Blind Operations
The team cannot tell if a deployment is healthy. No metrics, no log aggregation, no tracing. Issues are discovered when customers call support.
9 minute read
The team cannot tell if a deployment is healthy. No metrics, no log aggregation, no tracing. Issues are discovered when customers call support.
9 minute read
After deploying, there is no automated verification that the new version is working. The team waits and watches rather than verifying.
11 minute read
The team builds services but doesn’t run them, eliminating the feedback loop from production problems back to the developers who can fix them.
9 minute read
Alert volume is so high that pages fire for non-issues. Real problems are lost in the noise.
3 minute read
There are no documented response procedures. Critical knowledge lives in one person’s head. Incidents are improvised every time.
3 minute read
Production deployments cause anxiety because they frequently fail. The team delays deployments, which increases batch size, which increases risk.
4 minute read
The team finds out about production problems from support tickets, not alerts.
3 minute read
Every service writes logs, but they are not aggregated or queryable. Debugging requires SSH access to individual servers.
3 minute read
The team cannot prove what version is running in production, who deployed it, or what tests it passed.
3 minute read
If a deployment breaks production, the only option is a forward fix under pressure. Rolling back has never been practiced or tested.
4 minute read
Deployment procedures, architecture diagrams, and operational runbooks describe a system that no longer matches reality.
3 minute read
No criteria exist for what a service needs before going live. New services deploy to production with no observability in place.
3 minute read
Issues in production are not discovered until users report them. There is no automated detection or alerting.
3 minute read