AI-200
Azure
Back to Develop AI solutions with Azure Cosmos DB for NoSQL

Optimize query performance for Azure Cosmos DB for NoSQL

Exercise - Optimize query performance with vector indexes on Azure Cosmos DB

Overview

Hands-on exercise covering Exercise - Optimize query performance with vector indexes on Azure Cosmos DB as part of the Optimize query performance for Azure Cosmos DB for NoSQL module in the Develop AI solutions with Azure Cosmos DB for NoSQL learning path.

Key concepts

  • Core concepts and terminology for this topic
  • How it fits into Azure AI solution development
  • Common patterns used in production workloads

Exam tips

  • Focus on when and why to use this capability on Azure
  • Know the trade-offs and how it connects to other AI-200 skills
  • Review official Microsoft Learn docs for the latest service behavior

Azure CLI

Azure CLI
# Replace with resource group and names for your environment
az group create --name rg-ai200 --location eastus

# Add service-specific commands for: Exercise - Optimize query performance with vector indexes on Azure Cosmos DB

Python

Python
# Example pattern for: Exercise - Optimize query performance with vector indexes on Azure Cosmos DB
# Integrate with Azure SDKs using managed identity where possible

def main():
    pass  # Implement based on module lab steps

if __name__ == "__main__":
    main()

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