Distributed terminal-native issue tracker backed by Git.

kage (影, "shadow") clones a website into a folder you can browse offline, with every script stripped out. It opens each page in real headless Chrome, waits for the page to settle, snapshots the DOM a human would have seen, then deletes all the JavaScript and pulls the CSS, images, and fonts down to local paths. What lands on disk looks like the live site and runs no code.

There’s a particular kind of infrastructure bug that’s deeply annoying to debug: the kind that only appears when your cluster is under load. Everything runs fine in steady state. Then you push a release, or traffic spikes and your autoscaler kicks in, and suddenly you’re chasing 502s that resolve on their own a few minutes later. Your first instinct is to blame the app. Then the deployment. Then the cluster. Then yourself.

We hit exactly this pattern at Simon AI. The culprit turned out to be something fundamental about how nginx handles DNS — and fixing it properly required waiting for a feature that was finally open-sourced at the end of 2024.

Here’s what we found, what we tried, and how we solved it.

A practical guide to building the technical-financial baseline that tells you whether autoscaling will actually save money — and how much.

How we built an intelligent 'finally task' that turns 170,000 lines of logs into a 10-line diagnosis in under 30 seconds.

How treating Service Level Objectives as declarative infrastructure changed the way I think about reliability.

In this article we deploy ArgoCD in a bare-metal Kubernetes cluster built on Proxmox.

Image Trust with Cosign and Kyverno

In this guide, I'll explain how to collect Prometheus metrics from an application running in a Kubernetes cluster and push the data to a Prometheus instance on a VM in a different geographic region using Prometheus's remote write endpoint.

Docker-compatible container CLI built on Apple's Containerization framework. Same commands, same flags — mocker run, ps, stop, build, compose, stats — all working on macOS 26.

eBPF egress firewall for Kubernetes

Cluster API is a Kubernetes subproject focused on providing declarative APIs and tooling to simplify provisioning, upgrading, and operating multiple Kubernetes clusters.

Started by the Kubernetes Special Interest Group (SIG) Cluster Lifecycle, the Cluster API project uses Kubernetes-style APIs and patterns to automate cluster lifecycle management for platform operators. The supporting infrastructure, like virtual machines, networks, load balancers, and VPCs, as well as the Kubernetes cluster configuration are all defined in the same way that application developers operate deploying and managing their workloads. This enables consistent and repeatable cluster deployments across a wide variety of infrastructure environments.

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