Simplifying Docker and envisioning an invisible Kubernetes
Discover insights into the future of platform engineering and DevOps with Ivan Pedrazas, Principal Engineer at Docker.
In this interview, Ivan discusses:
The challenge of managing complexity and knowledge gaps in the platform space to reduce cognitive load and assist teams in problem-solving.
The importance of hands-on experience, making mistakes, and continuous practice for effective learning.
His vision of Kubernetes as an invisible framework enables a shift in focus from managing infrastructure to building applications.
Transcription
Bart: Who are you? What's your role? And who do you work for?
Ivan: My name is Ivan Pedrezas. I'm a principal engineer at Docker.
Bart: What are three emerging Kubernetes tools that you're keeping an eye on?
Ivan: Timoni is probably the one that I'm most excited about. It's very different from what we've seen. Crossplane is the other one for all the platform engineering things. And last but not least, the K8sGPT project is really interesting. It's trying to solve a problem that we have in Kubernetes by applying AI, which is something I've been doing for the last month. Looking at AI and how it can help us to be better.
Bart: One of our guests, Ori, shared that rushing into solutions without understanding the root cause can lead to fixing symptoms instead of the actual problem. He mentioned the case of network policies and how sometimes the root cause of a problem is a people problem, and the solution lies in addressing that. What is your experience with providing tooling and platforms on Kubernetes to other engineers? What are some of the soft challenges that you faced?
Ivan: The biggest challenge that we face by far is knowledge or lack of expertise. And complexity. The last month I've been basically doing research about complexity theory at Docker, particularly in the platform space. It's like, why it happens? Number of elements, number of relationships, number of dependencies, number of contexts. All these things have a huge impact on increasing the complexity. And as you can see in the CNCF Landscape, we have a lot of many things. So it's how we can help to reduce the cognitive load, not a different cognitive load from complexity, but how we can help teams to adopt and solve problems.
Bart: Another guest, Mathias, suggests that the best way to learn Kubernetes is by doing and getting your hands dirty. He built his own Bare-metal Kubernetes cluster in his spare time. What's your strategy for learning new Kubernetes tools and features?
Ivan: The best way of learning is by getting your hands dirty and breaking things. Once you get the frustration of why something doesn't work, it's usually a signal that you may not understand something. Then you have to go and learn, and by learning, you start being more confident about the problem and the solutions. So, doing, doing, and doing.
Bart: Kubernetes is turning 10 years old this year.
Ivan: We always talk about Kubernetes being a framework where people should build things on top. I hope in the next 10 years, we turn Kubernetes into something invisible and focus more on all the things we want to build on top. Talk more about applications, talk less about all the plumbing and the need.
Bart: What's next for you?
Ivan: We've been looking a lot at... GenAI and how it can help change the way we work and improve the platform engineering and DevOps space. We've been through all these changes. We got Virtualization, Docker, and Kubernetes. So I don't see GenAI or AI as a threat. I see it more as a transformation. We're going to do much more, much faster. I'm really excited about that.
Bart: How can people get in touch with you?
Ivan: The best way is Twitter. My handle is Ipedrazas. Nobody can pronounce my name. So I hope that you can write it and people can link it.
