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

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

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

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

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

Here are some excerpts:

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

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

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Sandholm

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

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

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

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

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

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

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

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

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

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

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

Sandholm: Ha-ha, basically yes.

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

Three part harmony

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

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

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

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

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

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

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

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

HPC from HPE

Overcomes Barriers

To Supercomputing and Deep Learning

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

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

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

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

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

Human modeling, AI solving

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

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

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

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

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

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

Superhuman business strategies

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

 HPC from HPE

Overcomes Barriers 

To Supercomputing and Deep Learning

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

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

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

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

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

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

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

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

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

Gaming your own immune system

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

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

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

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

Algorithms at the edge

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

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

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

HPC from HPE

Overcomes Barriers 

To Supercomputing and Deep Learning

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

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

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

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

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

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

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

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

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

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

Here are some excerpts:

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

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

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

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

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

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

Big data value add

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

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

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

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

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

Healthy hardware relationships 

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

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

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

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

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

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

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

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

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

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

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

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

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

Saving time, money, and people

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

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

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

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

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

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

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

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

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

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

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

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

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

Here are some excerpts:

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

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

 

Orlando Bayter (1)

Bayter

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

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

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

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

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

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

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

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

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

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

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

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

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

Community collaboration

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

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

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

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

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

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

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

Global ecosystem, by choice

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

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

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

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

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

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

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

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

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

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

Development to deployment 

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

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

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

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Of Cloud Service Providers

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

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

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

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

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

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

Digital transformation

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

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

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

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

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

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

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

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

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

Learn How Cloud 28+

Provides an Open Community

Of Cloud Service Providers

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

Partnership is top priority

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

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

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

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Posted in application transformation, Cloud computing, cloud messaging, Enterprise architect, enterprise architecture, Hewlett Packard Enterprise, HP | Tagged , , , , , , , , | Leave a comment

How Nokia refactors the video delivery business with new time-managed IT financing models

The next BriefingsDirect IT financing and technology acquisition strategies interview examines how Nokia is refactoring the video delivery business. Learn both about new video delivery architectures and the creative ways media companies are paying for the technology that supports them.

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

Here to describe new models of Internet Protocol (IP) video and time-managed IT financing is Paul Larbey, Head of the Video Business Unit at Nokia, based in Cambridge, UK. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: It seems that the video-delivery business is in upheaval. How are video delivery trends coming together to make it necessary for rethinking architectures? How are pricing models and business models changing, too?

Larbey: We sit here in 2017, but let’s look back 10 years to 2007. There were a couple key events in 2007 that dramatically shaped how we all consume video today and how, as a company, we use technology to go to market.

Paul Larbey (1)

Larbey

It’s been 10 years since the creation of the Apple iPhone. The iPhone sparked whole new device-types, moving eventually into the iPad. Not only that, Apple underneath developed a lot of technology in terms of how you stream video, how you protect video over IP, and the technology underneath that, which we still use today. Not only did they create a new device-type and avenue for us to watch video, they also created new underlying protocols.

It was also 10 years ago that Netflix began to first offer a video streaming service. So if you look back, I see one year in which how we all consume our video today was dramatically changed by a couple of events.

If we fast-forward, and look to where that goes to in the future, there are two trends we see today that will create challenges tomorrow. Video has become truly mobile. When we talk about mobile video, we mean watching some films on our iPad or on our iPhone — so not on a big TV screen, that is what most people mean by mobile video today.

The future is personalized

When you can take your video with you, you want to take all your content with you. You can’t do that today. That has to happen in the future. When you are on an airplane, you can’t take your content with you. You need connectivity to extend so that you can take your content with you no matter where you are.

Take the simple example of a driverless car. Now, you are driving along and you are watching the satellite-navigation feed, watching the traffic, and keeping the kids quiet in the back. When driverless cars come, what you are going to be doing? You are still going to be keeping the kids quiet, but there is a void, a space that needs to be filled with activity, and clearly extending the content into the car is the natural next step.

And the final challenge is around personalization. TV will become a lot more personalized. Today we all get the same user experience. If we are all on the same service provider, it looks the same — it’s the same color, it’s the same grid. There is no reason why that should all be the same. There is no reason why my kids shouldn’t have a different user interface.

There is no reason why I should have 10 pages of channels that I have to through to find something that I want to watch.

The user interface presented to me in the morning may be different than the user interface presented to me in the evening. There is no reason why I should have 10 pages of channels that I have to go through to find something that I want to watch. Why aren’t all those channels specifically curated for me? That’s what we mean by personalization. So if you put those all together and extrapolate those 10 years into the future, then 2027 will be a very different place for video.

Gardner: It sounds like a few things need to change between the original content’s location and those mobile screens and those customized user scenarios you just described. What underlying architecture needs to change in order to get us to 2027 safely?

Larbey: It’s a journey; this is not a step-change. This is something that’s going to happen gradually.

But if you step back and look at the fundamental changes — all video will be streamed. Today, the majority of what we view is via broadcasting, from cable TV, or from a satellite. It’s a signal that’s going to everybody at the same time.

If you think about the mobile video concept, if you think about personalization, that is not going be the case. Today we watch a portion of our video streamed over IP. In the future, it will all be streamed over IP.

And that clearly creates challenges for operators in terms of how to architect the network, how to optimize the delivery, and how to recreate that broadcast experience using streaming video. This is where a lot of our innovation is focused today.

Gardner: You also mentioned in the case of an airplane, where it’s not just streaming but also bringing a video object down to the device. What will be different in terms of the boundary between the stream and a download?

IT’s all about intelligence

Larbey: It’s all about intelligence. Firstly, connectivity has to extend and become really ubiquitous via technology such as 5G. The increase in fiber technology will dramatically enable truly ubiquitous connectivity, which we don’t really have today. That will resolve some of the problems, but not all.

But, by the fact that television will be personalized, the network will know what’s in my schedule. If I have an upcoming flight, machine learning can automatically predict what I’m going to do and make sure it suggests the right content in context. It may download the content because it knows I am going to be sitting in a flight for the next 12 hours.

Gardner: We are putting intelligence into the network to be beneficial to the user experience. But it sounds like it’s also going to give you the opportunity to be more efficient, with just-in-time utilization — minimal viable streaming, if you will.

How does the network becoming more intelligent also benefit the carriers, the deliverers of the content, and even the content creators and owners? There must be an increased benefit for them on utility as well as in the user experience?

Larbey: Absolutely. We think everything moves into the network, and the intelligence becomes the network. So what does that do immediately? That means the operators don’t have to buy set-top boxes. They are expensive. They are very costly to maintain. They stay in the network a long time. They can have a much lighter client capability, which basically just renders the user interface.

The first obvious example of all this, that we are heavily focused on, is the storage. So taking the hard drive out of the set-top box and putting that data back into the network. Some huge deployments are going on at the moment in collaboration with Hewlett Packard Enterprise (HPE) using the HPE Apollo platform to deploy high-density storage systems that remove the need to ship a set-top box with a hard drive in it.

HPE Rethinks

How to Acquire, Pay For

And Use IT

Now, what are the advantages of that? Everybody thinks it’s costly, so you’ve taken the hard drive out, you have the storage in the network, and that’s clearly one element. But actually if you talk to any operator, their biggest cause of subscriber churn is when somebody’s set-top box fails and they lose their personalized recordings.

The personal connection you had with your service isn’t there any longer. It’s a lot easier to then look at competing services. So if that content is in the network, then clearly you don’t have that churn issue. Not only can you access your content from any mobile device, it’s protected and it will always be with you.

Taking the CDN private

Gardner: For the past few decades, part of the solution to this problem was to employ a content delivery network (CDN) and use that in a variety of ways. It started with web pages and the downloading of flat graphic files. Now that’s extended into all sorts of objects and content. Are we going to do away with the CDN? Are we going to refactor it, is it going to evolve? How does that pan out over the next decade?

Larbey: The CDN will still exist. That still becomes the key way of optimizing video delivery — but it changes. If you go back 10 years, the only CDNs available were CDNs in the Internet. So it was a shared service, you bought capacity on the shared service.

Even today that’s how a lot of video from the content owners and broadcasters is streamed. For the past seven years, we have been taking that technology and deploying it in private network — with both telcos and cable operators — so they can have their own private CDN, and there are a lot of advantages to having your own private CDN.

You get complete control of the roadmap. You can start to introduce advanced features such as targeted ad insertion, blackout, and features like that to generate more revenue. You have complete control over the quality of experience, which you don’t if you outsource to a shared service.

There are a lot of advantages to having your own private CDN. You have complete control over the quality of experience which you don’t if you outsource to a shared service.

What we’re seeing now is both the programmers and broadcasters taking an interest in that private CDN because they want the control. Video is their business, so the quality they deliver is even more important to them. We’re seeing a lot of the programmers and broadcasters starting to look at adopting the private CDN model as well.

The challenge is how do you build that? You have to build for peak. Peak is generally driven by live sporting events and one-off news events. So that leaves you with a lot of capacity that’s sitting idle a lot of the time. With cloud and orchestration, we have solved that technically — we can add servers in very quickly, we can take them out very quickly, react to the traffic demands and we can technically move things around.

But the commercial model has lagged behind. So we have been working with HPE Financial Services to understand how we can innovate on that commercial model as well and get that flexibility — not just from an IT perspective, but also from a commercial perspective.

Gardner:  Tell me about Private CDN technology. Is that a Nokia product? Tell us about your business unit and the commercial models.

Larbey: We basically help as a business unit. Anyone who has content — be that broadcasters or programmers – they pay the operators to stream the content over IP, and to launch new services. We have a product focused on video networking: How to optimize a video, how it’s delivered, how it’s streamed, and how it’s personalized.

It can be a private CDN product, which we have deployed for the last seven years, and we have a cloud digital video recorder (DVR) product, which is all about moving the storage capacity into the network. We also have a systems integration part, which brings a lot of technology together and allows operators to combine vendors and partners from the ecosystem into a complete end-to-end solution.

HPE Rethinks

How to Acquire, Pay For

And Use IT

Gardner: With HPE being a major supplier for a lot of the hardware and infrastructure, how does the new cost model change from the old model of pay up-front?

Flexible financial formats

Larbey: I would not classify HPE as a supplier; I think they are our partner. We work very closely together. We use HPE ProLiant DL380 Gen9 Servers, the HPE Apollo platform, and the HPE Moonshot platform, which are, as you know, world-leading compute-storage platforms that deliver these services cost-effectively. We have had a long-term technical relationship.

We are now moving toward how we advance the commercial relationship. We are working with the HPE Financial Services team to look at how we can get additional flexibility. There are a lot of pay-as-you-go-type financial IT models that have been in existence for some time — but these don’t necessarily work for my applications from a financial perspective.

Our goal is to use 100 percent of the storage all of the time to maximize the cache hit-rate.

In the private CDN and the video applications, our goal is to use 100 percent of the storage all of the time to maximize the cache hit-rate. With the traditional IT payment model for storage, my application fundamentally breaks that. So having a partner like HPE that was flexible and could understand the application is really important.

We also needed flexibility of compute scaling. We needed to be able to deploy for the peak, but not pay for that peak at all times. That’s easy from the software technology side, but we needed it from the commercial side as well.

And thirdly, we have been trying to enter a new market and be focused on the programmers and broadcasters, which is not our traditional segment. We have been deploying our CDN to the largest telcos and cable operators in the world, but now, selling to that programmers and broadcasters segment — they are used to buying a service from the Internet and they work in a different way and they have different requirements.

So we needed a financial model that allowed us to address that, but also a partner who would take some of the risk, too, because we didn’t know if it was going to be successful. Thankfully it has, and we have grown incredibly well, but it was a risk at the start. Finding a partner like HPE Financial Services who could share some of that risk was really important.

Gardner: These video delivery organizations are increasingly operating on subscription basis, so they would like to have their costs be incurred on a similar basis, so it all makes sense across the services ecosystem.

Our tolerance just doesn’t exist anymore for buffering and we demand and expect the highest-quality video.

Larbey: Yes, absolutely. That is becoming more and more important. If you go back to the very first the Internet video, you watched of a cat falling off a chair on YouTube. It didn’t matter if it was buffering, that wasn’t relevant. Now, our tolerance just doesn’t exist anymore for buffering and we demand and expect the highest-quality video.

If TV in 2027 is going to be purely IP, then clearly that has to deliver exactly the same quality of experience as the broadcasting technologies. And that creates challenges. The biggest obvious example is if you go to any IP TV operator and look at their streamed video channel that is live versus the one on broadcast, there is a big delay.

So there is a lag between the live event and what you are seeing on your IP stream, which is 30 to 40 seconds. If you are in an apartment block, watching a live sporting event, and your neighbor sees it 30 to 40 seconds before you, that creates a big issue. A lot of the innovations we’re now doing with streaming technologies are to deliver that same broadcast experience.

HPE Rethinks

How to Acquire, Pay For

And Use IT

Gardner: We now also have to think about 4K resolution, the intelligent edge, no latency, and all with managed costs. Fortunately at this time HPE is also working on a lot of edge technologies, like Edgeline and Universal IoT, and so forth. There’s a lot more technology being driven to the edge for storage, for large memory processing, and so forth. How are these advances affecting your organization?

Optimal edge: functionality and storage

Larbey: There are two elements. The compute, the edge, is absolutely critical. We are going to move all the intelligence into the network, and clearly you need to reduce the latency, and you need to able to scale that functionality. This functionality was scaled in millions of households, and now it has to be done in the network. The only way you can effectively build the network to handle that scale is to put as much functionality as you can at the edge of the network.

The HPE platforms will allow you to deploy that computer storage deep into the network, and they are absolutely critical for our success. We will run our CDN, our ad insertion, and all that capability as deeply into the network as an operator wants to go — and certainly the deeper, the better.

The other thing we try to optimize all of the time is storage. One of the challenges with network-based recording — especially in the US due to the content-use regulations compliance — is that you have to store a copy per user. If, for example, both of us record the same program, there are two versions of that program in the cloud. That’s clearly very inefficient.

The question is how do you optimize that, and also support just-in-time transcoding techniques that have been talked about for some time. That would create the right quality of bitrate on the fly, so you don’t have to store all the different formats. It would dramatically reduce storage costs.

The challenge has always been that the computing processing units (CPUs) needed to do that, and that’s where HPE and the Moonshot platform, which has great compute density, come in. We have the Intel media library for doing the transcoding. It’s a really nice storage platform. But we still wanted to get even more out of it, so at our Bell Labs research facility we developed a capability called skim storage, which for a slight increase in storage, allows us to double the number of transcodes we can do on a single CPU.

That approach takes a really, really efficient hardware platform with nice technology and doubles the density we can get from it — and that’s a big change for the business case.

Gardner: It’s astonishing to think that that much encoding would need to happen on the fly for a mass market; that’s a tremendous amount of compute, and an intense compute requirement.

Content popularity

Larbey: Absolutely, and you have to be intelligent about it. At the end of the day, human behavior works in our favor. If you look at most programs that people record, if they do not watch within the first seven days, they are probably not going to watch that recording. That content in particular then can be optimized from a storage perspective. You still need the ability to recreate it on the fly, but it improves the scale model.

Gardner: So the more intelligent you can be about what the users’ behavior and/or their use patterns, the more efficient you can be. Intelligence seems to be the real key here.

Larbey: Yes, we have a number of algorithms even within the CDN itself today that predict content popularity. We want to maximize the disk usage. We want the popular content on the disk, so what’s the point of us deleting a piece of a popular content just because a piece of long-tail content has been requested. We do a lot of algorithms looking at and trying to predict the content popularity so that we can make sure we are optimizing the hardware platform accordingly.

Gardner: Perhaps we can deepen our knowledge about this all through some examples. Do have some examples that demonstrate how your clients and customers are taking these new technologies and making better business decisions that help them in their cost structure — but also deliver a far better user experience?

In-house control

Larbey: One of our largest customers is Liberty Global, with a large number of cable operators in a variety of countries across Europe. They were enhancing an IP service. They started with an Internet-based CDN and that’s how they were delivering their service. But recognizing the importance of gaining more control over costs and the quality experience, they wanted to take that in-house and put the content on a private CDN.

We worked with them to deliver that technology. One of things that they noticed very quickly, which I don’t think they were expecting, was a dramatic reduction in the number of people calling in to complain because the stream had stopped or buffered. They enjoyed a big decrease in call-center calls as soon as they switched on our new CDN technology, which is quite an interesting use-case benefit.

When they deployed a private CDN, they reached costs payback in less than 12 months.

We do a lot with Sky in the UK, which was also looking to migrate away from an Internet-based CDN service into something in-house so they could take more control over it and improve the users’ quality of experience.

One of our customers in Canada, TELUS, when they deployed a private CDN, they reached costs payback in less than 12 months in terms of both the network savings and the Internet CDN costs savings.

Gardner: Before we close out, perhaps a look to the future and thinking about some of the requirements on business models as we leverage edge intelligence. What about personalization services, or even inserting ads in different ways? Can there be more of a two-way relationship, or a one-to-one interaction with the end consumers? What are the increased benefits from that high-performing, high-efficiency edge architecture?

VR vision and beyond

Larbey: All of that generates more traffic — moving from standard-definition to high-definition to 4K, to beyond 4K — it all generates more network traffic. You then take into account a 360-degree-video capability and virtual reality (VR) services, which is a focus for Nokia with our Ozo camera, and it’s clear that the data is just going to explode.

So being able to optimize, and continue to optimize that, in terms of new codec technology and new streaming technologies — to be able to constrain the growth of video demands on the network – is essential, otherwise the traffic would just explode.

There is lot of innovation going on to optimize the content experience. People may not want to watch all their TV through VR headsets. That may not become the way you want to watch the latest episode of Game of Thrones. However, maybe there will be a uniquely created piece of content that’s an add-on in 360, and the real serious fans can go and look for it. I think we will see new types of content being created to address these different use-cases.

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

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Posted in Bimodal IT, Business intelligence, Business networks, Cloud computing, data analysis, data center, Data center transformation, Enterprise app stores, Enterprise architect, enterprise architecture, Enterprise transformation, Hewlett Packard Enterprise, Information management, Internet of Things, machine learning, managed services, Microsoft, server, Software-defined storage, storage, User experience, video delivery | Tagged , , , , , , , , , | Leave a comment

IoT capabilities open new doors for Miami telecoms platform provider Identidad IoT

The next BriefingsDirect Internet of Things (IoT) strategies insights interview focuses on how a Miami telecommunications products provider has developed new breeds of services to help manage complex edge and data scenarios.

We will now learn how IoT platforms and services help to improve network services, operations, and business goals — for carriers and end users alike.

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

Here to help us explore what is needed to build an efficient IoT support business is Andres Sanchez, CEO of Identidad IoT in Miami. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: How has your business changed in the telecoms support industry and why is IoT such a big opportunity for you?

Sanchez: With the new OTT (Over the Top content) technology, and the way that it came into the picture and took part of the whole communications chain of business, the business is basically getting very tough in telecoms. When we begin evaluating what IoT can do and seeing the possibilities, this is a new wave. We understand that it’s not about connectivity, it’s not about the 10 percent of the value chain — it’s more about the solutions.

Andres_SanchezWe saw a very good opportunity to start something new and to take the experience we have with the technology that we have in telecoms, and get new people, get new developers, and start building solutions, and that’s what we are doing right now.

Gardner: So as the voice telecoms business trails off, there is a new opportunity at the edge for data and networks to extend for a variety of use cases. What are some the use cases that you are seeing now in IoT that is a growth opportunity for your business?

Sanchez: IoT is everywhere. The beauty of IoT is that you can find solutions everywhere you look. What we have found is that when people think about IoT, they think about connected home, they think about connected car, or the smart parking where it’s just a green or red light when the parking is occupied or not. But IoT is more than that.

There are two ways to generate revenue in IoT. One is by having new products. The second is understanding what it is on the operational level that we can do better. And it’s in this way that we are putting in sensors, measuring things, and analyzing things. You can basically reduce your operational cost, or be more effective in the way that you are doing business. It’s not only getting the information, it’s using that information to automate processes that it will make your company better.

Gardner: As organizations recognize that there are new technologies coming in that are enabling this smart edge, smart network, what is it that’s preventing them from being able to take advantage of this?

Manage your solutions

with the HPE

Universal IoT Platform

Sanchez: Companies think that they just have to connect the sensors, that they only have to digitize their information. They haven’t realized that they really have to go through a digital transformation. It’s not about connecting the sensors that are already there; it’s building a solution using that information. They have to reorganize and to reinvent their organizations.

For example, it’s not about taking a sensor, putting the sensor in the machine and just start taking information and watching it on a screen. It’s taking the information and being able to see and check special patterns, to predict when a machine is going to break, when a machine at certain temperatures starts to work better or worse. It’s being able to be more productive without having to do more work. It’s just letting the machines do the work by themselves.

Gardner: A big part of that is bringing more of an IT mentality to the edge, creating a standard network and standard platforms that can take advantage of the underlying technologies that are now off-the-shelf.

Sanchez: Definitely. The approach that Identidad IoT takes is we are not building solutions based on what we think is good for the customer. What we are doing is building proof of concepts (PoCs) and tailored solutions for companies that need digital transformation.

I don’t think there are two companies doing the same thing that have the same problems. One manufacturer may have one problem, and another manufacturer using the same technology has another completely different problem. So the approach we are taking is that we generate a PoC, check exactly what the problems are, and then develop that application and solution.

This is not just a change of process. This is not purely putting in new software. This is trying to solve a problem when you may not even know the problem is there. It’s really digital transformation.

But it’s important to understand that IoT is not an IT thing. When we go to a customer, we don’t just go to an IT person, we go to the CEO, because this is a change of mentality. This is not just a change of process. This is not purely putting in new software. This is trying to solve a problem when you may not even know the problem is there. It’s really digital transformation.

Gardner: Where is this being successful? Where are you finding that people really understand it and are willing to take the leap, change their culture, rethink things to gain advantages?

One solution at a time

Sanchez: Unfortunately, people are afraid of what is coming, because people don’t understand what IoT is, and everybody thinks it’s really complicated. It does need expertise. It does need to have security — that is a very big topic right now. But it’s not impossible.

When we approach a company and that CEO, CIO or CTO understands that the benefits of IoT will be shown once you have that solution built — and that probably the initial solution is not going to be the final solution, but it’s going to be based on iterations — that’s when it starts working.

If people think it’s just an out-of-the-box solution, it’s not going to work. That’s the challenge we are having right now. The opportunity is when the head of the company understands that they need to go through a digital transformation.

Manage your solutions

with the HPE

Universal IoT Platform

Gardner: When you work with a partner like Hewlett PackardEnterprise (HPE), they have made big investments and developments in edge computing, such as Universal IoT Platform and Edgeline Systems. How does that help you as a solutions provider make that difficult transition for your customers easier, and encourage them to understand that it’s not impossible, that there are a lot of solutions already designed for their needs?

Sanchez: Our relationship with HPE has been a huge success for Identidad IoT. When we started looking at platforms, when we started this company, we couldn’t find the right platform to fulfill our needs. We were looking for a platform that we could build solutions on and then extrapolate that data with other data, and build other solutions over those solutions.

When we approached HPE, we saw that they do have a unique platform that allows us to generate whatever applications, for whatever verticals, for whatever organizations – whether a city or company. Even if you wanted to create a product just for end-users, they have the ability to do it.

Also, it’s a platform that is so robust that you know it’s going to work, it’s reliable, and it’s very secure. You can build security from the device right on up to the platform and the applications. Other platforms, they don’t have that.

We think that IoT is about relationships and partnerships — it’s about an ecosystem.

Our business model correlates a lot with the HPE business model. We think that IoT is about relationships and partnerships — it’s about an ecosystem. The approach that HPE has to IoT and to ecosystem is exactly the same approach that we have. They are building this big ecosystem of partners. They are helping each other to build relationships and in that way, they build a better and more robust platform.

Gardner: For companies and network providers looking to take advantage of IoT, what would you suggest that they do in preparation? Is there a typical on-ramp to an IoT project?

A leap of faith

Sanchez: There’s no time to be prepared right now. I think they have to take a leap of faith and start building the IoT applications. The pace of the technology transformation is incredible.

When you see the technology right now, today — probably in four months it’s going to be obsolete. You are going to have even better technology, a better sensor. So if you wait –most likely the competition is not going to wait and they will have a very big advantage.

Our approach at Identidad IoT is about platform-as-a-service (PaaS). We are helping companies take that leap without having to create very big financial struggles. And the companies will know that by our using the HPE platform, they are using the state-of-the-art platform. They are not using just a mom-and pop-platform built in a garage. It’s a robust PaaS — so why not to take that leap of faith and start building it? Now is the time.

Gardner: Once you pick up that success, perhaps via a PoC, that gives you ammunition to show economic and productivity benefits that then would lead to even more investment. It seems like there is a virtuous adoption cycle potential here.

Sanchez: Definitely! Once we start a new solution, usually the people who are seeing that solution, they start seeing things that they are not used to seeing. They can pinpoint problems that they have been having for years – but they didn’t understand why.

For example, there’s one manufacturer of T-shirts in Colombia. They were having issues with one specific machine. That machine used to break after two or three weeks. There was just this small piece that was broken. When we installed the sensor and we started gathering their information, after two or three breaks, we understood that it was not the amount of work — it was the temperature at which the machine was working.

So what they did is once the temperature reached a certain point, we automatically started some fans to normalize the temperature, and then they haven’t had any broken pieces for months. It was a simple solution, but it took a lot of study and gathering of information to be able to understand that break point — and that’s the beauty of IoT.

Gardner: It’s data-driven, it’s empirical, it’s understood, but you can’t know what you don’t know until you start measuring things, right?

Listen to things

Sanchez: Exactly! I always say that the “things” are trying to say something, and we are not listening. IoT enables the people, the companies, and the organization to start listening to the things, and not only to start listening, but to make the things to work for us. We need the applications to be able to trigger something to fix the problem without any human intervention — and that’s also the beauty of IoT.

Gardner: And that IoT philosophy even extends to healthcare, manufacturing, transportation, any place where you have complexity, it is pertinent.

Manage your solutions

with the HPE

Universal IoT Platform

Sanchez: Yes, the solution for IoT is everywhere. You can think about healthcare or tracking people or tracking guns or building solutions for cities in which the city can understand what is triggering certain pollution levels that they can fix. Or it can be in manufacturing, or even a small thing like finding your cellphone.

It’s everything that you can measure. Everything that you can put a sensor on, you can measure — that’s IoT. The idea is that IoT will help people live better lives without having to take care of the “thing;” things will have to take care of themselves.

Gardner: You seem quite confident that this is a growth industry. You are betting a significant amount of your future growth on it. How do you see it increasing over the next couple of years? Is this a modest change or do you really see some potential for a much larger market?

Once people understand the capability of IoT, there’s going to be an explosion of solutions.

Sanchez: That’s a really good question. I do see that IoT is the next wave of technology. There are several studies that say that by 2020 there are going to be 50 billion devices connected. I am not that futuristic, but I do see that IoT will start working now and probably within the next two or three years we are going to start seeing an incremental growth of the solutions. Once people understand the capability of IoT, there’s going to be an explosion of solutions. And I think the moment to start doing it is now. I think that next year it’s going to be too late.

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

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Posted in application transformation, big data, Cloud computing, data analysis, enterprise architecture, Hewlett Packard Enterprise, Internet of Things, machine learning | Tagged , , , , , , , , , | Leave a comment

Inside story on developing the ultimate SDN-enabled hybrid cloud object storage environment

The next BriefingsDirect inside story interview explores how a software-defined data center (SDDC)-focused systems integrator developed an ultimate open-source object storage environment.

We’re now going to learn how Key Information Systems crafted a storage capability that may have broad extensibility into such realms as hybrid cloud and multi-cloud support.

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

Here to help us better understand a new approach to open-source object storage is Clayton Weise, Director of Cloud Services at Key Information Systems in Agoura Hills, California. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: What prompted you to improve on the way that object storage is being offered as a service? How might this become a new business opportunity for you?

Weise: About a year ago, at Hewlett Packard Enterprise (HPE) Discover, I was wandering the event floor. We had just gotten out of a meeting with SwitchNAP, which is a major data center in Las Vegas. We had been talking to them about some preferred concepts and deployments for storage for their clients.

Clayton Weise (1)That discussion evolved into realizing that there are number of clients inside of Switch and their ecosystem that could make use of storage that was more locally based, that needed to be closer at hand. There were cost savings that could be gained if you have a connection within the same data center, or within the same fiber network.

Pulling data in and out of a cloud

Under this model, there would be significantly less expensive ways of pulling data in and out of a cloud, since you wouldn’t have transfer fees as you normally would. There would also be an advantage to privacy, and to cutting latency, and other beneficial things because of a private network all run by Switch and through their fiber network. So we looked at this and thought this might be interesting.

In discussions with the number of groups within HPE while wandering the floor at Discover, we found that there were some pretty interesting ways that we could play games with the network to allow clients to not have to uproot the way they do things, or force them to do things, for lack of a better term, “Our way.”

If you go to Amazon Web Services or you go to Microsoft Azure, you do it the Microsoft way, or you do it the Amazon way. You don’t really have a choice, since you have to follow their guidelines.

They generally use object storage as an inexpensive way to store archival or less-frequently accessed data. Cloud storage became an alternative to tape and long-term storage.

Where we saw value is, there are times in the mid-market space for clients — ranging from a couple of hundred million dollars up to maybe a couple of billion dollars in annual revenue — where they generally use object storage as kind of an inexpensive way to store archival, or less-frequently accessed, data. So [the cloud storage] became an alternative to tape and long-term storage.

We’ve had this massive explosion of unstructured data, files, and all sorts of things. We have a number of clients in medical and finance, and they have just seen this huge spike in data.

The challenge is: To deploy your own object storage is a fairly complex operation, and it requires a minimum number of petabytes to get started. In that mid-market, they are not typically measuring their storage in that petabytes level.

These customers are more typically in the tens to hundreds of terabytes range, and so they need an inexpensive way to offload that data and put it somewhere where it makes sense. In the medical industry particularly, there’s a lot of concern about putting any kind of patient data up in a public cloud environment — even with encryption.

We thought that if we are in the same data center, and it is a completely private operation that exists within these facilities, that will fulfill the total need — and we can encrypt the data.

But we needed a way to support such private-cloud object storage that would be multitenant. Also, we just have had better luck working with open standards. The challenge with dealing with proprietary systems is you end up locked into a standard, and if you pick wrong, you find yourself having to reinvent everything later on.

I come from a networking background; I was an Internet plumber for many years. We saw the transition then on our side when routing protocols first got introduced. There were proprietary routing protocols, and there were open standards, and that’s what we still use today.

Transition to

Cloud-first

HPE Data Center Networking

So we took a similar approach in object storage as a private-cloud service. We went down the open source path in terms of how we handled the provisioning. We needed something that integrated well with that. We needed a system that had the multitenancy, that understood the tenancy, and that is provided by OpenStack. We found a solution from HPE called Distributed Cloud Networking (DCN) that allows us to carve up the network in all sorts of interesting ways, and that way we don’t have to dictate to the client how to run it.

Many clients are still running traditional networks. The adoption of Virtual Extensible LAN (VXLAN) and other types of SDDC within the network is still pretty low, especially in the mid-market space. So to go to a client and dictate that they have to change how they run the network it is not going to work.

And we wanted it to be as simple as possible. We wanted to treat this as much as we could as a flat network. By using a combination of DCN, Altoline switches from HPE, and some of other software, we were able to give clients a complete network carrying regular Virtual Local Area Networks (VLANs) across it. We then could tie this together in a hybrid fashion, whereby the customers can actually treat our cloud environment as a natural extension of their existing networks, of their existing data centers.

Gardner: You are calling this hybrid storage as a service. It’s focused on object storage at this point, and you can take this into different data center environments. What are some of the sweet spots in the market?

The object service becomes a very inexpensive way to store large amounts of data, and unlike tape — with object as a service, everything is accessible easily.

Weise: The areas where we are seeing the most interest have been backup and archive. It’s an alternative to tape. The object service becomes a very inexpensive way to store large amounts of data, and unlike tape — where it’s inconvenient to access the data — with object as a service everything is accessible very, very easily.

For customers that cannot directly integrate into that object service as supported by their backup software, we can make use of object gateways to provide a method that’s more like traditional access. It looks like a file, or file share, and you edit the file share to be written to the object storage, and so it acts as a go-between. For backup and archive, it makes a really, really great solution.

The other two areas where we seen the most interest have been in the medical space, specifically for large medical image files and archival. We’re working now specifically to build that type of solution, with HIPAA compliance. We have gone through the audits and compliance verification.

The second use-case has been in the media and entertainment industry. In fact, they are the very first to consume this new system and put in hundreds of terabytes worth of storage — they are an entertainment industry client in Burbank, California. A lot of these guys are just shuffling along on external drives.

For them it’s often external arrays, and it’s a lot more Mac OS users. They needed something that was better, and so hybrid object storage as a service has created a great opportunity for them and allows them to collaborate.

They have a location in Burbank, and then they brought up another office in the UK. There is yet another office for them coming up in Europe. The object storage approach allows a kind of central repository, an inexpensive place to place the data — but it also allows them to be more collaborative as well.

Gardner: We have had a weak link in cloud computing storage, which has been the network — and you solved some of those issues. You found a prime use-case with backup and archival, but it seems to me that given the storage capabilities that we’ve seen that this has extensibility. So where it might go next in terms of a storage-as-a service that hybrid cloud providers would use? Where can this go?

Carving up the network

Weise: It’s an interesting question because one of the challenges we have all faced in the world of cloud is we have virtualized servers and virtualized storage, meaning there is disaggregation; there is a separation between the workload that’s running and the actual hardware it’s running on.

In many cases, and for almost all clients in the mid-market, that level of virtualization has not occurred at the network level. We are still nailed to things. We are all tied down to the cable, to the switch port, and to the human that can figure those things out. It’s not as flexible or as extensible as some of the other solutions that are out there.

In our case, when we build this out, the real magic is with the network. That improved connection might be a cost savings for a client — especially from a bandwidth standpoint. But as you get a private cross-connect into that environment to make use of, in this case, storage as a service, we can now carve that up in a number of different ways and allow the client to use it for other things.

For example, if they want to have burst capability within the environments, they can have it — and it’s on the same network as their existing system. So that’s where it gets really interesting: Instead of having to have complex virtual guest package configurations, and tiny networks, and dealing with some the routing of other pieces, you can literally treat our cloud environment as if it’s a network cable thrown over the wall — and it becomes just an extension of the existing network.

We can secure that traffic and ensure that there is high-performance, low-latency and complete separation of tenancy. If you have Coke and Pepsi as clients, they will never see each other.

That opens up some additional possibilities. Some things to work on eventually would be block storage, file storage, right there existing on the same network. We can secure that traffic and ensure that there is high-performance, low-latency and complete separation of tenancy. So if you have Coke and Pepsi as clients, they will never see each other.

Gardner: Very cool. You can take this object storage benefit — and by the way, the cost of that can be significantly lower because you don’t have egress charges and some of the other unfriendly aspects of economics of public cloud providers. But you also have an avenue into a true hybrid cloud environment, where you can move data but also burst workloads and manage that accordingly. Now, what about making this work toward a multi-cloud capability?

Transition to

Cloud-first

HPE Data Center Networking

Weise: Right. So this is where HPE’s DCN software-defined networking (SDN) really starts to shine and separates itself from the pack. We can tie environments together regardless of where they are. If there is a virtual endpoint or physical appliance; if it’s at a remote location that can be deployed, which can act as a gateway — that links everything together.

We can take a client network that’s going from their environment into our environment, we can deploy a small virtual machine inside of a public cloud, and it will tie the networks together and allow them to treat it all as the same. The same policy enforcement engine and things that they use to segregate traffic in microsegmentation and service chaining can be done just as easily in the public cloud environment.

One of the reasons we went to Switch was because they have multiple locations. So in the case of our object storage, we deployed the objects across all three of their data center sites. So a single repository that’s written the data is distributed among three different regions. This protects against a possible regional outage that could mean data is inaccessible, and this is the kind of recent thing that we in the US have seen, where clients were down anywhere from 6 to 16 hours.

One big network, wherever you are

This eliminates that. But the nice thing is because of the network technology that theywere using from HPE, it allowed us to treat that all as one big network — and we can carve that up and virtualize it. So clients inside of the data center — maybe they need resources for disaster recovery or for additional backups or those things — it’s all part of that. We can tie-in from a network standpoint and regardless of where you want to exist — if you are in Vegas, you may want to recover in Reno, or you may want to recover in Grand Rapids. We can make that network look exactly the same in your location.

You want to recover in AWS? You want to recover in Azure? We can tie it in that way, too. So it opens up these great possibilities that allows this true hybrid cloud — and not as a completely separate entity.

Gardner: Very cool. Now there’s nothing wrong, of course, with Switch, but there are other fiber and data center folks out there. Some names that begin with “E” come to mind that you might want to drop in this and that should even increase the opportunity for distribution.

Weise: That’s right. So this initial deployment is focused on Switch, but we do a grand scheme to work this into other data centers. There are a handful of major data center operators out there, including the one that starts with an “E” along with another that starts with a “D.” We do have plans to expand this, or use this as a success use-case.

As this continues to grow, and we get some additional momentum and some good feedback, and really refine the offering to make sure we know exactly what everything needs to be, then we can work with those other data center providers.

Whenever clients deploy their workloads in those public clouds, that means there is equipment that has not been collocated inside one of your facilities.

From the data center operators’ perspective, if you’re one of those facilities, you are at war with AWS or with Azure. Because whenever clients deploy their workloads in those public clouds, that means there is equipment that has not been collocated inside one of your facilities.

So they have a vested interest in doing this, and there is a benefit to the clients inside of those facilities too because they get to live inside of the ecosystem that exists within those data centers, and the private networks that they carry in there deliver the same benefits to all in that ecosystem.

We do plan to use this hybrid cloud object storage as a service capability as a model to deploy in several other data center environments. There is not only a private cloud, but also a multitenant private cloud that could be operative for clients that have a large enough need. You can talk about this in a multi-petabyte scale, or you talk about thousands of virtual machines. Then it’s a question of should you do a private cloud deployment just for you? The same technology, fulfilling the same requirements, and the same solutions could still be used.

Partners in time

Gardner: It sounds like it makes sense, on the back of a napkin basis, for you and HPE to get together and brand something along these lines and go to market together with it.

Weise: It certainly does. We’ve had some great discussions with them. Actually there is a group that was popular in Europe that is now starting to take its growth here in US called Cloud28+.

We had some great discussions with them. We are going to be joining that, and it’s a great thing as well.

The goal is building out this sort of partner network, and working with HPE to do that has been extremely supportive. In addition to these crazy ideas, I also have a really crazy timeline for deployment. When we initially met with HPE and talked about what we wanted to do, they estimated that I should reserve about 6 to 8 weeks for planning and then another 1.5 months for deployment.

Transition to

Cloud-first

HPE Data Center Networking

I said, “Great we have 3 weeks to do the whole thing,” and everyone thought we were crazy. But we actually had it completed in a little over 2.5 weeks. So we have a huge amount of thanks to HPE, and to their technical services group who were able to assist us in getting this going extremely quickly.

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

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Posted in application transformation, big data, Business networks, Cloud computing, data center, Data center transformation, disaster recovery, Enterprise architect, enterprise architecture, Enterprise transformation, Hewlett Packard Enterprise, Information management, Software-defined storage, storage | Tagged , , , , , , , , , , , , | Leave a comment

How IoT and OT collaborate to usher in the data-driven factory of the future

The next BriefingsDirect Internet of Things (IoT) technology trends interview explores how innovation is impacting modern factories and supply chains.

We’ll now learn how a leading-edge manufacturer, Hirotec, in the global automotive industry, takes advantage of IoT and Operational Technology (OT) combined to deliver dependable, managed, and continuous operations.

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

Here to help us to find the best factory of the future attributes is Justin Hester, Senior Researcher in the IoT Lab at Hirotec Corp. in Hiroshima, Japan. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: What’s happening in the market with business and technology trends that’s driving this need for more modern factories and more responsive supply chains?

Hester: Our customers are demanding shorter lead times. There is a drive for even higher quality, especially in automotive manufacturing. We’re also seeing a much higher level of customization requests coming from our customers. So how can we create products that better match the unique needs of each customer?

As we look at how we can continue to compete in an ever-competitive environment, we are starting to see how the solutions from IoT can help us.

Gardner: What is it about IoT and Industrial IoT (IIoT) that allows you to do things that you could not have done before?

Hester: Within the manufacturing space, a lot of data has been there for years; for decades. Manufacturing has been very good at collecting data. The challenges we’ve had, though, is bringing in that data in real-time, because the amount of data is so large. How can we act on that data quicker, not on a day-by-day basis or week-by-week basis, but actually on a minute-by-minute basis, or a second-by-second basis? And how do we take that data and contextualize it?

Justin Hester

Hester

It’s one thing in a manufacturing environment to say, “Okay, this machine is having a challenge.” But it’s another thing if I can say, “This machine is having a challenge, and in the context of the factory, here’s how it’s affecting downstream processes, and here’s what we can do to mitigate those downstream challenges that we’re going to have.” That’s where IoT starts bringing us a lot of value.

The analytics, the real-time contextualization of that data that we’ve already had in the manufacturing area, is very helpful.

Gardner: So moving from what may have been a gather, batch, analyze, report process — we’re now taking more discrete analysis opportunities and injecting that into a wider context of efficiency and productivity. So this is a fairly big change. This is not incremental; this is a step-change advancement, right?

A huge step-change 

Hester: It’s a huge change for the market. It’s a huge change for us at Hirotec. One of the things we like to talk about is what we jokingly call the Tuesday Morning Meeting. We talk about this idea that in the morning at a manufacturing facility, everyone gets together and talks about what happened yesterday, and what we can do today to make up for what happened yesterday.

Why don’t we get the data to the right people with the right context and let them make a decision so they can affect what’s going on, instead of waiting until tomorrow to react?

Instead, now we’re making that huge step-change to say,  “Why don’t we get the data to the right people with the right context and let them make a decision so they can affect what’s going on, instead of waiting until tomorrow to react to what’s going on?” It’s a huge step-change. We’re really looking at it as how can we take small steps right away to get to that larger goal.

In manufacturing areas, there’s been a lot of delay, confusion, and hesitancy to move forward because everyone sees the value, but it’s this huge change, this huge project. At Hirotec, we’re taking more of a scaled approach, and saying let’s start small, let’s scale up, let’s learn along the way, let’s bring value back to the organization — and that’s helped us move very quickly.

Gardner: We’d like to hear more about that success story but in the meantime, tell us about Hirotec for those who don’t know of it. What role do you play in the automotive industry, and how are you succeeding in your markets?

Hester: Hirotec is a large, tier-1 automotive supplier. What that means is we supply parts and systems directly to the automotive original equipment manufacturers (OEMs), like Mazda, General Motors, FCA, Ford, and we specialize in door manufacturing, as well as exhaust system manufacturing. So every year we make about 8 million doors, 1.8 million exhaust systems, and we provide those systems mainly to Mazda and General Motors, but also we provide that expertise through tooling.

For example, if an automotive OEM would like Hirotec’s expertise in producing these parts, but they would like to produce them in-house, Hirotec has a tooling arm where we can provide that tooling for automotive manufacturing. It’s an interesting strategy that allows us to take advantage of data both in our facilities, but then also work with our customers on the tooling side to provide those lessons learned and bring them value there as well.

Gardner: How big of a distribution are we talking about? How many factories, how many countries; what’s the scale here?

Hester: We are based in Hiroshima, Japan, but we’re actually in nine countries around the world, currently with 27 facilities. We have reached into all the major continents with automotive manufacturing: we’re in North America, we’re in Europe, we’re all throughout Asia, in China and India. We have a large global presence. Anywhere you find automotive manufacturing, we’re there supporting it.

Discover How the 

IoT Advantage

Works in Multiple Industries 

Gardner: With that massive scale, very small improvements can turn into very big benefits. Tell us why the opportunity in a manufacturing environment to eke out efficiency and productivity has such big payoffs.

Hester: So especially in manufacturing, what we find when we get to those large scales like you’re alluding to is that a 1 percent or 2 percent improvement has huge financial benefits. And so the other thing is in manufacturing, especially automotive manufacturing, we tend to standardize our processes, and within Hirotec, we’ve done a great job of standardizing that world-class leadership in door manufacturing.

And so what we find is when we get improvements not only in IoT but anywhere in manufacturing, if we can get 1 percent or 2 percent, not only is that a huge financial benefit but because we standardized globally, we can move that to our other facilities very quickly, doubling down on that benefit.

Gardner: Well, clearly Hirotec sees this as something to really invest in, they’ve created the IoT Lab. Tell me a little bit about that and how that fits into this?

The IoT Lab works

Hester: The IoT Lab is a very exciting new group, it’s part of our Advanced Engineering Center (AEC). The AEC is a group out of our global headquarters and this group is tasked with the five- to 10-year horizon. So they’re able to work across all of our global organizations with tooling, with engineering, with production, with sales, and even our global operations groups. Our IoT group goes and finds solutions that can bring value anywhere in the organization through bringing in new technologies, new ideas, and new solutions.

And so we formed the IoT Lab to find how can we bring IoT-based solutions into the manufacturing space, into the tooling space, and how actually can those solutions not only help our manufacturing and tooling teams but also help our IT teams, our finance teams, and our sales teams.

Gardner: Let’s dig back down a little bit into why IT, IoT and Operational Technology (OT) are into this step-change opportunity, looking for some significant benefits but being careful in how to institute that. What is required when you move to a more an IT-focused, a standard-platform approach — across all the different systems — that allows you to eke these great benefits?

Tell us about how IoT as a concept is working its way into the very edge of the factory floor.

Discover How the 

IoT Advantage

Works in Multiple Industries 

Hester: One of the things we’re seeing is that IT is beginning to meld, like you alluded to, with OT — and there really isn’t a distinction between OT and IT anymore. What we’re finding is that we’re starting to get to these solution levels by working with partners such as PTC and Hewlett Packard Enterprise (HPE) to bring our IT group and our OT group all together within Hirotec and bring value to the organization.

What we find is there is no longer a need in OT that becomes a request for IT to support it, and also that IT has a need and so they go to OT for support. What we are finding is we have organizational needs, and we’re coming to the table together to make these changes. And that actually within itself is bringing even more value to the organization.

Instead of coming last-minute to the IT group and saying, “Hey, we need your support for all these different solutions, and we’ve already got everything set, and you are just here to put it in,” what we are seeing, is that they bring the expertise in, help us out upfront, and we’re finding better solutions because we are getting experts both from OT and IT together.

We are seeing this convergence of these two teams working on solutions to bring value. And they’re really moving everything to the edge. So where everyone talks about cloud-based computing — or maybe it’s in their data center — where we are finding value is in bringing all of these solutions right out to the production line.

We are doing data collection right there, but we are also starting to do data analytics right at the production line level, where it can bring the best value in the fastest way.

Gardner: So it’s an auspicious time because just as you are seeking to do this, the providers of technology are creating micro data centers, and they are creating Edgeline converged systems, and they are looking at energy conservation so that they can do this in an affordable way — and with storage models that can support this at a competitive price.

What is it about the way that IT is evolving and providing platforms and systems that has gotten you and The IoT Lab so excited?

Excitement at the edge  

Hester: With IoT and IT platforms, originally to do the analytics, we had to go up to the cloud — that was the only place where the compute power existed. Solution providers now are bringing that level of intelligence down to the edge. We’re hearing some exciting things from HPE on memory-driven computing, and that’s huge for us because as we start doing these very complex analytics at the edge, we need that power, that horsepower, to run different applications at the same time at the production line. And something like memory-driven solutions helps us accomplish that.

It’s one thing to have higher-performance computing, but another to gain edge computing that’s proper for the factory environment.

It’s one thing to have higher-performance computing, but another thing to gain edge computing that’s proper for the factory environment. In a manufacturing environment it’s not conducive to a standard servers, a standard rack where it needs dust protection and heat protection — that doesn’t exist in a manufacturing environment.

The other thing we’re beginning to see with edge computing, that HPE provides with Edgeline products, is that we have computers that have high power, high ability to perform the analytics and data collection capabilities — but they’re also proper for the environment.

I don’t need to build out a special protection unit with special temperature control, humidity control – all of which drives up energy costs, which drives up total costs. Instead, we’re able to run edge computing in the environment as it should be on its own, protected from what comes in a manufacturing environment — and that’s huge for us.

Gardner: They are engineering these systems now with such ruggedized micro facilities in mind. It’s quite impressive that the very best of what a data center can do, can now be brought to the very worst types of environments. I’m sure we’ll see more of that, and I am sure we’ll see it get even smaller and more powerful.

Do you have any examples of where you have already been able to take IoT in the confluence of OT and IT to a point where you can demonstrate entirely new types of benefits? I know this is still early in the game, but it helps to demonstrate what you can do in terms of efficiency, productivity, and analytics. What are you getting when you do this well?

IoT insights save time and money

Hester: Taking the stepped strategy that we have, we actually started at Hirotec very small with only eight machines in North America and we were just looking to see if the machines are on, are they running, and even from there, we saw a value because all of a sudden we were getting that real-time contextualized insight into the whole facility. We then quickly moved over to one of our production facilities in Japan, where we have a brand-new robotic inspection system, and this system uses vision sensors, laser sensors, force sensors — and it’s actually inspecting exhaust systems before they leave the facility.

We very quickly implemented an IoT solution in that area, and all we did was we said, “Hey, we just want to get insight into the data, so we want to be able to see all these data points. Over 400 data points are created every inspection. We want to be able to see this data, compared in historical ways — so let’s bring context to that data, and we want to provide it in real-time.”

Discover How the 

IoT Advantage

Works in Multiple Industries 

What we found from just those two projects very quickly is that we’re bringing value to the organization because now our teams can go in and say, “Okay, the system is doing its job, it’s inspecting things before they leave our facility to make sure our customers always get a high-quality product.” But now, we’re able to dive in and find different trends that we weren’t able to see before because all we were doing is saying, “Okay, this system leaves the facility or this system doesn’t.”

And so already just from that application, we’ve been able to find ways that our engineers can even increase the throughput and the reliability of the system because now they have these historical trends. They were able to do a root-cause analysis on some improvements that would have taken months of investigation; it was completed in less than a week for us.

And so that’s a huge value — not only in that my project costs go down but now I am able to impact the organization quicker, and that’s the big thing that Hirotec is seeing. It’s one thing to talk about the financial cost of a project, or I can say, “Okay, here is the financial impact,” but what we are seeing is that we’re moving quicker.

And so, we’re having long-term financial benefits because we’re able to react to things much faster. In this case, we’re able to reduce months of investigation down to a week. That means that when I implement my solution quicker, I’m now bringing that impact to the organization even faster, which has long-term benefits. We are already seeing those benefits today.

Gardner: You’ll obviously be able to improve quality, you’ll be able to reduce the time to improving that quality, gain predictive analytics in your operations, but also it sounds like you are going to gain metadata insights that you can take back into design for the next iteration of not only the design for the parts but the design for the tooling as well and even the operations around that. So that intelligence at the edge can be something that is a full lifecycle process, it goes right back to the very initiation of both the design and the tooling.

Data-driven design, decisions

As you loop this data back to our engineering teams — what kind of benefits can we see, how can we improve our processes, how can we drive out into the organization?

Hester: Absolutely, and so, these solutions, they can’t live in a silo. We’re really starting to look at these ideas of what some people call the Digital Thread, the Digital Twin. We’re starting to understand what does that mean as you loop this data back to our engineering teams — what kind of benefits can we see, how can we improve our processes, how can we drive out into the organization?

And one of the biggest things with IoT-based solutions is that they can’t stay inside this box, where we talked about OT to IT, we are talking about manufacturing, engineering, these IoT solutions at their best, all they really do is bring these groups together and bring a whole organization together with more contextualized data to make better decisions faster.

And so, exactly to your point, as we are looping back, we’re able to start understanding the benefit we’re going to be seeing from bringing these teams together.

Gardner: One last point before we close out. It seems to me as well that at a macro level, this type of data insight and efficiency can be brought into the entire supply chain. As you’re providing certain elements of an automobile, other suppliers are providing what they specialize in, too, and having that quality control and integration and reduced time-to-value or mean-time-to-resolution of the production issues, and so forth, can be applied at a macro level.

So how does the automotive supplier itself look at this when it can take into consideration all of its suppliers like Hirotec are doing?

Start small 

Hester: It’s a very early phase, so a lot of the suppliers are starting to understand what this means for them. There is definitely a macro benefit that the industry is going to see in five to 10 years. Suppliers now need to start small. One of my favorite pictures is a picture of the ocean and a guy holding a lighter. It [boiling the ocean] is not going to happen. So we see these huge macro benefits of where we’re going, but we have to start out somewhere.

Discover How the 

IoT Advantage

Works in Multiple Industries 

A lot of suppliers, what we’re recommending to them, is to do the same thing we did, just start small with a couple of machines, start getting that data visualized, start pulling that data into the organization. Once you do that, you start benefiting from the data, and then start finding new use-cases.

As these suppliers all start doing their own small projects and working together, I think that’s when we are going to start to see the macro benefits but in about five to 10 years out in the industry.

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