Incident-Ready Observability: What to Set Up Before You Need It

When incidents happen, the difference between a 10-minute fix and a 2-hour outage is usually not “more engineers” — it’s whether your observability gives clear answers fast.

This post is a practical baseline you can implement without rebuilding your entire platform.

The goal of observability during an incident

You need to answer four questions quickly:

• What is broken?
• Where is it broken?
• What changed?
• How do we stop the impact?

If your monitoring can’t support these questions, it becomes noise.

Baseline you should have in every environment

Logs

• Every request should have a correlation ID.
• Log format should be structured (JSON recommended).
• Include: service name, environment, request path, status code, latency, user or tenant identifier (if applicable).
• Centralize logs in one place with consistent retention.

Metrics

Minimum set per service:

• Request rate (RPS)
• Error rate (4xx/5xx)
• Latency (p50/p95/p99)
• Saturation (CPU, memory, queue depth)

Traces

Distributed tracing is optional until it’s not. If you have microservices or async flows, you want:

• trace ID propagated across services
• spans for external calls (DB, cache, HTTP dependencies)
• sampling rules you can adjust during incidents

Alerting that doesn’t create burnout

Good alerts are:

• actionable
• tied to impact
• routed to the right owner

Bad alerts are:

• “CPU > 80%” with no context
• flapping thresholds
• anything that pages without a runbook

A simple approach:

• Page on symptoms (error rate, latency)
• Create tickets on causes (CPU, memory, disk, scaling)

Add “change awareness”

Most incidents correlate with change. Make sure you can see:

• deployments
• config changes
• feature flag changes
• infrastructure changes

At minimum, annotate dashboards with deploy events.

A fast implementation plan (1–2 weeks)

1. Standardize structured logs + correlation IDs
2. Add golden signals dashboard for each service
3. Implement basic alerting for error rate + latency
4. Add deployment annotations
5. Add tracing where debugging is currently painful

Photo source

Cover image: Unsplash — https://unsplash.com/photos/laptop-computer-on-table-beside-turned-on-monitor-4hbJ-eymZ1o