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Logging Configuration

This example demonstrates comprehensive logging setup for SCIM servers, showing how to configure structured logging, multiple output formats, and operational visibility for production deployments. It covers everything from basic console logging to sophisticated structured logging with multiple backends.

What This Example Demonstrates

  • Structured Logging Setup - JSON and key-value formatted log output for machine processing
  • Multiple Log Levels - Fine-grained control over logging verbosity and filtering
  • Request Tracing - Correlation of log entries across complex operations
  • Performance Logging - Operation timing and performance metrics
  • Error Context Preservation - Detailed error information for debugging and monitoring
  • Production-Ready Patterns - Log management strategies for enterprise deployments

Key Features Showcased

Comprehensive Log Configuration

See how to set up logging that captures all aspects of SCIM server operations, from request processing to storage operations, with appropriate detail levels for different deployment environments.

Request Context Integration

Watch how RequestContext flows through all operations, enabling request correlation and distributed tracing across system boundaries.

Structured Data Logging

The example demonstrates logging complex SCIM data structures in formats that support automated processing, alerting, and analysis by log management systems.

Performance Monitoring

Explore how to capture operation timing, resource usage, and throughput metrics through logging, enabling performance analysis without dedicated monitoring infrastructure.

Concepts Explored

This example integrates logging throughout the SCIM architecture:

Perfect For Understanding

This example is essential if you're:

  • Building Production Systems - Comprehensive operational visibility requirements
  • Implementing Monitoring - Log-based observability and alerting strategies
  • Debugging Complex Issues - Detailed logging for troubleshooting and root cause analysis
  • Managing Enterprise Deployments - Audit trails and compliance logging

Logging Categories

The example covers different types of logging needs:

Request/Response Logging

  • Complete request and response capture for audit trails
  • Parameter sanitization for security-sensitive data
  • Response time and status code tracking
  • Error condition documentation

Business Logic Logging

  • SCIM operation execution with context
  • Validation failures and constraint violations
  • Resource lifecycle events (creation, updates, deletions)
  • Schema validation and extension processing

System Operations Logging

  • Storage backend operations and performance
  • Connection pool usage and database interactions
  • Cache operations and efficiency metrics
  • Background task execution and scheduling

Security and Audit Logging

  • Authentication and authorization events
  • Tenant boundary enforcement
  • Data access patterns and privacy compliance
  • Security policy violations and responses

Log Format Options

Explore different logging formats for various use cases:

Development Logging

  • Human-readable console output with color coding
  • Detailed stack traces and debug information
  • Interactive logging with immediate feedback
  • Local file rotation and management

Production Structured Logging

  • JSON format for log aggregation systems
  • Key-value pairs for efficient querying
  • Standardized field names and formats
  • Integration with monitoring and alerting systems

Compliance and Audit Logging

  • Immutable log entries with integrity verification
  • Standardized audit event formats
  • Long-term retention and archival strategies
  • Privacy-aware logging with data sanitization

Running the Example

# Basic logging setup
RUST_LOG=info cargo run --example logging_example

# Detailed debug logging
RUST_LOG=debug cargo run --example logging_example

# Structured JSON logging
RUST_LOG=info SCIM_LOG_FORMAT=json cargo run --example logging_example

The output demonstrates different logging levels, formats, and integration patterns with clear examples of request correlation and structured data capture.

Log Management Integration

The example shows integration with popular log management tools:

Log Aggregation

  • ELK Stack - Elasticsearch, Logstash, and Kibana integration
  • Fluentd/Fluent Bit - Log forwarding and processing
  • Splunk - Enterprise log management and analysis
  • DataDog/New Relic - Cloud-based logging and monitoring

Observability Platforms

  • Jaeger - Distributed tracing integration
  • Prometheus - Metrics extraction from logs
  • Grafana - Log-based dashboard and alerting
  • OpenTelemetry - Standardized observability data

Configuration Patterns

Learn flexible logging configuration approaches:

Environment-Based Configuration

  • Development vs. production logging levels
  • Feature-specific logging toggles
  • Performance vs. verbosity trade-offs
  • Security-sensitive data handling

Runtime Log Control

  • Dynamic log level adjustment without restarts
  • Feature-specific logging enable/disable
  • Performance-sensitive logging optimization
  • Emergency debugging activation

Production Considerations

The example illustrates enterprise logging requirements:

  • Performance Impact - Minimizing logging overhead in high-throughput scenarios
  • Storage Management - Log rotation, compression, and archival strategies
  • Security - Protecting sensitive data in log files
  • Compliance - Meeting regulatory requirements for audit logging

Next Steps

After exploring logging configuration:

Source Code

View the complete implementation: examples/logging_example.rs