Kubernetes

My dashboard is a wall of green. Pods running, replicas matched, CPU comfortable, no alerts firing. I look at it and feel that small dopamine hit of “everything is fine.” And for the most part, it is fine. The cluster has been up for weeks. Nothing has fallen over. That green wall is also the most dangerous thing in my homelab, because it tells me nothing about what happens when something goes wrong. It only tells me that, right now, nothing has. ...

What happens when your Kubernetes cluster can’t reach the internet? I don’t mean a slow connection. I mean no connection at all. Ships at sea. Remote mining sites. Factory floors with air-gapped networks. Military deployments. For a lot of people that sounds exotic, like a problem someone else has. I treat it as a baseline design requirement, and I’ll explain why it makes my homelab better even though I almost never actually pull the cable. ...

Everyone repeats the line that Kubernetes is self-healing. Pods die, they come back. Nodes drop, workloads reschedule. The system reconciles itself toward the state you declared, and most days you never have to think about it. Then one day the thing doing the healing is the thing that broke. The API server is down. etcd won’t respond. The scheduler is wedged. Now what? This is the question I actually care about, because “self-healing” is only useful if I understand its edges. I want to know what degrades gracefully and what takes the whole cluster with it. So I’ve run my clusters through a lot of failures on purpose: planned, unplanned, and a few “hold my beer” experiments on hardware I didn’t mind losing. Here is what actually happens when each piece breaks, and why most of it matters less than people fear. ...

When something goes wrong in Kubernetes, the trail usually leads back to etcd. API server timing out? Check etcd. Pods stuck in pending? Might be etcd. Cluster feels sluggish? Probably etcd. For a long time I treated etcd the way most operators do: as a black box that hums along next to the control plane. “The database.” You back it up and otherwise leave it alone. But black boxes feel like splinters to me, and the first time an etcd cluster fell over at 2am I realised I had no idea what I was actually looking at. So I learned. And it turns out the whole thing is built on a handful of ideas that, once they click, make most etcd problems diagnosable instead of terrifying. ...

The first “production” Kubernetes cluster I ran had a single control plane node. It hummed along happily for weeks, right up until a disk failed and took the whole thing with it. Every pod, every service, gone. That outage taught me what “single point of failure” actually feels like, and it pushed me toward a question that I keep seeing trip people up: when you build a cluster that survives node loss, do you run etcd on your control plane nodes, or on dedicated nodes of its own? ...