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Introducing Suspended Jobs

Author: Adhityaa Chandrasekar (Google)

Jobs are a crucial part of Kubernetes' API. While other kinds of workloads such as Deployments, ReplicaSets, StatefulSets, and DaemonSets solve use-cases that require Pods to run forever, Jobs are useful when Pods need to run to completion. Commonly used in parallel batch processing, Jobs can be used in a variety of applications ranging from video rendering and database maintenance to sending bulk emails and scientific computing.

While the amount of parallelism and the conditions for Job completion are configurable, the Kubernetes API lacked the ability to suspend and resume Jobs. This is often desired when cluster resources are limited and a higher priority Job needs to execute in the place of another Job. Deleting the lower priority Job is a poor workaround as Pod completion history and other metrics associated with the Job will be lost.

With the recent Kubernetes 1.21 release, you will be able to suspend a Job by updating its spec. The feature is currently in alpha and requires you to enable the SuspendJob feature gate on the API server and the controller manager in order to use it.

API changes

We introduced a new boolean field suspend into the .spec of Jobs. Let's say I create the following Job:

apiVersion: batch/v1
kind: Job
  name: my-job
  suspend: true
  parallelism: 2
  completions: 10
      - name: my-container
        image: busybox
        command: ["sleep", "5"]
      restartPolicy: Never

Jobs are not suspended by default, so I'm explicitly setting the suspend field to true in the .spec of the above Job manifest. In the above example, the Job controller will refrain from creating Pods until I'm ready to start the Job, which I can do by updating suspend to false.

As another example, consider a Job that was created with the suspend field omitted. The Job controller will happily create Pods to work towards Job completion. However, before the Job completes, if I explicitly set the field to true with a Job update, the Job controller will terminate all active Pods that are running and will wait indefinitely for the flag to be flipped back to false. Typically, Pod termination is done by sending a SIGTERM signal to all container processes in the Pod; the graceful termination period defined in the Pod spec will be honoured. Pods terminated this way will not be counted as failures by the Job controller.

It is important to understand that succeeded and failed Pods from the past will continue to exist after you suspend a Job. That is, that they will count towards Job completion once you resume it. You can verify this by looking at Job's status before and after suspension.

Read the documentation for a full overview of this new feature.

Where is this useful?

Let's say I'm the operator of a large cluster. I have many users submitting Jobs to the cluster, but not all Jobs are created equal — some Jobs are more important than others. Cluster resources aren't infinite either, so all users must share resources. If all Jobs were created in the suspended state and placed in a pending queue, I can achieve priority-based Job scheduling by resuming Jobs in the right order.

As another motivational use-case, consider a cloud provider where compute resources are cheaper at night than in the morning. If I have a long-running Job that takes multiple days to complete, being able to suspend the Job in the morning and then resume it in the evening every day can reduce costs.

Since this field is a part of the Job spec, CronJobs automatically get this feature for free too.

References and next steps

If you're interested in a deeper dive into the rationale behind this feature and the decisions we have taken, consider reading the enhancement proposal. There's more detail on suspending and resuming jobs in the documentation for Job.

As previously mentioned, this feature is currently in alpha and is available only if you explicitly opt-in through the SuspendJob feature gate. If this is a feature you're interested in, please consider testing suspended Jobs in your cluster and providing feedback. You can discuss this enhancement on GitHub. The SIG Apps community also meets regularly and can be reached through Slack or the mailing list. Barring any unexpected changes to the API, we intend to graduate the feature to beta in Kubernetes 1.22, so that the feature becomes available by default.