Overview
Refactron includes comprehensive logging and monitoring capabilities for production environments:
- Structured Logging - JSON-formatted logs for CI/CD
- Metrics Collection - Track analysis time and success rates
- Prometheus Integration - Expose metrics via HTTP endpoint
- Opt-in Telemetry - Anonymous usage analytics
Structured Logging
Configuration
log_level: INFO # DEBUG, INFO, WARNING, ERROR, CRITICAL
log_format: json # json or text
enable_console_logging: true
enable_file_logging: true
JSON Log Output
{
"timestamp": "2026-02-15T10:30:42Z",
"level": "INFO",
"logger": "refactron.core.refactron",
"message": "Analysis completed successfully",
"duration_ms": 123.45
}
CLI Usage
# JSON logging for CI/CD
refactron analyze mycode.py --log-format json
# Set log level
refactron analyze mycode.py --log-level DEBUG
Metrics Collection
Track detailed metrics about Refactron operations.
View Metrics
# Text format
refactron metrics
# JSON format
refactron metrics --format json
Example Output
📈 Refactron Metrics
Analysis Metrics:
Files analyzed: 45
Issues found: 123
Total time: 5234ms
Success rate: 95.6%
Analyzer Hit Counts:
complexity: 23
security: 15
type_hints: 45
Python API
stats = refactron.get_performance_stats()
print(f"Files analyzed: {stats['files_analyzed']}")
print(f"Issues found: {stats['issues_found']}")
Prometheus Integration
Expose metrics via HTTP endpoint for Prometheus scraping.
Start Metrics Server
# Default port 9090
refactron serve-metrics
# Custom port
refactron serve-metrics --port 8080
Available Metrics
Counters:
refactron_files_analyzed_totalrefactron_issues_found_totalrefactron_analyzer_hits_total{analyzer="name"}
Gauges:
refactron_analysis_duration_msrefactron_analysis_success_rate
Prometheus Configuration
Add to your prometheus.yml:
scrape_configs:
- job_name: 'refactron'
static_configs:
- targets: ['localhost:9090']
Telemetry
Telemetry is opt-in only and disabled by default. It collects anonymous usage statistics to help improve Refactron.
What is Collected
Collected:
- Number of files analyzed
- Analysis execution time
- Python version and OS platform
NOT Collected:
- Your code or file names
- Personal information
- Error messages or stack traces
Manage Telemetry
# Check status
refactron telemetry --status
# Enable telemetry
refactron telemetry --enable
# Disable telemetry
refactron telemetry --disable
Environment-Specific Configurations
Development
log_level: DEBUG
log_format: text
enable_metrics: true
enable_prometheus: false
CI/CD
log_level: INFO
log_format: json
enable_metrics: true
enable_prometheus: false
Production
log_level: WARNING
log_format: json
enable_metrics: true
enable_prometheus: true
prometheus_port: 9090
Best Practices
Use JSON Logging in CI/CD
JSON format integrates easily with log aggregation systems
Enable Metrics in Production
Track performance and identify bottlenecks
Set Up Prometheus Dashboards
Visualize Refactron metrics over time
Keep Telemetry Optional
Respect user privacy with opt-in telemetry
Next Steps
CI/CD Integration
Learn how to integrate Refactron into your CI/CD pipeline
