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@dolevshor dolevshor released this 03 Sep 19:23
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Azure OpenAI Insights

The 'Azure OpenAI Insights' workbook offers deep insights into Azure OpenAI usage, helping you manage costs, optimize performance, and make strategic decisions for a robust AI infrastructure.

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Introduction

In the ever-evolving world of Artificial Intelligence, organizations and entities across various sectors are on a quest to leverage advanced technologies efficiently. Azure OpenAI opens a realm of possibilities, offering both challenges and excitement, particularly for those at the early stages of AI adoption.

Read more in depth in this Tech Community blog: Azure OpenAI Insights: Monitoring AI with Confidence

This workbook offers deep insights into Azure OpenAI resources and usage (Platform Metrics and Logs) and can be powerful tool in analyzing & monitoring your AI initiatives.

Structure and Views

Structure

  • Overview - Holistic view of Azure OpenAI resources
  • Monitor - Holistic view of Azure OpenAI resources Metrics
  • Insights - Holistic view of Azure OpenAI resources Logs

Views

  • Overview

    • Azure OpenAI Resources by
      • SubscriptionId
      • Resource Group
      • Location
      • Kind
      • Public Network Access
      • Private Network Access
    • All Azure OpenAI Resources
  • Monitor

    • Overview
      • Requests
      • Processed Inference Tokens
      • Processed Prompt Tokens
      • Generated Completions Tokens
      • Processed FineTuned Training Hours
      • Provisioned-managed Utilization
      • Active Tokens
      • Prompt Token Cache Match Rate
      • Time to Response
    • HTTP Requests
      • Requests
        • by Model Name
        • by Model Version
        • by Model Deployment Name
        • by Status Code
        • by StreamType
        • by Operation Name
        • by API Name
        • by Region
      • Time to Response
        • by Model Name
        • by Model Deployment Name
      • Prompt Token Cache Match Rate
        • by Model Name
        • by Model Deployment Name
    • Token-Based Usage
      • Processed Inference Tokens
        • by Model Name
        • by Model Deployment Name
      • Processed Prompt Tokens
        • by Model Name
        • by Model Deployment Name
      • Generate Completion Tokens
        • by Model Name
        • by Model Deployment Name
      • Active Tokens
        • by Model Name
        • by Model Deployment Name
    • PTU Utilization
      • Provisioned-managed Utilization
        • by Model Name
        • Model Version
        • by Model Deployment Name
        • by StreamType
        • by Region
    • Fine-tuning
      • Processed FineTuned Training Hours
        • by Model Name
        • by Model Deployment Name
  • Insights

    • Overview
      • Requests
        • by Resource
        • by Location
        • by StreamType
        • by Api Version
        • by Model Deployment Name + Operation Name
        • by Model Deployment Name
        • by Model Name + Operation Name
        • by Model Name
        • by Operation Name
        • by Avg Duration (ms)
        • by Avg Request Length (bytes)
        • by Avg Response Length (bytes)
    • By CallerIP
      • Requests
      • Operation Name
      • Model Deployment Name + Operation Name
      • Model Name + Operation Name
      • Avg Duration (ms)
      • Avg Request Length (bytes)
      • Avg Response Length (bytes)
    • All Logs
      • Successful requests
    • Failures
      • Failed requests
        • by Resources
        • by Api Version
        • by Operation name
        • by Stream Type

Filters

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Filter supported:

  • Model Deployment Name
  • Model Name
  • Model Version
  • Api Version
  • Operation Name
  • Stream Type
  • Location

All the filters are related to each other to allow a granular view and simplify the tracking of the logs.

Average Duration (ms)
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Average Request / Response Length (bytes)
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