4.0 is The Convergence of All Tech Superpowers

by February 13, 2020 0 comments

Chris Wolf, Vice President and CTO, Global Field & Industry, VMware, talks about a host of issues including their cloud journey, the rising power of Kubernetes, the promise of 5G and what Industry 4.0 means for the tech industry.

The Cloud Journey 

We started on this journey about six years ago. We were connecting and working with organisations that were operating in two or more clouds for two or more years. That was kind of our criteria. We asked them: What are the problems you want us to solve? They turned out to be cost management, network, security and policy enforcement. They were trying to go cloud by cloud and to figure these things out on their own. It was very difficult to manage and scale. Our approach is to say, every cloud has unique intrinsic value. Every cloud is adding new capabilities on a daily basis. You’re never going to be able to do everything across all cloud. So you pick the things or the problems that customers want solved. You focus on that.

The Hybrid Cloud

Hybrid cloud is about having a consistent infrastructure and operational model anywhere you would want to run applications. We have the same infrastructure, same management, same tools, same processes for our applications, whether it’s in an AWS data centre or out an Edge site or anything in between. From an integration perspective, if I land an application in AWS and I want to hook that application into AWS Lambda, or Amazon RDS or any other services, you can do that. You have a lot of flexibility in how you compartmentalise different parts of the application stack. Not every customer and every application is going to land on the VMware fabric.

Chris Wolf, Vice President and CTO, Global Field & Industry, VMware

Chris Wolf, Vice President and CTO, Global Field & Industry, VMware

SMEs and their challenges

When it comes to SMEs in many cases, they have a smaller IT staff. They have to do much more with less people. They can be more aggressive in terms of trying to embrace new technologies that can give them more efficiency. It also applies to large enterprises, to always think about flexibility as a design principle. It can be appealing to say: I’m going to build the entire stack, all in this cloud, using all of their native tools and APIs. This can add a lot of business value, but at the same time that might make you not have some additional options in the future.

The ubiquitous Kubernetes

Kubernetes is highly strategic. The underlying container technology has for long had a value proposition of being able to build an application and run it anywhere. The technology has started to mature and you’re seeing a much broader ecosystem come in around those core capabilities. We have been driven to ensure that we cannot just run an application anywhere, but operate it anywhere, which is often harder. How do we enforce security policy? How do we do backup? How do we do change management? So when I can have that consistency, this is where this technology becomes really important.

When I build an application using upstream open source Kubernetes as the orchestration layer, I can deploy that application to cloud, I can deploy it to a data centre, I can deploy to an Edge site. As my business needs change, I have the same agility for my applications and that’s why Kubernetes is so important. As we start to build a richer developer services ecosystem, as a platform, you can see the Kubernetes community, potentially having even greater velocity than you see with the public cloud today in terms of what a single provider can do on his own. That’s very powerful from a business and strategy perspective that I can build all this intellectual property. And I can maintain all of this flexibility and control in terms of where I want to run that that those applications and services I’m creating.

5G: More data in more places

5G is really exciting because it means having broader, richer connectivity to more places allows us to get applications and data practically anywhere at an incredibly low cost. That can disrupt a number of markets. That gives more access to more technology, into more online services, whether that’s streaming videos or other personal services. There are lots of complementary technologies that are helping as well from a networking perspective. Our VeloCloud solution can dramatically help reduce networking costs, especially on some of the dependencies on heart circuits and improve performance.

We are making a lot of investments around 5G. We’ve had projects where we’re looking to virtualize 5G networks. From a telco provider perspective, as we create these circuits, we might want to be able to take full advantage of the bandwidth of those circuits. There’s definitely some debate on what 5G does in terms of how we actually build our solutions. Some people would say once we have 5G, we can literally just collect data from all these different places and just run it centrally. But I think it’s at the end of the day is going to be the opposite. Because we have all this ubiquitous connectivity, it’ll actually make it easier for us to have more data in more places, not more data in lesser places.

New ways of using data

I think the most obvious example is autonomous vehicles, but we see more practical examples where if I can build a Machine Learning model, I can actually deploy it close to where I’m collecting data and make some spot decisions about things. We have a customer operating autonomous trains. We have another customer that has cameras in the jetway of an airport. The camera is actually counting the suitcases getting rolled down the jetway. So they know after so many suitcases, the overhead bin space on the plane will get full. So the gate agents can just start checking the suitcases and putting them under the plane. The business benefit to that is to get the planes off the gate faster. You could apply more planes through that gate on a given day. That helps the bottom line of the airline.

Using ML to the max

Looking at ML, we’ve been focusing in three specific areas. One, we’re running ML algorithms against the various data sources that we collect. We’re getting feedback from customers and our global support services. We’re getting feedback from industry analysts logging across our different product sets. We’ve been using ML technologies to understand something as basic as: What are the most important features that we should add in the next version of the product? We can really analyse all of these different data sets and make really smart decisions.

Then there are smart products. We’ve been baking a lot of ML capabilities into the products. A great example is our acquisition of Carbon Black, which runs a massive data lake. We can stop, on average, up to a million attacks a day. We’ve added ML capabilities into our vRealize Operations tool. Finally we have smart customers. We’ve been ensuring that any of the ML technologies that they want to run anywhere is fully supported on our stack. We’ve had a lot of successes there. We already have customers that have built ML models into Google Cloud and they deploy them using TensorFlow on premises fully supported on VMware. And so on. There are open source projects too.

4.0: Democratisation of innovation

There is some debate: Are we in the third or fourth industrial revolution? We see Industry 4.0 as the convergence of all of these superpowers of technology: Cloud, mobile, IoT and AI-ML. What’s significant now is that we expect just the sheer volume of applications to have more than doubled in the next five years. We see a massive growth in terms of innovation, velocity and just a number of applications. Why you can say this is a new industrial revolution is the algorithms that we’ve been applying to technology such as AI have been around for decades but in the past we’ve not been able to scale them. But now that we have all this super dense, high performance, accessible compute power means that we can do some really incredible things. From making split second decisions based on an ML algorithm and data feed in real time, to increasing use of our mobile phones to present Augmented Reality and changing the way we’re experiencing both life and technology.

A key attribute of this fourth industrial revolution is that innovation has become democratised. We’ve hit a point now anybody with a great idea can participate in innovation, no matter where you are in the world. Look at small groups of developers that have made incredible applications in the iOS App Store and they just go viral and take off. Angry Birds was another such example.

Car companies are saying: Why can’t my car be an application platform? Why can’t I have an app store for my car? Think about your phone, once you once you start down the path with either an Android device or an iOS device, it becomes a lot harder to switch, so automobile manufacturers would try to build that same type of customer affinity around their platforms.

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