This interview with Data on Kubernetes Ambassador, Alex Lines, is part of series where we learn where each of our DoK Ambassadors got their start in open source and the Data on Kubernetes Community. Alex also tells his thoughts on the future of Data on Kubernetes.
What’s your name and what’s your day job?
(00:05) My name is Alex Lines. As my day job, I am part of a business development and go-to-market team at Amazon Web Services or AWS working on our Amazon EKS product, which is our elastic Kubernetes service to manage Kubernetes service that provides open source Kubernetes, but with an AWS managed control plane. So my day job is actually related to Kubernetes and even more within that related to data on Kubernetes. So I lead an open source project and initiative that we call data on EKS. Very similarly to the data on Kubernetes community, helping customers run the most common data and ML workloads or applications that we see customers building on EKS. We build open source patterns to help with that.
What are you passionate about outside of work?
(00:54) So I grew up playing baseball and now that my son is going to turn seven in the summer, spending a lot more time with baseball, kind of rekindling that to an extent and I love surfing. That’s been more of a recent passion of mine in the past four years, have put a lot more time into that and cooking in the wintertime. I get more into it in the summer. It’s more for sustenance what I have time for, but I’d say those are kind of the big three for me.
How did you get into open source?
I have been working on Amazon EKS for two, two and a half years now, and that’s really what drew me to open source. So I had been at Amazon for a long time before that and then I showed up and realized this is the first time I had really recognized kind of the passion of the open source community and also its effectiveness for developing. It’s kind that idea of the internet is undefeated, right? You have so many people taking cracks at jokes. You have so many people working on problems when they have the same set of code. The pace of innovation that comes from open source is really fascinating. And I would say that’s what drove me to it.
What drew you to the Data on Kubernetes community?
(02:02) Like I mentioned before. So I work on this data on EKS initiative and there’s a ton of overlap there. And while in my day job I’m helping AWS customers, the problems as it relates to running something like Apache Spark on Kubernetes are the same. And I wanted to get more involved with the community because, well, we could help our AWS customers. There’s a lot of improvement, a lot of innovation that can be done in the community overall. And there’s been a lot of progress already, but I just wanted to be part of taking that forward, helping to explore these best practices and, sorry, yeah, I call it best practice. I guess some people don’t like that term, explore the best way to get these things done and start to develop better ways to get them done.
What is the future of Data on Kubernetes?
(02:50) I think that the future is, everyone is talking about machine learning and generative AI in particular, and I think that that is certainly where things are headed, but data is foundational to get there. So I am really, really bullish on data processing becoming something that more people are doing with Kubernetes because not only do you need data processing for machine learning, you also need that for all of your business processes, whether it’s back of the house, financial bookkeeping or something like large scale financial simulations or pharmaceutical research. I really think that the data processing element is something that’s really important. And Kubernetes, while there’s some challenges right now, there’s a lot of benefits that can be gained from running these things on Kubernetes. So I think that’s where I think there’s going to be a lot of innovation in the coming years.
