$ cat post/cold-bare-metal-hum-/-i-ssh-to-ghosts-of-boxes-/-it-ran-in-the-dark.md

cold bare metal hum / I ssh to ghosts of boxes / it ran in the dark

Title: Kubernetes vs. Legacy: A Tale of Two Worlds

May 7th, 2018 was just another day in the life of an ops engineer who was knee-deep in legacy systems, but with a growing interest in modern container orchestration. The battle for dominance between traditional and cutting-edge technology seemed to be heating up every day, and I found myself on both sides of that divide.

On one hand, I had been working with Kubernetes for months now, trying to get our monolithic applications to fit into the world of microservices. The promise was clear: self-healing, auto-scaling containers would make deployments a breeze. But like many early adopters, we ran into roadblocks left and right. Configurations were tricky, and debugging could be a nightmare when a pod refused to come up.

On that day, I was troubleshooting an issue with our Kubernetes deployment on one of the bigger projects. We had recently moved this particular service over from its home in the legacy cluster to the new Kubernetes cluster, but we were getting mysterious connection timeouts whenever we tried to access it. The logs showed no errors, and all other services seemed to be functioning normally.

I spent hours pouring over manifests, examining service mesh configurations, and trying different network policies, but nothing seemed to help. It was a frustrating cycle: change something, test, realize it didn’t fix anything, revert the changes, try something else. The more I debugged, the more I realized that while Kubernetes had plenty of features, its complexity could be overwhelming.

Just as I was about to pull out my hair (yes, literally), one of our developers walked by and noticed an old-school Nagios alert popping up on a screen. “Hey,” he said, “didn’t you say this service used to have issues with the old cluster? Could it just be timing out because of some weird legacy networking thing?”

That was when I realized that sometimes, in tech, the simplest solutions are the most effective. With a fresh perspective and a bit of help from our trusty old Nagios, we quickly traced the problem to an outdated DNS configuration. Once fixed, everything worked as expected.

This experience highlighted two things for me:

  1. Legacy Systems Are Not So Bad: While I was eager to move away from our legacy systems, they still had their value in certain situations. Sometimes, what works is a mix of new and old—both have their strengths that can complement each other.

  2. Kubernetes Isn’t Perfect Yet: Despite its promise, Kubernetes wasn’t without its quirks. The learning curve was steep, and the complexity could be daunting. But with time and practice, these issues would become more manageable.

As I wrote up a ticket for our infrastructure team to review the DNS setup, I couldn’t help but think about the tech stories that had been making headlines this month. Google Duplex’s AI capabilities seemed so far removed from my current struggles, yet both highlighted how technology is constantly evolving and changing our world in unexpected ways.

In the end, Kubernetes won out for us that day—thanks to a little bit of old-fashioned troubleshooting. But the lesson was clear: while modern tools like Kubernetes are powerful, they’re not magic solutions. Sometimes, a good ol’ fashion problem-solving session with some help from your trusty legacy tools can be just what you need.

That’s my personal take on tech in 2018, Kubernetes vs. legacy, and the reality of ops work. Hope this adds to the conversation!