KubeJobNotCompleted

warningKubernetes Jobs & CronJobs

A Job started a long time ago, still has active pods, and has not finished.
Severity warning
Source kube-state-metrics v2.x
Key metrics kube_job_status_start_time, kube_job_status_active

What it means

The alert fires when a Job that is still active has been running for many hours, far beyond what typical batch work takes. It does not know how long your Job should take, so first decide whether this one is legitimately long or stuck.

A Job that never ends holds its resources, may keep a lock or a database connection open, and, if it belongs to a CronJob with concurrencyPolicy: Forbid, blocks every later scheduled run.

Common causes

  • Hung process: waiting forever on a network call without a timeout, a deadlock, or a lock held elsewhere.
  • Pods stuck Pending: no node fits the requests, or a volume cannot attach, so the Job counts as active but does nothing.
  • Retry loop inside the pod: with restartPolicy: OnFailure the container restarts in place while the Job stays active.
  • No activeDeadlineSeconds, so nothing ever stops a runaway run.
  • Wrong completions: completions set higher than the work queue can ever satisfy.

First checks

  1. Check progress and age:
    kubectl -n <namespace> get job <job> -o wide
kubectl -n <namespace> get pods -l job-name=<job> -o wide
  2. Compare succeeded pods with the target, to see if it is moving at all:
    kube_job_status_succeeded{job_name="<job>"}

    kube_job_spec_completions{job_name="<job>"}
  3. Is the pod doing work? Near-zero CPU for hours suggests it is hung:
    sum by (pod) (rate(container_cpu_usage_seconds_total{namespace="<namespace>", pod=~"<job>-.*", container!=""}[5m]))
  4. Read recent logs and restart counts:
    kubectl -n <namespace> logs <pod> --tail=50 --timestamps
kubectl -n <namespace> get pod <pod> -o jsonpath='{.status.containerStatuses[0].restartCount}{"\n"}'
  5. For Pending pods, kubectl -n <namespace> describe pod <pod> shows the scheduling or mount error.

Fixing it

If it is making progress and the duration is expected, let it finish and consider making it faster or splitting the work. If it is hung, capture a thread dump or logs, then stop it with kubectl -n <namespace> delete job <job> and rerun. Prevent repeats: set activeDeadlineSeconds, add timeouts to external calls, and make the work resumable.

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