualization brings with redundant infrastructure, lower cost of ownership, and those sorts of things.
Milne: It’s an interesting time to be in the IT space, because there's this new set of expectations being imposed on IT by the business to be strategic, to quickly adopt new technology, and boost innovation.
At the same time, IT still has the full set of responsibilities they've always had -- to stay secure, to avoid legacy debt, to drive operational excellence so they maintain uptime, security, and quality of service for transactional systems and business-critical systems.
It’s really an interesting paradox. How do you do these two things that are seemingly mutually exclusive -- go fast, but at the same time, stay in control?
Brian’s approach is what I call it "push button IT," where you give folks a button to push and they get what they need when they want it. But if IT controls the button and they control what happens when the user pushes the button, IT is able to maintain control. It’s really the best of both worlds.
Gardner: Brian, tell us a little bit about how long you have been there and what it was like before you began this journey?
Pietrewicz: I've been at UNM for about two-and-a-half years, and I can tell you the number one complaint. We suffer from a lot of the same problems that other large IT shops have, with funding and things like that. But the primary issue that we had when I walked in the door was customers being upset because we didn't have clearly-defined services, and we had sold these services to these customers.
We had sold virtual machines (VMs) with database backups, and all kinds of interesting things, with no service-level agreements (SLAs), no processes, nothing wrapped around it. The delivery of these services was completely inconsistent.
So I started out down the new path. The first thing that we did was to make the services more consistent. Just to give you an example, deploying a virtual machine for a customer. The way that it was when I got here was that a ticket came into the service desk. It went to a single technician, and then whichever technician got that ticket figured out their own way of getting that machine deployed.
At the same time, IT still has the full set of responsibilities they've always had -- to stay secure, to avoid legacy debt, to drive operational excellence.
As the next step in that process, we went through and, instead of just having it being done a different way by whoever received the ticket, we identified all the steps associated. In looking at all the steps associated, we identified over a 100 manual steps that went though six different completely separate groups inside of our organization.
Those included operating system, storage, virtualization, security, and networking for firewall changes. In all those various groups that deploy their individual piece of that puzzle, it was being done differently every time. Our deployment times were taking as long as three weeks. You can imagine how painful that is when it takes 20 minutes to spin up a VM -- but it was taking three weeks to deploy it to a customer.
We identified all the steps and defined the process very, very clearly; exactly what it takes to deploy a VM. The interesting thing that came out of that was that it gave us the content necessary to be able to start developing a true service description and an SLA.
It also made it so that it was consistent. We did a few things after we did the process development. We generated workflows within our ticketing system, so that all that happened was a ticket was put in and then it auto-generated all the necessary tickets to deploy the VM, so it happened in a very consistent way.
That dropped the deployment time from three weeks down to about three days, because it still had to go through certain approval process and things like that with security.
For the next step we said, "Okay, how can we do this better?" We looked at all of those steps that we put in place and found that they were all repetitive, manual steps that could be easily automated. So enters VMware vCAC.
We took all the steps, after we had them clearly defined, and we automated all the steps that we could. We couldn’t automate all of them, for example, sending information to our billing system to bill the customer back. From vCAC we shoot an email over to our ticketing system, that generates a ticket. Then, the billing information is still entered manually, and we are working on an upgrade to that.
UNM is approximately 45,000 faculty, staff, and students. We have about 100 either departments or affiliates, and today, we're running about 660 VMs for our organization. For central IT, we're between 98 percent and 99 percent virtualized.
When I first got here, the services were not defined and the processes were not defined. Since then, we have clearly defined the processes, narrowed those down into the very specific processes and tasks that had to be done, and then we automated. We're going through the process of automating every step in that process.
ITIL is very challenging to implement, but it's extremely helpful, because it gives you a framework to work within.
Now, we have a thing we call Lobo Cloud -- our mascot is the Lobo. Customers can now go online and deploy a machine within 20 minutes. So basically everything has transformed from extremely inconsistent service and taking as long as three weeks to deploy, to now it being the equivalent going into McDonald’s and ordering a Big Mac. It’s extremely consistent and down from three weeks to 20 minutes.
Gardner: I assume Brian that you've adopted some industry-standard methods, perhaps a framework, that gave you some guidance on this. How does your service delivery policy adhere to an industry standard like ITIL?
Pietrewicz: That’s what we use. We follow ITIL and we're at varying levels of maturity with it. ITIL is very challenging to implement, but it's extremely helpful, because it gives you a framework to work within, to start narrowing down these process, defining services, setting SLAs. It gives you a good overarching framework to work within.
The absolute hardest part of all of this is implementing the ITIL framework, identifying your processes, identifying what your service is, and identifying your SLA. Walking through all of that is exponentially harder than putting the technology in place.
Gardner: It seems to me that not only are you going to get faster servers, response times, and automation, but there are some other significant benefits to this approach. I'm thinking about security, disaster recovery (DR), the ability to budget better through an OPEX model, and then ultimately reduce total costs.
Is it too soon or have some of these other benefits that I have heard about typically when people move to a more automated cloud approach? How is that working for you?
Pietrewicz: We don’t really have good statistics on it. For the folks that had machines sitting underneath their desks and in closets before, we don’t have a lot of the statistics to know exactly the cost and the time they were spending on that.
Anybody who works with virtualization quickly learns that once you hit a certain size, it becomes significantly less expensive. You become far more agile and you get a huge number of benefits. Some of them are things that you mentioned -- the deployment time, DR, the ability to automate, the taking advantage of economies of scale.
Instead of deploying one $10,000 server per application, you're now loading up 70 machines on a $15,000 server. All of those things come into play. But we really don’t have good statistics, because we didn’t really have any good processes before we started.
What’s interesting now is that our next step in the process is to automate our billing process. Once we do that, we're going to have everything from our virtual infrastructure deployed into our billing system and either a charge-back or a show-back methodology.
The same kind of tools and processes that can automate the delivery of those services can also automate tearing down those services when they're done.
So we'll have complete detailed costs of all of our infrastructure associated with every department and every application that is using our service. We'll be able to really show the total cost of ownership (TCO).
Milne: Brian, it sounds like you're on a path that a lot of our customers are on. What we see typically is that there is a change in consumption behavior when your customers know that they can get IaaS on demand. They stop hoarding resources. The same kind of tools and processes that can automate the delivery of those services can also automate tearing down those services when they're done.
Virtualization by itself increases capacity utilization quite a bit, but then going to this kind of services delivery, service consumption for infrastructure, actually further increases utilization and drives down over-provisioning.
Adding that cost transparency to that service will further change your consumers' behavior and the ability to get it when you need it and only pay for what you use drives down the amount of resources that you have to keep in your data center.
Pietrewicz: Absolutely. It’s amazing what happens when you have to pay for something and it’s very visible.
Milne: I always feel that if IT is free that really changes the supply and demand equation, if you study economics. People don’t know what to do with free. They typically take too much.
Pietrewicz: Right. This really starts driving basic economic and social behavior into the equation in IT. It’s a difficult thing for organizations to get their head around, and they're sort of getting it here at the university. It’s not completely in place. The way that we look at it is as a, "We'll build it, and they'll come" kind of thing.
Most folks have figured out that they can really save that money. Instead of going out and buying a $10,000 server, they can buy a $1,000 VM from us that does the exact same thing. If they don’t want it any more, they can turn it off and not pay any more. All of those things come into play.
Another piece on that is the university was experimenting with a thing called reliability centered maintenance (RCM), which is a budgeting process that works toward the bottom line of a particular organization. That means that people have to be transparent and make clear decisions about where they're spending their money. That's also starting to drive adoption.
Gardner: We talked about some of the ancillary benefits of your approach, but there are some direct benefits when you go to a cloud model, which gives you more options. You can have your private cloud. You can look to public cloud and other hosting models, and then you can start to see a path or a vision towards a hybrid cloud environment, where you might actually move workloads around based on the right infrastructure approach for the right job at the right time. Any thoughts about where your clouds goals are vis-à-vis the hybrid potential?
Pietrewicz: We have a few things in play that we're actively working. Today, we have people using various cloud providers. The interesting part about that they're just paying for it with a credit card out of their department, and the university doesn’t have any clear way of knowing exactly what’s out there. We don’t really have any good security mechanisms in place for determining whether there's any sensitive data being stored out there inadvertently.
We're working with a lot of the cloud providers that we are already spending money with and we are already working with to develop consolidated accounts. One, we can save money through economies of scale. And two, we can get some visibility into what folks are actually using the cloud for. And then three, IT would like to act as an adviser to be able to point out for the various cloud providers that are out there -- this particular provider is good at functionality or this particular provider is good at security.
We envision setting up hybrid cloud services with those public cloud providers to be able to move the workloads back and forth when necessary.
The first step is to corral the use of public cloud for UNM and create an escorting process to the cloud. The second step is going to be a hybrid cloud that we'll set up from our private cloud here on site. We envision setting up hybrid cloud services with those public cloud providers to be able to move the workloads back and forth when necessary.
The other major benefit that we very much look forward to is being able to do DR in the cloud and taking advantage of the ability to replicate data and then spin up systems as you need them, rather than having a couple of million dollars in equipment sitting, waiting, and hoping you never use it. Things that you have to refresh every four years so that you have a viable DR plan.
Gardner: Is vCloud Automation Center something that will be useful in moving to this hybrid model? The one button to push, as it were, on the private cloud, will that become a one button to push in the hybrid model as well?
Pietrewicz: It will. I mentioned those various cloud service providers. Most of them are compatible with the vCloud Connector, so that you can simply just connect up that hybrid cloud service and with a little bit of work, be able to massage your portal.
We can have a menu option of public cloud providers through our portal that they could just select and say that they want to get a vCHS, Amazon, or Terremark, and then potentially move workloads back and forth. So vCAC and vCloud Connector are all at the center of it.
The other interesting piece that we're working on and going to try to figure out as part of this is that we really want to start looking into NSX and/or VIX to be able to provide very clear security boundaries, basically multi-tenancy, and then potentially be able to move those multi-tenant environments back and forth in the cloud or extend them from public to private cloud as well.
Gardner: Brian, you mentioned multi-tenancy earlier, and of course, there is a lot going on with software-defined data center, networking, and storage. What is it about it that’s interesting to you and why is this a priority for you, software-defined networking (SDN), for example?
Pietrewicz: SDN is the next sort of step in being able to truly automate your IaaS and your virtual environment. If you want to be able to dynamically deploy systems and have them be in a SAN box that is multi-tenant by customer, you really need to have an SDN-type solution, or at least that’s extremely helpful to do that.
One of the things that we are looking at next is to be able to implement something like NSX, so that we can deploy the equivalent of what’s a virtual wire, a multi-tenant environment, to individual customers, so that they can only see their stuff and can’t see their neighbors and vice versa.
The key is the ability to orchestrate that on demand and not have to deal with the legacy VLAN and firewall kind of issues that you have with the legacy environment.
Gardner: It’s interesting how a lot of these major trends -- service delivery, cloud, private cloud, DR, and SDN -- are interrelated. It’s a complex bundle, but the payoffs, when you do this inclusively, are pretty impressive.
From VMware’s perspective, that kind of network virtualization capability is critical for our hybrid cloud service.
Pietrewicz: Whenever you get to the point of abstracting things to the software level, you provide the ability to automate. When you have the ability to automate, you get tremendous flexibility. That sometimes can be an issue in and of itself, just making decisions on how you want to do something. But along with that flexibility, you get the ability to automate just about anything that you want or need to be able to do.
The second piece to that is that we're really excited about figuring out, when we build the hybrid cloud model, how we might be able to extend those tenants into the cloud, either as active running workloads or in a DR model, so that the multi-tenancy is retained.
Milne: From VMware’s perspective, that kind of network virtualization capability is critical for our hybrid cloud service. It’s that capability that NSX provides that creates that seamless experience from your data center out to the hybrid cloud.
As you said, Brian, that kind of network configuration, allocation, and reallocation of IP addresses, when you are moving things from one data center to another, is not something you want to do on a manual basis. So NSX is a key component of our hybrid cloud vision. It’s something that lot of the other cloud providers just don’t have.
Pietrewicz: I see it as the next frontier in IT. I think that when SDN starts taking off, it’s going to be a game changer in ways that we are not even recognizing yet, and that’s one example. Moving a workload from one network to another network is extremely powerful.
Gardner: Kurt, this sounds as if not only is Brian transitioning into being a service provider to his constituencies, but now he's also becoming a cloud broker. Is this typical of what you're seeing in the market as well?
Milne: It is. Some of our customers will take a step to try to get their arms around shadow IT, users going around IT, to just offer that provisioning option through the IT portal. So it’s like, "You're using Amazon? That’s fine. We can help you do that." So putting a button in the service catalog deploys the kind of work that they've been doing in a public cloud like Amazon, but it has to come through IT. Then, IT is aware of it.
There's a saying I like. It’s called the "cloud boomerang." A lot of times, the IT customers will put thing out in the public cloud, but like a boomerang, it seems to always come back. The customer wants to integrate it with an existing system or they realize that they have to support it up in the cloud. A lot of times, those rogue deployments make their way back to the IT organization. So putting an Amazon service in the vCAC portal and not changing anything else is a nice first step in corralling that.
Now, we're taking that next step and combining a lot of those capabilities into a single platform.
Pietrewicz: That is exactly what we're seeing. At a university, because there isn’t really governance, it’s more like build a good service and hope they come. We take the approach of trying to enable it. We want to make it very transparent and say that they can use Amazon or vCHS, but there's a better way to do it. If you do it through the portal, you may be able to move those workloads back and forth.
We are actually seeing exactly what you mentioned, Kurt. Folks are reaching the limitations of using some of the cloud providers, because they need to get access to data back here at UNM and are actually doing the boomerang approach. They started out there and now they're migrating their machines into our IaaS so that they can get access to the data that they need.
Gardner: Kurt, we heard some very interesting things at VMworld recently around the cloud-management platform. Why don’t you tell us a little bit about that and how that fits into what we've been discussing in terms of this ongoing maturity and evolution that a large organization like the University of New Mexico is well into?
Milne: We recently announced the vRealizeSuite, which is a cloud management platform. So we're moving our product management strategy to a common platform.
Over the years, VMware has either built or acquired quite a few different management products. We've combined those products into a number of suites, like our automation, operations, and our business management suites. Now, we're taking that next step and combining a lot of those capabilities into a single platform.
There are a couple of guiding ideas there. We see in organizations like Brian’s is that the lines between the automated provisioning of those workloads automation, provisioning those workloads, and the ongoing operations and maintenance and support of those workloads, is really starting to blur.
So you have automation tasks that might happen when you're doing a support call. Maybe you want to provision some more resources, and there are operations tasks like checking system health that you might want to do as a step in an automation routine.
Our product strategy change is to move toward a shared-services model, similar to a service-oriented architecture. The different services that are underlying our management products would be executable through a tool like vCAC, through a command line interface, or through like a REST API. There's kind of a mix-and-match opportunity to execute those services in different ways.
To build that platform with the shared service model on top, we need to start re-architecting some of our products in the back-end, so that we have a common orchestration engine, a common DR backup and a common policy engine. You don’t want one tool to undo the work that another tool did yesterday. You can’t have conflicting robots going out and doing automated tasks.
The general idea is to try to further consolidate these different management functions into a single platform. The overall goal is to try to help organizations maintain control, but then also increase flexibility and speed for their business users.
Gardner: Brian, is that something that you think is going to be on your radar? Is management so distributed now that you're looking for a more consolidated approach that’s inclusive?
The overall goal is to try to help organizations maintain control, but then also increase flexibility and speed for their business users.
Pietrewicz: That would be wonderful. We're doing things many different ways. If you take the example of orchestration, we are using Orchestrator, PowerShell, Perl, and starting to experiment with Puppet.
It would be really good if you could have one standardized way that you approach orchestration, as an example, and how that might tie into all the other pieces for back-end management, rather than handling it several different ways. As Kurt was mentioning, one part starts to step on another part. Having that be consolidated and consistent would be a huge value.
Milne: The other part of the strategy is also to make that work across environments. So the same tools and services would be available if you are provisioning up to Amazon or to your private cloud or hybrid cloud service, and even different hypervisors.
We're fully aware of the heterogeneous nature of the modern data center. So we're shifting to try to create that kind of powerful common management stack with that unified management experience across all of the environment. It’s kind of a nirvana. When we talk to people, they say that’s exactly what they want. So our vision is to kind of march towards delivering on that.
Gardner: Kurt, I am trying to recall from VMworld whether this was offered on-premises, as a service from a cloud, or some combination?
Milne: That’s the other interesting part of this. We're starting to go down the path of offering a number of our management products as a service. For example, at VMworld, we announced the availability of a beta for our vCAC product as a software as a service (SaaS), so you can without installing any software get a service portal, get that workflow and policy engine, and deploy infrastructure services across different environments.
We'll be rolling out betas for our other products in subsequent quarters over the next year or so. Then potentially we could have the SaaS services interact with and combine with the services that are available through the products that are installed on-premise. Our goal is to get these out there and then understand what the best use cases are, but that kind of mix and match is part of the vision.
Gardner: It’s interesting. We might have a reverse boomerang when it comes to the management of all of this. Does that sound appealing Brian? Is that something you would look to as a cloud service, comprehensive management?
Our goal is to get these out there and then understand what the best use cases are, but that kind of mix and match is part of the vision.
Pietrewicz: Absolutely, but it’s largely dependent on return on investment (ROI). It’s that balance of, when you get to a certain level in an IT shop, it’s sometimes cheaper to do things in-house than it is to outsource it, and sometimes not. You have to do the analysis on the ROI on what makes more sense to bring it in or to use a SaaS.
As an example, we completely outsourced all of our email, because it’s a lot of work. It's very simple and easy to do as a SaaS solution, but it’s a lot more work to do in-house. It’s definitely something that we would look into.
Milne: In a mid-sized organization that might have 300 different applications that the IT organization supports, maybe 50 of those are IT tools. Already we've seen progress with companies like ServiceNow that have a SaaS-based service desk. It makes sense to start to turn more of those management products into a SaaS delivery model.
Gardner: Brian, any thoughts about others who are starting to move in your direction, perhaps their own Lobo Cloud, their own portal rationalizing these services, being able to measure them better. What in 20/20 hindsight do you have that you could recommend for them as they go about this? Any learned lessons you could share?
Pietrewicz: The biggest lesson learned, without a doubt, is the focus on the process orientation, the ITIL model. The technology is really not that hard. It’s determining what your service is, what are you trying to deliver, and then how do you build that into a consistently delivered service, complete with SLAs and service descriptions that meet the customer needs. That's the most difficult part.
The technical folks can definitely sling the technology. That doesn’t seem to be that big of a deal. The partners and providers do a very good job of putting together products that make it happen, but the hard part is defining the processes and defining the services and making sure that they are meeting the customer needs.
Gardner: Kurt, any thoughts in reaction to what Brian said in terms of getting started on the right path around cloud rationalization of your IT organization?
Milne: One of the things that I've seen is a lot of organizations go through this process that Brian has described, trying to clearly define their services and figure out which parts of those services they're going to automate.
The hard part is defining the processes and defining the services and making sure that they are meeting the customer needs.
A lot of organizations start that service definition effort from an inside-out perspective, get a bunch of IT guys together, and try to define what you do on a daily basis in a service. That's hard.
The easier approach is just to go talk to your customers and users and ask, "If I were going to give you a button you could click to get what you need, what would you put behind the button?" Then, you define your services more from an outside-in perspective. It seems to be where companies get anyway and you just shortcut a lot of teeth gnashing and internal meetings when you do it that way.
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Posted By Dana L Gardner,
Monday, September 22, 2014
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What The Open Group refers to as Open Platform 3.0 encompasses the combined impacts of cloud, big data, mobile, and social. But to each of these now we can add a new cresting wave of complexity and scale as we consider the rapid explosion of new devices, sensors, and myriad endpoints that will be connected using internet protocols, standards and architectural frameworks.
This so-called Internet of Things means more data, more cloud connectivity and management, and an additional tier of “things” that are going to be part of the mobile edge -- and extending that mobile edge ever deeper into even our own bodies.
Yet the Internet of Things is more than the “things” – it means a higher order of software platforms. For example, if we are going to operate data centers with new dexterity thanks to software-defined networking (SDN) and storage (SDS) -- indeed the entire data center being software-defined (SDDC) -- then why not a software-defined automobile, or factory floor, or hospital operating room -- or even a software-defined city block or neighborhood?
And so how does this all actually work? Does it easily spin out of control? Or does it remain under proper management and governance? Do we have unknown unknowns about what to expect with this new level of complexity, scale, and volume of input devices?
To help answer these questions, The Open Group and BriefingsDirect recently assembled a distinguished panel at The Open Group Boston Conference 2014 to explore the practical implications and limits of the Internet of Things.
The panelist are: Said Tabet, Chief Technology Officer for Governance, Risk and Compliance Strategy at EMC, and a primary representative to the Industrial Internet Consortium; Penelope Gordon, Emerging Technology Strategist at 1Plug Corporation; Jean-Francois Barsoum, Senior Managing Consultant for Smarter Cities, Water and Transportation at IBM, and Dave Lounsbury, Chief Technical Officer at The Open Group. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: Jean-Francois, we have heard about this notion of "cities as platforms," and I think the public sector might offer us some opportunity to look at what is going to happen with the Internet of Things, and then extrapolate from that to understand what might happen in the private sector.
Hypothetically, the public sector has a lot to gain. It doesn't have to go through the same confines of a commercial market development, profit motive, and that sort of thing. Tell us a little bit about what the opportunity is in the public sector for smart cities.
Barsoum: It's immense. The first thing I want to do is link to something that Marshall Van Alstyne (Professor at Boston University and Researcher at MIT) had talked about, because I was thinking about his way of approaching platforms and thinking about how cities represent an example of that.
You don't have customers; you have citizens. Cities are starting to see themselves as platforms, as ways to communicate with their customers, their citizens, to get information from them and to communicate back to them. But the complexity with cities is that as a good a platform as they could be, they're relatively rigid. They're legislated into existence and what they're responsible for is written into law. It's not really a market.
Chris Harding (Forum Director of The Open Group Open Platform 3.0) earlier mentioned, for example, water and traffic management. Cities could benefit greatly by managing traffic a lot better.
Part of the issue is that you might have a state or provincial government that looks after highways. You might have the central part of the city that looks after arterial networks. You might have a borough that would look after residential streets, and these different platforms end up not talking to each other.
They gather their own data. They put in their own widgets to collect information that concerns them, but do not necessarily share with their neighbor. One of the conditions that Marshall said would favor the emergence of a platform had to do with how much overlap there would be in your constituents and your customers. In this case, there's perfect overlap. It's the same citizen, but they have to carry an Android and an iPhone, despite the fact it is not the best way of dealing with the situation.
The complexities are proportional to the amount of benefit you could get if you could solve them.
Gardner: More hurdles, more interoperability issues, and when you say commensurate, you're saying that the opportunity is huge, but the hurdles are huge and we're not quite sure how this is going to unfold.
Barsoum: That's right.
Gardner: Let's go to an area where the opportunity outstrips the challenge, manufacturing. Said, what is the opportunity for the software-defined factory floor for recognizing huge efficiencies and applying algorithmic benefits to how management occurs across domains of supply-chain, distribution, and logistics. It seems to me that this is a no-brainer. It's such an opportunity that the solution must be found.
Tabet: When it comes to manufacturing, the opportunities are probably much bigger. It's where we can see a lot of progress that has already been done and still work is going on. There are two ways to look at it.
One is the internal side of it, where you have improvements of business processes. For example, similar to what Jean-Francois said, in a lot of the larger companies that have factories all around the world, you'll see such improvements on a factory base level. You still have those silos at that level.
Now with this new technology, with this connectedness, those improvements are going to be made across factories, and there's a learning aspect to it in terms of trying to manage that data. In fact, they do a better job. We still have to deal with interoperability, of course, and additional issues that could be jurisdictional, etc.
However, there is that learning that allows them to improve their processes across factories. Maintenance is one of them, as well as creating new products, and connecting better with their customers. We can see a lot of examples in the marketplace. I won't mention names, but there are lots of them out there with the large manufacturers.
Gardner: We've had just-in-time manufacturing and lean processes for quite some time, trying to compress the supply chain and distribution networks, but these haven't necessarily been done through public networks, the internet, or standardized approaches.
But if we're to benefit, we're going to need to be able to be platform companies, not just product companies. How do you go from being a proprietary set of manufacturing protocols and approaches to this wider, standardized interoperability architecture?
Tabet: That's a very good question, because now we're talking about that connection to the customer. With the airline and the jet engine manufacturer, for example, when the plane lands and there has been some monitoring of the activity during the whole flight, at that moment, they'll get that data made available. There could be improvements and maybe solutions available as soon as the plane lands.
That requires interoperability. It requires Platform 3.0 for example. If you don't have open platforms, then you'll deal with the same hurdles in terms of proprietary technologies and integration in a silo-based manner.
Gardner: Penelope, you've been writing about the obstacles to decision-making that might become apparent as big data becomes more prolific and people try to capture all the data about all the processes and analyze it. That's a little bit of a departure from the way we've made decisions in organizations, public and private, in the past.
Of course, one of the bigger tenets of Internet of Things is all this great data that will be available to us from so many different points. Is there a conundrum of some sort? Is there an unknown obstacle for how we, as organizations and individuals, can deal with that data? Is this going to be chaos, or is this going to be all the promises many organizations have led us to believe around big data in the Internet of Things?
Gordon: It's something that has just been accelerated. This is not a new problem in terms of the decision-making styles not matching the inputs that are being provided into the decision-making process.
Former US President Bill Clinton was known for delaying making decisions. He's a head-type decision-maker and so he would always want more data and more data. That just gets into a never-ending loop, because as people collect data for him, there is always more data that you can collect, particularly on the quantitative side. Whereas, if it is distilled down and presented very succinctly and then balanced with the qualitative, that allows intuition to come to fore, and you can make optimal decisions in that fashion.
Conversely, if you have someone who is a heart-type or gut-type decision-maker and you present them with a lot of data, their first response is to ignore the data. It's just too much for them to take in. Then you end up completely going with whatever you feel is correct or whatever you have that instinct that it's the correct decision. If you're talking about strategic decisions, where you're making a decision that's going to influence your direction five years down the road, that could be a very wrong decision to make, a very expensive decision, and as you said, it could be chaos.
It just brings to mind to me Dr. Seuss’s The Cat in the Hat with Thing One and Thing Two. So, as we talk about the Internet of Things, we need to keep in mind that we need to have some sort of structure that we are tying this back to and understanding what are we trying to do with these things.
If you have someone who is a heart-type or gut-type decision-maker and you present them with a lot of data, their first response is to ignore the data.
Gardner: Openness is important, and governance is essential. Then, we can start moving toward higher-order business platform benefits. But, so far, our panel has been a little bit cynical. We've heard that the opportunity and the challenges are commensurate in the public sector and that in manufacturing we're moving into a whole new area of interoperability, when we think about reaching out to customers and having a boundary that is managed between internal processes and external communications.
And we've heard that an overload of data could become a very serious problem and that we might not get benefits from big data through the Internet of Things, but perhaps even stumble and have less quality of decisions.
So Dave Lounsbury of The Open Group, will the same level of standardization work? Do we need a new type of standards approach, a different type of framework, or is this a natural path and course what we have done in the past?
Lounsbury: We need to look at the problem at a different level than we institutionally think about an interoperability problem. Internet of Things is riding two very powerful waves, one of which is Moore's Law, that these sensors, actuators, and network get smaller and smaller. Now we can put Ethernet in a light switch right, a tag, or something like that.
Also, Metcalfe's Law that says that the value of all this connectivity goes up with the square of the number of connected points, and that applies to both the connection of the things but more importantly the connection of the data.
The trouble is, as we have said, that there's so much data here. The question is how do you manage it and how do you keep control over it so that you actually get business value from it. That's going to require us to have this new concept of a platform to not only to aggregate, but to just connect the data, aggregate it, correlate it as you said, and present it in ways that people can make decisions however they want.
Also, because of the raw volume, we have to start thinking about machine agency. We have to think about the system actually making the routine decisions or giving advice to the humans who are actually doing it. Those are important parts of the solution beyond just a simple "How do we connect all the stuff together?"
Gardner: We might need a higher order of intelligence, now that we have reached this border of what we can do with our conventional approaches to data, information, and process.
Thinking about where this works best first in order to then understand where it might end up later, I was intrigued again this morning by Professor Van Alstyne. He mentioned that in healthcare, we should expect major battles, that there is a turf element to this, that the organization, entity or even commercial corporation that controls and manages certain types of information and access to that information might have some very serious platform benefits.
The question is how do you manage it and how do you keep control over it so that you actually get business value from it.
The openness element now is something to look at, and I'll come back to the public sector. Is there a degree of openness that we could legislate or regulate to require enough control to prevent the next generation of lock-in, which might not be to a platform to access to data information and endpoints? Where is it in the public sector that we might look to a leadership position to establish needed openness and not just interoperability.
Barsoum: I'm not even sure where to start answering that question. To take healthcare as an example, I certainly didn't write the bible on healthcare IT systems and if someone did write that, I think they really need to publish it quickly.
We have a single-payer system in Canada, and you would think that would be relatively easy to manage. There is one entity that manages paying the doctors, and everybody gets covered the same way. Therefore, the data should be easily shared among all the players and it should be easy for you to go from your doctor, to your oncologist, to whomever, and maybe to your pharmacy, so that everybody has access to this same information.
We don't have that and we're nowhere near having that. If I look to other areas in the public sector, areas where we're beginning to solve the problem are ones where we face a crisis, and so we need to address that crisis rapidly.
Possibility of improvement
In the transportation infrastructure, we're getting to that point where the infrastructure we have just doesn't meet the needs. There's a constraint in terms of money, and we can't put much more money into the structure. Then, there are new technologies that are coming in. Chris had talked about driverless cars earlier. They're essentially throwing a wrench into the works or may be offering the possibility of improvement.
On any given piece of infrastructure, you could fit twice as many driverless cars as cars with human drivers in them. Given that set of circumstances, the governments are going to find they have no choice but to share data in order to be able to manage those. Are there cases where we could go ahead of a crisis in order to manage it? I certainly hope so.
Gardner: How about allowing some of the natural forces of marketplaces, behavior, groups, maybe even chaos theory, where if sufficient openness is maintained there will be some kind of a pattern that will emerge? We need to let this go through its paces, but if we have artificial barriers, that might be thwarted or power could go to places that we would regret later.
Barsoum: I agree. People often focus on structure. So the governance doesn't work. We should find some way to change the governance of transportation. London has done a very good job of that. They've created something called Transport for London that manages everything related to transportation. It doesn't matter if it's taxis, bicycles, pedestrians, boats, cargo trains, or whatever, they manage it.
In the transportation infrastructure, we're getting to that point where the infrastructure we have just doesn't meet the needs.
You could do that, but it requires a lot of political effort. The other way to go about doing it is saying, "I'm not going to mess with the structures. I'm just going to require you to open and share all your data." So, you're creating a new environment where the governance, the structures, don't really matter so much anymore. Everybody shares the same data.
Gardner: Said, to the private sector example of manufacturing, you still want to have a global fabric of manufacturing capabilities. This is requiring many partners to work in concert, but with a vast new amount of data and new potential for efficiency.
How do you expect that openness will emerge in the manufacturing sector? How will interoperability play when you don't have to wait for legislation, but you do need to have cooperation and openness nonetheless?
Tabet: It comes back to the question you asked Dave about standards. I'll just give you some examples. For example, in the automotive industry, there have been some activities in Europe around specific standards for communication.
The Europeans came to the US and started to have discussions, and the Japanese have interest, as well as the Chinese. That shows, because there is a common interest in creating these new models from a business standpoint, that these challenges they have to be dealt with together.
When we talk about the amounts of data, what we call now big data, and what we are going to see in about five years or so, you can't even imagine. How do we manage that complexity, which is multidimensional? We talked about this sort of platform and then further, that capability and the data that will be there. From that point of view, openness is the only way to go.
There's no way that we can stay away from it and still be able to work in silos in that new environment. There are lots of things that we take for granted today. I invite some of you to go back and read articles from 10 years ago that try to predict the future in technology in the 21st century. Look at your smart phones. Adoption is there, because the business models are there, and we can see that progress moving forward.
Collaboration is a must, because it is a multidimensional level. It's not just manufacturing like jet engines, car manufacturers, or agriculture, where you have very specific areas. They really they have to work with their customers and the customers of their customers.
Adoption is there, because the business models are there, and we can see that progress moving forward.
Gardner: Dave, I have a question for both you and Penelope. I've seen some instances where there has been a cooperative endeavor for accessing data, but then making it available as a service, whether it's an API, a data set, access to a data library, or even analytics applications set. The Ocean Observatories Initiative is one example, where it has created a sensor network across the oceans and have created data that then they make available.
Do you think we expect to see an intermediary organization level that gets between the sensors and the consumers or even controllers of the processes? Is there's a model inherent in that that we might look to -- something like that cooperative data structure that in some ways creates structure and governance, but also allows for freedom? It's sort of an entity that we don't have yet in many organizations or many ecosystems and that needs to evolve.
Lounsbury: We're already seeing that in the marketplace. If you look at the commercial and social Internet of Things area, we're starting to see intermediaries or brokers cropping up that will connect the silo of my android ecosystem to the ecosystem of package tracking or something like that. There are dozens and dozens of these cropping up.
In fact, you now see APIs even into a silo of what you might consider a proprietary system and what people are doing is to to build a layer on top of those APIs that intermediate the data.
This is happening on a point-to-point basis now, but you can easily see the path forward. That's going to expand to large amounts of data that people will share through a third party. I can see this being a whole new emerging market much as what Google did for search. You could see that happening for the Internet of Things.
Gardner: Penelope, do you have any thoughts about how that would work? Is there a mutually assured benefit that would allow people to want to participate and cooperate with that third entity? Should they have governance and rules about good practices, best practices for that intermediary organization? Any thoughts about how data can be managed in this sort of hierarchical model?
Gordon: First, I'll contradict it a little bit. To me, a lot of this is nothing new, particularly coming from a marketing strategy perspective, with business intelligence (BI). Having various types of intermediaries, who are not only collecting the data, but then doing what we call data hygiene, synthesis, and even correlation of the data has been around for a long time.
It was an interesting, when I looked at recent listing of the big-data companies, that some notable companies were excluded from that list -- companies like Nielsen. Nielsen's been collecting data for a long time. Harte-Hanks is another one that collects a tremendous amount of information and sells that to companies.
That leads into the another part of it that I think there's going to be. We're seeing an increasing amount of opportunity that involves taking public sources of data and then providing synthesis on it. What remains to be seen is how much of the output of that is going to be provided for “free”, as opposed to “fee”. We're going to see a lot more companies figuring out creative ways of extracting more value out of data and then charging directly for that, rather than using that as an indirect way of generating traffic.
Gardner: We've seen examples of how this has been in place. Does it scale and does the governance or lack of governance that might be in the market now sustain us through the transition into Platform 3.0 and the Internet of Things.
Having standards is going to increasingly become important, unless we really address a lot of the data illiteracy that we have.
Gordon: That aspect is the lead-on part of “you get what you pay for”. If you're using a free source of data, you don't have any guarantee that it is from authoritative sources of data. Often, what we're getting now is something somebody put it in a blog post, and then that will get referenced elsewhere, but there was nothing to go back to. It's the shaky supply chain for data.
You need to think about the data supply and that is where the governance comes in. Having standards is going to increasingly become important, unless we really address a lot of the data illiteracy that we have. A lot of people do not understand how to analyze data.
One aspect of that is a lot of people expect that we have to do full population surveys, as opposed representative sampling to get much more accurate and much more cost-effective collection of data. That's just one example, and we do need a lot more in governance and standards.
Gardner: What would you like to see changed most in order for the benefits and rewards of the Internet of Things to develop and overcome the drawbacks, the risks, the downside? What, in your opinion, would you like to see happen to make this a positive, rapid outcome? Let's start with you Jean-Francois.
Barsoum: There are things that I have seen cities start to do now. There are couple of examples: Philadelphia is one and Barcelona does this too. Rather than do the typical request for proposal (RFP), where they say, "This is the kind of solution we're looking for, and here are our parameters. Can l you tell us how much it is going to cost to build," they come to you with the problem and they say, "Here is the problem I want to fix. Here are my priorities, and you're at liberty to decide how best to fix the problem, but tell us how much that would cost."
If you do that and you combine it with access to the public data that is available -- if public sector opens up its data -- you end up with a very powerful combination that liberates a lot of creativity. You can create a lot of new business models. We need to see much more of that. That's where I would start.
Tabet: I agree with Jean-Francois on that. What I'd like to add is that I think we need to push the relation a little further. We need more education, to your point earlier, around the data and the capabilities.
We need these platforms that we can leverage a little bit further with the analytics, with machine learning, and with all of these capabilities that are out there. We have to also remember, when we talk about the Internet of Things, it is things talking to each other.
So it is not human-machine communication. Machine-to-machine automation will be further than that, and we need more innovation and more work in this area, particularly more activity from the governments. We've seen that, but it is a little bit frail from that point of view right now.
Gardner: Dave Lounsbury, thoughts about what need to happen in order to keep this on the tracks?
Thank you for mentioning the machine-to-machine part, because there are plenty of projections that show that it's going to be the dominant form of Internet communication, probably within the next four years.
Lounsbury: We've touched on lot of them already. Thank you for mentioning the machine-to-machine part, because there are plenty of projections that show that it's going to be the dominant form of Internet communication, probably within the next four years.
So we need to start thinking of that and moving beyond our traditional models of humans talking through interfaces to set of services. We need to identify the building blocks of capability that you need to manage, not only the information flow and the skilled person that is going to produce it, but also how you manage the machine-to-machine interactions.
Gordon: I'd like to see not so much focus on data management, but focus on what is the data managing and helping us to do. Focusing on the machine-to-machine and the devices is great, but it should be not on the devices or on the machines… it should be on what can they accomplish by communicating; what can you accomplish with the devices and then have a reverse engineer from that.
Gardner: Let's go to some questions from the audience. The first one asks about a high order of intelligence which we mentioned earlier. It could be artificial intelligence, perhaps, but they ask whether that's really the issue. Is the nature of the data substantially different, or we are just creating more of the same, so that it is a storage, plumbing, and processing problem? What, if anything, are we lacking in our current analytics capabilities that are holding us back from exploiting the Internet of Things?
Gordon: I've definitely seen that. That has a lot to do with not setting your decision objectives and your decision criteria ahead of time so that you end up collecting a whole bunch of data, and the important data gets lost in the mix. There is a term "data smog."
The solution is to figure out, before you go collecting data, what data is most important to you. If you can't collect certain kinds of data that are important to you directly, then think about how to indirectly collect that data and how to get proxies. But don't try to go and collect all the data for that. Narrow in on what is going to be most important and most representative of what you're trying to accomplish.
Gardner: Does anyone want to add to this idea of understanding what current analytics capabilities are lacking, if we have to adopt and absorb the Internet of Things?
Barsoum: There is one element around projection into the future. We've been very good at analyzing historical information to understand what's been happening in the past. We need to become better at projecting into the future, and obviously we've been doing that for some time already.
But so many variables are changing. Just to take the driverless car as an example. We've been collecting data from loop detectors, radar detectors, and even Bluetooth antennas to understand how traffic moves in the city. But we need to think harder about what that means and how we understand the city of tomorrow is going to work. That requires more thinking about the data, a little bit like what Penelope mentioned, how we interpret that, and how we push that out into the future.
Lounsbury: I have to agree with both. It's not about statistics. We can use historical data. It helps with lot of things, but one of the major issues we still deal with today is the question of semantics, the meaning of the data. This goes back to your point, Penelope, around the relevance and the context of that information – how you get what you need when you need it, so you can make the right decisions.
As soon as you talk about interoperability in the health sector, people start wondering where is their data going to go.
Gardner: Our last question from the audience goes back to Jean-Francois’s comments about the Canadian healthcare system. I imagine it applies to almost any healthcare system around the world. But it asks why interoperability is so difficult to achieve, when we have the power of the purse, that is the market. We also supposedly have the power of the legislation and regulation. You would think between one or the other or both that interoperability, because the stakes are so high, would happen. What's holding it up?
Barsoum: There are a couple of reasons. One, in the particular case of healthcare, is privacy, but that is one that you could see going elsewhere. As soon as you talk about interoperability in the health sector, people start wondering where is their data going to go and how accessible is it going to be and to whom.
You need to put a certain number of controls over top of that. What is happening in parallel is that you have people who own some data, who believe they have some power from owning that data, and that they will lose that power if they share it. That can come from doctors, hospitals, anywhere.
So there's a certain amount of change management you have to get beyond. Everybody has to focus on the welfare of the patient. They have to understand that there has to be a priority, but you also have to understand the welfare of the different stakeholders in the system and make sure that you do not forget about them, because if you forget about them they will find some way to slow you down.
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Posted By Dana L Gardner,
Wednesday, September 10, 2014
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It's only been a few years since Waste Management's IT organization began rebuilding their quality assurance processes from the ground up.
"Our availability scorecard was pretty bad. Our services were down. At times, we didn’t know that our services were down. Our first indication of a problem was from customers calling us," remembers Gautam Roy, Vice President of Infrastructure, Operations and Technical Services at Waste Management in Houston, Texas.
"Now, fast-forward a few years -- with making the appropriate choices and investments in technology, such as in people and processes -- and our scorecard is very good. We know of the problems rapidly. We proactively detect problems and fix the problems before they impact our customers," he says.
To learn how Waste Management came to deliver 4 9s availability for its critical applications, BriefingsDirect sat down with Roy at the recent HP Discover conference in Las Vegas. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Roy: Water Management is an environmental services company. We have primarily three lines of business. First is waste service. This is our traditional waste pickup, transfer, and disposal. Our second line of business is renewable energy or green energy, and our third is recycling.
What makes Waste Management different from others in the waste industry is that we also invest quite a lot of effort in next-generation waste technology. We invest in companies like Agilyx, which converts very hard-to-recycle waste, such as plastic, into crude oil. We convert organic food waste into natural gas. We pressurize, scrub, and dry municipal solid waste into solid fuel, which burns cleaner than coal.
And we're quite diverse, a global company. We have operations in the US and Canada, Asia, and Europe. We have our renewable energy plants. There is quite a large array of technology and IT to support these business processes to ensure consistent business-services availability.
Gardner: As with many organizations, gaining greater visibility into operations -- having earlier detection of problems, and therefore earlier remediation -- means better performance. What were some of the drivers for your organization specifically to mature your IT operations?
Roy: I'll give a few business reasons, and a couple of technology reasons. From the business side, we began business transformation a couple of years ago. We wanted to ensure that we unlocked the value for our customers and for us, and to institutionalize the benefits for Waste Management.
Customer care, providing outstanding, world-class customer service is aligned completely with our business strategy. Business services availability is crucial, it's in our DNA. Our IT business service availability scorecard a few years ago wasn't too good. So we had to put the focus on people, process, and technology to ensure that we provide a very consistent service set to our customers.
Gardner: Moving across the spectrum of development, test, and operations can be challenging for many organizations. You have put in place standardized processes to measure, organize, and perform better across the DevOps spectrum. Tell us how you accomplished that. How did you get there?
Roy: That's a very good question. For us, IT business-service availability is really not about having a great monitoring solution. It starts even before the services are in production. It starts with partnership with our business and business requirements. It starts with having a great development methodology and a robust testing program. It starts with architecture processes, standardization, and communication. All those things have to be in place. And you have to have security services and a monitoring solution to wrap it up.
We try to approach it from the front end, instead of chasing it from the back end.
What we are trying to do is to not fight the issue at the back-end. If a service is down, our monitoring software picks it up, our operational team and engineering team jumps on it, we are able to fix the problem ASAP before it impacts the customer. Great. But, boy, wouldn’t it be nice if those services aren't going down in the first place? So we try to approach it from the front-end, instead of just chasing it from the back-end.
Gardner: So it’s Application Lifecycle Management (ALM) and Business Service Management (BSM), not one or the other, but really both -- and simultaneously?
Roy: Exactly, ALM, BSM, testing, and security products. We also want to make sure that the services are not down from intentional disruption. We want to make sure that we produce code with quality and velocity, and code that is consistent with the experience of our customer.
With our operational processes, ITIL and Lean IT, we want to make sure that the change management and incident management are followed to our prescription. We want to make sure that the disaster-recovery (DR) program, the high-availability (HA) program, the security operation center (SOC), the network operation center (NOC), and the command centers are all working together to ensure that the services are up 24/7, 365.
Gardner: And when you do this well, when you have put in place many of the capabilities that we have been describing, do you have any sense of payback? Do you keep score?
Roy: A few years ago, when we were not as good at it, we started rebuilding this all from the ground up, and our availability scorecard was pretty bad. Our services were down. At times, we didn’t know that our services were down. Our first indication of a problem was from customers calling us.
Now, fast-forward a few years, with making the appropriate choices and investments in technology -- such as in people and processes -- and our scorecard is very good. We know of the problems rapidly. We proactively detect problems and fix the problems before they impact our customers.
We have 4 9s availability for our critical applications. We're able to provide services to our customers via wm.com, our digital channel, and it has been quite a success story. We still have work to cover, but it has been following the right trajectory.
Gardner: Here at HP Discover, are there any developments that you're monitoring closely? Are there some things that you're particularly interested in that might help you continue to close the gap on quality?
We want to provide optimal solutions at a right price point for our customers and our business.
Roy: Sure. Things like understanding what's happening in the world of big data and HP’s views and position on that. I want to understand and learn about testing, software testing, how to test faster and produce better code, and to ensure, on a continuous basis that we're reducing the cost of running the business. We want to provide optimal solutions at a right price point for our customers and our business.
Gardner: On that topic of big data, are you referring to the data generated within IT, in your systems, to be able to better analyze and react to that? Or perhaps also the data from your marketplace, things that your customers might be saying in social media, for example? Or is it all of the above?
Roy: It’s all of the above. We have internal data that we're harvesting. We want to understand what it’s telling us. And we'd like to predict certain trends of our system, across the use of our applications.
Externally, we have 18 call centers. We get user calls. We also want to know our customer better and serve them the best. So we want to move into a situation where we can take their issues, frame them into solutions, and proactively service them the best in our industry.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.
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Posted By Dana L Gardner,
Monday, September 08, 2014
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It's a shame when the data analysis providers inside a company get the cold shoulder from the business leaders because the data keeps proving the status quo wrong, or contradicts the conventional corporate wisdom.
Fortunately for GSN Games in San Francisco, there's no such culture clash there. "The real thing that's helped us get to the point we are is a culture where everybody is open to being wrong -- and open to being proven wrong by the data," says Portman Wills, Vice President of Data at GSN Games.
"One of the things we use data for is to challenge all of our assumptions about our own products and our own businesses, says Wills. "It's really gotten to a point where it's almost religious in our company. The moment two people start debating what should or shouldn't happen, they say, 'Well let's just let the data decide.' That's been a core change not just for us, but for the game industry as a whole."
How did GSN Games get to the point where the data usually wins? It took a blazing fast data warehouse of 1.3 trillion rows that consumes, stores and produces analysis from some 110 million registered game-players in near real time. The next BriefingsDirect podcast focuses on just how GSN Games exploits such big data to effectively uncover game-changing entertainment trends for their audience. Oh, and it changes corporate cultures, too.
The discussion, at the recent HP Discover conference in Barcelona, is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Wills: GSN started as a cable network in the U.S. We’re distributed in 80 million households as the Game Show Network, and then we also have a digital wing that produces casual and social games on Facebook, web, tablets, and mobile. That division has 110 million registered game-players. My team takes data from all over those worlds, throws them into a big data warehouse, and starts trying to find trends and insights for both our TV audience and our online game-players.
In terms of the games, which is really where the growth is, our core demographic is older females, believe it or not, who love playing casual games. We skew more in the 55-plus age range, and we have players from all over the world.
Gardner: The word “games” means a lot of different things to a lot of people. We’re talking about a heritage of network television games back in the ’60s and ’70s that have led us to what is now your organization. But what sort of newer games are we talking about, and what proportion of them are online games, versus more of the passive watching like that on a cable or other media outlets?
Wills: Originally, when our games division started as a branch of GSN, it was companion games to Wheel of Fortune, Minute to Win It, whatever the hot game show was. That's still a part of it, but the growth in the last few years has been in social games on Facebook, where a lot of our games are more casual titles and have nothing to do with the game shows -- tile-matching games or solitaire games, for example.
In the last year or year-and-a-half for us, like everyone else, there’s been this explosion in mobile.
Then, in the last year or year-and-a-half for us, like everyone else, there’s been this explosion in mobile. So it’s iPad, Android, and iPhone games, and there we have the solitaires and the tile matching, too.
Increasingly, a lot of our success and growth has come from virtual casino games. People are playing Bingo, video poker, even slots, virtual slots. We have this title called GSN Casino. That’s an umbrella app with a lot of mini games that are casino-themed, and that one has really just exploded really in the last six months. It's a long way from the Point A of Family Feud reruns to the Point Z of virtual slot machines, but hopefully you can see how we got there.
Gardner: It seems like a long distance, but it’s been also a fairly short amount of time. It wasn't that long ago that the information you might have in your audience came through Nielsen for passive audiences, and you had basically a one- or two-dimension view of that individual, based on the estimate of what time was devoted to a show. But now, with the mobile devices in particular, you have a plethora of data.
Tell us about the types of data that you can get, and what volumes are we talking about.
Wills: Let’s take mobile, because I think it's easy to grok. Everything about the device is exposed to us. The fact that you’re playing on an iPad Mini Retina versus an iPad 1 tells us a lot about you, whether you know it or not.
Then, a lot of our users sign-in via Facebook, which is another vector for information. If you sign-in via Facebook, Facebook provides us your age range, gender, some granular location information. For every player, we get between 40 and 50 dimensions of data about that player or about that device.
That’s one bucket. But the actual gameplay is another whole bucket. What games do you choose to play in our catalog? How long do you play them? What time of day do you play them? Those start to classify users into various buckets -- from the casual commute player, who plays for 15 minutes every morning and afternoon, to the hard-core player who spends 8 to 10 hours a day, believe it or not, playing our games on their mobile devices.
Mobile doesn’t necessarily mean mobile, like out and about. A lot of our players are on their iPad, sitting on the couch in their home.
At that point, and this is a little bit of a pet peeve of mine, mobile doesn’t necessarily mean mobile, like out and about. A lot of our players are on their iPad, sitting on the couch in their home.
It’s not mobility. They’re not using 3G. They’re not using augmented reality. It’s just a device that happens to be a very convenient device for playing games. So it’s much more of a laptop replacement than any sort of mobile thing. That’s sort of a side track.
We collect all of this data, and it’s a fair amount. Right now, we’re generating about 900 million events per day across all of our players. That’s all streamed into our HP Vertica data warehouse, and there are a few tables, event time series tables, that we put the stuff into. A small table for us would be a few hundred billion records, and a large table, as I said, is 1.3 trillion records right now.
So the scale is big for us. I know that for other companies that seems like peanuts. It’s funny how big data is so broad. What’s big to one person is tiny to someone else, but this is the world that we’re dealing in right now.
We have 110 million players. Thankfully, not all of them are active at one time. That would be really big data. But we will have about 20 million at any given time in peak time playing concurrently. That’s a little bit about the numbers in our data warehouse.
Gardner: Understanding your audience through this data is something fairly new. Before, you couldn’t get this amount of data. Now that you have it, what is it able to do for you? Are you crafting new games based on your findings? Are you finding information that you can deliver back to a marketer or advertiser that links them to the audience better? There must be many things you can do.
Wills: First of all, we don’t do any advertising in our mobile games. So that’s one piece that we’re not doing, although I know others are. But there are two broad buckets in which we use data. The first is that we run a lot of the A/B tests, experiments. All of our games are constantly being multivariate tested with different versions of that same game in the field.
We run 20 to 40 tests per week. As an example, we have a Wheel of Fortune game that we recently released, and there was all this debate about the difficulty of the puzzles. How hard should the puzzles be? Should they be very obscure pieces of Eastern literature, mainstream pop culture, or even easier?
So, we tested different levels of difficulty. Some players got the easy, some players got the medium, and some players got the hard ones. We can measure the return rate, the session duration, and the monetization for people who buy power-ups, and we see which level of difficulty performs the best. In the first test of easy, medium, hard, easy overwhelmingly did the best.
So we generated a whole bunch of new puzzles that were even easier than were the previous easy ones and tested that against what was now the control level. The easier puzzles won again. So we generated a whole new set of puzzles that were absurdly easy. We were trying to prove the point that if we gave Wheel of Fortune puzzles that are four-letter words like “bird” and “cups,” nobody would enjoy playing something that simplistic.
Well it turns that they do -- surprise, surprise -- and so that’s how we evolved into a version of Wheel of Fortune that, compared to the game show, looks very different, but it’s actually what customers want. It’s what players want. They want to relax and solve simple puzzles like “door.”
Hopefully faster than overnight. Overnight is a little too slow these days.
Gardner: So Vertica analysis determined that everyone is a winner on GSN, but you’re able to do real-time focus-group types of activities. The data -- because it's so fast, because there is so much information available and you can deal with it so quickly -- means that you’re able to tune your games to the audience virtually overnight.
Wills: Hopefully faster than overnight. Overnight is a little too slow these days. We push twice a day both to our platform code and updates to all of our games in the morning around 11 a.m and in the afternoon around 3:30. Each one of those releases is based on the data that came from the prior release.
So we're constantly evolving these games. I want to go back to your previous question, because I only got to talk about one bucket, which is this experimentation. The other bucket is using the usage patterns that customers have to evolve our product in ways that aren’t necessarily structured around an A/B test.
We thought when we launched our iPhone app that there would be a lot of commuting usage. We had in our head this hypothetical bus player, who plays on the bus in the morning. And so we thought we would build all the stuff around daily patterns. We built this daily return bonus that you can do in the morning and then again in the evening.
The data showed us that that really was only a tiny fraction of our players. There were, in fact, very few players who had this bimodal, morning and evening usage pattern. Most people didn't play at all until after dinner and then they would play a lot, sometimes even binge from 7 p.m. until 2 a.m. on games.
That was an area where we didn't even set up an experiment. We just had false assumptions about our player base. And that happens a surprising amount of the time. We all -- especially the game-design team and people who spent their careers designing video games -- have assumptions about their audience that half the time are just wrong. One of the things we use data for is to challenge all of our assumptions about our own products and our own businesses.
It's really gotten to a point where it's almost religious in our company. The moment two people start debating what should or shouldn't happen, they say, “Well let's just let the data decide.” That's been a core change not just for us, but for the game industry as a whole.
Because we’re here in Spain, a quick tidbit that we uncovered recently is that our main time-frame in every country on Earth, when people play games, is 7 p.m. to 11 p.m., except in Spain where it’s 1 p.m. to 3 p.m. -- siesta time. That’s just one of the examples of how we use big data to use discover insights about our players and our audiences worldwide.
Understanding the audience
Gardner: I have to imagine that the data that led you to that inference in Spain was something other than what we might consider typical structured data. How did the different data brought together allow you to understand your audience better?
Wills: We use this product from HP called Vertica, which is just a tremendous data warehouse, that lets us throw every single click, touch, or swipe in all of our games into a big table. By big, I mean right now it’s I think 1.3 trillion rows. We keep saying that we should really archive this thing. Then, we say we’ll archive it when it slows down, and then it just never slows down, so we have yet to archive it.
We put all of the click stream data in there. The traditional joins, schemas, and all of that don’t really have to happen because we have one table with all of the interactions. You have the device, the country, the player, all these attributes. It’s a very wide table. So if you want to do things like ask what is the usage in five-minute slices by country, it’s a simple SQL query, and you get your results.
Gardner: What you’re describing is very much desired by a lot of types of businesses through understanding a massive amount of data from their audience, to be able to react quickly to that, and then to stop guessing about products and pricing and distribution and logistics and supply chain and be driven purely by the data. You’re a really interesting harbinger of things to come.
One of the things we use data for is to challenge all of our assumptions about our own products and our own businesses.
Portman, tell me little bit about the process by which you were able to do this. Did you have an older data warehouse? What did you use before, and how did you make a transition to HP Vertica?
Wills: When we started the social mobile business three years ago, we were on MySQL, which we are still on for our transactional load. We have three data centers around the world. When people are playing our games, it’s recording, reading, and writing 125,000 transactions per second, and that MySQL, sharded out, works great for that.
When you want to look at your entire player base and do a cross-shard query, we found that MySQL really fell down. Our original Vertica proof of concept (POC) was just to replace these A/B test queries, which have to look across the entire population.
So in comes Vertica. We set up a single node, a Vertica data warehouse. We pull in a year's worth of data, and the same query to synthesize these sessions ran in 800 milliseconds.
So the thing that took 24 hours, which is 86,400 seconds, ran in less than one second. By the way, that 24-hour query was running across dozens of machines, and this Vertica query was running on a single server of commodity hardware.
That's when we really became believers in the power of the column store and column-oriented data warehouses. From the small beginning of just one simple query, it’s now expanded -- and pretty much our whole business runs on top of HP Vertica on the data warehouse side.
Gardner: As I said, I think GSN Games is a really harbinger of what a lot of other companies in many different vertical industries will be seeking. Looking back, if you had to do it again, what might you have done differently or what suggestions might you have for others who would like to be able to do what you are doing?
Wills: I definitely wish that we had switched to a column store sooner. I think the reason that we've been so successful at this is because of our game design team, which was so open to using data.
I definitely wish that we had switched to a column store sooner.
I’ve heard hard stories from other companies where they want to use a data-driven approach, and there's just a lot of cultural inertia and push back against doing that. It's hard to be consistently proven wrong in your job, which is always what happens when you rely on data.
The real thing that's helped us get to the point we are in is a culture and a company where everybody is open to being wrong -- and open to being proven wrong by the data, which I am very thankful for.
Gardner: Well, it's good to be data-driven, and I think you should feel good being responsible for making 110 million people feel good about themselves every day.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.
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Posted By Dana L Gardner,
Friday, August 22, 2014
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The old model of just being an outsourcer or on-premises service provider is dead for many IT solutions providers. Instead, we’re all now in a hybrid world where will have some private-cloud solutions and multiple public clouds. The challenge is to have the right level of governance, and to be in a position to move the workloads, and adjust the workloads with the needs.
These words of wisdom come from European IT services provider Steria, which along with hundreds of its customers are charting a journey to hybrid cloud while maintaining control, automation, and reporting across all IT infrastructure.
To learn more about how services standardization leads to improved hybrid cloud automation, BriefingsDirect spoke to Eric Fradet, Industrialization Director at Steria in Paris. The discussion, at the recent HP Discover conference in Barcelona, is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Fradet: Steria is a 40-year-old service provider company, mainly based in Europe, with a huge location in India and also Singapore. We provide all types of services related to IT, starting from infrastructure management to application management. We help to develop and deploy new IT services for all our customers.
Gardner: How are your activities at Steria helping you better deliver the choice of cloud and software-as-a-service (SaaS) to your customers?
Fradet: That change may be quicker than expected. So, we must be in a position to manage the services wherever they’re from. The old model of saying that we’re an outsourcer or on-premises service provider is dead. Today, we’re in a hybrid world and we must manage that type of world. That must be done in collaboration with partners, and we share the same target, the same ambition, and the same vision.
Benefit, not a pain
The cloud must not be seen as disruptive by our customers. Cloud is here to accompany your transformation. It must be a benefit for them, and not a pain.
A private solution should be the best as a starting point for some customers. The full public solution should be a target. We’re here to manage their journey and to define with the customer what is the best solution for the best need.
Gardner: And in order for that transition from private to public or multiple public or sourced-infrastructure support, a degree of standardization is required. Otherwise, it's not possible. Do you have a preferred approach to standardization?
Fradet: The choice of HP as a partner was based on two main criteria. First of all, the quality of the solution, obviously, but there are multiple good solutions on the market. The second one is the capacity with HP to have a smooth transition, and that means getting to the industrialization benefits and the economic benefits while also being open and interconnected with existing IT systems.
That's why the future model is quite simple. Our work is to know we have on-premises and physical remaining infrastructure. We will have some private-cloud solutions and multiple public clouds, as you mentioned. The challenge is to have the right level of governance, and to be in a position to move the workload and adjust the workloads with the needs.
We continue to invest deeply in ITSM because ITSM is service management.
Gardner: Of course, once you've been able to implement across a spectrum of hosting possibilities, then there is the task of managing that over time, being able to govern and have control.
Fradet: With HP, we have a layer approach which is quite simple. First of all, if you want to manage, you must control, as you mentioned. We continue to invest deeply in IT Service Management (ITSM) because ITSM is service governance. In addition, we have some more innovative solutions based on the last version of Cloud Services Automation (CSA). Control, automate, and report remain as key whatever the cloud or non-cloud infrastructure.
Gardner: Of course, another big topic these days is big data. I would think that a part of the management capability would be the ability to track all the data from all the systems, regardless of where they’re physically hosted. Do you have a preference or have you embarked on a big-data platform that would allow you to manage and monitor IT systems regardless of the volume, and the location?
Fradet: Yes, we have some very interesting initiatives with HP around HAVEn, which is obviously one of the most mature big-data platforms. The challenge for us is to transform a technologically wonderful solution into a business solution. We’re working with our business units to define use-cases that are totally tailored and adjusted for the business, but big data is one of our big challenges.
Gardner: Have you been using a more traditional data-warehouse approach, or are you not yet architecting the capability? Are you still in a proof-of-concept stage?
Fradet: Unfortunately, we have hundreds of data-warehouse solutions, which are customer-dedicated, starting from very old-fashioned level to operational key performance indicators (KPI) to advanced business intelligence (BI).
The challenge now is really to design for what will be top requirements for the data warehouse, and you know that there is a mix of needs in terms of data warehouses. Some are pure operational KPIs, some are analytics, and some are really big data needs. To design the right solution for the customer remains a challenge. But, we’re very confident that with HAVEn, sometime in 2014, we will have the right solution for those issues.
Gardner: Lastly, Eric, the movement toward cloud models for a lot of organizations is still in the planning stages. They are mindful of the vision, but they have also IT housecleaning to do internally. Do you have any suggestions as to how to properly modernize, or move toward a certain architecture that would then give them a better approach to cloud and set them up for less risk and less disruption? What are some observations that you have had for how to prepare for moving toward a cloud model?
Cloud can offer many combinations or many benefits, but you have to define as a first step your preferred benefits.
Fradet: As with any transformation program, the cloud’s eligibility program remains key. That means we have to define the policy with the customer. What is their expectation -- time to market, cost saving, to be more efficient in terms of management?
Cloud can offer many combinations or many benefits, but you have to define as a first step your preferred benefits. Then, when the methodology is clearly defined, the journey to the cloud is not very different than from any other program. It must not be seen as disruptive, keeping in mind that you do it for benefits and not only for technical reasons or whatever.
So don't jump to the cloud without having strong resources below the cloud.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.
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Posted By Dana L Gardner,
Monday, August 11, 2014
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It’s no secret that communication service providers (CSPs) are under a lot of pressure as they make massive investments in upgraded networks while facing shrinking margins and revenues from their eroding traditional voice or broadcasting businesses.
Traditional operators understand that they must go beyond what they did before. They need to offer more compelling services to reduce churn and acquire new customers. But how to know what services customers want most, and how much to charge for them?
A key asset CSPs have is the huge amount of information that they generate and maintain. And so it's the analytics from their massive data sets that becomes the go-to knowledge resource as CSPs re-invent themselves.
Our next Big Data innovation discussion therefore explores how the telecommunication service-provider industry is gaining new business analytic value and strategic return through the better use and refinement of their Big Data assets.
To learn more about how analytics has become a business imperative for service providers, peruse this interview with Oded Ringer, Worldwide Solution Enablement Lead for HP Communication and Media Solutions. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: What are the major trends leading CSPs to view themselves as being more data-driven organizations?
Ringer: CSPs are under a lot of pressure. On one hand, this industry has never been more central. Everybody is connected, spending so much more time online than ever before, and carrying with them small devices through which they connect to the network. So CSPs are central to our work and personal lives – as a result, they’re under lot of pressure.
They’re under a lot of pressure, because they’re required to make massive investments in the networks, but they also need to deal with shrinking margins and revenues to subsidize these investments. So, at the end of the day, they’re squeezed between these two motions.
One approach many CSPs have adopted in the last year was to reduce cost and to cut operations. But this is pretty much a trip to nowhere. Going into most basic services and commodity services is no way for these kinds of things to survive.
In the last two to three years, more and more traditional operators understand that they must go beyond what they did before. They need to offer more compelling services to reduce churn and acquire new customers. They need to leverage their position as a central place between consumers and what they are looking for to become some kind of brokers of information.
The key asset they have in their hand to become such brokers is the huge amount of information that they maintain. It’s exactly where analytics comes into play.
Gardner: When we say CSP and telecommunication companies these days, we’re more and more talking about mobile, right? How big a shift has mobile been in terms of the need to analyze use patterns and get to know what's really happening out in the mobile network?
Ringer: Mobile services are certainly the leading tool in most operator’s arsenals. Operators that have the subscriber “connected” with them wherever they go, around the clock, have an advantage over those that are more dependent upon or only provide tethered services.
But we need to keep in mind that there’s also a whole space for analytics solutions that are related to fixed-line services, like cable, satellite, broadband, and other, landline services. CSPs are investing a lot in becoming more predictive, finding out what the subscriber really wants, what the quality of those services are at any given time, and how we can reduce churn in their customer base.
Another kind of analytics practices that operators take is trying to be predictive in their investments in the network, understanding which network segments are used by more high-worth individuals, those that they do want to improve service to, beefing up those networks and not the other networks.
Again, it’s these mobile operators who are on the front lines of doing more with subscriber data and information in general, but it is also true for cable operators and pay-TV operators, and landline CSPs.
CSPs, unlike most enterprises, need to handle not only the structured data that’s coming from databases and so on, but also unstructured data.
Gardner: Oded, what are some of the data challenges specific to CSPs?
Ringer: In the CSP industry, Big Data is bigger than in any other industry. Bigger, first of all, in volume. There is no other industry that runs this amount of data – if you take into consideration they’re carrying everybody’s data, consumer and enterprise. But that’s one aspect and is not even the most complicated one.
The more complicated thing is the fact that CSPs, unlike most enterprises, need to handle not only the structured data that’s coming from databases and so on, but also unstructured data, such as web communication, voice communication, and video content. They want to analyze all those things, and this requires analyzing unstructured data.
So that’s a significant change in that type of process flow. They are also facing the need to look at new sets of structured data, data from IT management and security log files, from sensors and end-point mobile device telematics, cable set-top boxes, etc.
And two, in the CSP industry, because everything is coming from the wire, there’s no such thing as off-line analytics or batch analytics. Everything needs to be real-time analytics. Of course, this doesn’t mean that there will not be off-line or batch analytics, but even these are becoming more complex and span many more data sets across multiple enterprise silos.
If you analyze subscriber behavior right now and you want to make an offer to improve the experience that he’s having in real time, you need to capture the degradation of service right now and correlate it with what you know about the subscriber right now. So it's so much more real time than in any other industry.
The market is still young. So it's very hard to say which one will be more dominant.
We’re not talking here about projects of data consolidation. It may be necessary in some cases, but that’s not really the practice that we’re talking about here. We’re talking about federating, referring to external information, analyzing in the context of the logic that we want to apply, and making real-time decisions.
In short, CSP Big Data analytics is Big Data analytics on steroids.
Gardner: What does a long-term solution look like, rather than cherry picking against some of these analytics requirements? Is there a more strategic overview approach that would pay off longer term and put these organizations in a better position as they know more and more requirements will be coming their way?
Ringer: Actually we see two kinds of behaviors. The market is still young. So it's very hard to say which one will be more dominant. We see some CSPs that are coming to us with a very clear idea on what business process they want to implement and how they believe a data-driven approach can be applied to it.
They have clear model, a clear return on investment (ROI) and they want to go for it and implement it. Of course, they need the technology, the processes, and the business projects, but their focus is pretty much on a single use case or a variety of use cases that are interrelated. That’s one trend.
There’s another trend in which operators say they need to start looking at their data as an asset, as an area that they want to centralize. They want to control it in a productive manner, both for security, for privacy, and for the ability to leverage it to different purposes.
Those will typically come with a roadmap of different implementations that they would like to do via this Big Data facility that they have in mind and want to implement. But what’s more important for them is not the quickest time to launch specific processes, but to start treating the data as a central asset and to start building a business plan around it.
I guess both trends will continue for quite some while, but we see them both in the market sometimes even in the same company in different organizations.
Gardner: How does a CSP can really change their identity from being a pipe, a conduit, to being more of a rich services provider on top of communications?
And what is it that HP is bringing to the table? What is it about HP HAVEn, in particular, that is well suited to where the telecommunications industry is going and what the requirements are?
Ringer: HP has made huge investments in the space of Big Data in general and analytics in particular, both in-house developments, multiple products, as well as acquisitions of external assets.
HAVEn is now the complete platform that includes multiple best-in-class product elements based multiple, cutting edge yet proven technologies, for exploiting Big Data and analytics. Our solution for the space is pretty much based on HAVEn and expanded with specific solutions for CSP needs, with a wide gallery of connectors for external data sources that exist within the CSP space.
In short, we’re taking HAVEn and using it for the CSP industry with lots of knowledge about what traditional CSP operators need to become next-generation CSPs. Why?
Because we have a very large group within HP of telecom experts who interact with and leverage what we’re doing in other industries and with many of the new age service providers like the Amazons, Googles, Facebook and Twitters of the world. We go a long way back in expertise in telecom -- but combine this with forward thinking customers and our internal visionaries in HP Labs and across our business units.
Gardner: Just to be clear for our audience, HAVEn translates to Hadoop, Autonomy, Vertica, and Enterprise Security, along with a whole suite of horizontally and vertically integrated set of applications that are vertical industry specific. Is that right?
It’s coming from the business people that understand that they need to do something with the data and monetize it.
Gardner: Tell me what you do in terms of how you reach out to communications organizations. Is there something about meeting them at the hardware level and then alerting them to what these other Big Data capabilities are? Is this a cross-discipline type of approach? How do you actually integrate HP services and then take that and engage with these CSPs?
Ringer: Those things exist, like engaging at a hardware level, but those are the less common go-to-market motions that we see. The more popular ones are more top-down, in the sense that we are meeting with business stakeholders who wants to know how to leverage Big Data and analytics to improve their business.
They don’t care about the data other than how it’s going to be result in actionable intelligence. So, at the CSP level, it can be with marketing officers within the CSP who are looking to create more personalized services or more sticky services to increase the attention of their subscribers. They’re looking to analytics for that.
It can be with business-development managers within the CSP organization that are looking to create models of collaboration with the Yahoos and Facebooks of the world, with retailers, or with any kind of other participants of their ecosystem where they can bring the ability to provide the pipe, back-end hosting of services and intelligence about how the pipe is providing the services and the sentiment of the customers on the other end of the pipe.
They want to share information of value to their customers, making them dependent on them in new ways that aren’t just about the pipe thereby gaining new revenue streams. That’s the kind of motivation they have. It can be with IT folks as well, but at the end of the day the discussion about CSP Big Data isn’t coming from the technology. It’s coming from the business people that understand that they need to do something with the data and monetize it.
Then, of course, it becomes pretty quickly a technical discussion that the motion is business to technology, rather than infrastructure to technology.
We also developed the support practice within our organization that does exactly that, business advisory workshops. It’s for stakeholders of different roles to realize what the priorities are in using Big Data. What is the roadmap that they want to implement?
The purpose of this exercise is to quickly bring everybody to the same room, sit together for a day or two, and come out with an agreement on how to turn themselves from conventional services to more personalized services and diversify the business channels via using information data.
For several years now, we have one large customer, Telefónica a Latin American conglomerate, has been working with us on analytics projects to improve the quality of experience of their subscribers.
In Latin America, most people are interested in football, and many of them want to watch it on their mobile device. The challenge is that they all want to watch it during the same 90 minutes. That’s a challenge for any mobile operator, and that’s exactly where we started a critical project with Telefónica.
We’re helping them analyze the quality of experience. Realizing the quality of the experience isn’t a very complicated thing. There are probes in the network to do that. We can pretty accurately get the quality of experience for every single video streaming session. It’s no big deal.
Analytics kicks in when you want to correlate this aggregation of quality with who the subscriber is, how the subscriber is expected to behave, and what he’s interested in. We know that the quality isn’t good enough for many subscribers during the football game, but we need to differentiate and know to which one of them we want to make an offer to upgrade his package. What’s the right offer? When’s the right time to make the offer? How many different offers do we test to zero in on the best set of offers?
We want to know which one of them we don’t want to promote anything to, but just want to make him happy. We want to give him a better quality experience for free, because he is a good customer and we don’t want to lose him. And we want to know which customer we want to come back to later, apologize, and offer him a better deal.
Based on real-time triggering of events from the network, degradation of quality with information that is ongoing about the subscriber, who the subscriber is, what marketing segment he belongs to, what package is he subscribed to and so on, we do the analytics in real time, and decide what the right action is and what the right move is, in order for us to give the best experience for the individual subscriber.
It’s working very nicely for them. I like this example, first of all, because it’s real, but also because it shows the variety of processes we have here with correlation of real-time information with ongoing information for the subscribers. We have contextual action that is taken to monetize and to improve quality and to improve satisfaction.
This example touches so many needs of an operator and is all done in a pretty straightforward manner. The implementation is rather simple. It’s all based on running the right processes and putting the right business process in place. But this isn’t always straightforward for enterprise customers, particularly those in the small to medium enterprise segment so imagine what CSPs could do for their customers once they’ve gotten a handle on this for their own businesses.
We have contextual action that is taken to monetize and to improve quality and to improve satisfaction.
Gardner: It seems to me that that helps reduce the risk of a provider or their customers coming out with new services. If they know that they can adjust rapidly and can make good on services, perhaps this gives them more runway to take off with new services, knowing that they can adjust and be more agile. It seems like it really fundamentally changes how well they can do their business.
Ringer: Absolutely. It also reduces quite a lot the risk of investment. If you launch a new service and you find out that you need to beef up your entire network, that is a major hit for your investment strategy. At the same time, if you realize that you can be very granular and very selective in your investment, you can do it much more easily and justify subsequent investments more clearly.
Gardner: Are there any other examples of how this is manifesting itself in the market -- the use of Big Data in the telecommunication’s industry?
Ringer: Let me give another example in North America. This is an implementation that we did for a large mobile operator in North America, in collaboration with a chain of retail malls.
What we did there is combine their ongoing information that the mobile operator has about its subscribers -- he knows what the subscriber is interested in, what they’re prior buying pattern and transactions were and so on -- with the location information of where the individual person is at the mall.
The mall operator runs a private wi-fi network there, so he has his own system of being able to track where the individual is exactly within the mall. He knows within two meters where a person is in the mall but with the map overlay of the physical mall and all product and service offerings to the same grid.
When we know a person is in the mall, we can correlate it with what the CSP knows about this person already. He knows that the specific person has high probability of looking for a specific running shoe. The mobile operator knows it because he tracks the web behavior of the specific individual. He tracks the profile of the specific individual and he can have pretty good accuracy in telling that this guy, for the right offer, will say yes for running shoes.
So combining these two things, the ongoing analytics of the preferences, together with real-time location information, give us the ability to push out targeted and timely promotions and coupons.
Imagine that you go in the mall and suddenly you pass next to the shoe store. Here, your device pops up a message and that says right now, Nike shoes are 50 percent off for the next 15 minutes. You know that you’re looking for Nike shoes. So the chance that you’ll go into the store is very good, and the results are very good because you create a “buy-now or you’ll miss-out” feeling in the prospect. Many subscribers take the coupons that are pushed to them in this way.
Of course, it’s all based on opt-in, and of course, it’s very granular in the sense that there are analytics that we do on subscriber information that is opted in at the level of what they allow us to look at. For instance, a specific person may allow us to look at his behavior on retail sites, but not on financial sites.
Gardner: Again, this shows a fundamental shift that the communications provider is not just a conduit for information, but can also offer value-added services to both the seller and the buyer -- radically changing their position in their markets.
If I am an organization in the CSP industry and I listen to you and I have some interest in pursuing better Big Data analytics, how do I get started? Where can I go for more information? What is it that you’ve put together that allows me to work on this rather quickly?
Ringer: As I mentioned before, we typically recommend engaging in a two-day workshop with our business consultants. We have a large team of Big Data advisory consultants, and that’s exactly what they do. They understand the priorities and work together with the telecom organizations to come up with some kind of a roadmap -- what they want to do, what they can do, what they are going to do first, and what they are going to do later.
They all look to become more proactive, they all realize that data is an asset and is something that you need to keep handy, keep private, and keep secured.
That’s our preferred way of approaching this discipline. Overall, there are so many kinds of use cases, and we need to decide where to start. So that’s how we start. To engage, the best place is to go to our website. We have lots of information there. The URL is hp.com/go/telcoBigData, that’s one word, and from there you just click Contact Us, and we’ll get back to you. We’ll take you from there. There are no commitments, but chances are very good.
Gardner: Before we sign off, I just wanted to look into the future. As you pointed out, more and more entertainment and media services are being delivered through communication providers. The mobile aspect of our lives continues to grow rapidly. And, of course, now that cloud computing has become more prominent, we can expect that more data will be available across cloud infrastructures, which can be daunting, but also very powerful. Where do you see the future challenges, and what are some of the opportunities?
Ringer: We can summarize four main trends that we’re seeing increasing and accelerating. One is that CSPs are becoming more active in enabling new business models with partnerships, collaborations, internet players, and so on. This is a major trend.
The second trend that we see increasing quite intensively is operators becoming like marketing organizations, promoting services for their own or for others.
The third one is more related to the operation of the CSP itself. They need to be more aware of where they invest, what’s their risk and probability of seeing an specific ROI and when will that occur. In short, Big Data and Analytics will make them smarter and more proactive in making the investments. That’s another driver that increases their interest in using the data.
Overall they all look to become more proactive, they all realize that data is an asset and is something that you need to keep handy, keep private, and keep secured, but be able to use it for variety of use cases and processes to be ready for the next move.
Posted By Dana L Gardner,
Monday, August 04, 2014
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The next BriefingsDirect deep-dive discussion explores how one of the most costly and complex parts of any enterprises IT infrastructure -- storage -- is being dramatically improved by the accelerating adoption of software-defined storage (SDS).
The ability to choose low-cost hardware, to manage across different types of storage, and radically simplify data storage via intelligent automation means a virtual rewriting of the economics of data.
But just as IT leaders seek to simultaneously tackle storage pain points of scalability, availability, agility, and cost -- software-defined storage is also providing significant strategic- and architectural-level benefits.
We're joined by two executives from VMware to unpack these efficiencies and examine the broad innovation behind the rush to exploit software-defined storage, Alberto Farronato, Director of Product Marketing for Cloud Infrastructure Storage and Availability at VMware, and Christos Karamanolis, Chief Architect and a Principal Engineer in the Storage and Availability Engineering Organization at VMware. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: Software-defined storage is changing something more fundamental than just data and economics of data. How do you see the wider implications of what’s happening now that software-defined storage is becoming more common?
Farronato: Software-defined storage is certainly about addressing the cost issue of storage, but more importantly, as you said, it’s also about operations. In fact, the overarching goal that VMware has is to bring to storage the efficient operational model that we brought to compute with server virtualization. So we have a set of initiatives around improving storage on all levels, and building a parallel evolution of storage to what we did with compute. We're very excited about what’s coming.
Gardner: Christos, one of my favorite sayings is that "architecture is IT destiny." How you see software-defined storage at that architectural level? How does it change the game?
Concept of flexibility
Karamanolis: The fundamental architectural principle behind software-defined storage is the concept of flexibility. It's the idea of being able to adapt to different hardware resources, whether those are magnetic disks, flash storage, or other types of non-volatile memories in the future.
How does the end user adapt their storage platform to the needs they have in terms of the capabilities of the hardware, the ratios of the different types of storage, the networking, the CPU resources, and the memory resources needed for executing and providing their service to what's ahead?
That’s one part of flexibility, but there is another very interesting part, which is a very acute problem for VMware customers today. Their operational complexity of provisioning storage for applications and virtual machines (VMs) has been one way of packaging applications.
Today, customers virtualize environments, but also in general have to provision physical storage containers. They have to anticipate their uses over time and have make an investment up front in resources that they'll need over a long period of time. So they create those logical unit number (LUN) file services, or whatever that is needed, for a period of time that spans anything from weeks to years.
Software-defined storage advocates a new model, where applications and VMs are provisioned at the time that the user needs them. The storage resources that they need are provisioned on-demand, exactly for what the application and the user needs -- nothing more or less.
The idea is that you do this in a way that is really intuitive to the end-user, in a way that reflects the abstractions that user understands -- applications, the data containers that the applications need, and the characteristics of the application workloads.
So those two aspects of flexibility are the two fundamental aspects of any software-defined storage.
Gardner: As we see this increased agility, flexibility, the on-demand nature of virtualization now coupled with software-defined storage, how are organizations benefiting at a business level?
Farronato: There are several benefits and several outcomes of adopting software-defined storage. The first that I would call out is the ability to be much more responsive to the business needs -- and the changing business needs -- in the form of what your application needs faster.
As Christos was saying, in the old model, you had to guess ahead of time what the applications will need, spend a lot of time trying to preconfigure and predetermine the various services levels, performance, availability and other things that our storage really would be required by your application, and so spend a lot of time setting things up, and then hopefully, down the line, consume it the way you thought you would.
Difficult change management
In many cases, this causes long provisioning cycles. It causes difficult change management after you provision the application. You find that you need to change things around, because either the business needs have changed or what you guessed was wrong. For example, customers have to face constant data migration.
With the policy-driven approach that Christos has just described -- with the ability to create these storage services on-the-fly for a policy approach -- you don’t have to do all that pre-provisioning and preconfiguring. As you create the VMs and specify the requirements, the system responds accordingly. When you have to change things, you just modify the policy and everything in the underlying infrastructure changes accordingly.
Responsiveness, in my opinion, is the one biggest benefit that IT will deliver to the business by shifting to software-defined storage. There are many others, but I want to focus on the most important one.
When you have to change things, you just modify the policy and everything in the underlying infrastructure will change accordingly.
Gardner: Can you explain what happens when software-defined storage becomes strategic at the applications level, perhaps with implications across the entire data lifecycle?
Karamanolis: One thing we already see, not only among VMware customers, but as a more generic trend, is that infrastructure administrators -- the guys who do the heavy-lifting in the data centers day in and day out, who manage much more beyond what is traditionally servers and applications -- are getting more and more into managing networks and data storage.
Talking about changing models here, what we see is that tools have to be developed and software-defined storage is a key technology evolution behind that. These are tools for those administrators to manage all those resources that they need to make their day-to-day jobs happen.
Here, software-defined storage is playing a key role. With technology like Virtual SAN, we make the management of storage visible for people who are not necessarily experts in the esoterics of a certain vendor's hardware. It allows more IT professionals to specify the requirements of their applications.
Then, the software storage platform can apply those requirements on the fly to provision, configure, and dynamically monitor and enforce compliance for the policy and requirements that are specified for the applications. This is a major shift we see in the IT industry today, and it’s going to be accelerated by technologies like Virtual SAN.
Gardner: When you go to software-defined storage, you can get to policy level, automation, and intelligence when it comes to how you're executing on storage. How does software-defined storage simplify storage overall?
Karamanolis: That's an interesting point, because if you think about this superficially, we’ll now go from a single, monolithic storage entity to a storage platform that is distributed, controlled by software, and can span tens or sometimes hundreds of physical nodes and/or entities. Isn’t complexity harder in the latter case?
The reality is that whether it's because of necessity or because we've learned a lot over the last 10 to 15 years about how to manage and control large distributed systems, that there is a parallel evolution of these ideas of how you manage your infrastructure, including the management of storage.
The user has to be exposed to the consequences of the policy they choose. There is a cost there for every one of those services.
As we alluded to already, the fundamental model here is that the end user, the IT professional that manages this infrastructure, expresses in a descriptive way, what they need for their applications in terms of CPU, memory, networking, and, in our case, storage.
What do I mean by descriptive? The IT professional does not need to understand all the internal details of the technologies or the hardware used at any point in time, and which may evolve over a period of time.
Instead, they express at a high level a set of requirements -- we call them policies -- that capture the requirements of the application. For example, in the case of storage, they specify the level of availability that is required for certain applications and performance goals, and they can also specify things like the data protection policies for certain data sets.
Of course, for all those things, nothing comes for free. So the user has to be exposed to the consequences of the policy that they choose. There is a cost there for every one of those services.
But the key point is that the software platform automatically configures the appropriate resources, whether they're arrayed across multiple physical devices, arrayed across the network, or whether they get asynchronous data as specified in a remote location in order to comply with certain disaster recovery (DR) policies.
All those things are done by the software, without the user having to worry about whether the storage underneath is highly available storage, in which case they need to be able to create only two copies of the data, or whether it is of some low-end hardware for which that would require three or four copies of the data. All those things are determined automatically by the platform.
This is the new mode. Perhaps I'm oversimplifying some of these problems, but the idea is that the user should really not have to know the specific hardware configurations of a disk array. If the requirements can not be met, it is because these new technologies are not incorporated into the storage platform.
Farronato: Virtual SAN is a completely policy-driven product, and we call it VM-centric or application-centric. The whole management paradigm for storage, when you use Virtual SAN, is predicated around the VM and the policies that you create and you assign to the VMs as you create your VMs, as you scale your environment.
One of the great things that you can achieve with Virtual SAN is providing differentiated service levels to individual VMs from a single data store. In the past, you had to create individual LUNs or volumes, assign data services like replication or RAID levels to each individual volume, and then map the application to them.
With Virtual SAN, you're simply going to have a capacity container that happens to be distributed across a number of nodes in your cluster -- and everything that happens from that point on is just dropping your VMs into this container. It automatically instantiates all the data services by virtue of having built-in intelligence that interprets the requirements of the policy.
One of the great things that you can achieve with Virtual SAN is providing differentiated service levels to individual VMs from a single data store.
That makes this system extremely simple and intuitive to use. In fact, one of the core design objectives of Virtual SAN is simplicity. If you look at a short description of the system, the radically simple hypervisor-converged storage means bringing that idea of eliminating the complexity of storage to the next level.
Gardner: We've talked about simplicity, policy driven, automation, and optimization. It seems to me that those add up very quickly to a fit-for-purpose approach to storage, so that we are not under-provisioning or over-provisioning, and that can lead to significant cost-savings.
So let’s translate this back to economics. Alberto, do you have any thoughts on how we lower total cost of ownership (TCO) through these SDS approaches of simplicity, optimization, policy driven, and intelligence?
Farronato: There are always two sides of the equation. There is a CAPEX and an OPEX component. Looking at how a product like Virtual SAN reduces CAPEX, there are several ways, but I can mention a couple of key components or drivers.
First, I'd call out the fact that it is an x86 server-based storage area network (SAN). So it leverages server-side components to deliver shared storage. By virtue of using server-side resources right off the bat there are significant savings that you can achieve through lower-cost hardware components. So the same hard drive or solid-state drive (SSD) that you deploy on a shared external storage array could be on the order of 80 percent cheaper.
The other aspect that I would call out that reduces the overall CAPEX cost is more along the lines of this, as you said, consume on-demand approach or, as we put it in many other terms, grow-as-you-go. With a scale-out model, you can start with a small deployment and a small upfront investment.
You can then progressively scale out as your environment grows by the much finer granularity that you would with a monolithic array. And as you scale, you scale both compute, but also IOPs and that goes hand in hand with often the number of VMs that you are running out of your cluster.
So the system grows with the size of your environment, rather than requiring you to buy a lot of resources upfront that many times remain under-utilized for a long time.
On the OPEX side, when things become simpler, it means that overall administration productivity increases. So we expect a trend where individual administrators will be able to manage a greater amount of capacity, and to do so in conjunction with management of the virtual infrastructure to achieve additional benefits.
Gardner: Virtual SAN has been in general availability now for several months, since March 2014, after being announced last year at VMworld 2013. Now that it’s in place and growing in the market, are there any unintended benefits or unintended consequences from that total-cost perspective in real-world day-in, day-out operations?
The system grows with the size of your environment, rather than require you to buy a lot of resources upfront that many times remain under-utilized for a long time.
I'm looking for ways in which a typical organization is seeing software-defined storage benefiting them culturally and organizationally in terms of skills, labor, and that sort of softer metric.
Karamanolis: That’s a very interesting point. Our technologists sometimes tend to overlook the cultural shifts that technology causes in the field. In the case of Virtual SAN, we see a lot of, as one customer put it, being empowered to manage their own storage, in the vertical that we are controlling in their IT organization, without having to depend on the centralized storage organization in this company.
What we really see here is a shift in paradigm about how our customers use Virtual SAN today to enable them to have a much faster turnaround for trying new applications, new workloads, and getting them from test and dev into production without having to be constrained by the processes and the timelines that are imposed by a central storage IT organization.
This is a major achievement, and the major tool for VMware administrators in the field, which we believe is going to lead the way to a much wider adoption of Virtual SAN and software-defined storage in general.
Gardner: How does this simplification and automation have a governance, risk, and compliance (GRC) benefit?
Farronato: With this approach you have a more granular way to control the service levels that you deliver to your customers, to your internal customers, and a more efficient way to do it by standardizing through polices rather than trying to standardize service levels over a category of hardware.
You can more easily keep track of what each individual application is receiving, whether it’s in compliance to that particular policy that you specified. You can also now enable self-service consumption more easily and effectively.
We have, as part of our Policy-Based Management Engine, APIs that will allow for integration with cloud automation frameworks, such as vCloud Automation Center for OpenStack, where end users will be able to consume a predefined category of service.
It will speed up the provisioning process, while at the same time, enabling IT to maintain that control and visibility that all the admins want to maintain over how the resources are consumed and allocated.
You can also now enable self-service consumption more easily and effectively.
Gardner: I suppose there are as many on-ramps to software-defined data center as there are enterprises. So it's interesting that it can be done at that custom level, based on actual implementation, but also have a strategic vision or a strategic architectural direction. So, it's future-proof as well as supporting legacy.
How about some examples? Do we have either use-case scenarios or an actual organization that we can look to and say that they have deployed these VSAN and they have benefited in certain ways and they are indicative of what others should expect?
Farronato: Let me give you some statistics and some interesting facts. We can look at some of the early examples where, in the last three months since the product has become available, we've found a significant success already in the marketplace, with a great start in terms of adoption from our customers.
We already have more than 300 paying customers in just one quarter. That follows the great success of the public beta that ran through the fall and the early winter with several thousand customers testing and taking a look at the product.
We are finding that virtual desktop infrastructure (VDI) is the most popular use case for Virtual SAN right now. There are a number of reasons why Virtual SAN fits this model from the scale out, as well as the fact that the hyper-converged storage architecture is particularly suitable to address the storage issues of a VDI deployment.
DevOps, or if you want, preproduction environments, loosely defined as test dev, is another area. There are disaster recovery targets in combination with vSphere Replication and Site Recovery Manager. And some of the more aggressive customers are also starting to deploy it in production use cases.
In the last three months since the product has become available, we've found a significant success already in the marketplace.
As I said, the 300 customers that we already have span the gamut in terms of size and names. We have large enterprises, banking, down to the smaller accounts and companies, including education or smaller SMBs.
There are a couple of interesting cases that we'll be showcasing at VMworld 2014 in late-August. If you look at the session list, they're already available as actual use cases presented by our customers themselves.
Adobe will be talking about their massive implementation of Virtual SAN. And for their our production environment, on their data analytics platform, there will be another interesting use case with TeleTech talking about how they have leveraged Cisco UCS to progress VDI deployments.
Gardner: I'd like to revisit the VDI equation for a moment, because one of the things that’s held people up is the impact on storage, and the costs associated with the storage to support VDI. But if you're able to bring down costs by 50 percent, in some cases, using software-defined storage. That radically changes the VDI equation. Isn’t that the case, Christos, where you can now say that you can do VDI cheaper than almost any other approach to a virtualized desktop?
Karamanolis: Absolutely, and the cost of storage is the main impediment in organizations to implement a VDI strategy. With Virtual SAN, as Alberto mentioned earlier, we provide a very compelling cost proposition, both in terms of the capacity of the storage, as well as the performance you gain out of the storage.
You get the needs, both capacity and performance of your VDI workloads for a fraction of the cost you would pay for with a traditional disk array storage.
Alberto already touched on the cost of the capacity, referring to the difference in prices one can get from server vendors and from the market, as opposed to single hardware being procured as part of a traditional disk array.
I'd like to touch on something that is an unsung hero of Virtual SAN and of VDI deployment especially, and that's performance. Virtual SAN, as should be clear by now, is a storage platform that is strongly integrated with our hypervisor. Specifically, the data path implementation and the distributed protocols that are implemented in Virtual SAN are part of the ESXi kernel.
That means that, because of that, we can actually achieve very high performance goals, while we minimize the CPU cycles that are consumed to serve those high I/Os per second. What that means, especially for VDI, is that we use a small slice of the CPU and memory of every single ESXi host to implement this distributed software-driven storage controller.
It doesn't affect all the VMs that run on the same ESXi host, who have already published extensive and detailed performance evaluations, where we compare VDI deployments only on Virtual SAN versus using an external disk array.
And even though Virtual SAN use percentage is cut to be 10 percent of local CPU and memory on those hosts, the consolidation ratio, the number of virtual desktops we run on those clusters, is virtually unaffected, while we get the full performance that is realized with an external, all-flash disk array. So this is the value of Virtual SAN in those environments.
Essentially, you get the needs, both capacity and performance of your VDI workloads, for a fraction of the cost you would pay for with a traditional disk array storage.
Gardner: We're only a few weeks from VMworld 2014 in San Francisco, and I know there's going to be a lot of interest in mobile and in desktop infrastructure for virtualized desktops and applications.
Do you think that we can make some sort of a determination about 2014? Maybe this is the year that we turn the corner on VDI, and that that is a bigger driver to some of these higher efficiencies. Any closing thoughts on the vision for software-defined data center and VDI and the timing with VMworld. Alberto?
Farronato: Certainly, one of the goals that we set ourselves for this Virtual SAN release, solving the VDI use case, eliminating probably the last barrier, and enabling a broader adoption of VDI across the enterprise, and we hope that will materialize. We're very excited about what the early findings show.
With respect to VMworld and some of the other things that we'll be talking about at the conference with respect to storage, we'll continue to explain our vision of software-defined storage, talk about the Virtual SAN momentum, some of the key initiatives that we are rolling out with our OEM partners around things such as Virtual SAN Ready Nodes.
We're going to talk about how we will extend the concept of policy management and dynamic composition of storage services to external storage, with a technology called Virtual Volumes.
There are many other things, and it's gearing up to be a very exciting VMworld Conference for storage-related issues.
Gardner: Last word to you, Christos. Do you have any thoughts about why 2014 is such a pivotal time in the software-defined storage evolution?
Karamanolis: I think that this is the year where the vision that we've been talking about, us and the industry at large, is going to become real in the eyes of some of the bigger, more conservative enterprise IT organizations.
With Virtual SAN from VMware, we're going to make a very strong case at VMworld that this is a real enterprise-class storage system that's applicable across a very wide range of use cases and customers.
With actual customers using the product in the field, I believe that it is going to be a strong evidence for the rest of the industry that software-defined storage is real, it is solving real world problems, and it is here to stay.
Together with opening up some of the management APIs that Virtual SAN uses in VMware products to third parties through this Virtual Volumes technology that Alberto mentioned, we'll also be initiating an industry-wide initiative of making, providing, and offering software-defined storage solutions beyond just VMware and the early companies, mostly startups so far, that have been adopting this model. It’s going to become a key industry direction.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: VMware.
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Posted By Dana L Gardner,
Thursday, July 31, 2014
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As a provider of both application development management and infrastructure outsourcing, Denmark-based NNIT needed a better way to track, manage and govern the more than 10,000 services across its global data centers.
Beginning in 2010, the journey to better overall services automation paved the way to far stronger cloud services delivery, too. NNIT uses HP Cloud Service Automation (CSA) to improve their deployment of IT applications and data, and to provide higher overall service delivery speed and efficiency.
To learn more about how services standardization leads to improved cloud automation, BriefingsDirect spoke with Jesper Bagh, IT Architect and cloud expert at NNIT, based in Copenhagen. The discussion, at the HP Discover conference in Barcelona, is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: Tell us about your company and what you do. Then, we’ll get into some of the services delivery problems and solutions that you've been tasked with resolving.
Bagh: NNIT is a service provider located in Denmark. We have offices around the world, China, Philippines, Czech Republic, and the United States. We’re 2,200 employees globally and we're a subsidiary of Novo Nordisk, the pharmaceutical company.
My responsibility is to ensure for the company that business goals can be delivered through functional requirements, and in turning the functional requirements into projects that can be delivered by the organization.
We’re a wall-to-wall, full-service provider. So we provide both application development management and infrastructure outsourcing. Cloud is just one aspect that we’re delivering services on. We started off by doing service-portfolio management and cataloging of our services, trying to standardize the services that we have on the shelf ready for our customers.
That allowed us to then put offerings into a cloud, and to show the process benefits of standardizing of services, doing cloud well, and of focusing on the dedicated customers. We still have customers using our facility management who are not able to leverage cloud services because of compliance or regulatory demands.
We have roughly over 10,000 services in our data centers. We’re trying now to broaden the capabilities of cloud delivery to the rest of the infrastructure so that we get a more competitive edge. We’re able to deliver better quality, and the end users -- at the end of the day -- get their services faster.
Back in the good old days, developers were in one silo and operations were in another silo. Now, we see a mix of resources, both in operations and in development.
We embarked on CSA together with HP back in 2010. Back then, CSA consisted of many different software applications. It wasn't really complete software back then. Now, it’s a full suite of software.
It has helped us to show to our internal groups -- and our customers -- that we have services in the cloud. For us it has been a tremendous journey to show that you can deliver these services fully automatically, and by running them well, we can gain great efficiency.
Gardner: How has this benefited your speed-to-value when it comes to new applications?
Bagh: The adoption of automation is an ongoing journey. I imagine other companies have also had the opportunity of adopting a new breed of software, and a new life in automation and orchestration. What we see is that the traditional operations divisions now suddenly get developers trying to comprehend what they mean, and trying to have them work together to deliver operations automatically.
Back in the good old days, developers were in one silo, and operations were in another silo. Now, we see a mix of resources -- both in operations and in development. So the organizational change management derived from automation projects is key. We started up, when we did service cataloging and service portfolio management, by doing organizational change to see if this could fit into our vision.
Gardner: Now, a lot of people these days like to measure things. It’s a very data-driven era. Have you been able to develop any metrics of how your service automation and cloud-infrastructure developments have shown results, whether it’s productivity benefits or speeds and feeds? Have you measured this as a time-to-value or a time-to-delivery benefit? What have you come up with?
Bagh: As part of the cloud project, we did two things. We did infrastructure as a service (IaaS), but we also did a value add on IaaS. We were able to deliver qualified IaaS to the life science industry fully compliant. That alone, in the traditional infrastructure, would have taken us weeks or months to deliver servers because of all the process work involved. When we did the CSA and the GxP Cloud, we were able to deliver the same server within a matter of hours. So that’s a measurable efficiency that is highly recognized.
Gardner: For other organizations that are also grappling with these issues and trying to go over organization and silo boundaries for improvement in collaboration, do you have any words of advice? Now that you've been doing this for some time and at that key architect level, which I think is really important, what thoughts do you have that you could share with others, lessons learned perhaps?
Bagh: The lesson learned is that having senior management focus on the entire process is key. Having the organization recognized is a matter of change management. So communication is key. Standardization before automation is key.
You need to start out by doing your standardization of your services, doing the real architectural work, identifying which components you have and which components you don't have, and matching them up. It’s trying to do all the Lego blocks in order to build the house. That’s key. The parallel that I always use is there is nothing different for me as an architect than there is for an architect building a house.
The next step for us is to be more proactive than reactive in our monitoring and reporting capabilities, because we want to be more transparent to our customers.
Gardner: Looking to the future, are there other aspects of service delivery, perhaps ways in which you could gather insights into what's happening across your infrastructure and the results, that end users are seeing through the applications? Do you have any thoughts about where the next steps might be?
Bagh: The next step for us is to be more transparent to our customers. So the vision is now we can deliver services fully automatically. We can run them semi-automatically. We will still do funny stuff from time to time that you need to keep your eyes on. But in order for us to show the value, we need to report on it.
The next step for us is to be more proactive than reactive in our monitoring and reporting capabilities, because we want to be more transparent to our customers. We have a policy called Open and Honest Value-Adding. From that, we want to show our customers that if we can deliver a service fully automatically and standardized, they know what they get because they see it in a catalog. Then, we should be able to report on it live for the users.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.
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Cloud Service Automation