
Developed and enhanced Spark monitoring and analytics capabilities for Microsoft Fabric within the microsoft/fabric-toolbox repository over a two-month period. Delivered an end-to-end monitoring solution using Python and Spark, integrating performance metrics, resource management, and a KQL dashboard to improve observability and capacity planning. Enhanced the SparkLens notebook by implementing direct error logging to Kusto, enabling real-time monitoring and improved data retention. Introduced dashboard features such as stage summaries and per-application analytics, while refining setup scripts and documentation for smoother onboarding. Focused on data engineering, dashboard development, and cloud services to enable faster insights and more reliable troubleshooting for stakeholders.
November 2025 monthly summary for microsoft/fabric-toolbox focused on delivering observability enhancements and per-app analytics, coupled with stability fixes in the SparkLens notebook. The two primary features completed strengthened data collection, monitoring, and dashboard capabilities, enabling faster insights and better decision-making for stakeholders.
November 2025 monthly summary for microsoft/fabric-toolbox focused on delivering observability enhancements and per-app analytics, coupled with stability fixes in the SparkLens notebook. The two primary features completed strengthened data collection, monitoring, and dashboard capabilities, enabling faster insights and better decision-making for stakeholders.
October 2025: Delivered end-to-end Spark Monitoring for Microsoft Fabric within the microsoft/fabric-toolbox repo. Implemented initial monitoring push and subsequent enhancements, including performance metrics, resource management, a new KQL dashboard, and setup/configuration improvements. The work significantly improves observability, reduces onboarding friction, and enables proactive capacity planning and faster issue diagnosis.
October 2025: Delivered end-to-end Spark Monitoring for Microsoft Fabric within the microsoft/fabric-toolbox repo. Implemented initial monitoring push and subsequent enhancements, including performance metrics, resource management, a new KQL dashboard, and setup/configuration improvements. The work significantly improves observability, reduces onboarding friction, and enables proactive capacity planning and faster issue diagnosis.

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