Uploaded June 2025 | Updated September 2026, 1 week ago
In this video, you'll learn how to design Pydantic models that optimize Azure Cosmos DB performance and eliminate common scaling bottlenecks. Instead of using one generic model everywhere, we'll create a targeted inheritance hierarchy that enforces database constraints at the type level and prevents expensive cross-partition operations.
What You'll Learn:
• Strategic partition key selection that avoids hot partitions
• Pydantic inheritance patterns that eliminate code duplication
• Field validation techniques that reduce RU consumption
• Identity management classes for efficient document lookups
• Batch operation modeling aligned with Azure Cosmos DB constraints
• Custom validators that prevent costly database mistakes
• Response modeling that handles Azure Cosmos DB metadata cleanly
Perfect for: Python developers building scalable APIs with FastAPI and Azure Cosmos DB, especially those preparing backends for AI workloads that require high-throughput data operations.
Presenter Gwyneth Peña-Siguenza
Links:
• Complete code: github.com/madebygps/cosmosdb-fastapi-functions
• Microsoft FastAPI + Azure Cosmos DB integration: devblogs.microsoft.com/cosmosdb/azure-cosmos-db-python-and-fastapi
• Azure Cosmos DB Python best practices: learn.microsoft.com/en-us/azure/cosmos-db/nosql/best-practice-python
• Pydantic documentation: https://docs.pydantic.dev/
• Subscribe to Azure Cosmos DB on YouTube – youtube.com/AzureCosmosDB
• Follow Azure Cosmos DB on X – twitter.com/AzureCosmosDB
• Follow Azure Cosmos DB on LinkedIn – linkedin.com/company/azure-cosmos-db
#Python #AzureCosmosDB #Azure #NoSQL #DatabaseTutorial #PythonSDK
In this video, you'll learn how to design Pydantic models that optimize Azure Cosmos DB performance and eliminate common scaling bottlenecks. Instead of using one generic model everywhere, we'll create a targeted inheritance hierarchy that enforces database constraints at the type level and prevents expensive cross-partition operations.
What You'll Learn:
• Strategic partition key selection that avoids hot partitions
• Pydantic inheritance patterns that eliminate code duplication
• Field validation techniques that reduce RU consumption
• Identity management classes for efficient document lookups
• Batch operation modeling aligned with Azure Cosmos DB constraints
• Custom validators that prevent costly database mistakes
• Response modeling that handles Azure Cosmos DB metadata cleanly
Perfect for: Python developers building scalable APIs with FastAPI and Azure Cosmos DB, especially those preparing backends for AI workloads that require high-throughput data operations.
Presenter Gwyneth Peña-Siguenza
Links:
• Complete code: github.com/madebygps/cosmosdb-fastapi-functions
• Microsoft FastAPI + Azure Cosmos DB integration: devblogs.microsoft.com/cosmosdb/azure-cosmos-db-python-and-fastapi
• Azure Cosmos DB Python best practices: learn.microsoft.com/en-us/azure/cosmos-db/nosql/best-practice-python
• Pydantic documentation: https://docs.pydantic.dev/
• Subscribe to Azure Cosmos DB on YouTube – youtube.com/AzureCosmosDB
• Follow Azure Cosmos DB on X – twitter.com/AzureCosmosDB
• Follow Azure Cosmos DB on LinkedIn – linkedin.com/company/azure-cosmos-db
#Python #AzureCosmosDB #Azure #NoSQL #DatabaseTutorial #PythonSDK
