New at hackr.io
This week we are focusing on developer-friendly logging, with a playbook you can apply in your next release.
Good logs tell the truth fast. With the right fields, smart alerts, and a simple triage flow, your team can find root causes quickly, keep users happy, and spend less time guessing.
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The Scoop
A Practical Logging Checklist You Can Use Today
Capture the right events
Log authentication attempts, permission checks, database queries over a threshold, external API calls, background job starts and failures, and all errors with stack traces.
Add rich context
Include timestamp in UTC, environment, service name, version, request ID, user ID or account ID, session ID, route, HTTP method, status code, and latency in milliseconds.
Use structured logs
Emit JSON, one event per line. Avoid free-form strings that break parsing. Keep keys consistent across services.
Handle PII safely
Hash or tokenize user identifiers where possible. Never log secrets, access tokens, or raw passwords. Redact payloads that may contain sensitive data.
Control volume
Sample verbose success events, never sample errors. Use per-route or per-feature sampling when traffic spikes. Keep debug logs behind a feature flag.
Make correlation easy
Propagate a correlation ID across services. Include it in every log line, metric, and trace span so you can pivot quickly.
Keep retention reasonable
Short retention for verbose logs, longer retention for security and audit logs. Write the policy down and automate cleanup.
Advanced Skills
Alerting That Reduces Noise
Alert on symptoms users feel
Use SLO-based alerts on latency, error rate, and saturation. Reserve cause-based alerts for critical dependencies.
Set clear thresholds and routes
Define warning and critical levels, page ownership, and escalation. Group by service and route to avoid alert storms.
Dedupe and suppress
Use time windows to group similar errors. Suppress repeats during active incidents so responders can focus.
Triage Playbook That Works Under Pressure
First look
Check recent deploys, status of core dependencies, and dashboards for spikes in error rate or latency.
Narrow the blast radius
Use correlation IDs to follow a failing request. Compare failing and healthy paths. Grab one concrete example.
Form a hypothesis
Read the most recent stack traces. Inspect the last code changes in the affected service. Reproduce in a canary or staging if possible.
Mitigate and verify
Roll back or feature-flag the suspect path. Verify recovery with live metrics and a few realistic test requests.
Document and prevent
Write a short incident note with timeline, root cause, and follow-ups. Add a test, a dashboard panel, or a guardrail to prevent repeats.
That’s it for today.
Thanks for being part of the community at Hackr.io. Keep learning, keep sharing your projects, and keep building reliable software.
The Hackr.io Team