Build & Deploy a Real-World Python App: Flask, API, Docker & K8s
Ready to move beyond coding on your local machine? In this step-by-step beginner tutorial, we build a Python Weather App using Flask and Pandas, containerize it with Docker, and deploy it to a local Kubernetes (K8s) cluster using Kind.
Whether you are a developer looking to learn DevOps or a beginner starting with the cloud, this project gives you the hands-on experience you need for your portfolio.
Timestamps:
[00:01] – Introduction & Project Overview [01:09] – Python Flask Code Walkthrough (Weather API Integration) [02:12] – Working with the OpenWeatherMap API & API Keys [03:41] – Handling JSON Data in Python [04:12] – Flask App Views: Root View vs. Pandas Data Frame View [07:38] – Dockerizing the Python App: Writing the Dockerfile [08:31] – Managing Python Dependencies (requirements.txt) [10:00] – GitLab CI/CD Pipeline & Kubernetes Overview [11:14] – Triggering the Deployment Pipeline [12:35] – Monitoring the Build & Pushing to Container Registry [13:55] – Deploying to Kubernetes (KIND Cluster) [14:32] – Port Forwarding & Verifying the Live App [15:03] – Testing the Weather Dashboard (London & Tokyo Examples) [16:23] – Alternative Method: Running the App in VS Code (Local Dev) [17:41] – Setting up a Python Virtual Environment (venv) [18:41] – Running the App locally without Docker [19:51] – Summary & Final Tips
What You’ll Learn:
Python/Flask: Create a functional web app that fetches weather forecasts.
Pandas: Learn to handle and display data efficiently.
Docker: Create optimized Docker images for your Python apps.
Kubernetes (Kind): Run a local K8s cluster and deploy your application.
VS Code Integration: Best practices for running cloud-native apps in your IDE.
Source Code & Resources:
GitHub Repository: https://github.com/devopsmoduless1/py...
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#Python #Kubernetes #Docker #DevOps #Flask #DataScience #WebDevelopment #CloudComputing #Kind
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