What a job is
A job is a finite operation over records, or a continuous stream, with an identity that outlives the request, conversation or sandbox that submitted it. The platform seals inputs and code at admission, cuts records into partitions, places attempts on eligible outposts, retries under the operation’s declared replay policy, accepts exactly one output per partition and settles the job with explicit coverage. Finite work and streams alike survive an outpost restart.Follow the lifecycle
States arequeued, running, input_required and the four terminal states completed, partial, failed and canceled; the console shows canceled as Stopped. Coverage counts partitions: expected, completed, failed, running, pending. A job completes when every partition is accepted, settles partial when some are, and fails when none are. A partial result keeps its coverage and is never a complete dataset with holes.
Read its current state, wait for settlement and retrieve accepted rows from any later run with the job ID.
Inspect an existing job
Make retries intentional
Silence is not failure. An attempt that times out is recorded as unknown and one that is stopped as canceled; both are silence. A replay-safe operation’s partition returns to the queue for another attempt while attempts remain. A script declaredreplay_safe=False fails instead of running twice, and since a script is one partition, its job fails. Silence counts against max_attempts; a receiver’s busy refusal does not. The attempt timeout restarts when the receiver reports work in progress, and an attempt still queued at a receiver may wait up to four timeout windows for a slot before it is recorded as unknown.
A submission key is scoped to you: the same key with the same sealed work replays the existing job, the same key with different work is refused with a conflict, and renaming a retry still replays because the name is outside the fingerprint.
Terminal
In the console, the Jobs tab of the Outposts page groups work as Running, Needs an answer and Finished, with filters by author and kind and a search by name or ID. A job’s page shows where its partitions ran, why work moved, the errors behind its failed partitions grouped by message, and the download of a settled result.