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Patterns for building cloud platforms that teams can operate, govern and evolve.
Platform engineering is the work of turning architectural intent into dependable paths for delivery and operations. This collection focuses on useful abstractions, GitOps, governance and the decisions behind sustainable cloud platforms.
Recommended entry point
A concrete example of turning platform intent into a repeatable operating model.
Selected reading
The Unseen Work of a Cloud Architect: A Story About Building Azure the Hard (and Right) Way The story of implementing an Azure cloud environment rarely starts with technology. It …
Inside Microsoft’s New AKS Desktop
Kubernetes is very good at reporting desired state. A Deployment can be available while its pods restart every few hours. A cluster can show green nodes while workloads have no …
Kubernetes has become so familiar that many teams don’t choose to adopt it anymore; they just start using it. When a new internal API appears, someone sets up an AKS …
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Governance and operating patterns for platforms that have grown beyond one cluster.
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Ingress-NGINX has stopped receiving patches, so it's time to plan the move. Here's what I would look at, whether you run AKS or managed Kubernetes at a hosting provider, plus what I learned testing the migration paths.
Production readiness starts where most tutorials end. Installing Dapr, deploying sidecars, and proving the building blocks are necessary milestones, but they do not answer the …
A Dapr-enabled application can work perfectly with one replica and still be unprepared for production. The sidecar may have no resource requests, every application may be able to …
A request can fail even when every Kubernetes pod is Running. The application may be waiting for a Dapr component, a retry may mask a slow dependency, or a call may reach the …
The first six parts of this series covered Dapr’s most familiar building blocks: service invocation, state management, and pub/sub. They solve application-to-application …
A synchronous request establishes a direct dependency: the caller pauses while the destination handles the task. This approach is suitable when an immediate response is required. …