logging-best-practices

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6155 months ago

Logging best practices for applications and services including structured logging, log levels, and log management strategies

Quick Install

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Instructions

Logging Best Practices

Apply these logging principles to ensure effective debugging, monitoring, and audit capabilities across applications and services.

Structured Logging

Use structured logging formats (JSON) for all log output
Include consistent fields across all log entries
Make logs machine-parseable while remaining human-readable
Use a logging library that supports structured output natively
Avoid string concatenation for log messages; use structured fields

Standard Log Fields

Include these fields in every log entry:

timestamp: ISO 8601 format with timezone
level: Log severity (DEBUG, INFO, WARN, ERROR, FATAL)
message: Human-readable description of the event
service: Name of the service or application
version: Application version or build identifier
trace_id: Distributed tracing correlation ID
span_id: Current span identifier
request_id: Unique identifier for the request

Log Levels

Use appropriate log levels consistently:

DEBUG: Detailed diagnostic information for development
INFO: Normal operational events and state changes
WARN: Unexpected situations that are handled gracefully
ERROR: Failures that affect current operation but not the service
FATAL: Critical failures requiring immediate attention

Context Propagation

Include request context in all log entries within a request lifecycle
Propagate trace IDs across service boundaries
Add user context (anonymized) for user-initiated actions
Include relevant business context for domain events
Use MDC (Mapped Diagnostic Context) or equivalent for context management

Security and Privacy

Never log sensitive information (passwords, tokens, PII)
Mask or redact sensitive data when it must be referenced
Implement log access controls appropriate to data sensitivity
Consider data retention policies and compliance requirements
Audit log access for sensitive systems

Performance Considerations

Use asynchronous logging to avoid blocking application threads
Implement log sampling for high-volume debug logs in production
Buffer logs appropriately to balance latency and throughput
Monitor logging infrastructure for bottlenecks
Set appropriate log levels per environment

Log Aggregation

Centralize logs from all services into a single platform
Use consistent formatting across all services
Implement log rotation and retention policies
Enable full-text search and filtering capabilities
Set up log-based alerts for critical patterns

Error Logging

Include full error context: message, code, stack trace
Log the chain of errors in wrapped/nested exceptions
Include relevant request and state information
Avoid duplicate error logging across layers
Log error recovery actions and outcomes

Best Practices

Log at service boundaries (entry and exit points)
Include timing information for performance analysis
Log configuration changes and deployments
Create actionable log messages that aid debugging
Review and clean up logging regularly to reduce noise

Log Message Guidelines

Write clear, descriptive messages
Include relevant identifiers (user ID, order ID, etc.)
Avoid generic messages like "Error occurred"
Use consistent terminology across the application
Include enough context to understand the event without additional lookups

Environment-Specific Configuration

Development: DEBUG level, console output, verbose formatting
Staging: INFO level, structured JSON, full context
Production: INFO/WARN level, structured JSON, sampling for DEBUG

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