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Request/Response Logging

Structured logging of API request metadata, response details, and timing information for debugging, monitoring, and audit compliance.

Also known as: API Logging, Access Logging, Audit Logging

Description

Request/response logging captures structured metadata about every API interaction for debugging, performance monitoring, and audit compliance. A well-designed logging pipeline records the request method, path, query parameters, headers (excluding sensitive values), request body (for mutations), response status code, response time, and a correlation ID that links the log entry to distributed traces. Logs should be structured (JSON format) rather than plaintext to enable efficient querying and aggregation in log management systems.

Sensitive data handling is critical: request and response logs must redact or mask PII (personally identifiable information), authentication tokens, passwords, credit card numbers, and other sensitive fields. This is typically implemented as a middleware that applies redaction rules before writing log entries. Headers like Authorization should be logged as 'Bearer [REDACTED]', and request bodies should have sensitive fields replaced based on a configurable deny-list.

Log levels should be used consistently: INFO for successful requests, WARN for client errors (4xx), ERROR for server errors (5xx), and DEBUG for verbose request/response body logging (enabled only in development or troubleshooting scenarios). In production, log volume management is important -- high-traffic APIs can generate enormous log volumes, so sampling strategies (log 100% of errors, 10% of successful requests) and retention policies (7 days hot, 30 days warm, 1 year cold for compliance) should be defined upfront.

Prompt Snippet

Implement structured JSON request logging via Express middleware capturing: { method, path, query, status_code, duration_ms, request_id, user_id, ip, user_agent, content_length }. Redact Authorization headers, request body fields matching a deny-list (password, ssn, card_number), and response bodies on non-2xx status codes. Correlate logs with distributed traces by including trace_id and span_id from OpenTelemetry context. Ship logs to Datadog via Fluentd with 100% sampling for 4xx/5xx and 10% sampling for 2xx in production. Set retention policies: 14 days hot search, 90 days archive.

Tags

loggingobservabilityauditdebuggingstructured-logging