// 42 - How to choose the 'Right' Datastore for your scenario

Are you running dedicated compute for every tenant, microservice, or application instance — and paying for it? The Compute Resource Consolidation pattern shows you how to consolidate tasks onto shared infrastructure, such as a single AKS cluster with namespace isolation or an Azure SQL elastic pool, to reduce costs and management overhead. This episode explores the key trade-offs: blast radius containment, noisy neighbour contention, scalability profiles, and multi-tenancy strategies. Part of the "Architecting for the Cloud, One Pattern at a Time" series.

Chris Reddington and Will Eastbury cover three closely related messaging patterns in one packed episode. They start with the Publish-Subscribe (Pub/Sub) pattern — arguably the most transformative shift in enterprise messaging — where a single producer broadcasts to multiple isolated subscribers via Azure Service Bus topics or Azure Event Grid. Real-world use cases include insurance aggregators, credit check pipelines, and bank account sign-up workflows. From there they move to the Priority Queue pattern, which ensures high-priority messages are processed before lower-priority ones even when consumers are under load. Finally, the Pipes and Filters pattern decomposes complex message processing into a chain of discrete, reusable transformation steps — reducing complexity and enabling independent scaling of each stage. The episode also connects these patterns back to earlier topics like Competing Consumers and Queue-Based Load Leveling, and flags related patterns including Choreography and Compensating Transactions.

Concerned about the scalability of your data layer, or do you need data segregation for customers with regional data residency requirements? The Sharding pattern addresses exactly these challenges. If you are using a NoSQL data store without native secondary index support, the Index Table pattern provides an elegant solution for efficient querying. In this episode, Chris is joined by Steph Martin to explore both patterns in depth: shard key strategies (lookup, range, hash), cross-shard query design, the Azure SQL Database elastic client library, and how the Index Table pattern solves query efficiency challenges in stores like Cassandra and Cosmos DB.