Content by Patty Chow (4)

Patty Chow shares real-world Azure Cosmos DB Conf stories about teams using Azure Cosmos DB as an operational backbone, including one case where a single database replaced four systems, reduced costs by 73%, and cut latency by 65%.

Patty Chow recaps an Azure Cosmos DB Conf story where a team reduced Cosmos DB costs by 60% while eliminating throttling and dramatically improving P99 latency, focusing on design choices like RU/s tuning, partition keys, indexing, and query patterns.

Patty Chow uses a “two people, one seat” scenario to highlight why concurrency bugs show up in real systems, then points to Azure Cosmos DB patterns—like multi-region writes, conflict resolution, change feed, event sourcing, and replay/replayable architectures—to design for issues you can’t easily simulate.

Patty Chow explains what it takes to move an AI agent beyond a demo, focusing on “memory” as an architecture decision that affects cost, recall quality, and user experience, and demonstrating an MCP server running inside GitHub Copilot backed by Azure Cosmos DB.