Udemy – Flask API Scaling: Parallel Processing with RQ & Supervisor 2024-11

What you will learn:

• Building scalable Flask APIs: Configure and structure a microservice-based Flask API that can handle high traffic and concurrent requests.
• Implement background task processing with RQ: Use Redis Queue (RQ) to manage and execute background tasks in parallel.
• Deploying Flask Applications with Docker: Learn how to containerize your Flask applications using Docker for consistent deployment across different environments.
• Monitor and manage workers with Supervisor and RQ Dashboard: Gain practical experience in worker management.
• Building a Comprehensive Flask Microservice: Learn how to build a modular and scalable Flask API and create a solid foundation for building reliable microservices.
• Efficient task processing with Redis Queue (RQ): Discover how to seamlessly manage background processes. By integrating Redis Queue (RQ), you enable parallel execution of tasks, ensuring smooth API performance even under heavy traffic.
• Simple Deployment with Docker: Master the deployment of your Flask applications using Docker. Containerize your microservices for consistent, environment-independent performance and easy scalability.
• Inter-process communication: Implement a publish/subscribe mechanism that allows multiple processes to communicate efficiently, making your application more modular and robust.
• Advanced Worker Management: Learn how to control and monitor your background jobs with the Redis CLI and track real-time updates with the RQ Dashboard for smooth workflow management and effective scalability.
• Inter-process communication: Implement various inter-process communication mechanisms.

Who is this course suitable for?

• Intermediate to advanced Python developers who are familiar with Flask and ready to take their API skills to the next level by implementing parallel processing, increasing scalability, and optimizing performance on heavy workloads.

Installation Guide

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