Interview with Nicolas Chaillan: Container Technology Paves the Way to a New Era of Avionics Software

Benefits of Containers for Organizations

I think it’s not really an issue, whether or not to use containers. Organizations don’t have a choice. Otherwise, they cannot keep up. You’re going to be causing a massive negative impact to your velocity if you don’t embrace the modern way of building software. By being modular and flexible, containers have the ability to update software multiple times a day, enabling tremendous capabilities for deployment. It works well with jets, and other aircraft. My team and I were the first ones to put Kubernetes on jets and then update software while flying the jet. We also put AI on the jet without changing the architecture and keeping the legacy hardware. Having the ability to decouple the flight control — that doesn’t really need to change — and bring in new capabilities as a separate set of containers enables you to update those containers rapidly, without impacting the airworthiness of the aircraft. And it’s not only the modularity, and the reuse across teams, and your ability to receive — particularly if you’re a larger organization. You also see the benefit of security. I think this is a game-changer — especially when moving to zero trust, which I think everybody should.

Wanted: More Tools and Understanding

The adoption of containerization, and Kubernetes as a container orchestration stack, is obviously complex because of the complete change of thinking and culture. Software is a factor, both in terms of architecture design and the effort of going to modular architecture. The software is more flexible and nimble, but it is also different in terms of tools and our understanding of everything that we know. There’s definitely a massive talent gap. It’s a big issue. People are realizing that they have no choice but to reinvent themselves every year. I argue that first you need to catch up, and then you need to keep up. And it’s funny how we underinvest in our people. It reminds me of this meme where you have a CTO saying, “What if we invest in our people and they leave?” And the CEO says, “Well, what if we don’t invest in them and they stay?”

Insights from Simulation and Modeling

A digital twin exponentially enhances modeling and simulation. It empowers teams to know exactly how the system is going to behave before bending metal. A lot of people look at software agility and forget that you can do a lot with that. You don’t have to always be in a waterfall universe in hardware. You can now easily swap hardware, swap compute with a rack or some type of easily replaceable hardware, or increase storage capability — on jets, on ships, you name it. We have to demonstrate the value of being able to do that. A digital twin is going to show you exactly how the system is going to behave.

Accelerating Change

The velocity of change used to be in a 20-year cycle, maybe 10. But now it has really accelerated drastically, to the point where a startup can show up and disrupt an entire market. We’ve seen this with Uber and many other examples, such as Netflix. Big companies had the opportunity to buy them, and they missed the boat. Then they pay the price — and suddenly they don’t exist anymore. We laugh about it, but I can tell you that I think this effect is going to grow. With embedded systems, particularly in the fast-moving avionics sector — if you don’t have that knowledge on a day-to-day basis, you’re not going to be able to compete. Today, some organizations are getting away with ignoring the issue, but it doesn’t mean you should.

The Concept of “Software Defined”

The term software defined is great. To me, it sounds like something that will be nimble and more agile and less stuck in time. Like Tesla: You buy a car. It might be four years old, but you are still getting new features. That’s really something that was created by Tesla and no one else. You can buy any other brands and the software updates you get, if any, are mostly bug fixes. You would never see a new feature show up magically on your dashboard. But that is the kind of world people are getting used to living in. Software defined tells me that it’s nimble, it’s agile, it’s decoupled from hardware, and it’s able to move at a pace of relevance. It’s intangible in terms of the physical world, in terms of being stuck with hardware or legacy constraints.

Strengthening Embedded Systems with AI Capabilities

Paying attention to the capabilities we’re building in terms of continuous integration, scanning, and testing…. I think the world is moving to a continuously monitored universe of behavior detection using AI capabilities. Increasingly, we’re going to have the ability to bring this stuff up on smaller footprints. Embedded systems have limited memory, but there’s enough nowadays to do some cool, lightweight AI behavior detection. With this feature, we can see exactly what’s going on and proactively detect malicious behavior that scanners would not be able to detect.

Containerization and AI/ML

When it comes to containerization in the future, I think the important point is how it is going to streamline the adoption of artificial intelligence and machine learning. They are both dependent on containerization and the scalability of containers. I think having the enabler baked in, and having the ability to do machine-learning operations and deploy models rapidly — as containers — is just the right way to do business.

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