April 2026 monthly summary focusing on key architectural and feature outcomes for harupy/mlflow. Implemented Token Usage Tracking Enhancements with Cache Metrics for the @mlflow/anthropic TypeScript SDK, introducing support for cached token usage metrics (cache read and creation input tokens). Updated extraction logic and tests to cover the new metrics. This work improves observability, accuracy of token-usage data, and cost visibility for token-based workflows, enabling better usage planning and optimization.

February 2026 recap for mlflow/mlflow: Delivered two high-impact features that enhance performance, observability, and real-time capabilities. Upgraded the OpenTelemetry SDK and related dependencies to boost performance and compatibility, and added streaming support for the Anthropic API integration to enable real-time message processing and end-to-end tracing. No major bugs fixed this month. Overall, these improvements strengthen observability, reduce latency, and expand integration capabilities, delivering measurable business value for analytics workflows and AI-enabled deployments.

January 2026: Delivered Anthropic SDK Integration Enhancement for mlflow/mlflow by upgrading the @anthropic-ai/sdk to a newer version (commit eae0acb3f1d7ec9f0038b7dea11347c1fc992dff). The change improves integration reliability and overall functionality, supported by tracing instrumentation updates (tracing-typescript-anthropic) and cross-author collaboration. No major bugs fixed for this feature this month; focus was on upgrade, observability, and maintainability.