Logging provides event-level detail for debugging. Structured JSON logs (vs plain text) are machine-parseable — enabling powerful queries in aggregation systems. Every log line should include: timestamp, level, message, service name, trace_id/request_id (correlation), and relevant context fields. Log aggregation: Grafana Loki (label-based, cost-effective), ElasticSearch/Kibana (full-text indexed, expensive), CloudWatch Logs (AWS-native). Sampling high-volume debug logs prevents storage explosion.
Required and optional fields for structured log lines.
Plain text logs require regex parsing — slow and brittle. JSON logs are directly parseable by every aggregation system. One-time investment in a structured logger pays dividends forever.
Without trace_id, debugging a distributed request means manually correlating timestamps across log streams. With trace_id, one LogQL query shows the complete request journey across all services.
Logs are often stored for 90+ days in multiple systems with broad access. A password, credit card number, or SSN in a log line is a data breach. Audit log fields and add redaction middleware.
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