Engineering

Observability Before Features: What to Monitor on Day One

Shipping blind is how small bugs become outages. Instrument logs, metrics, and traces before you celebrate launch.

SI

Shehzad Iqbal

Principal Backend Engineer

9 min read

Key takeaways

  • Cover the four golden signals plus business-critical paths
  • Alert on symptoms users feel - not every CPU blip
  • Tie errors to releases so rollback is obvious

Feature velocity without observability is gambling. Day-one monitoring doesn’t need a full platform engineering org - it needs a minimum set that answers: is it broken, for whom, and since when?

Minimum viable monitoring

  • Uptime check on the real production URL
  • Error tracking with source maps and release versions
  • Latency for critical API routes (p95, not just average)
  • Saturation signals: queue depth, DB connections, rate limits
  • One business metric: signups, checkouts, or jobs completed

4

Golden signals: latency, traffic, errors, saturation

p95

Latency percentile that catches pain

1

Business KPI on the same dashboard

Alerts people will actually answer

Noisy alert
Useful alert
CPU > 70% for 1 minute
Error rate 5× baseline for 5 minutes
Every 404
Spike in 5xx on checkout paths
Disk 80% on staging
Disk projected full on prod < 24h

If every alert pages someone, eventually no alert will.

  1. 01

    Instrument critical paths

    Auth, payment, and the core job-to-be-done get explicit spans or logs.

  2. 02

    Tag releases

    Every deploy marks a version so regressions are obvious in the timeline.

  3. 03

    Write the first runbook

    For each page-worthy alert: what to check, how to mitigate, when to roll back.

Good enough to grow

You can deepen tracing later. On day one, aim for a team that knows within minutes whether launch is healthy - and can roll back without archaeology.

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