AWS Resource Health Monitor Built with Python and boto3

A stylized SVG illustration that visualizes the full project in a dark, technical aesthetic. It shows the three-stage pipeline on the left (CSV → Python → LDIF), the AWS VPC with the EC2 server and directory tree on the right, the CloudShell terminal with real command syntax, and key metrics summarized at the bottom. ❤️

I used to click around AWS Console like I was playing a video game 🎮 Click here. Wait. Click there. Pray nothing breaks. Then I learned you can do ALL of that with just Python. I've been learning how to manage EC2 instances via Python (boto3) instead of the console. And honestly? No going back. Here's why Python > Console for EC2: 🔁 Repeatable: run the same script 100 times, same result. Console? Depends on your mood that day. ⚡ Faster: one script to launch, configure, and terminate. No tab switching, no clicking through 10 menus. 🧠 Version-controlled: your infra lives in code. Your team can read it, review it and reuse it. 🤖 Automatable: connect it to your ML pipeline. Spin up EC2 when needed, kill it when done. No bill surprises. The console is great for learning what exists. Python is how you actually work. Still clicking manually? Try boto3. Your future self will thank you. 😄 #AWS #Python #MachineLearning #MLOps #CloudComputing #LearningInPublic #boto3

🚀 Running FastAPI on AWS Lambda (with Mangum) Want to build Python APIs without managing servers? You can run FastAPI on AWS Lambda using Mangum, an adapter that bridges ASGI apps with Lambda’s event system. 👉 Why this stack? ⚡ FastAPI = high-performance async APIs ☁️ Lambda = serverless, auto-scaling 🔌 Mangum = connects both seamlessly 💡 Bonus: Use container images in Lambda This lets you package your app + dependencies in Docker and deploy with more flexibility. Flow: Client → API Gateway → Lambda → Container → FastAPI → Response Perfect for modern, scalable, and cost-efficient APIs. #AWS #Lambda #FastAPI #Python #Serverless #CloudComputing #Docker #DevOps #APIs

[Azure Updates] [Launched] Generally Available: Microsoft Agent Framework 1.0. Microsoft Agent Framework is now version 1.0 for both .NET and Python, with stable APIs and a long-term support commitment. Agent Framework 1.0 supports multi-agent orchestration, multi-provider model support, and cross-runtime interoperability via A2A an #azure #azureupdates https://lnkd.in/esqS8KXe

#Apache Beam is an open-source framework that lets you write portable batch and streaming data pipelines in languages like #Java and #Python. While these pipelines can run on various execution engines such as #Spark or #Flink, #Dataflow is #Google Cloud's fully managed, serverless runner for Beam. For more insights, visit https://yunacloud.com #GCP #GoogleCloud #Academy #Education #Skills #Learning

Built a multi-container Python Todo API project from scratch to strengthen my backend and DevOps skills. What I implemented: • Python Flask backend API • PostgreSQL database • Dockerized services using Dockerfile • Multi-container architecture with Docker Compose • Persistent storage using volumes • CI/CD pipeline with GitHub Actions Currently running locally with separate app and database containers. Next step: Public cloud deployment. GitHub Repo: https://lnkd.in/dN3nvEzD #Docker #Python #PostgreSQL #DevOps #GitHubActions #LearningByBuilding

How many unused Lambda functions are running in your AWS account right now? I built a simple Python script that helped identify 53 wasteful functions within minutes,highlighting gaps in visibility and cost optimization in serverless setups. Take a look: https://lnkd.in/d9evji-B

🚀 Week 7 – From Scripts to a CLI Tool This week I focused on improving my Python scripting by building something more practical instead of just solving small problems. Here’s what I worked on: • Built a CLI-based tool to simulate EC2 instance monitoring • Implemented filtering for running and stopped instances • Parsed AWS-style JSON data instead of using hardcoded values • Added summary reporting (total, running, stopped) • Enabled command-line arguments using sys.argv • Added option to export output to a file • Structured the tool similar to real CLI tools (like AWS CLI) Also cleaned up my GitHub repository to keep the project focused and professional. This week helped me understand how scripting is actually used in cloud and automation scenarios. Next: Planning to make this more aligned with real AWS CLI behavior and improve data handling further. #Python #Automation #CloudComputing #CLI #LearningJourney

Just published a deep-dive blog on Docker + Python 🐳 Covered everything from scratch: → What Docker actually is (with a Maggie noodles analogy, yes) → Writing your first Dockerfile → Docker Compose for multi-service apps → Production setup with Gunicorn + Nginx → Deploying on AWS EC2 If you've been confused about containers, images, port mapping, or why your app "works on your machine" but breaks on the server - this one's for you. Link https://lnkd.in/gcn7atem #Docker #Python #DevOps #WebDevelopment #Flask #CloudComputing #AWS #Programming #100DaysOfCode #TechBlog

Developers Deploy Python MCP Servers on Azure Kubernetes Service for Scalable AI Orchestration 📌 Developers now run Python MCP servers on Azure Kubernetes Service, letting AI agents autonomously manage clusters without human oversight. This opens the door to cross-cloud AI orchestration, decoupling tools like Google’s Gemini CLI from vendor lock-in. With auto-scaling, secure auth, and Python 3.13 support, it’s a game-changer for scalable, zero-trust AI infrastructure. 🔗 Read more: https://lnkd.in/dBX8Az3G #Python #Mcp #Azureaks #Aiorchestration #Googlegemini