Scheduler filtering and scoring phases
WHAT IT TESTS: how Pods get placed on Nodes. OUTLINE: filtering eliminates infeasible Nodes via resources, taints, and affinity, then scoring ranks the survivors to pick the best, after which the Pod is bound.
WHAT IT TESTS: whether you understand the two-stage scheduling pipeline. ANSWER OUTLINE: filtering, also called predicates, removes Nodes that cannot run the Pod, considering free CPU and memory, node selectors and required affinity, taints the Pod does not tolerate, and volume constraints. Scoring, also called priorities, ranks the remaining feasible Nodes by criteria like least or most used resources, preferred affinity, and spreading, then the scheduler binds the Pod to the highest-scoring Node.
Read the original → interview
- #kubernetes
- #scheduler
- #affinity
- #taints
- #scheduling
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