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Advanced Job Features

Advanced Job Features

Admittedly, running a simple Job as earlier has little advantage over running a single Pod but there is more to Jobs than meets the eye as you will see in the following lessons.

Automatic Retry-Logic

The Job concept in Kubernetes provides options when a container has not been executed successfully. This does not only cover the creation of Pods and their containers but also the workload running inside them.

A Failing Job

Run the following Job which will fail with certainty. Create the file 30-failing-job.yaml:

apiVersion: batch/v1
kind: Job
name: simple-one-off-job-from-yaml
- name: simple-one-off-job-container
image: busybox
imagePullPolicy: Always
command: ['/bin/sh', '-c']
- 'echo "I represent a failing maintenance task"; exit 1'
restartPolicy: OnFailure

Apply it:

kubectl apply -f 30-failing-job.yaml

As usual a kubectl describe is executed to obtain more information:

kubectl describe job simple-one-off-job-from-yaml

Interestingly, this produces an event SuccessfulCreate originating from the job-controller. Everything seems normal, although we know that the Job must have failed. A closer look reveals there is no contradiction. The event informs that the Pod simple-one-off-job-from-yaml-5x2xt has been created successfully and in fact it has been. It's just that the container inside the Pod has failed. So a closer look at the pod is necessary:

kubectl get pods -l job-name=simple-one-off-job-from-yaml

This time we see a clear indication that something went wrong:

  • STATUS is CrashLoopBackOff
  • RESTARTS is 4

And an even closer look with:

kubectl describe pod simple-one-off-job-from-yaml-547xc

Reveals a warning: Back-off restarting failed container which indicated a non-zero return value from starting the container. For those new to Unix/Linux systems [2]:

For the shell's purposes, a command which exits with a status code of zero has succeeded. A non-zero exit status indicates failure. This seemingly counter-intuitive scheme is used so there is one well-defined way to indicate success and a variety of ways to indicate various failure modes. When a command terminates on a fatal signal whose number is N, Bash uses the value 128+N as the exit status.

Without further specification Kubernetes determines the success of a container start by looking at the exit value of the container startup command to be zero. Any non-zero value will be considered a failing container start.

A Flaky Job

But there is more to the previous example. The field RESTARTS: 4 suggests that Kubernetes has not given up immediately but only after four (4) failed attempts. This means that if a failure is sporadic, the retry logic can help to accomplish a Job nevertheless.

Consider a Job that sometimes fails and sometimes succeeds. While such a case calls for a bugfix by the developer, it is also nice if Kubernetes can help so that the developer does not have to get up at night.

We simulate a flaky Job with the following shell command:

(( RANDOM%3 == 0 )) && exit 0 || exit 1

This will randomly exit with either success (0) or failure (1) with a bias towards failure.

Use this version of you want to try it without existing your shell:

(( RANDOM%3 == 0 )) && echo 0 || echo 1

Create the file 40-flaky-job.yaml:

apiVersion: batch/v1
kind: Job
name: flaky-job
backoffLimit: 5
- name: flaky-job-container
image: ubuntu
imagePullPolicy: Always
command: ['/bin/bash', '-c']
- 'echo "I represent a flaky maintenance task"; (( RANDOM%3 == 0 )) && exit 0 || exit 1'
restartPolicy: OnFailure

Execute the Job:

kubectl apply -f 40-flaky-job.yaml

While the Job is being created open another terminal and observe the Pods belonging to the Job:

kubectl get pods -l job-name=flaky-job -w

The option -w as in "watch" keeps kubectl polling for changes. So you are likely to see a sequence of events such as:

flaky-job-b7nj8   0/1     Pending             0          0s
flaky-job-b7nj8 0/1 Pending 0 0s
flaky-job-b7nj8 0/1 ContainerCreating 0 1s
flaky-job-b7nj8 0/1 Error 0 3s
flaky-job-b7nj8 0/1 Error 1 5s
flaky-job-b7nj8 0/1 CrashLoopBackOff 1 6s
flaky-job-b7nj8 0/1 Completed 2 24s

As the containers are failing randomly you may have to delete and create the Job several times to observe a similar sequence. Give it a try.

You can see from the output that the Pod has failed two times before it succeeded. This is free robustness for workloads when using Kubernetes Jobs.

  1. Kubernetes Documentation, Tasks, Jobs,
  2., Bash Manual,