What Are the Biggest Challenges in Managing Kubernetes Clusters?

Setting appropriate resource requests and limits is critical. Beyond that, managing local disks and network PVCs, and ensuring everything is up-to-date can be quite overwhelming.

One major issue is resource management. We've had instances where pods were getting OOMKilled because developers didn’t set proper memory limits. Another big problem is the reliance on the 'latest' tag for deployments; it's a recipe for disaster! Always pin down your versions to avoid surprises. Don't forget about network policies too—they're often overlooked in the chaos.

If you’re running on bare metal, be prepared for a tough ride. It requires a lot of careful monitoring of your control planes and core API services, which adds another layer of complexity on top of everything else.

Resource allocation can get pretty messy. We faced challenges with handling massive traffic spikes, going from 50 requests per second to 400,000! We eventually found a tool called Thoras.ai that predicts traffic better. This isn't an ad, just a tip from our experience!

Using the latest AWS AMI versions has led us to some serious outages. Now we hardcode these versions and test them in staging before rolling them out. Keeping clusters updated can also be tricky, but with Infrastructure as Code, we can automate updates across multiple clusters easily. Also, configuring node pools properly is key to avoiding distractions—once you get Karpenter set up, it really helps with resource allocation.