Does Increasing Pods Impact CPU Performance in Kubernetes?

I totally agree! Using a daemonset like that isn’t its intended purpose. It might lead to having too many pods for small applications and not enough for larger ones. Swapping to deployments could help manage your load distribution more effectively. Besides, reducing the number of pods but increasing their resources might help reduce overhead from context switches.

In terms of context switching, yes, it might have an impact but generally it’s small. The real concern is how you’re managing your pods—daemonsets might not be the best for optimization. Investigate Kubernetes CPU Manager and look into NUMA awareness for really latency-sensitive tasks.

Remember, context switches are just a natural outcome of your workload. They’re influenced more by the nature of what you’re running rather than just the number of processes. If you're worried about scaling, deployments usually handle such loads better and Horizontal Pod Autoscaling could be a helpful feature to manage spikes.

You might want to keep an eye on CPU usage. CPUs are pretty fast, so load monitoring can help determine if you need more cores. But honestly, having a daemonset for everything could be your main issue. Running 16 replicas of every service seems excessive. It might be better to switch to deployments with a sensible number of replicas per service. This could streamline your resources—consider using pod disruption budgets to make updating the nodes easier.

Yeah, using a daemonset for load or performance balancing is not ideal. Just switch to deployment and measure what you actually need. Even with multiple pods on a node, if you use anti-affinity rules, you might manage to maintain availability. But you definitely need to consider having a few more nodes for better performance.