Automate machine-learning model monitoring with New Relic One and DAGsHub

Integrating DAGsHub with New Relic One offers a streamlined solution for tracking and analyzing machine learning models by automating monitoring processes, providing real-time metrics, and enabling custom visualizations. This collaboration allows data scientists and machine learning engineers to better manage the complexities of model experiments through a unified platform. DAGsHub, known for its focus on versioning data, models, experiments, and code, integrates seamlessly with New Relic's monitoring capabilities, leveraging open-source tools like Git, DVC, MLFlow, and Jenkins. Users can set alerts, create custom dashboards, and utilize NRQL queries to effectively track model performance, thus enhancing workflow efficiency and visibility into ML-powered applications. The partnership aims to optimize data science workflows by offering a comprehensive view of experiment performance, enabling custom alerts, and facilitating efficient incident correlation.

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