Log Analyzer

A Python script that parses log files, filters entries by timestamp, log level, or message content, and summarizes errors. Designed to demonstrate troubleshooting and log analysis skills for IT operations roles.

Setup

1. Ensure Python 3.6+ is installed.
2. Save test.log with sample log entries (provided in this repository).
3. Run the script with optional arguments:
   • Filter by log level: python analyzer.py test.log --level=ERROR
   • Filter by timestamp: python analyzer.py test.log --start="2025-07-14 10:00:00" --end="2025-07-14 10:02:00"
   • Filter by message: python analyzer.py test.log --message="timeout"
4. Output includes filtered logs and error count; a summary.txt file is generated with the error count.

Purpose

This project showcases:

• Log parsing and filtering to identify critical issues (e.g., ERROR logs).
• Command-line argument handling for flexible analysis.
• Summarization of operational issues, useful for incident reporting and documentation.
• Skills in Python programming and troubleshooting for IT operations environments.

Code Overview

• Language: Python
• Libraries: argparse for command-line arguments, datetime for timestamp parsing
• Functionality:
  • Reads log files in format: YYYY-MM-DD HH:MM:SS - LEVEL - Message
  • Filters logs based on optional parameters (start/end time, level, message)
  • Outputs filtered logs and counts errors
  • Writes error count to summary.txt

Output Example

Running python analyzer.py test.log --level=ERROR with the provided test.log:
Filtered logs (2):
2025-07-14 10:00:00 - ERROR - Server timeout occurred
2025-07-14 10:02:00 - ERROR - Database connection failed
Errors found: 2

Generates summary.txt with content:
Errors: 2

Job Relevance

Aligns with IT operations needs for:

• Troubleshooting system issues through log analysis
• Managing and documenting operational incidents
• Supporting tools like Jira/Confluence for knowledge base updates