If I am unsure about readiness, I ask who is on call at 2 AM; the answer is telling. If the room gets quiet, the system is not ready. What production ready means in product engineering is often misunderstood. It is not a badge you get at launch. It is a set of operational behaviors that keep a system stable after launch.
Start with reliability basics. Define availability and performance targets. Add timeouts, retries, and sensible defaults. Health checks should match real user paths, not just process status.
Observability and alerts: Ensure logs, metrics, and traces exist for core flows. Alerts should trigger action, not panic. Link alerts to short runbooks so the team can respond without searching. Deployment and rollback: Automate deployments and keep rollback simple. Avoid manual steps during releases. Track every change with a clear audit trail so issues can be traced quickly.
Ownership and operations: Assign on call ownership and escalation paths. Keep documentation short and current. If nobody owns it, it is not production ready. Add a short readiness review before major launches. A small checklist for risk, observability, and rollback is usually enough to catch gaps.
Production readiness is most visible after the first incident. If the team can respond calmly and restore service, the system is ready. Define load and failure testing expectations. Even a simple load test before launch can expose performance limits. Add a small failure test, such as dependency timeouts, to validate resilience.
Include support readiness. If customers report issues, the team needs a clear intake path and response playbook. Production readiness is not just about code, it is about how you respond. Keep production configuration simple and documented. If the system depends on hidden settings, it will be hard to reproduce and hard to recover.
Example readiness review: a production readiness review
Before launching a new service, the team runs a short readiness review. They confirm service level objectives, on call ownership, and alerting. They verify that backups are running and restore tests are documented. They also make sure deployment automation exists so a rollback is fast and safe. A simple review like this turns production readiness from a vague idea into a practical standard.
Where launches fail
- Launching without clear ownership or on call coverage.
- No runbooks, so incidents require tribal knowledge.
- Missing monitoring for the user facing paths.
- Backups exist but have never been restored.
- Treating security as a separate phase after launch.
Readiness checklist
- Define SLOs and the error budget policy.
- Assign on call ownership and escalation paths.
- Implement dashboards and alerts for key user journeys.
- Automate backups and test restores on a schedule.
- Create runbooks for the top failure modes.
- Document deployment and rollback steps.
Ownership and support model: Production readiness requires a clear ownership model. Each service should have a primary owner, a backup owner, and an escalation path. Define how incidents are handed off between teams and how post incident reviews are handled. Ownership makes it clear who maintains the service after launch.
If the service is customer facing, ensure support teams have access to status dashboards and a summary of the most common failure modes. Pre launch tests: Before launch, run a load test that matches expected traffic. Include a chaos or failure test for a critical dependency to ensure the service degrades safely. These tests do not need to be complex, but they should be documented so future changes can repeat them.
Documentation set: Keep a small but complete documentation set. At minimum, include a service overview, deployment steps, dependency list, and a troubleshooting guide. Link to dashboards and logs so responders can move quickly during incidents. Documentation should be updated during releases, not after incidents.
Capacity planning: Estimate expected traffic and resource usage before launch. Decide how the service scales, and set capacity thresholds that trigger scaling or alerts. If demand is uncertain, run a short load test and plan for the high end. Capacity planning prevents the first production traffic spike from becoming an outage.
Service lifecycle review: Schedule a review after 30 and 90 days in production. Check whether SLOs are met, whether incidents are decreasing, and whether the team can support the service sustainably. If not, adjust staffing, tooling, or scope. Production readiness is not a one time event.
Decommissioning plan: Production readiness also means knowing how to retire a service. Define how data is archived or deleted, how dependencies are updated, and how users are notified. A simple decommissioning plan prevents long term maintenance debt. Feature flag strategy: Use feature flags to decouple deployment from release. Launch features gradually and monitor impact. If issues appear, disable the flag rather than rolling back the entire release. This reduces risk for new functionality.
Data ownership and retention: Define who owns production data and how long it is kept. If data must be deleted, document the process. Clear ownership prevents retention from becoming an afterthought.
