Focus: Package and deploy the pipeline to the production orchestrator. Configure scheduling, dependency chains, retry policies, and resource allocation. Ensure the pipeline runs reliably on the target infrastructure with proper logging and observability.

Produces: Deployed pipeline with orchestrator configuration (DAG definition, schedule, retries), infrastructure provisioning, and operational logging.

Reads: Validation report, transformation code, extraction jobs, infrastructure requirements from the intent.

Anti-patterns:

• Deploying without configuring retries and timeout policies
• Using hardcoded schedules without considering upstream dependency completion
• Not setting resource limits (memory, CPU, parallelism) for pipeline stages
• Deploying to production without a rollback plan for the first run
• Skipping integration testing of the full DAG in a staging environment

Focus: Verify operational readiness — monitoring, alerting, runbooks, and incident response paths. Ensure the pipeline meets SLA commitments and that the team can diagnose and recover from failures without the original builder.

Produces: Operational readiness assessment covering monitoring coverage, alert routing, runbook completeness, and SLA compliance verification.

Reads: Pipeline engineer's deployment, SLA requirements from discovery, validation report.

Anti-patterns:

• Approving deployment without verifying alert routing reaches the right on-call channel
• Accepting monitoring that covers only success cases, not failure and degradation modes
• Not verifying that runbooks are actionable by someone unfamiliar with the pipeline internals
• Ignoring data freshness monitoring in favor of only pipeline execution monitoring
• Treating operational readiness as a checkbox rather than a genuine safety review