Welcome to the Docker Projects Repository! This collection features Dockerized applications, including ML apps, databases, network experiments, and AWS deployments.
Each project showcases real-world use cases of containerization, helping you master Docker for software development & cloud deployments.
Here are some useful resources I frequently refer to:
📖 Official Docker Docs
🎥 Docker YouTube Playlist
📜 Docker Cheat Sheet
Make sure you have the following installed:
✅ Docker → docker --version
✅ Python (for Streamlit apps)
✅ AWS CLI (for EC2 deployment)
Here are some exciting projects and experiments you can explore:
🔷 Streamlit Spiral Visualization: A Dockerized Streamlit app to generate interactive spiral patterns.
🔷 Binary Classification WebApp: A Streamlit-based ML app for binary classification using Logistic Regression.
🔷 Python Logging with Docker: Demonstrates best practices for logging inside a Dockerized Python environment.
🔷 Streamlit + PostgreSQL: Connect Streamlit with PostgreSQL database inside a Docker container.
🔷 MySQL Docker Container: Deploy a MySQL database container and connect it to applications.
🔷 Docker Network Experiment: Understand networking in Docker by connecting multiple containers.
🔷 ML Model Deployment with Evidently: Deploy an ML model with Evidently AI inside a Docker container.
🔷 Deploying on AWS EC2: Deploy Dockerized applications on an AWS EC2 instance.
🔷 Minikube with Docker: Run Kubernetes locally using Minikube with Docker.
🔷 Docker Bake: A Docker Bake implementation.
🔷 Titanic Survival Predictor: A machine learning application that predicts whether a passenger would have survived the Titanic disaster
🔷 Microservices Architecture with Docker Swarm ⚓: how to deploy a microservices architecture using Docker Swarm
📌 Description: A Dockerized Streamlit app to generate interactive spiral patterns.
🛠 How to Run:
docker build -t streamlit-spiral .
docker run -p 8501:8501 streamlit-spiral 📌 Description: A Streamlit-based ML app for binary classification using Logistic Regression.
🛠 How to Run:
docker build -t binary-classifier .
docker run -p 8501:8501 binary-classifier 📌 Description: Demonstrates best practices for logging inside a Dockerized Python environment.
🛠 How to Run:
docker build -t python-logging .
docker run python-logging 📌 Description: Connect Streamlit with PostgreSQL database inside a Docker container.
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📌 Description: Deploy a MySQL database container and connect it to applications.
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📌 Description: Understand networking in Docker by connecting multiple containers.
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📌 Description: Deploy an ML model with Evidently AI inside a Docker container.
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📌 Description: Deploy Dockerized applications on an AWS EC2 instance.
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📌 Description: Run Kubernetes locally using Minikube with Docker.
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📌 Description: A Docker Bake implementation.
📌 Description: The Titanic Survival Prediction Model is a machine learning application that predicts whether a passenger would have survived the Titanic disaster based on various input features.
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📌 Description: This guide explains how to deploy a microservices architecture using Docker Swarm, featuring an API Gateway and a Backend Service.
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📖 Docker Docs
📖 Streamlit Docs
📖 AWS CLI Setup
💡 Found a bug? Open an issue!
✨ Have an idea? Submit a PR!
📖 Want to improve docs? Contribute!
🔥 Happy Learning & Containerizing! 🐳🚀