cannectors

run

Validate and execute a pipeline — once, on CRON, or as a long-running listener.

cannectors run [--dry-run] <pipeline.yaml>

Reads the pipeline, validates it (same checks as validate), resolves environment variables, then executes it. The process lifetime depends on the input.

Examples

# Run once and exit
cannectors run ./examples/01-http-polling-basic-to-http-batch.yaml

# Preview without writing to the output
cannectors run --dry-run ./examples/19-http-output-single-template.yaml

# Stay alive on CRON
cannectors run ./examples/04-http-polling-cursor-oauth2.yaml

Lifetime

InputLifetime
httpPolling without scheduleOne-shot. Exits 0 on success.
httpPolling with scheduleStays alive. Triggers on every CRON match. Exit on SIGINT/SIGTERM.
database without scheduleOne-shot.
database with scheduleStays alive on CRON.
webhookLong-running HTTP listener. Exit on SIGINT/SIGTERM.

The runtime drains in-flight work and persists state on shutdown — a graceful stop never loses a batch.

Dry-run mode

--dry-run runs everything except the output's side effect: the input fetches, every filter executes, then the would-be output payload is printed to stdout instead of being sent.

cannectors run --dry-run sync-orders.yaml

See Dry-run mode for the full mental model and dryRunOptions tuning.

Flags

FlagEffect
--dry-runSkip the output side effect; print a preview instead.
--verbosePer-record trace lines on stdout.
--quietSuppress informational logs (errors still print).
--log-file <path>Write structured logs to a file.

See Flags for the full reference.

Exit codes

CodeMeaning
0Pipeline completed successfully (one-shot mode) or was stopped cleanly.
1Validation errors before execution.
2Parse error.
3Runtime error — a stage failed past its onError policy.

Production process management

The run process is single-replica by design. Don't run two copies of the same scheduled pipeline — they'd fire on the same CRON tick and double-process records. Use a single-replica Deployment, StatefulSet, or systemd unit.

See Operations · scheduling in production for the deployment patterns.

See also