Python Microservices: Build, Scale, And Deploy Like A Pro!

Learn to build, secure, and scale Python microservices with FastAPI, Flask, Docker, and Kubernetes.

What you'll learn

Design scalable microservices using Python frameworks like FastAPI and Flask.

Build RESTful APIs with efficient data handling and endpoint design.

Containerize microservices using Docker and Docker Compose.

Implement interservice communication with REST, RabbitMQ, and gRPC.

Connect microservices to SQL and NoSQL databases with PostgreSQL.

Optimize microservices with caching solutions like Redis.

Secure APIs with authentication, HTTPS, and API gateways.

Monitor microservices with Prometheus, Grafana, and logging tools.

Orchestrate microservices deployments using Kubernetes.

Set up CI/CD pipelines for seamless microservices integration.

Requirements

Basic Python programming knowledge

A computer with minimum 8GB RAM

A computer with internet access

No prior microservices experience needed

Description

Did you know that 77% of enterprises are adopting microservices, yet only 6% of developers feel confident building production-ready distributed systems?Unlock your potential in the booming field of microservices architecture with our cutting-edge Python Microservices course. Whether you're a developer aiming to level up your career or an organization seeking to modernize your infrastructure, this hands-on program transforms you from a Python developer into a microservices architect.From day one, you'll build real-world microservices using both FastAPI and Flask, gaining practical experience with two of the most powerful frameworks in the industry. Our curriculum doesn't just teach theory – you'll containerize your services with Docker, orchestrate them with Kubernetes, and implement robust security measures that meet enterprise standards.What sets this course apart is our production-first approach. You'll master inter-service communication using REST, gRPC, and message queues, implement database patterns with PostgreSQL, and set up professional monitoring solutions with Prometheus and Grafana. By the end, you'll have deployed a complete microservices ecosystem to Google Kubernetes Engine (GKE), equipped with CI/CD pipelines and production-grade monitoring.This comprehensive journey covers everything from API design to cloud deployment, database management to security implementation. Our step-by-step approach ensures you're not just learning – you're building a portfolio of production-ready microservices that showcase your expertise to potential employers.Join thousands of developers who have transformed their careers through our programs. With microservices architects commanding salaries up to $150,000+, there's never been a better time to master this critical skill set.Ready to dominate the world of microservices architecture? Let's GO!

Overview

Section 1: Introduction

Lecture 1 • Overview of Microservices Architecture

Lecture 2 • Why Choose Python for Microservices?

Section 2: Setting Up the Development Environment

Lecture 3 • Installing Python and Pip

Lecture 4 • Setting Up a Virtual Environment

Lecture 5 • Overview of Python Microservices Frameworks (Flask, FastAPI)

Section 3: Creating Your First Microservice

Lecture 6 • Building a Simple Service with FastAPI

Lecture 7 • Defining Endpoints and Routes with FastAPI

Lecture 8 • Handling HTTP Methods (GET, POST, PUT, DELETE) with

Lecture 9 • JSON Handling and Response Formatting with FastAPI

Section 4: Creating Microservices with Flask

Lecture 10 • Building a Simple Service with Flask

Lecture 11 • Handling HTTP Methods with Flask

Section 5: Containerizing the Microservice with Docker

Lecture 12 • Introduction to Docker and Containers

Lecture 13 • Writing a Dockerfile for the Microservice

Lecture 14 • Building and Running the Docker Image

Lecture 15 • Writing a Docker-compose for a microservice

Section 6: Interservice Communication

Lecture 16 • RESTful APIs for Synchronous Communication

Lecture 17 • Asynchronous Communication with Message Queues (e.g., RabbitMQ, Kafka)

Lecture 18 • Implementing gRPC for Efficient Data Transfer

Section 7: Managing State and Data Persistence

Lecture 19 • Setting up a database with postgreSQL

Lecture 20 • Connecting Microservices to Databases (SQL, NoSQL)

Lecture 21 • Implementing the Database Per Service Pattern

Lecture 22 • Using Caching for Performance Optimization (e.g., Redis)

Section 8: Securing Microservices

Lecture 23 • Implementing Authentication and Authorization

Lecture 24 • API Gateway for Centralized Security

Lecture 25 • Secure Communication with HTTPS and SSL/TLS

Section 9: Monitoring and Logging

Lecture 26 • Setting Up Logging with Python (e.g., Logstash)

Lecture 27 • Monitoring Microservices with Prometheus and Grafana

Lecture 28 • Distributed Tracing (e.g., Jaeger) for Debugging

Lecture 29 • Managing pods and scaling services

Section 10: Orchestrating Microservices with Kubernetes

Lecture 30 • Basics of Kubernetes and Its Role in Microservices

Lecture 31 • Setting up Kubernetes with Minikube

Lecture 32 • Creating Kubernetes Deployments and Services

Section 11: Testing and Continuous Integration/Continuous Deployment (CI/CD)

Lecture 33 • Writing Unit tests and integration test for microservices

Lecture 34 • Setting Up a GKE for CI/CD

Lecture 35 • Deploying microservices to production

Lecture 36 • Next Steps

Developers new to microservices architecture.,Python programmers seeking to expand their skills.,Backend developers aiming to learn FastAPI and Flask.,DevOps enthusiasts exploring Docker and Kubernetes.,Students or professionals transitioning into cloud-based development.,Anyone interested in building scalable, modern software systems.