These are end-to-end engineering projects built and documented as products — covering design, implementation, observability, and operations.
Each project includes architecture diagrams, code, and operational learnings.
These are end-to-end engineering projects built and documented as products — covering design, implementation, observability, and operations.
Each project includes architecture diagrams, code, and operational learnings.
Introduction In this post, I’ll walk you through my journey of integrating Google’s Gemini CLI (v0.24.0) with my self-hosted n8n instance (v2.2.6) using the Model Context Protocol (MCP). While n8n provides built-in MCP support, it only exposes read-only actions. To unlock full workflow automation—creating, modifying, and deleting workflows via Gemini CLI—I built a custom Python MCP server that leverages n8n’s API. Project Overview Goal: Enable Gemini CLI to create, read, update, and delete n8n workflows programmatically. ...
🚀 Project Overview This project captures a practical, reproducible edge platform built on a Raspberry Pi 3 Model B. It demonstrates platform-oriented practices (ingress, observability, minimal workloads) while remaining lightweight enough for constrained edge hardware. TL;DR: A single-node, container-based edge platform using Docker + Traefik for ingress and Prometheus/Grafana for observability. Designed for reproducibility and learning, not for production scale. Table of contents Overview Goals Hardware & Software Quickstart (commands) Architecture Networking & Ingress (Traefik) Observability (Node Exporter, Prometheus, Grafana) Example workload (whoami) Optimization & Swap Logging & Persistence Security, TLS & Limitations Next steps References 🎯 Goals Build a production-inspired, reproducible edge platform on Raspberry Pi 3 Run and route containerized workloads using a lightweight ingress Provide minimal observability while conserving resources Document the steps so the platform can be recreated via Git/Hugo 🧰 Hardware & Software Hardware ...