Server Log Analyzer
Analyzes server log files to identify problems, extract performance metrics, and provide actionable insights for troubleshooting.
Supported Log Formats
[YYYY/MM/DD HH:MM:SS] module.path LEVEL line_number: message
Example:
[2026/04/15 12:08:03] sanhai.flow.linear_data_flow INFO 127: flow_id:2044266474671067136 - Worker completed
Usage
Basic Analysis
python scripts/log_analyzer.py /path/to/your/logfile.log
JSON Output (for automation)
python scripts/log_analyzer.py /path/to/your/logfile.log --json
Features
1. Log Statistics
- Counts INFO, WARNING, ERROR, CRITICAL entries
- Shows time range and duration
- Module-level statistics
2. Problem Detection
Automatically detects common issues:
| Severity | Issue Type | Detection Pattern |
|---|---|---|
| High | Database failures | [DB] update/insert failed |
| High | Missing components | has no corrector |
| Medium | Notification failures | email notification failed |
| Medium | Classification errors | paper type error |
| Low | ID recognition failures | invalid student number |
3. Python Exception Tracking
Extracts Python traceback information:
- Exception type and message
- Source file locations (filters out framework code)
- Key code location in your project
4. Performance Metrics
- TPS (Tasks Per Second)
- Batch processing time
- Worker-level timing
Output Sections
| Section | Content |
|---|---|
| Summary | Log level counts, time range |
| Exceptions | Python exceptions (highest priority) |
| Performance | TPS, processing time |
| Issues | Problems by severity |
| Modules | Module call frequency |
Performance Thresholds
| Metric | Normal | Warning | Critical |
|---|---|---|---|
| TPS | 50-300 | <20 | <10 |
| Batch Time | <2s | >5s | >10s |
Notes
- Large log files (>10MB) may take longer to process
- Exception tracking filters out framework/library code
- Results are sorted by severity (exceptions first)