Does OS Context Switching Affect Pod Performance?

Daemonset for load and performance balancing is a bit of a no-go—deployment is the way to go here.

CPUs are pretty quick, so it’s good to monitor your CPU load to see if you need more cores. However, running a daemonset for everything might be overkill—16 replicas of each service sounds excessive. Consider using deployments instead and adjusting the number of replicas per service. This can save resources and allow CPU-heavy workloads to get more CPU. Also, check out pod disruption budgets to make node draining simpler for updates.

The deploy versus daemonset debate is secondary if you’re not measuring your actual needed scale. You could set anti-affinity rules on your deployments and end up in a similar situation as now. Running multiple pods on the same node works fine for uptime, but you'll need more nodes for better performance.

Context switches are a natural part of workloads and not directly tied to the number of processes. I wouldn’t worry unless issues arise. Typically, deployments are better for scaling applications, and you could use Horizontal Pod Autoscaling (HPA) for spikes, along with pod disruption budgets to keep some always up.

Yeah, it can affect performance, but the impact is usually small. If you’re really looking to optimize, daemonsets aren’t the key. Explore Kubernetes CPU Manager and think about NUMA awareness, especially for latency-sensitive workloads.

Using a daemonset for load balancing isn't the best approach. Switching to deployments might be more efficient. It seems like you're accidentally creating too many pods for smaller apps while not having enough for larger ones. Your concern is valid, but you could try scaling down the number of pods and allocating more resources to see if it reduces context switch overhead.