Restarting
datumctl compute restart triggers a rolling restart — instances are replaced without changing the image or configuration, useful for picking up an external change like a secret rotation:
Watching a rollout
Any change that replaces instances — adeploy with a new image, or a restart — starts a rollout. datumctl compute rollout attaches to it and prints progress per placement and city as it happens:
Pending, Updating, Done — until every placement finishes. 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.
Ctrl-C detaches from the watch; it never cancels the rollout. Re-run
datumctl compute rollout api at any time to reattach and see current progress.Inspecting instances
datumctl compute instances lists every instance in the project — one row per running (or attempting-to-run) copy of a workload’s container in a specific city:
Pending (quota exceeded) rather than a generic “not ready.” Add -o wide for the underlying instance type alongside the default columns, or -o json/-o yaml for the full resource.
For everything about a single instance — runtime configuration, environment, network addresses, and a plain-English explanation of any failure — use describe:
describe also prints the exact next commands to run — typically checking datumctl compute quota.
Next steps
datumctl compute restart --help,rollout --help, andinstances --helpfor the full flag reference.- Deploying workloads — the
deployandworkloadscommands that create what you’re operating on here. - Destroying workloads — remove a workload and every instance it created.