microsoft/Application-Insights-Workbooks
Oct 2024 – Nov 2024
2 Months active
Languages Used
JSONKQL
Technical Skills
Application InsightsAzure AI StudioData VisualizationTelemetry AnalysisAI MonitoringAzure
Sushant Divate
PROFILE
Sushant Divate
Worked on the microsoft/Application-Insights-Workbooks repository to deliver and enhance the Azure AI Studio Insights Workbook, enabling comprehensive observability for generative AI workloads. Focused on integrating telemetry for token usage, user feedback, evaluation metrics, and AI spans to support performance monitoring and incident response. Improved session data presentation, span clarity, and resource configurations, while aligning instrumentation with otel-openai-v2 standards for scalable AI monitoring. Utilized KQL and JSON to refine data analysis and visualization, and addressed a typographical error to improve documentation accuracy. The work strengthened operational insight, maintainability, and data-driven optimization for AI applications deployed on Azure.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
4Total
Bugs
1
Commits
4
Features
2
Lines of code
1,767
Activity Months2
Your Network
4752 peopleSame Organization
@microsoft.com4720
GitOpsMember
Ananta GuptaMember
Abi GicicMember
Abigail HartmanMember
Abram SandersonMember
Adam EttenbergerMember
Alexandre GattikerMember
Ami HollanderMember
AndersMember
Work History
November 2024
3 Commits • 1 Features
Nov 1, 2024In November 2024, delivered substantial enhancements to the AI Studio Insights workbook within the Microsoft/Application-Insights-Workbooks repository, strengthening observability for generative AI workloads. Key work included otel-openai-v2 instrumentation support, improved session data presentation, clearer span information, and refined resource configurations to enable more accurate telemetry and operational visibility. The updates also refined processing of AI-related events, spans, and evaluations, including user/system message identification and LLM responses, positioning the team to detect issues faster and optimize AI deployments.
3 Commits • 1 Features
Nov 1, 2024In November 2024, delivered substantial enhancements to the AI Studio Insights workbook within the Microsoft/Application-Insights-Workbooks repository, strengthening observability for generative AI workloads. Key work included otel-openai-v2 instrumentation support, improved session data presentation, clearer span information, and refined resource configurations to enable more accurate telemetry and operational visibility. The updates also refined processing of AI-related events, spans, and evaluations, including user/system message identification and LLM responses, positioning the team to detect issues faster and optimize AI deployments.
November 2024
October 2024
1 Commits • 1 Features
Oct 1, 2024October 2024 summary for microsoft/Application-Insights-Workbooks: Delivered the Azure AI Studio Insights Workbook to enable comprehensive observability for generative AI workloads. The workbook provides telemetry on token usage, user feedback, evaluation metrics, exceptions, and AI spans/sessions to track performance and identify bottlenecks, supporting data-driven optimization and faster incident response. Release anchored by commit d22d3ac63c411ac2e143f58ac8b103414abd7a2f (Azure AI Studio Insights #2806). This work enhances business value by improving reliability, efficiency, and actionable insight for AI applications.
October 2024
1 Commits • 1 Features
Oct 1, 2024October 2024 summary for microsoft/Application-Insights-Workbooks: Delivered the Azure AI Studio Insights Workbook to enable comprehensive observability for generative AI workloads. The workbook provides telemetry on token usage, user feedback, evaluation metrics, exceptions, and AI spans/sessions to track performance and identify bottlenecks, supporting data-driven optimization and faster incident response. Release anchored by commit d22d3ac63c411ac2e143f58ac8b103414abd7a2f (Azure AI Studio Insights #2806). This work enhances business value by improving reliability, efficiency, and actionable insight for AI applications.
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage30.0%
Skills & Technologies
Programming Languages
JSONKQL
Technical Skills
AI MonitoringApplication InsightsAzureAzure AI StudioData AnalysisData VisualizationDocumentationGenerative AIObservabilityTelemetry Analysis
Repositories Contributed To
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