Custom Metric And Test Composition With Python Plugin Architecture

ML/LLM monitoring — data drift, model quality, 100+ metrics, dashboards, test suites.

Unique: Provides a minimal base class interface (Metric, TestCondition) that integrates directly into the PythonEngine execution model, enabling custom metrics to compose seamlessly with built-in metrics without adapter code. The architecture separates metric definition from execution, allowing custom metrics to benefit from framework features (batching, caching, result serialization) automatically.

vs others: More extensible than closed-source monitoring tools because the plugin system is code-first and version-controlled; more integrated than standalone metric libraries because custom metrics inherit framework features (dashboard integration, test suite composition) without duplication.