Observability and SRE

Most monitoring setups fail the same way. They alert on everything, the team learns to ignore alerts, and the one that mattered arrives at 3am in a muted channel.

Instrument for the questions you will ask

We instrument around what you will actually need during an incident. Metrics, logs and traces correlated, so a latency spike leads to the specific request path and the dependency causing it - not four dashboards and a guess.

Dashboards are built around user-visible symptoms rather than machine internals. CPU at 90% may be fine. Checkout failing for 2% of users is not, and that is the one that should be on the wall.

Alert on things worth waking up for

Thresholds derive from your actual traffic patterns, not arbitrary defaults. We define SLOs for the things users care about and alert on error budget burn rate, which means you get paged when you are genuinely trending toward a breach, not every time a metric wobbles.

Everything else becomes a ticket. A pager that fires twice a week for something nobody acts on is worse than no pager.

Contain it automatically where you can

Failure modes with a known safe response - restart the unhealthy pod, fail over the replica, scale out ahead of the queue backlog - should be handled by automation and never become incidents at all.

For the rest, we design the on-call structure: who is paged, what they see, which escalation path applies, and what context attaches automatically. Whoever picks up the page should already have the dashboard, the recent deploys and the runbook in front of them.

Learn from it

Every significant incident gets a blameless review producing concrete follow-ups - a missing alert, an unclear runbook, a fragile dependency - tracked to completion. An incident you do not learn from is one you will have again.