Jobs Operations
Capacity
Section titled “Capacity”Throughput is a function of connected agents. The queue absorbs bursts; sustained queue growth means the trigger rate exceeds what the fleet can drain.
Scale by running more agents. There is no per-job concurrency setting to tune first — that is deliberate, since the usual cause of a backed-up queue is not enough workers rather than badly-tuned ones.
Failure modes
Section titled “Failure modes”An agent disconnects mid-run. The run is recoverable and the queue holds the work until another agent takes it. Runs are not lost on agent restart.
A job fails. The run records the failure with logs. Retry by id re-dispatches with the original input.
The queue grows without draining. Either agents are gone or a job is consuming them. Check agent count first — a silent drop in connected agents is capacity you believe you have and do not.
A trigger stops firing. Scheduled triggers are the ones to watch; a cron that silently stops produces no error, just an absence. Alert on expected runs not happening, not only on runs failing.
Jobs, workflows and flows
Section titled “Jobs, workflows and flows”Three things on the platform run multi-step work, and they are not interchangeable:
| Use | When |
|---|---|
| Jobs | Background work on a schedule or a trigger |
| Workflows | Long-running business processes with human steps |
| AI Flow | DAGs of tasks, including model calls and agentic loops |
The distinction that matters: a job is fired, a workflow waits. If your process needs to pause for a human approval and resume days later, that is a workflow.
What to watch
Section titled “What to watch”| Signal | Why it matters |
|---|---|
| Queue depth trend | Not enough agents for the trigger rate |
| Connected agent count | A silent drop is invisible capacity loss |
| Run failure rate by job | One job degrading, not the fleet |
| Retry rate | Work that only succeeds on a second attempt is still a defect |
| Expected-but-missing runs | A trigger that stopped firing produces no error |