Handling retriable and non-retriable pod failures with Pod failure policy
FEATURE STATE: Kubernetes v1.31 [stable]
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:
Your Kubernetes server must be at or later than version v1.25. To check the version, enter kubectl version
.
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 areason
field set toPodFailurePolicy
and amessage
field with more information about the termination, likeContainer 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: samereason
andmessage
as theFailureTarget
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.
Caution:
Timing is important for this example, so you may want to read the steps before execution. In order to trigger a Pod disruption it is important to drain the node while the Pod is running on it (within 90s since the Pod is scheduled).
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
```
Run this command to check the
nodeName
the Pod is scheduled to:nodeName=$(kubectl get pods -l job-name=job-pod-failure-policy-ignore -o jsonpath='{.items[0].spec.nodeName}')
Drain the node to evict the Pod before it completes (within 90s):
kubectl drain nodes/$nodeName --ignore-daemonsets --grace-period=0
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
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.
Note:
The example below works since version 1.27 as it relies on transitioning of deleted pods, in the Pending
phase, to a terminal phase (see: Pod Phase).
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.
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.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 $podName --subresource=status --patch-file=patch.yaml
If applied successfully, you will get a notification like this:
pod/job-pod-failure-policy-config-issue-k6pvp patched
Delete the pod to transition it to
Failed
phase, by running the command:kubectl delete pods/$podName
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 fieldreason
equalPodFailurePolicy
. Additionally, themessage
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
.
Note:
In a production environment, the steps 3 and 4 should be automated by a user-provided controller.
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.