Aravind Krishna stops by to chat with Scott Hanselman and take a look at common design patterns for building highly scalable solutions with Azure Cosmos DB. We will talk a little bit about modeling data and how to choose an appropriate partition key. We then look at a few patterns like event sourcing, time series data, and patterns for addressing bottlenecks/hot spots for reads, writes, and storage.For more information:Azure Cosmos DB (overview)Azure Cosmos DB (docs)Partition and scale in Azure Cosmos DBCreate a Free Account (Azure)Follow @SHanselman Follow @AzureFriday Follow @arkramac