In today's workplace, communication tools like Slack or Microsoft Teams are essential for staying connected at work. However, as orchestration and automation needs increase, so does the volume of notifications flooding these channels. What’s meant to streamline work can quickly become overwhelming. We call it "ChatOps fatigue" - when teams get so many alerts, they start tuning them out.

Modern Kubernetes deployment methodologies have grown increasingly complex, layering abstraction upon abstraction in pursuit of flexibility. This article challenges that trajectory by examining how fundamental Unix tools combined with Makefiles can provide a more transparent and maintainable alternative to popular solutions like Helm and Kustomize.

Freelens is a free and open-source user interface designed for managing Kubernetes clusters. It provides a standalone application compatible with macOS, Windows, and Linux operating systems, making it accessible to a wide range of users. The application aims to simplify the complexities of Kubernetes management by offering an intuitive and user-friendly interface.

Kubetail is a general-purpose logging dashboard for Kubernetes, optimized for tailing logs across multi-container workloads in real-time. With Kubetail, you can view logs from all the containers in a workload (e.g. Deployment or DaemonSet) merged into a single, chronological timeline, delivered to your browser or terminal.

Nelm is a Helm 3 alternative. It is a Kubernetes deployment tool that manages Helm Charts and deploys them to Kubernetes. It is also the deployment engine of werf. Nelm can do (almost) everything that Helm does, but better, and even quite some on top of it.

At RudderStack, we decided to use PostgreSQL as our main streaming engine and queuing system instead of specialized tools like Apache Kafka. We picked PostgreSQL because it's flexible, reliable for transactions, and easier to debug. If you are curious to learn more about that decision, read the previous post about the rationale behind why we chose Postgres over Apache Kafka and the initial architectural patterns we employed. Over the past six years, this system has proven reliable and has scaled to handle 100,000 events per second—but only after we successfully navigated challenges like table bloat, query performance degradation, index bottlenecks, and retry storms.

This post is a chronicle of the critical, hard-won lessons learned while maturing PostgreSQL into a highly performant and resilient queuing system.

Terminal-based group chat app with real-time WebSocket messaging, file sharing, themes, and admin tools — built with Go and Bubble Tea.

Self-hosted task management that combines the simplicity of personal with the power of professional project organization. Built for individuals and teams who value privacy, control, and efficiency.