How I Almost Exposed My API Keys and Learned a Valuable Lesson

The incident that didn’t wake anyone up. Most teams already see problems. The pain starts after the alert: classify → decide → fix → verify. That is where nights get lost and folks start burning out. I built Smart-Monitor to close that gap. It senses service health, classifies what is happening, applies guardrails, executes a safe fix, and verifies, live in the UI. Every step is auditable. Stack: Docker, Flask API, PostgreSQL, systemd (D-Bus), Nginx (TLS/SSE). Principles: guardrails-first, smallest blast radius, audit everything. 🎥 Short clip shows: classification → policy → automated fix → verified recovery—in seconds. Question: Would this fit your Platform/DevOps/SRE roadmap? What’s the one incident you’d automate first if guardrails were solid? Curious how many teams fold this into a Platform/DevOps/SRE roadmap? Repo link in first comment 👇 #PlatformEngineering #DevOps #SRE #Observability #Reliability #Automation #MTTR #IncidentManagement #PostgreSQL #Python #Linux

🚀 Excited to share my latest project — ToolBox! 🧰 Over the past few days, I’ve been working on building a developer-focused web application that simplifies daily DevOps and engineering workflows. 🔹 🔗 GitHub Repository: https://lnkd.in/gipjq3Cp 🔹 Tech Stack: Python (Flask) | Docker | HTML | JSON-based utilities 💡 About ToolBox: ToolBox is a collection of handy utilities and dashboards designed to make day-to-day development and operations tasks faster and more organized. You can easily extend it by adding your own tools — perfect for anyone who wants a central hub for local dev utilities. 🧩 Features: ✅ Simple web-based interface ✅ Multiple utilities combined in one place ✅ Easy to run with Docker ✅ Customizable and developer-friendly ⚙️ How to Run: git clone https://lnkd.in/gvhGZgMz cd ToolBox docker build -t toolbox-app . docker run -p 3000:3000 toolbox-app 🌐 Then open: http://localhost:3000 ✨ I’d love to hear your feedback or suggestions for new tools to add! If you find it useful, don’t forget to ⭐ the repo! #DevOps #Python #Flask #Docker #OpenSource #ToolBox #DeveloperTools #Automation #Productivity

🚀 New Project Completed! – Multi-Container Application using Docker Compose The main goal was to understand how to structure a Compose file for multiple services, manage environment variables, and handle service dependencies. 🐳 🔹 Project Overview: • Frontend (HTTPD) → Displays my name and communicates with the backend. • Backend (Flask) → Provides REST API endpoints and connects to the database. • Database (MariaDB) → Stores and retrieves user data dynamically. 🔹 Docker Compose Configuration: • Created two networks: - frontend_network (Frontend ↔ Backend) - backend_network (Backend ↔ Database) • Configured dependencies so containers start in the correct order. • Used environment variables to connect Flask to MariaDB securely. 🔹 Tech Stack: 🐳 Docker & Docker Compose ⚙️ Flask (Python) 🗄️ MariaDB 🌐 Apache HTTPD 🔹 Key Features: ✅ Frontend container shows custom content. ✅ Flask backend connects automatically to the database. ✅ Networks isolate services and ensure secure communication. ✅ Containers restart automatically on failure. ⸻ GitHub Repository 🔗 Example: https://lnkd.in/dXJub7yv ⸻ #DevOps #Docker #Flask #MariaDB #BackendDevelopment #WebDevelopment #FullStack #SoftwareEngineering #Containerization #DockerCompose

🚀 Writing Optimized & Lightweight Dockerfiles When working with containers, one of the easiest ways to improve performance, build time, and deployment efficiency is to optimize your Dockerfile. Here are a few best practices I follow to create small, fast, and secure images: 1. 🧱 Start with a minimal base image • Prefer alpine, distroless, or language-specific slim variants (python:3.11-slim, node:20-alpine, etc.) 2. 🧹 Reduce layers • Combine related commands: RUN apt-get update && apt-get install -y curl git && rm -rf /var/lib/apt/lists/* 3. ⚙️ Use multi-stage builds • Build dependencies in one stage, then copy only the final artifacts: FROM node:20 as build WORKDIR /app COPY . . RUN npm ci && npm run build FROM node:20-alpine COPY --from=build /app/dist ./dist CMD ["node", "dist/index.js"] 4. 🔒 Avoid copying unnecessary files • Use .dockerignore to skip logs, node_modules, and build artifacts. 5. 🧊 Pin versions and clean up • Keeps builds reproducible and smaller. By keeping your images lean, you get: ✅ Faster build and deploy times ✅ Lower storage and bandwidth usage ✅ Fewer security vulnerabilities 💬 How do you optimize your Dockerfiles? Share your favorite trick below ⬇️ #Docker #DevOps #Containers #SoftwareEngineering #PerformanceOptimization #CloudNative

I love competitive programming, but I kept missing contest registrations. So, I built a solution. I created a 100% free, serverless bot that automatically scrapes upcoming contests from Codeforces, LeetCode, and AtCoder every morning at 7:30 AM. Here's the architecture: Scheduler: A GitHub Actions workflow runs a Python script on a daily cron schedule. Backend: The script fetches and parses data from the CLIST.by API. Database: I built a fully automated user-list system. A Google Form collects new sign-ups, which automatically populates a Google Sheet. My script uses a Google Service Account to read this list every morning. Logic: If there are no contests, it falls back to a "Problem of the Day" mode, pulling a random DSA problem from a problems.json file I curated from the NeetCode 150. Templating: It uses Jinja2 to render a clean, styled HTML email (separating logic from presentation). Delivery: It sends the final email to all subscribers using the SendGrid API, with all recipients in BCC to protect user privacy. It was a fantastic project for learning how to build a real-world, scalable product. I navigated API authentication errors (401s), request issues (400s), and the infamous "cron scheduler not running" bug in GitHub Actions. The best part? It's now a fully automated system. Users can sign up and start receiving emails without me lifting a finger. You can check out the full, refactored code on my GitHub: https://lnkd.in/dkJGwmCh #Python #GitHubActions #Automation #SendGrid #GoogleSheets #Jinja2 #API #SoftwareEngineering #DSA #CompetitiveProgramming P.S. If you're a programmer and want to receive this free daily email, here's the sign-up form: https://lnkd.in/dH_M5w9q

🚀 Dockerizing My Project — Step-by-Step Guide from Code to Container! 🐋 After exploring Docker in depth, I finally containerized my own FastAPI project — turning a normal app into a fully functional Docker image ready to run anywhere! 🌍 From writing the Dockerfile and defining base images, working directories, and environment variables — to building, running, exposing ports, and finally pushing the image to Docker Hub, this journey helped me deeply understand how real-world deployment pipelines work. 💻⚙️ Here’s what this guide covers: ✅ Creating and understanding Dockerfile commands (FROM, WORKDIR, COPY, RUN, CMD, EXPOSE, ENV) ✅ Building custom Docker images (docker build -t appname:version .) ✅ Running containers with port binding (docker run -p 8000:8000 --name myapp appname:1.0) ✅ Hosting your image on Docker Hub 🌐 ✅ Complete example: House Price Prediction App with FastAPI & Docker 📂 Full Step-by-Step Setup + Example Code available on GitHub 👇 🔗 Material Link:- https://lnkd.in/edkr-uFv 🔗 Sample Project:- https://lnkd.in/eHwa7VKD 🔗 Docker Image Link:- https://lnkd.in/ea26qdPG This hands-on experience made me realize how Docker makes deployment, scalability, and portability so effortless across environments! 💙 #Docker #DevOps #FastAPI #Python #Containerization #CloudComputing #SoftwareEngineering #Dockerfile #OpenSource #LearningJourney #DockerHub #GitHub #ProjectShowcase #TechCommunity #DeveloperJourney

Docker CLI vs Docker Compose — same destination, different journeys 🚢 When I first started using Docker, I ran everything from the CLI — one container at a time. It worked fine… until my project needed a database, a cache, and a backend 😅 Let’s break down the difference 👇 ⚙️ Docker CLI (docker run) This is the manual way — great for single containers. Example: docker run -d -p 8000:8000 --name webapp my_django_app Flags explained: -d → Run in detached mode (background) -p → Map ports (host:container) --name → Give your container a name Simple, but imagine running Django, PostgreSQL, and Redis separately — that’s a lot of typing 😬 📘 Docker Compose (docker-compose.yaml) This is the automatic way — define everything once, and start all containers together. Example: version: '3' services: web: build: . ports: - "8000:8000" db: image: postgres environment: POSTGRES_PASSWORD: example Then just run: docker-compose up -d Everything spins up in harmony 🎶 🧠 In short: CLI → precise, single-container control 🧩 Compose → effortless multi-container orchestration 🚀 Both are powerful — it depends on your workflow. 👉 Do you prefer the hands-on control of CLI or the simplicity of Compose? #Docker #DevOps #Python #Django #WebDevelopment #Learning

---Stop the Tutorial Loop — Start Building, Even If You Don’t Know Everything We’ve all been there. Jumping from tutorial to tutorial. Learning 10 new things a day… but forgetting 9 of them the next. 😅 At some point, I realized — I wasn’t really learning. I was just watching others build. So this time, I flipped the script: I stopped following tutorials and started building something small but real. 🧩 My Goal Build a real backend in Go — from scratch. No frameworks pre-set, no boilerplate, no “copy-paste and hope it runs.” Just one goal: understand every line I write. -- What I built A simple Go + MongoDB backend that can: 1) Register users 2) Hash passwords securely with bcrypt 3) Log in users 4) Store everything in MongoDB All inside one clean Go file. No JWTs. No overengineering. Just logic that works. 🧠 What I learned (and unlearned) You don’t have to know everything before you start. Every error teaches you more than 10 YouTube videos. Go feels strict at first, but that’s what makes it beautiful. c *gin.Context is like the Go version of req + res in Express — and once you get that, everything clicks. And most importantly — you remember what you build. ===>> Why I’m sharing this Because you’ll forget what you read. You’ll forget what you watch. But you won’t forget what you build with your own hands. The stack will keep changing every year — Go, Node, Rust, Bun, whatever comes next. But building and problem-solving? That skill never expires. 💪 🌱 So here’s my advice Stop the tutorial binge. Start your mini project — no matter how messy it looks. Learn by doing, not by watching. That’s how I built my first backend in Go. #golang #backenddevelopment #learnbybuilding #devjourney   #softwareengineering #codingjourney #buildinpublic #100DaysOfCode   #selftaughtdeveloper #programming #mongodb #ginframework   #learnbydoing #developercommunity #codeinpublic #golangdeveloper   #motivation #startbuilding #softwaredev #programmerlife Read the doc to see :