Sarfaraz097/log-analytics-monitoring-system

# log-analytics-monitoring-system ## What is this? A Format-Agnostic log-analytics-monitoring-system that parses any timestamped log file and generates a System Health Intelligence Report via the command line. ## Folder Structure log-engine/ ├── exec/ │ ├── main.py # Entry point - run this file │ ├── parser.py # Reads and parses log file │ ├── analyzer.py # Calculates KPIs and detects anomalies │ └── reporter.py # Prints report to CLI and saves markdown ├── config/ │ ├── log_mapping.json # Log format configuration │ └── requirements.txt # Python dependencies ├── hackathon_logs.txt # Sample log file └── README.md ## Requirements - Python 3.8+ - rich library ## Installation ### Step 1 - Create virtual environment python -m venv venv ### Step 2 - Activate virtual environment Windows: venv\Scripts\activate ### Step 3 - Install dependencies pip install rich ## How to Run python exec/main.py --log hackathon_logs.txt --config config/log_mapping.json --output both ## Output Options | Option | Description | |--------|-------------| | cli | Show report in terminal only | | markdown | Save report.md file only | | both | CLI + markdown both | ## Sample Output Total Events → 200,000 Error Rate → 25.13% Uptime Score → 74.87% Error Density → 5.03 errors/min Suspicious Users → 899 Unauthorized IPs → 6,631 ## How Config Works Example log line: 2026-04-01 00:00:00 ERROR [DBService] Payment failed orderId=O462 Config maps each part: - timestamp → `2026-04-01 00:00:00` - level → `ERROR` - component → `DBService` - message → `Payment failed orderId=O462` ## Key Features - Dynamic log parsing via JSON config — no hardcoded logic - KPI extraction — error density, uptime score, error rate - Top 5 failing components detection - Failure nature breakdown — 15+ event categories - Anomaly insights — cascading failures, security threats - Markdown report export