How to achieve good cost/performance with Azure Cosmos DB elasticity
summary
Shows how to cut wasted RU spend by enabling the preview Dynamic scaling so autoscale scales each region and partition independently instead of to the hottest one; demo uses East US2/West US2 with a shopping cart (provisioned 10,000 RUs autoscale) and shows per-region deltas as cost savings. Demonstrates partition key impact: date key wastes capacity (50,000 RUs provisioned but only ~10,000 RUs usable) versus device ID hitting near 50,000. Covers partition merge via CLI/PowerShell what‑if to collapse five physical partitions into one (≈4GB) after downsizing.
AI-written summary · about
chapters (4)
related talks
08mOptimize for the Best Cost and Performance for Azure Cosmos DB NoSQL API
01h 00mCost cutting strategies for Azure Cosmos DB
48mPerformance tuning for Azure Cosmos DB
52mPerformance tuning for Azure Cosmos DB
46mDesign and build multi-tenant SaaS apps at scale with Azure Cosmos DB
01h 13mBuilding Planet Scale .NET Apps with Azure Cosmos DB
18mIntelligent Resource Optimization: Mastering Azure Cosmos DB for Enterprise Workloads
01h 03mData Modeling and Partitioning in Azure Cosmos DB
