Book Image

Hands-On Docker for Microservices with Python

By : Jaime Buelta
Book Image

Hands-On Docker for Microservices with Python

By: Jaime Buelta

Overview of this book

Microservices architecture helps create complex systems with multiple, interconnected services that can be maintained by independent teams working in parallel. This book guides you on how to develop these complex systems with the help of containers. You’ll start by learning to design an efficient strategy for migrating a legacy monolithic system to microservices. You’ll build a RESTful microservice with Python and learn how to encapsulate the code for the services into a container using Docker. While developing the services, you’ll understand how to use tools such as GitHub and Travis CI to ensure continuous delivery (CD) and continuous integration (CI). As the systems become complex and grow in size, you’ll be introduced to Kubernetes and explore how to orchestrate a system of containers while managing multiple services. Next, you’ll configure Kubernetes clusters for production-ready environments and secure them for reliable deployments. In the concluding chapters, you’ll learn how to detect and debug critical problems with the help of logs and metrics. Finally, you’ll discover a variety of strategies for working with multiple teams dealing with different microservices for effective collaboration. By the end of this book, you’ll be able to build production-grade microservices as well as orchestrate a complex system of services using containers.
Table of Contents (19 chapters)
Free Chapter
1
Section 1: Introduction to Microservices
3
Section 2: Designing and Operating a Single Service – Creating a Docker Container
7
Section 3:Working with Multiple Services – Operating the System through Kubernetes
13
Section 4: Production-Ready System – Making It Work in Real-Life Environments

Defining the database schema

The database schema is simple and inherited from the monolith. We care only about the thoughts, stored in the thought_model table, so the database structure is as follows:

Field Type Comments
id INTEGER NOT NULL Primary key
username VARCHAR(50)
text VARCHAR(250)
timestamp DATETIME Creation time
The thought_model table

This table is represented in code in the thoughts_backend/models.py file, described in SQLAlchemy format with the following code:

class ThoughtModel(db.Model):
id = db.Column(db.Integer, primary_key=True)
username = db.Column(db.String(50))
text = db.Column(db.String(250))
timestamp = db.Column(db.DateTime, server_default=func.now())

SQLAlchemy is capable of creating the table for testing purposes or for development mode. For this chapter, we defined the database to be SQLite, which stores the data in the db...