Kubernetes

Part 1 introduced AppNet, while Part 2 demonstrated its use in zero-trust and multi-cluster patterns. This concluding section explores a shared AI gateway, the operational signals derived from the mesh, and the architectural tradeoffs that influence whether AppNet should be integrated into your platform. Series navigation Part 1: What AppNet is and how to get started Part 2: Zero-trust and multi-cluster patterns Part 3: AI gateway, observability and production fit Example three: a shared AI gateway that rate-limits by application AI Gateway with Per-Application Token Rate Limiting] ...

In Part 1, we discussed the AppNet architecture, setup process, and waypoint model. This second part shifts focus from mechanics to platform patterns: it covers enforcing service-to-service authorization for a payments platform, and then using AppNet across AKS clusters for active-active regional architectures. Series navigation Part 1: What AppNet is and how to get started Part 2: Zero-trust and multi-cluster patterns Part 3: AI gateway, observability and production fit Example one: Zero-trust authorization for a payments platform Zero-Trust Authorization — Payments Namespace ...

Azure Kubernetes Application Network, Part 1: What AppNet Is and How to Get Started The space between ‘we have ingress’ and ‘we run a full service mesh with sidecars on every pod’ has always been a challenging middle ground. Platform teams want encrypted east-west traffic, identity-based authorization, and good observability, but aim to avoid the CPU, memory, startup delay, and on-call burden associated with a sidecar on each workload. Security architects look for a zero-trust framework they can verify during audits, not just visual diagrams. Application developers need routing, retries, and traffic shifting without needing to understand Envoy’s internals. Meanwhile, platform engineers prefer these features as first-class Azure resources rather than managing complex Helm charts that require constant oversight. ...

When Your Cluster Isn’t Sufficient: Introducing Virtual Pools in AKS There’s a moment in every Kubernetes journey when the cluster begins to feel… heavy. Not broken, not misconfigured, but stretched in ways that weren’t obvious at first. You scale node pools, adjust autoscaling thresholds, maybe even add spot nodes. Yet, some workloads still don’t quite fit. They either need to scale instantly beyond your node capacity or represent spiky, unpredictable demand that makes your carefully tuned AKS cluster feel rigid. ...

GitOps on Azure Kubernetes Service: Building a Production-Ready Platform with Flux Kubernetes platforms seldom fail due to the technology itself; instead, failures are usually caused by operational issues. Between the initial successful ‘kubectl apply’ and the deployment of the twentieth production cluster, platform teams realize a harsh reality: Kubernetes isn’t hard to run, but maintaining consistent operations is very challenging. Configuration drifts occur. Hotfixes are often applied directly, skipping pipelines. Infrastructure ends up as a patchwork of Git repositories, YAML files, CI/CD pipelines, and manual tweaks performed from someone’s laptop at midnight. ...

When Kubernetes Lies: Seeing the Truth Inside AKS with Inspektor Gadget Cloud platforms are built on abstractions. We tell developers that services talk to services. We tell security teams that network policies enforce isolation. We tell architects that identity is the new perimeter and that zero trust ensures nothing moves unless explicitly allowed. In Azure Kubernetes Service, these abstractions become even more powerful. Managed control planes, private clusters, Cilium networking, workload identity, Azure Firewall, private endpoints, and policy enforcement create the feeling of a highly controlled, highly predictable platform. ...

Operating AKS from your workstation: Inside Microsoft’s New AKS Desktop There has long been a peculiar duality in managing Azure Kubernetes Service. The Azure portal offers abundant information but often feels disconnected from the cluster’s core functions. Meanwhile, Kubernetes is accessible through kubectl, YAML files, and dashboards like Headlamp. One exists within the Azure control plane, and the other entirely within the Kubernetes API. Operators frequently switch between these two realms multiple times daily, yet they never quite close the gap. ...

Beyond the Cloud: Running Kubernetes with Talos: Comparing Talos, k3s, AKS, and EKS “If Kubernetes is the engine, Talos is the chassis built specifically for it.” Introduction: Rethinking the Kubernetes Operating System When Kubernetes first appeared, it was celebrated as the “Linux of the cloud.” But beneath every Kubernetes cluster, there’s always a traditional operating system like Ubuntu, CentOS, Flatcar, or another Linux distribution. These weren’t originally built specifically for the orchestration layer that overlays them. This historical setup has quietly influenced how we manage, patch, and secure our clusters. Even as control planes have shifted to managed services such as Azure Kubernetes Service (AKS) and Amazon Elastic Kubernetes Service (EKS), the nodes themselves still rely on an operating system that wasn’t initially designed for immutability or declarative control. ...

Fleet, Arc, sovereign clouds, and the edge-first world of 2030 This article is the last part of the Azure Kubernetes Chronicles: Multi-Cluster Edition. Read the series introduction here. Examining today’s multi-cluster landscape, it is tempting to focus solely on the pain points: identity fragmentation, policy drift, networking complexity, and monitoring silos. But the story does not end there. Kubernetes itself has evolved from a single-cluster dream to a multi-cluster necessity, and the governance ecosystem around it is growing just as quickly. To understand where things are headed, we have to look beyond today’s tools and into the future that is already taking shape. ...

Azure Kubernetes Service (AKS) has long been the leading platform for containerized workloads on Microsoft Azure. While AKS offers scalability and resilience, managing it day-to-day still involves switching between various tools: Azure CLI, kubectl, ARM templates, and portal dashboards. This is where the Microsoft AKS-MCP Server, part of the Model Context Protocol (MCP) ecosystem, makes a difference. By providing a structured, secure interface for agents and tools to perform Azure and Kubernetes actions, AKS-MCP changes how engineers interact with clusters. ...