ADR-007: Structured Logging System¶
Status: Accepted
Date: 2026-03-30
Context¶
Initial pipeline and scraping processes relied on print statements to track execution progress and identify issues.
While sufficient for early experimentation, this approach presented several limitations:
- Lack of structured output
- Difficulty tracking execution across multiple pipelines
- No persistent record of execution history
- Limited visibility into warnings and errors
As the system grew in complexity, a more robust observability mechanism became necessary.
Decision¶
The system adopts a structured logging approach using Python’s logging module.
Logging is integrated across pipelines and scraping modules, providing:
- multiple log levels (info, warning, error)
- consistent log formatting
- persistent log storage in files
Logs are stored in a dedicated directory and are used for debugging, monitoring and traceability.
Consequences¶
Benefits include:
- Improved observability of pipeline execution
- Easier debugging and error tracing
- Persistent execution history
- Better support for production environments
Trade-offs include:
- Increased complexity compared to simple print statements
- Need for consistent logging practices across modules
This decision enhances the reliability and maintainability of the system as it evolves.