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This page shows how to check on a running workload, change it, and delete it. To find out why an Instance isn’t running, see Troubleshooting.
Compute is in preview, and the v1alpha API can change.

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Before you begin

  • Select a project, install the compute plugin, and get access to Compute. For more information, see Compute commands.

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Check workload status

To list the workloads in your project, run the following command:
The HEALTH column shows Available, Degraded, Unavailable, or Unknown. The READY column shows how many Instances are ready out of how many the workload wants, and UP-TO-DATE shows how many run the latest template. To filter the list, add --health with a health value in lowercase, such as --health=degraded, or --location with a location, such as --location=us-central-1. To see the configuration, ALB hostname, and per-location health of one workload, run the following command:
Replace WORKLOAD_NAME with the name of your workload. In the Cloud Portal, Compute > Workloads lists the same workloads, with each one’s health, recent CPU and memory, network, and locations.
The Workloads page with totals for workloads, Instances, healthy workloads, and requests, and a table of workloads with status, CPU and memory sparklines, network, and locations

Workloads in the Cloud Portal

The workload’s Available condition also has a reason, which you can see with datumctl get workloads. When a workload isn’t available, the reason points to the cause, and the Instance has the details.

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Check Instances

To list the Instances of a workload, run the following command:
To list Instances in one location, add --location with a location, such as --location=us-central-1. To add the instance type column, add -o wide. The STATUS column describes each Instance in plain language: To see an Instance’s conditions, network addresses, and a plain-language explanation of any failure, run the following command:
Replace INSTANCE_NAME with a name from the NAME column of datumctl compute instances. To open an interactive shell or run a command in a running Instance, see Instance shell sessions. To inspect CPU and memory usage or read Instance output, see Observability.

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Update a workload

To change the image or placement of a workload that you deployed with flags, run datumctl compute deploy again with the same name and the new values. For example, the following command deploys a new image version:
Replace the following:
  • WORKLOAD_NAME: the name of your workload.
  • IMAGE: the new image reference.
  • LOCATION: the locations that the workload runs in.
  • COUNT: the number of Instances to run in each location.
A flag-based datumctl compute deploy replaces the workload’s whole template and placements with what the flags describe. It keeps environment variables, ConfigMap and Secret imports, volumes, and labels. It removes registry credentials, custom commands, and extra placements that you set in a manifest, and it sets the Instance count to the --min value, which defaults to 1. Once you manage a workload with a manifest, update it with datumctl compute deploy -f FILE.
To update a workload from a manifest, edit the manifest and run datumctl compute deploy -f FILE, where FILE is the path to your manifest. The command shows the changes and asks for confirmation before it applies them.
Push each new image version with a new tag, or reference it by digest, such as ghcr.io/example/api@sha256:.... Hosts cache images by tag, so pushing a new image under a tag you already deployed might not reach every Instance.
Datum rolls out template changes one Instance at a time in each location. For more information, see How rollouts work. To restart Instances without changing the template, see Restart Instances. You can’t change the following settings after you create a workload:
  • The workload name
  • The runtime class
  • The network, and the network interface’s name, ipFamilies, addresses, and reclaimPolicy
To change one of these settings, deploy a new workload with a different name, and then delete the old one.

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Delete a workload

Deleting a workload with datumctl compute destroy also deletes its Instances, its ALB, and the network service that selects it, even if you created the network service separately.
You can’t undo the deletion. Anything that an Instance stored on its own filesystem is lost.
To delete a workload, follow these steps:
  1. Run the following command:
    Replace WORKLOAD_NAME with the name of your workload.
  2. Review the summary of placements, locations, Instances, and the ALB’s hostnames that the command prints.
  3. Enter y to confirm. The command prints workload/WORKLOAD_NAME deleted.
To skip the confirmation in scripts, add -y. If you delete a workload with datumctl delete workload, Datum deletes the workload and its Instances, but leaves in place any ALB that datumctl compute deploy created. Use datumctl compute destroy to remove both.

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What’s next

Last modified on October 23, 2026