aganiezgoda / Azure-OpenAI-Insights

Workbook for Azure OpenAI service

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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

This workbook contains 3 main parts:

  • Overview - Holistic view of Azure OpenAI resources
  • Monitor - Holistic view of Azure OpenAI resources Metrics
  • Insights - Holistic view of Azure OpenAI resources Logs
    • Requires by enabling Diagnostic Settings to Log Analytics Workspace.

Views

Types of views this workbook provides:

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

The information displayed uses KQL queries to query the Azure Resource Graph.

  • Monitor
    • Overview
      • Requests
      • Processed Inference Tokens
      • Processed Prompt Tokens
      • Generated Completions Tokens
      • Processed FineTuned Training Hours
      • Provisioned-managed Utilization
    • HTTP Requests
      • by Model Name
      • by Model Version
      • by Model Deployment Name
      • by Status Code
      • by StreamType
      • by Operation Name
      • by API Name
      • by Region
    • Token-Based Usage
      • Processed Inference Tokens
        • by Model Name
        • by Model Deployment Name
      • Processed Prompt Tokens
        • by Model Name
        • by Model Deployment Name
      • Generate Completitions 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
    • Fine-tuning
      • Processed FineTuned Training Hours
        • by Model Name
        • by Model Deployment Name

The information displayed uses Azure OpenAI Platform Metrics and presented by multiple dimensions.

  • 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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This workbook support to filter all the logs by several fields:

  • 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.

The information displayed uses KQL queries to query the Log Analytics Workspace that store the logs.

Note: The Logs will be available on resources that enabled Diagnostic Settings to Log Analytics Workspace.

Average Duration (ms) image

Average Request / Response Length (bytes) image

How to use it?

Importing this Workbook to your Azure environment is quite simple.

Follow this steps to use the Workbook:

  • Click on '+ Create'

  • Click on '+ New'

  • Open the Advanced Editor using the '</>' button on the toolbar

  • Select the 'Gallery Template' (step 1)
  • Replace the JSON code with this JSON code Azure OpenAI Insights JSON (step 2)
    • We use the Gallery Templaty type (step 1), so we need to use the 'Azure OpenAI Insights.workbook' and not the 'Azure OpenAI Insights.json'.
  • Click 'Apply' (step 3)

  • Click in the ‘Save’ button on the toolbar

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  • Select a name and where to save the Workbook:
    • Title: 'Azure OpenAI Insights'
    • Subscription: <Subscription Name>
    • Resource group: <Resource Group Name>
    • Location: <Region>
  • Click 'Save'

The Workbook is ready to use!

  • Click on 'Workbooks'
  • Click on 'Azure OpenAI Insights' Workbook.

Start using the Workbook and analyze your Azure OpenAI resources.

(Optional) You can filter by specific subscription/s or resource/s.

About

Workbook for Azure OpenAI service

License:MIT License