Continuous Intelligence¶

This site provides documentation for this project. Use the navigation to explore module-specific materials.

How-To Guide¶

Many instructions are common to all our projects.

See ⭐ Workflow: Apply Example to get these projects running on your machine.

Project Documentation Pages (docs/)¶

• Home - this documentation landing page
• Project Instructions - instructions specific to this module
• Your Files - how to copy the example and create your version
• Glossary - project terms and concepts

Additional Resources¶

• Suggested Datasets

Custom Project¶

Dataset¶

Two CSV files: a reference dataset and a current dataset (recent behavior). Each contains requests, errors, and total_latency_ms columns, where each row is one system observation.

Signals¶

Three difference signals (current avg minus reference avg) with drift flags: - requests_mean_difference — flagged if absolute difference > 20.0 - errors_mean_difference — flagged if absolute difference > 2.0 - latency_mean_difference_ms — flagged if absolute difference > 1000.0

Experiments¶

Added rows to current_metrics_jugurtha.csv that mirror reference values, to test whether the pipeline would correctly resolve previously detected drift.

Results¶

All three drift flags returned False after adding the reference values — no drift detected.

Interpretation¶

Mean-based drift detection self-corrects as accurate data accumulates. A drift flag signals a need to investigate, not necessarily a permanent failure — if values stabilize, the flag clears on its own.