A few years ago, Roland Huss and I wrote Kubernetes Patterns, a catalogue of repeatable solutions for building cloud-native applications on Kubernetes. The book covers patterns across six categories: foundational, behavioral, structural, configuration, security, and advanced, everything from health probes and init containers to controllers, operators, and elastic scaling. Recently, Roland and Daniele Zonca co-authored a new book, Generative AI on Kubernetes, which covers the operational side of running LLMs on Kubernetes. I was a reviewer on that book, and the more I read through it, the more I recognized patterns from our original work, just applied to a very different class of workload. Deployments, StatefulSets, Init Containers, DaemonSets. They were all there. Just with bigger numbers.

Here is a high-level summary of how Kubernetes patterns apply to LLM workloads, which Roland and I will cover in more detail in our upcoming KubeCon + CloudNativeCon Europe 2026 talk in Amsterdam.

How we eliminated crash loops and hundreds of errors and why “high availability” was making everything worse.

In this article we explain how we built a new observability platform over the span of approximately two years to address a variety of problems.

A practical guide to packaging kong custom plugins as Helm charts, deploying them as ConfigMaps, and automating releases with GitHub Actions

In this post, we'll take a polyglot microservice app from local source code to a production Kubernetes cluster with TLS, Auth0 login, and Stripe webhooks — all working end-to-end. No cloud staging environment. No Docker Compose. No YAML by hand.

Here we’ll walk through a small, concrete demo where a single hub control plane actively reconciles cert-manager.io/v1 Certificate resources across multiple downstream clusters, issues TLS Secrets, and does so safely from multiple controller replicas without relying on leader election.

Step-by-step guide to deploying a private Amazon EKS cluster with zero public API exposure, self-hosted OpenVPN access, kube-prometheus-stack monitoring, and Route 53 private DNS — all automated with Terraform.

This article walks through a production deployment that solves all of the above using llm-d for intelligent inference scheduling, Istio as a Gateway API provider with Inference Extension support, and LiteLLM as a unified API gateway.

Chainloop is an open-source evidence store for your Software Supply Chain attestations, Software Bill of Materials (SBOMs), VEX, SARIF, QA reports, and more. With Chainloop, Security, Compliance, and Risk management teams can define security and compliance policies, what evidence and artifacts they want to receive, and where to store them. On the other hand, developers are shielded from all this complexity by being given simple instructions on what to provide when instrumenting their CI/CD pipelines.

OpenRun is an Apache-2.0 licensed open source web app deployment platform for deploying internal tools. OpenRun makes it easy to declaratively deploy containerized web apps. OpenRun can deploy apps on a single-node or onto a Kubernetes cluster. OpenRun provides declarative GitOps based blue-green deployment, OAuth/OIDC/SAML access controls, TLS certs & secrets management. OpenRun is built for teams to easily deploy internal tools, with full RBAC support. OpenRun apps are deployed directly from the git repo, no build server required. OpenRun scales idles apps down to zero and supports atomic updates across multiple apps.

Sealed Secrets Web is a web interface for Sealed Secrets by Bitnami. The web interface let you encode, decode the keys in the data field of a secret, load existing Sealed Secrets and create Sealed Secrets. Under the hood it uses Sealed Secrets service API to encrypt your secrets. The web interface should be installed to your Kubernetes cluster, so your developers do not need access to your cluster via kubectl.

Our ASP.NET Core pods on Kubernetes were OOM-killed every few hours during a pre-launch pilot. The managed heap was clean — 95% of the memory was native, invisible to every .NET diagnostic tool we threw at it.