Hands On Microservices With Python

Hands-on Microservices with Python [ video], published by Packt
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Hands-On Microservices with Python [Video]

This is the code repository for Hands-On Microservices with Python [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.

Author: Peter Fisher


About the Video Course

This course covers microservice fundamentals and advanced topics with a hands-on demonstration of how to implement microservices using real-world examples. Learn how to design and build a microservice software architecture in Python. You will learn to make your applications more reliable and fault-tolerant using microservices with Python, no matter how complex the business logic. This course demonstrates how to design and build an application using a series of microservices. The application in question is an order management system, which we will split up into individual services. In a hands-on manner, you will learn topics such as data modeling, data storage, writing API requests, and you will learn to secure, monitor, and scale your microservices. Finally, you will learn to use Docker's containerization technology to isolate, manage, monitor, and deploy microservices in Docker containers.

What You Will Learn

  • What defines a microservice and how a microservice differs from other architectures.
  • How to design a microservice architecture
  • Advantages and disadvantages of using microservices
  • How to manage and monitor microservices
  • How to deploy microservices in Docker containers
  • What Python tools are best suited for microservices 
  • How to secure microservices

Instructions and Navigation

Assumed Knowledge

To fully benefit from the coverage included in this course, you will need:
This course is for developers who want to build Microservice-based applications with Python.They know Python programming.No knowledge of the Microservice architecture is needed.If you want to code to build robust and fault tolerant systems with Python, this course is for you.

Technical Requirements

This course has the following software requirements:
SETUP AND INSTALLATION This will vary on a product-by-product basis, but should be a standard PI element for ILT products. This example is relatively basic.

Minimum Hardware Requirements For successful completion of this course, students will require the computer systems with at least the following:

OS: Apple MacOS or Linux. Windows can be used but examples will be presented in a Unix based operating system

Processor: Intel I3+

Memory: 6GB

Storage: 20GB

Recommended Hardware Requirements For an optimal experience with hands-on labs and other practical activities, we recommend the following configuration:

OS: Apple MacOS or Linux

Processor: Intel i5

Memory: 16GB

Storage: 20GB

Software Requirements

Operating system: Apple MacOS or Linux

Browser: Safari/FireFox

pyCharm Latest Version

Docker version Latest Version

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