Book Image

Python Microservices Development – 2nd edition - Second Edition

By : Simon Fraser, Tarek Ziadé
Book Image

Python Microservices Development – 2nd edition - Second Edition

By: Simon Fraser, Tarek Ziadé

Overview of this book

The small scope and self-contained nature of microservices make them faster, cleaner, and more scalable than code-heavy monolithic applications. However, building microservices architecture that is efficient as well as lightweight into your applications can be challenging due to the complexity of all the interacting pieces. Python Microservices Development, Second Edition will teach you how to overcome these issues and craft applications that are built as small standard units using proven best practices and avoiding common pitfalls. Through hands-on examples, this book will help you to build efficient microservices using Quart, SQLAlchemy, and other modern Python tools In this updated edition, you will learn how to secure connections between services and how to script Nginx using Lua to build web application firewall features such as rate limiting. Python Microservices Development, Second Edition describes how to use containers and AWS to deploy your services. By the end of the book, you’ll have created a complete Python application based on microservices.
Table of Contents (14 chapters)
12
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13
Index

Expanding monitoring

In Chapter 5, Splitting the Monolith, we discussed monitoring and collecting metrics to record what an application is doing. Measurements can tell some of the story and give a picture involving a count, a size, or time passing. To get even more information, we can use logging services to record messages our application produces.

If you have set up a Linux server, you may be familiar with the logs that pass through rsyslog and end up in a file that exists in /var/log. In a cloud service, and especially in a container, logging locally is far less useful, as we would have to then investigate all the running containers and cloud instances to discover what was happening. Instead, we can use a centralized logging service.

This could be done using tools such as AWS CloudWatch or Google's Cloud Logging, but it's also possible to run services such as Splunk or Logstash. The latter is part of a popular open source trio of tools called the ELK stack, as...