devops

One of the superpowers of containers is their isolated filesystem view — from inside a container it looks like a full Linux distro, often different from the host. Run docker run nginx, and Nginx lands in its familiar Debian userspace no matter what Linux flavor your host runs. But how is that illusion built? In this post, we’ll walk through how to assemble a tiny but realistic container using only stock Linux tools: unshare, mount, and pivot_root....

Martin Fowler published a fascinating report from a February 2026 retreat where senior engineering practitioners from major tech companies gathered to discuss how AI is reshaping software development. It’s dense, so here’s what stood out to me. Where Does the Rigor Go? The biggest question of the retreat: if AI writes the code, where does the engineering discipline move? The answer is — it doesn’t disappear, it migrates: Upstream to specs — Bad specs produce bad code at scale....

If you’re building AI systems in production — or just getting started — these repos are worth bookmarking. LLM Serving & Inference vLLM (66k+ stars) — The industry standard for high-throughput LLM serving. Continuous batching and maximum GPU utilization. If you’re serving LLMs in production, this is probably what you should be using. Ollama (162k+ stars) — The easiest way to run LLMs locally. Great for fast experimentation before you commit to a cloud setup....

Essential Terraform best practices for organizing and structuring your infrastructure code: 1. Separate Configuration Files Instead of putting all code in main.tf, distribute it across multiple files: main.tf: Calls modules, locals, and data sources to create all resources variables.tf: Contains variable declarations used in main.tf. Place required variables at the top and optional ones at the bottom, separated by a comment line for better readability outputs.tf: Contains outputs from resources created in main....

GitHub’s platform engineering team shares their approach to tackling infrastructure challenges at scale. Key strategies include: Understanding your domain: Talk to neighboring teams with more experience Investigate old issues to understand system limitations Read documentation to build foundational knowledge Platform-specific skills: Network fundamentals (TCP, UDP, L4 load balancing, debugging tools) Operating systems and hardware selection for scalability and cost Infrastructure as Code (Terraform, Ansible, Consul) Distributed systems understanding (failures are inevitable, need failover/recovery) Impact radius considerations:...