// Cloud Design Patterns

Weekly Vlog #15 covers a lighter-than-usual Azure week, spotlighting Azure Cloud Services extended support GA with a migration tool preview, Azure Orbital's ground station-as-a-service partnership updates, and a great Azure DevOps blog post on building and publishing your first GitHub Action. Cloud with Chris highlights include a Windows Terminal productivity Cloud Drop, the Bulkhead resilience pattern episode, a Microsoft Learn introductory video, and a recap of the Northern Azure User Group talk alongside Scott Hanselman — with two Global Azure sessions on Hugo static sites and GitHub Actions just around the corner.

The Bulkhead pattern takes its name from the watertight compartments in a ship's hull. Just as those compartments prevent a single breach from sinking the whole vessel, the Bulkhead pattern isolates components of a cloud application so that failures or resource exhaustion in one service cannot cascade to others. This episode covers partitioning strategies, connection pools, Kubernetes resource limits, and multi-tenancy considerations.

In this Easter Sunday livestream, Chris covers Microsoft's Forrester Wave leader recognition for Azure Functions (FaaS), a wave of AKS updates including the new run command feature and Open Service Mesh add-on, and the GitHub Advanced Security security overview beta plus GA of secret scanning for private repositories. Delivery Plans 2.0 in Azure DevOps approaches GA with card styling and dependency visualisation, while GitHub Desktop gains cherry-pick support and GitHub Mobile adds working-hours notification controls. Cloud with Chris highlights include a beginner Git 101 Cloud Drop, a community blogging panel, the External Configuration and Claim Check architecture pattern episode with Peter Piper, and a preview of the upcoming Northern Azure User Group talk alongside Scott Hanselman.

Chris and Peter cover two cloud design patterns in depth. The External Configuration Store pattern addresses one of the most critical security concerns in cloud development: keeping secrets and connection strings out of source code. They explore Azure Key Vault and Azure App Configuration as canonical implementations, discuss deployment slot behaviour, and highlight the risks of committing credentials to version control. The Claim Check pattern tackles a different challenge — what happens when your message payload exceeds the size limits of your messaging infrastructure (Azure Service Bus, Azure Queue Storage)? By externalising the payload to a data store and passing only a correlation ID on the queue, you gain scalability and flexibility at the cost of added latency. Azure Event Grid's automatic claim check generation is also demonstrated. Security is a thread running through both patterns: compromised config stores and poisoned messages both demand an operational response plan.

The cache-aside pattern loads data on demand from a data store into a cache, placing the synchronisation logic in the application layer when the cache does not natively support read-through or write-through operations. This episode covers cache-miss handling, expiration and eviction policies for Azure Cache for Redis, consistency challenges across distributed instances, and when to pre-warm the cache at startup instead.

When modernising a legacy application, rewriting everything from scratch is rarely feasible. The Sidecar and Ambassador cloud design patterns offer a pragmatic alternative — attach a companion process to offload cross-cutting concerns like retry logic, circuit breaking, and protocol translation without modifying the application itself. Chris and Peter explore both patterns in depth, covering when to use each, how they relate to service meshes, and their role in Kubernetes-based architectures.

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.

Ever thought about what it takes to host a game in the Cloud? Well, this is the series for you! On the first Wednesday of every month, we explore Cloud Concepts that impact your journey to a connected multiplayer gaming experience! In this first session, we'll play some Minecraft and talk to the concept of a hosted game server.

Chris recaps the health endpoint monitoring pattern episode and a PC build blog, then previews the debut of Cloud Gaming Notes with Lee Williams on game server hosting, and a candid mental health conversation with Andrew Nathan. He reviews Azure updates including Azure Cloud Services Extended Support ARM-based deployment, Azure AD Premium 99.99% SLA, the Azure Architecture Center January digest, and GitHub engineering posts on canary deployment strategies and JavaScript performance optimisation.