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

Using Kubernetes in the wild

When deploying a cluster to be used as production, the best possible advice is to use a commercial service. All the main cloud providers (AWS EKS, Google Kubernetes Engine (GKE), and Azure Kubernetes Service (AKS)) allow you to create a managed Kubernetes cluster, meaning that the only required parameter is to choose the number and type of physical nodes and then access it through kubectl.

We will use AWS for the examples in this book, but take a look at the documentation of other providers in case they work better for your use case.

Kubernetes is an abstraction layer, so this way of operation is very convenient. The pricing is similar to paying for raw instances to act as node servers and removes the need to install and manage the Kubernetes Control Plane so the instances act as Kubernetes nodes.

It's worth saying it again: unless you have a...