Driver for Data-Driven Change - Azure Cosmos DB Performance, Security & Cost Optimization Done Right
summary
Practical findings and concrete knobs are offered: two collections of ~2.2–2.3 million documents show a nonindexed pagination query returning double the rows and higher RU cost until a composite index is added, partition key choice (Mongo ObjectId) gives high cardinality scaling, and local read multiplier is 1.5. Use Studio 3T, Azure Cosmos DB .NET SDK v3 bulk executor >1 TB/hr, Change Feed with Azure Functions cuts notification latency from 1–2 minutes to seconds, serverless model removes the 400 RU minimum and reserved capacity saves up to 60%.
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chapters (12)
- 0:00Introduction
- 1:16DataDriven Economy
- 5:51Choosing the right abstraction
- 11:14Successful optimization
- 12:25Demo
- 20:42Confidentiality
- 21:22Bulk Execution
- 21:54DataDriven Solutions
- 27:09New Features
- 28:02Capacity Calculator
- 29:04Contact Details
- 29:24Conclusion
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