Python based Microservices - go from zero to hero!
This Learning Path will get you started with designing, building and deploying microservices in production using Python, Flask and Docker containers. We start off by providing you with an explanation of what microservices are. Next, the Learning Path prepares you with the process of packaging and containerization, using Docker together with Docker Compose for orchestration. Finally, you'll get to observe the end-to-end development of a fully functioning microservices based e-commerce demonstration using each of previously learnt tools and technologies.
- Learn the basic principles of building Docker containers and working with Dockerfiles
- Understand the benefits of using Docker for application development
- Learn how to package and run microservices as lightweight containers using Docker
- Anyone interested in learning Python, Flask, Docker, and Docker Compose
- Anyone interested in learning how to architect microservices
- Anyone interested in containerisation
- DevOps Practitioners
- A basic understanding of software engineering
- A basic understanding of Python (development experience)
- A basic understanding of containers and containerization
Learning Path Steps
Microservices are a way of breaking large software projects into loosely coupled modules, which communicate with each other through simple APIs.
In this course, you'll learn how to use Docker containers to isolate your running processes.
Get started with Docker on Linux for AWS: Go from 0 to 60 in this lab from installing Docker to running your first app inside a container.
In this course, you'll learn what Docker Compose is: its files, its command-line interface, and how to manage your applications using it.
This course shows how Flask can be used to quickly prototype and build microservices, and how Docker can be used to deploy them.
Exam: Python, Flask, and Docker based Microservices
Jeremy is the DevOps Content Lead at Cloud Academy where he specializes in developing technical training documentation for DevOps.
He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 20+ years. In recent times, Jeremy has been focused on DevOps, Cloud, Security, and Machine Learning.
Jeremy holds professional certifications for both the AWS and GCP cloud platforms.