Q: How do you protect Kubernetes API servers from being overloaded by misconfigured tenant operators, CI/CD polling scripts, or massive burst scaling events, and how do you tune API Priority and Fairness (APF) to safeguard critical control plane operations?

Understand Kubernetes APF architecture: incoming requests are classified into FlowSchemas and assigned to PriorityLevelConfigurations (e.g., exempt, system-high, workload-high, catch-all). Each priority level defines a concurrency limit and fair queuing parameters.

kubectl get flowschemas
kubectl get prioritylevelconfigurations

Create custom FlowSchemas that match tenant service accounts and CI runner tokens, routing their requests to a throttled priority level (workload-low or ci-burst). This ensures rogue tenant list requests encounter HTTP 429 Too Many Requests before degrading system controllers.

apiVersion: flowcontrol.apiserver.k8s.io/v1
kind: FlowSchema
metadata:
  name: tenant-ci-flow
spec:
  priorityLevelConfiguration:
    name: low-priority-tenants
  matchingPrecedence: 800
  rules:
  - subjects:
    - kind: Group
      group:
        name: system:serviceaccounts:ci-runner

Audit and enforce client-side best practices across internal microservices and operators: mandate client-go shared informers or controller-runtime cached clients, disallow uncached full-cluster LIST requests, and inject exponential backoff jitter into automated tooling.

// Mandate manager cache in controller-runtime
mgr, err := ctrl.NewManager(ctrl.GetConfigOrDie(), ctrl.Options{
    Cache: cache.Options{ SyncPeriod: &defaultSyncPeriod },
})