log-analyzer

To analyze application logs, this skill parses plain text stack traces and structured JSON logs to automatically identify error patterns and exceptions. It uses standard Unix utilities like grep, awk, and Python 3 to process files and generate summaries of frequent errors.

Tracing a correlation ID across distributed service logs is done by searching and correlating specific request IDs across multiple log files. This skill visualizes the full lifecycle of a transaction by matching identifiers to track request flows between services.

Yes, you can filter structured JSON logs using jq and awk. This skill leverages these standard Unix dependencies to parse, search, and analyze JSON log entries, extracting specific fields and correlating events across services for debugging.

Real-time monitoring of application logs is achieved by streaming and filtering log entries as they are generated. This skill detects anomalies and performance bottlenecks on the fly, allowing you to identify issues and optimize system health during execution.

Yes, Python 3 is required for advanced traceback parsing and debugging application logs. Alongside Python 3, the skill depends on standard Unix utilities like grep, awk, and jq to perform comprehensive log analysis and pattern recognition.