
During a two-month period, Sudivate developed and enhanced the Azure AI Studio Insights Workbook within the microsoft/Application-Insights-Workbooks repository, focusing on observability for generative AI workloads. Leveraging Application Insights, Azure AI Studio, and KQL, Sudivate implemented telemetry features to monitor token usage, user feedback, evaluation metrics, and AI session performance, enabling data-driven optimization and faster incident response. The work included support for otel-openai-v2 instrumentation, improved session data presentation, and refined resource configurations for scalable monitoring. Sudivate also addressed data accuracy by correcting evaluation metric labels, demonstrating attention to detail and a strong grasp of telemetry analysis and data visualization.

In 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.
In 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.
October 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 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.
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