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After you deploy a workload, use these commands for day-to-day operation: scaling, restarting Instances, watching a rollout, and inspecting a single Instance when something isn’t right.

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Scaling

datumctl compute scale sets the minimum number of Instances per location for every placement of a workload:
The count is per location, from 1 to 1,000. Workloads don’t scale automatically. For different counts per placement, edit scaleSettings.minReplicas in the manifest and apply it with datumctl compute deploy -f. For more information, see Placement and scaling.

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Restarting

datumctl compute restart starts a rolling restart. Datum replaces Instances without changing the image or configuration. A restart is useful to pick up an external change, such as a rotated Secret:
restart replaces every Instance of the workload in every location.

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Watching a rollout

Any change that replaces Instances, such as a deploy with a new image or a restart, starts a rollout. datumctl compute rollout attaches to the rollout and prints progress for each placement and location:
Each row moves through phases — Pending, Updating, Done — until every placement finishes. Datum replaces Instances one at a time in each location, and waits for each replacement to be ready before it starts the next one. If a placement stalls for more than 30 seconds without progress, its phase becomes Blocked and the command prints the reason (a quota limit, a scheduling issue) reported by the platform.
Press Control+C to detach from the watch. The rollout continues in the background. To reattach and see current progress, run datumctl compute rollout api.

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Inspecting Instances

datumctl compute instances lists every Instance in the project. Each row is one copy of a workload’s container in one location, whether it’s running or trying to start:
The status reflects availability, not only whether a process is running. For example, an Instance blocked on quota shows Pending (quota exceeded) instead of a generic “not ready” status. Add -o wide for the underlying instance type alongside the default columns, or -o json/-o yaml for the full resource. To see the runtime configuration, environment, network addresses, and a plain-language explanation of any failure for one Instance, use describe:
When an Instance can’t start because of quota, describe also prints the next commands to run, such as datumctl compute quota.

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Next steps

  • datumctl compute scale --help, restart --help, rollout --help, and instances --help for the full flag reference.
  • Deploying workloads — the deploy and workloads commands that create what you’re operating on here.
  • Destroying workloads — remove a workload and every Instance it created.
Last modified on September 23, 2026