Platform Engineering for .NET & Azure Teams

Platform Engineering represents the discipline of designing and building internal developer platforms (IDPs) that enable development teams to deliver software faster and with less cognitive load. Rather than forcing developers to manage infrastructure complexity directly, platform engineering teams create self-service capabilities, golden paths, and automated workflows that abstract away operational concerns.

At its core, platform engineering focuses on treating the platform as a product with developers as customers. This means understanding developer needs, measuring platform adoption, and continuously improving the developer experience (DevEx). The goal is to reduce toil, standardize best practices, and enable teams to focus on business logic rather than infrastructure configuration.

Key Focus Areas

Self-Service Infrastructure: Providing developers with on-demand access to environments, services, and resources through APIs, portals, or CLI tools. This includes provisioning databases, deploying applications, configuring observability, and managing secrets—all without requiring manual operations team intervention.

Golden Paths: Establishing opinionated, well-paved workflows that guide developers toward secure, compliant, and efficient patterns. Golden paths reduce decision fatigue and ensure consistency across teams while still allowing flexibility when needed.

Developer Experience (DevEx): Optimizing tooling, documentation, and workflows to minimize friction in the development lifecycle. This includes reducing build times, simplifying deployment processes, and providing clear feedback loops.

Platform Engineering intersects with DevOps, Infrastructure as Code, Kubernetes, CI/CD, and Cloud Native practices. It also draws heavily on Automation principles and increasingly leverages GitOps methodologies.

AKS Networking Clash: kubenet vs. CNI vs. CNI Overlay

AKS Networking Clash: kubenet vs. CNI vs. CNI Overlay

Selecting the right network model is arguably one of the most critical architectural decisions you will make when deploying a Kubernetes cluster on Azure Kubernetes Service (AKS). This choice ripples through nearly every aspect of your cluster’s lifecycle, influencing how pods communicate, how efficiently you use your IP address space, which Azure services integrate seamlessly with your workloads, and ultimately, how well your infrastructure scales to meet future demands. It affects scalability, security posture, operational cost, performance characteristics, available integration options, and your long-term operational flexibility.