KubernetesJobFailed #

Job {{ $labels.namespace }}/{{ $labels.job_name }} failed to complete

alert: KubernetesJobFailed
annotations:
  description: |-
    Job {{ $labels.namespace }}/{{ $labels.job_name }} failed to complete
      VALUE = {{ $value }}
      LABELS = {{ $labels }}    
  runbook: https://srerun.github.io/prometheus-alerts/runbooks/kubestate-exporter/kubernetesjobfailed/
  summary: Kubernetes Job failed ({{ $labels.namespace }}/{{ $labels.job_name }})
expr: kube_job_status_failed > 0
for: 0m
labels:
  severity: warning

Here is a sample runbook for the KubernetesJobFailed alert:

Meaning #

The KubernetesJobFailed alert is triggered when a Kubernetes Job fails to complete successfully. This alert indicates that a Job, which is a batch process that runs to completion, has failed. This failure can impact the availability and reliability of the affected application or service.

Impact #

The impact of a failed Kubernetes Job can vary depending on the specific use case and application. However, some possible consequences include:

• Delayed or lost data processing
• Incomplete or inaccurate results
• Disruption to dependent services or applications
• Increased error rates or failed requests
• Decreased system reliability and availability

Diagnosis #

To diagnose the root cause of the failed Kubernetes Job, follow these steps:

1. Check the Job’s pod logs for error messages or exceptions that may indicate the cause of the failure.
2. Verify that the Job’s configuration and resources are correct and up-to-date.
3. Check the Kubernetes cluster’s event log for any errors or warnings related to the failed Job.
4. Verify that the dependent services or applications are functioning correctly and that there are no issues with networking or connectivity.
5. Review the Job’s history and previous runs to identify any patterns or trends that may indicate a recurring issue.

Mitigation #

To mitigate the impact of a failed Kubernetes Job, follow these steps:

1. Investigate and resolve the root cause of the failure, as identified during diagnosis.
2. Restart the failed Job, if possible, to retry the processing.
3. Check and update the Job’s configuration and resources to prevent similar failures in the future.
4. Implement additional logging or monitoring to detect and alert on similar issues earlier.
5. Consider implementing retry mechanisms or fallbacks to minimize the impact of future failures.

Remember to consult the Kubernetes Job’s documentation and specific use case requirements for more detailed guidance on mitigation and resolution.