Differences

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--- ai_pipeline_audit_logger [2025/05/29 12:46] – [Extending the Framework] eagleeyenebula
+++ ai_pipeline_audit_logger [2025/05/29 12:47] (current) – [Best Practices] eagleeyenebula
@@ Line 261: / Line 261: @@
 . **Define Clear Log Levels:**
-   Use consistent log statuses (e.g., `INFO`, `WARNING`, `FAILURE`) to facilitate pipeline observability and debugging.
+   * Use consistent log statuses (e.g., **INFO**, **WARNING**, **FAILURE**) to facilitate pipeline observability and debugging.
 . **Enrich Logs with Context:**
-   Always include additional `details` to provide actionable information to downstream systems or engineers.
+   * Always include additional `details` to provide actionable information to downstream systems or engineers.
 . **Enable Structured Logging:**
-   Use structured formats (e.g., JSON) for easier parsing, searching, and integration with external systems.
+   * Use structured formats (e.g., JSON) for easier parsing, searching, and integration with external systems.
 . **Monitor and Alert in Real Time:**
-   Integrate log messages into monitoring frameworks to enable proactive alerts.
+   * Integrate log messages into monitoring frameworks to enable proactive alerts.
 . **Extend for Domain-Specific Needs:**
-   Develop custom child classes for unique pipeline scenarios like anomaly detection or multi-pipeline orchestration.
+   * Develop custom child classes for unique pipeline scenarios like anomaly detection or multi-pipeline orchestration.
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 ===== Conclusion =====