Traditional text logs are human-readable but machine-hostile. Structured logging outputs JSON or similar formats enabling powerful queries and aggregations. This transformation converts logs from write-only archives into actionable operational data.
Implementation Patterns
Structured loggers output key-value data in consistent formats. Include contextual fields—request IDs, user IDs, service names—in every log. Use log levels appropriately to enable filtering. Ensure sensitive data is redacted before logging.
- Include correlation IDs linking logs across service boundaries
- Add contextual metadata enriching logs with request and user information
- Use consistent field names across services for unified querying
- Implement log levels enabling appropriate verbosity control
- Redact sensitive information like passwords and tokens automatically
Analysis and Alerting
Log aggregation platforms like Elasticsearch, Loki, and cloud services enable powerful queries. Create dashboards visualizing error rates, latency distributions, and business metrics. Alert on log patterns indicating problems before users notice.