Symphony is a framework and set of patterns and best practices for developing, testing, and deploying infrastructure on Azure using Infrastructure as Code (IAC.) It includes modern DevOps practices for IAC such as Main and Pull Request workflows, IaC Code Validation & Linting, Automated Testing, Security Scanning, Multi-environment deployments, modules dependencies and more.

mlinfra is the swiss army knife for deploying scalable MLOps infrastructure. It aims to make MLOps infrastructure deployment easy and accessible to all ML teams by liberating IaC logic for creating MLOps stacks which is usually tied to other frameworks.

A 5 slide formula with some advice.

Go is not aware of the limits set for its container, causing some issues not easy to track. This is a story about how I stumbled into one of them.

asdf is a CLI tool that can manage multiple language runtime versions on a per-project basis. It is like gvm, nvm, rbenv & pyenv (and more) all in one! Simply install your language's plugin!

Pretty fancy and modern terminal file manager

Openpanel is a simple analytics tool for logging events on web, apps and backend.

Reverst is a (load-balanced) reverse-tunnel server and Go server-client library built on QUIC and HTTP/3.

Discover some important tips about running JVM applications in containerized environments orchestrated by Kubernetes

understanding containers inside out

Splitting service traffic on-prem with MetalLB

Distributed systems are often described as a double-edged sword. There is plenty of excellent content out there written on both why they suck and also why they are great. This is not one of those posts. I would say generally I am an advocate and believer in distributed systems where they make sense, but the goal of this blog post (and the two others that will follow) is to share some stories with you about where I have got something wrong within a distributed system that has led to a far reaching impact.

In this first post, I will share a mistake that I have seen made in multiple companies now that can lead to cascading failure. I call it the Kubernetes deep health check.