Debugging a Kubernetes Cluster on Christmas Eve

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Christmas Eve, 2016. I’m sitting in my home office, sipping eggnog and trying to keep warm despite the blizzard outside. The holiday spirit is high, but so are the stakes. Our team at Red Hat had just deployed our first Kubernetes cluster, and it was acting up.

It all started innocently enough. We were testing out a new feature for our platform, which involved setting up an isolated development environment using Kubernetes. We used Helm to manage deployments and everything seemed to be going smoothly until I got a call from one of the dev teams: “Hey Brandon, our pods are just hanging there.”

At first, it felt like a minor hiccup, but as the day wore on, more and more teams reported issues. My phone was non-stop, with urgent calls and emails pouring in.

The cluster was running fine when I checked at 6 PM, but by midnight, half of our applications were offline. The Kubernetes dashboard showed healthy nodes, so it couldn’t be a node issue. I started digging through the logs, hoping to find some breadcrumbs that would lead me to the culprit.

After a few hours of wading through container output and Kubernetes event logs, I found something peculiar: a pattern in the timestamps. The pods were failing just after they were scheduled by the scheduler. Could it be an issue with how we configured our pods or deployments? Or maybe some misconfiguration in Helm?

I decided to dive deeper into one of the failing services. I used kubectl describe pod to gather more information, but what I found was not comforting: the root cause wasn’t a config issue, it was a networking problem.

It turned out that due to a recent update to our network infrastructure, we hadn’t properly configured the Kubernetes service to route traffic correctly. The pods were being created and scheduled just fine, but they couldn’t connect to other services in the cluster or outside of it.

This was a classic case of “works on my machine” syndrome. I had been testing locally where everything was working perfectly, but we hadn’t thoroughly tested the deployment with all the network changes.

I quickly put together a fix and applied it using kubectl apply to the services in question. Within minutes, pods started coming back online. Relief washed over me as I saw teams starting to report that their applications were up again.

But this wasn’t just about fixing the immediate issue; it was about learning from it. We needed better processes for managing network changes and ensuring they didn’t impact our Kubernetes deployments. We updated our playbook to include more rigorous testing in staging environments before rolling out changes.

Looking back, it’s easy to see how a small network tweak could have such wide-reaching effects. This incident highlighted the importance of thorough testing and the complexity that comes with containerized systems like Kubernetes. It was also a reminder that even seasoned engineers can get caught up in their own assumptions—hence the need for robust verification practices.

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That’s the story of a Christmas Eve crisis, solved by sheer grit and a little bit of luck. As 2017 approached, I reflected on how quickly technology was evolving, with Kubernetes at the heart of it all. The year ahead promised to be just as exciting—and challenging—as the one that had just passed.