microsoft/Application-Insights-Workbooks
Sep 2025 – Sep 2025
1 Month active
Languages Used
KQL
Technical Skills
Azure Machine LearningData AnalysisKusto Query LanguageMonitoringObservability
Vinutha Karanth
PROFILE
Vinutha Karanth
Vikarant worked on the microsoft/Application-Insights-Workbooks repository, delivering KQL-driven improvements to the Azure ML Studio Foundry Dashboard. He consolidated and refined Kusto Query Language logic to enhance the accuracy and clarity of key metrics, including total tokens, average inference duration, total inference calls, and error rates. By improving deduplication and filtering in AI quality and risk scoring calculations, Vikarant enabled more reliable monitoring and data-driven decision-making. His work focused on data analysis and observability, updating aggregation and percentage-change calculations for token usage. These enhancements provided a clearer, more actionable dashboard for monitoring Azure Machine Learning workloads.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
26
Activity Months1
Your Network
4183 people
Work History
September 2025
2 Commits • 1 Features
Sep 1, 2025September 2025 summary for microsoft/Application-Insights-Workbooks: Delivered Azure ML Studio Foundry Dashboard: KQL Improvements for Metrics and Token Usage. Consolidated KQL logic across the Foundry Dashboard and workbook to improve data accuracy and presentation of key metrics including total tokens, average inference duration, total inference calls, and error rates. Refined AI quality and risk/safety score calculations via improved deduplication and filtering. Improved token usage aggregation and percentage-change calculations for a clearer token usage dashboard, enabling more reliable monitoring and data-driven decisions. Commit references: 1193395368629551de8a03eb28ef1f0a2dac62b8 (add (#3079)) and b3f3c1999a0df659cf21c082278e6c2e8e4867f0 (Update total_token query and token usage chart query (#3086)).
2 Commits • 1 Features
Sep 1, 2025September 2025 summary for microsoft/Application-Insights-Workbooks: Delivered Azure ML Studio Foundry Dashboard: KQL Improvements for Metrics and Token Usage. Consolidated KQL logic across the Foundry Dashboard and workbook to improve data accuracy and presentation of key metrics including total tokens, average inference duration, total inference calls, and error rates. Refined AI quality and risk/safety score calculations via improved deduplication and filtering. Improved token usage aggregation and percentage-change calculations for a clearer token usage dashboard, enabling more reliable monitoring and data-driven decisions. Commit references: 1193395368629551de8a03eb28ef1f0a2dac62b8 (add (#3079)) and b3f3c1999a0df659cf21c082278e6c2e8e4867f0 (Update total_token query and token usage chart query (#3086)).
September 2025
Activity
Loading activity data...
Quality Metrics
Correctness85.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
KQL
Technical Skills
Azure Machine LearningData AnalysisKusto Query LanguageMonitoringObservability
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline