This month delivered the Alpha release of the Anomaly Detection Component using Online Isolation Forest for streaming data (traces, metrics, or logs) in the open-telemetry/opentelemetry-collector-releases project. This feature establishes the first ML-driven anomaly detection capability in the collector pipeline and sets the foundation for production-ready monitoring, alerting, and feedback-driven improvements. No major bugs were reported this period; the focus was on feature development, integration, and preparing for stakeholder feedback in the alpha phase. The work enhances observability reliability by enabling early anomaly detection, supports faster MTTR, and creates a scalable path for future enhancements. Technologies demonstrated include the Online Isolation Forest algorithm, streaming data processing, and release-engineering practices within the OpenTelemetry ecosystem.