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

Observability of a live system

Observability is the capability of knowing what's going on in a live system. We can deal with low-observability systems, where we have no way of knowing what's going on, or high-observability systems, where we can infer the events and internal state from the outside through tools.

Observability is a property of the system itself. Typically, monitoring is the action of obtaining information about the current or past state of the system. It's all a bit of a naming debate, but you monitor the system to collect the observable parts of it.

For the most part, monitoring is easy. There are great tools out there that can help us capture and analyze information and present it in all kinds of ways. However, the system needs to expose the relevant information so that it can be collected.

Exposing the correct amount of information is difficult...