Handling retriable and non-retriable pod failures with Pod failure policy

This document shows you how to use the Pod failure policy, in combination with the default Pod backoff failure policy, to improve the control over the handling of container- or Pod-level failure within a Job.

The definition of Pod failure policy may help you to:

• better utilize the computational resources by avoiding unnecessary Pod retries.
• avoid Job failures due to Pod disruptions (such preemption, API-initiated eviction or taint-based eviction).

Before you begin

You should already be familiar with the basic use of Job.

You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. It is recommended to run this tutorial on a cluster with at least two nodes that are not acting as control plane hosts. If you do not already have a cluster, you can create one by using minikube or you can use one of these Kubernetes playgrounds:

• Killercoda
• Play with Kubernetes

Using Pod failure policy to avoid unnecessary Pod retries

With the following example, you can learn how to use Pod failure policy to avoid unnecessary Pod restarts when a Pod failure indicates a non-retriable software bug.

First, create a Job based on the config:

/controllers/job-pod-failure-policy-failjob.yaml

apiVersion: batch/v1
kind: Job
metadata:
  name: job-pod-failure-policy-failjob
spec:
  completions: 8
  parallelism: 2
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: main
        image: docker.io/library/bash:5
        command: ["bash"]
        args:
        - -c
        - echo "Hello world! I'm going to exit with 42 to simulate a software bug." && sleep 30 && exit 42
  backoffLimit: 6
  podFailurePolicy:
    rules:
    - action: FailJob
      onExitCodes:
        containerName: main
        operator: In
        values: [42]

by running:

kubectl create -f job-pod-failure-policy-failjob.yaml

After around 30s the entire Job should be terminated. Inspect the status of the Job by running:

kubectl get jobs -l job-name=job-pod-failure-policy-failjob -o yaml

In the Job status, the following conditions display:

• FailureTarget condition: has a reason field set to PodFailurePolicy and a message field with more information about the termination, like Container main for pod default/job-pod-failure-policy-failjob-8ckj8 failed with exit code 42 matching FailJob rule at index 0. The Job controller adds this condition as soon as the Job is considered a failure. For details, see Termination of Job Pods.
• Failed condition: same reason and message as the FailureTarget condition. The Job controller adds this condition after all of the Job's Pods are terminated.

For comparison, if the Pod failure policy was disabled it would take 6 retries of the Pod, taking at least 2 minutes.

Clean up

Delete the Job you created:

kubectl delete jobs/job-pod-failure-policy-failjob

The cluster automatically cleans up the Pods.

Using Pod failure policy to ignore Pod disruptions

With the following example, you can learn how to use Pod failure policy to ignore Pod disruptions from incrementing the Pod retry counter towards the .spec.backoffLimit limit.

1. Create a Job based on the config:

   /controllers/job-pod-failure-policy-ignore.yaml

   apiVersion: batch/v1
   kind: Job
   metadata:
     name: job-pod-failure-policy-ignore
   spec:
     completions: 4
     parallelism: 2
     template:
       spec:
         restartPolicy: Never
         containers:
         - name: main
           image: docker.io/library/bash:5
           command: ["bash"]
           args:
           - -c
           - echo "Hello world! I'm going to exit with 0 (success)." && sleep 90 && exit 0
     backoffLimit: 0
     podFailurePolicy:
       rules:
       - action: Ignore
         onPodConditions:
         - type: DisruptionTarget
   

   by running:

   kubectl create -f job-pod-failure-policy-ignore.yaml
   

2. Run this command to check the nodeName the Pod is scheduled to:

   nodeName=$(kubectl get pods -l job-name=job-pod-failure-policy-ignore -o jsonpath='{.items[0].spec.nodeName}')
   

3. Drain the node to evict the Pod before it completes (within 90s):

   kubectl drain nodes/$nodeName --ignore-daemonsets --grace-period=0
   

4. Inspect the .status.failed to check the counter for the Job is not incremented:

   kubectl get jobs -l job-name=job-pod-failure-policy-ignore -o yaml
   

5. Uncordon the node:

   kubectl uncordon nodes/$nodeName
   

The Job resumes and succeeds.

For comparison, if the Pod failure policy was disabled the Pod disruption would result in terminating the entire Job (as the .spec.backoffLimit is set to 0).

Cleaning up

Delete the Job you created:

kubectl delete jobs/job-pod-failure-policy-ignore

The cluster automatically cleans up the Pods.

Using Pod failure policy to avoid unnecessary Pod retries based on custom Pod Conditions

With the following example, you can learn how to use Pod failure policy to avoid unnecessary Pod restarts based on custom Pod Conditions.

1. First, create a Job based on the config:

   /controllers/job-pod-failure-policy-config-issue.yaml

   apiVersion: batch/v1
   kind: Job
   metadata:
     name: job-pod-failure-policy-config-issue
   spec:
     completions: 8
     parallelism: 2
     template:
       spec:
         restartPolicy: Never
         containers:
         - name: main
           image: "non-existing-repo/non-existing-image:example"
     backoffLimit: 6
     podFailurePolicy:
       rules:
       - action: FailJob
         onPodConditions:
         - type: ConfigIssue
   

   by running:

   kubectl create -f job-pod-failure-policy-config-issue.yaml
   

   Note that, the image is misconfigured, as it does not exist.

2. Inspect the status of the job's Pods by running:

   kubectl get pods -l job-name=job-pod-failure-policy-config-issue -o yaml
   

   You will see output similar to this:

   containerStatuses:
   - image: non-existing-repo/non-existing-image:example
      ...
      state:
      waiting:
         message: Back-off pulling image "non-existing-repo/non-existing-image:example"
         reason: ImagePullBackOff
         ...
   phase: Pending
   

   Note that the pod remains in the Pending phase as it fails to pull the misconfigured image. This, in principle, could be a transient issue and the image could get pulled. However, in this case, the image does not exist so we indicate this fact by a custom condition.

3. Add the custom condition. First prepare the patch by running:

   cat <<EOF > patch.yaml
   status:
     conditions:
     - type: ConfigIssue
       status: "True"
       reason: "NonExistingImage"
       lastTransitionTime: "$(date -u +"%Y-%m-%dT%H:%M:%SZ")"
   EOF
   

   Second, select one of the pods created by the job by running:

   podName=$(kubectl get pods -l job-name=job-pod-failure-policy-config-issue -o jsonpath='{.items[0].metadata.name}')
   

   Then, apply the patch on one of the pods by running the following command:

   kubectl patch pod $podName --subresource=status --patch-file=patch.yaml
   

   If applied successfully, you will get a notification like this:

   pod/job-pod-failure-policy-config-issue-k6pvp patched
   

4. Delete the pod to transition it to Failed phase, by running the command:

   kubectl delete pods/$podName
   

5. Inspect the status of the Job by running:

   kubectl get jobs -l job-name=job-pod-failure-policy-config-issue -o yaml
   

   In the Job status, see a job Failed condition with the field reason equal PodFailurePolicy. Additionally, the message field contains a more detailed information about the Job termination, such as: Pod default/job-pod-failure-policy-config-issue-k6pvp has condition ConfigIssue matching FailJob rule at index 0.

Cleaning up

Delete the Job you created:

kubectl delete jobs/job-pod-failure-policy-config-issue

The cluster automatically cleans up the Pods.

Alternatives

You could rely solely on the Pod backoff failure policy, by specifying the Job's .spec.backoffLimit field. However, in many situations it is problematic to find a balance between setting a low value for .spec.backoffLimit to avoid unnecessary Pod retries, yet high enough to make sure the Job would not be terminated by Pod disruptions.