Operational Readiness for Data Pipelines
Essential practices for keeping data pipelines reliable and maintainable in production.
What operational readiness means
Operational readiness isn’t about perfect code—it’s about systems that fail gracefully and can be fixed quickly.
Alerting strategy
Alert on symptoms, not causes:
- Data freshness: Alert when data is stale beyond SLA
- Volume anomalies: Alert on unexpected drops or spikes
- Quality gates: Alert when tests fail, not just when jobs fail
- Downstream impact: Alert when dependent systems are affected
Runbooks that actually work
Good runbooks answer three questions:
- What is this pipeline? (Purpose, dependencies, owners)
- How do I know it’s broken? (Key metrics, dashboards)
- How do I fix common issues? (Step-by-step recovery procedures)
Ownership models
Define clear ownership:
- Primary on-call: First responder for incidents
- Secondary on-call: Backup when primary is unavailable
- Data owner: Business stakeholder who defines requirements
- Pipeline owner: Technical owner who maintains the code
The incident response playbook
- Acknowledge the alert within SLA
- Check runbook for known issues
- Escalate if resolution isn’t clear
- Document the incident and update runbooks