Explained: Node Affinity in Kubernetes

When you deploy a workload to a Kubernetes cluster, the scheduler makes a decision: which node should run this pod? By default it balances across available nodes, picking whichever has the capacity. Most of the time that's fine. But in the real world, infrastructure is rarely uniform. You've got GPU nodes for ML workloads, high-memory nodes for caching tiers, nodes in specific availability zones for compliance, and bare-metal nodes for … Read More

Explained: Taints and Tolerations in Kubernetes

"Not every workload belongs on every node. Taints and tolerations are how Kubernetes enforces that." The Problem They Solve Imagine your cluster has a mix of nodes: some with expensive GPUs, some reserved for critical production workloads, and some designated for a specific team. By default, Kubernetes' scheduler is happy to place any pod on any node — it just looks for available resources. That's a problem. You don't want a b… Read More