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Hands-On Docker for Microservices with Python

You're reading from   Hands-On Docker for Microservices with Python Design, deploy, and operate a complex system with multiple microservices using Docker and Kubernetes

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Product type Paperback
Published in Nov 2019
Publisher Packt
ISBN-13 9781838823818
Length 408 pages
Edition 1st Edition
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Author (1):
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Jaime Buelta Jaime Buelta
Author Profile Icon Jaime Buelta
Jaime Buelta
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Table of Contents (19) Chapters Close

Preface 1. Section 1: Introduction to Microservices
2. Making the Move – Design, Plan, and Execute FREE CHAPTER 3. Section 2: Designing and Operating a Single Service – Creating a Docker Container
4. Creating a REST Service with Python 5. Build, Run, and Test Your Service Using Docker 6. Creating a Pipeline and Workflow 7. Section 3:Working with Multiple Services – Operating the System through Kubernetes
8. Using Kubernetes to Coordinate Microservices 9. Local Development with Kubernetes 10. Configuring and Securing the Production System 11. Using GitOps Principles 12. Managing Workflows 13. Section 4: Production-Ready System – Making It Work in Real-Life Environments
14. Monitoring Logs and Metrics 15. Handling Change, Dependencies, and Secrets in the System 16. Collaborating and Communicating across Teams 17. Assessments 18. Other Books You May Enjoy

Monitoring Logs and Metrics

In real-life operations, the ability to quickly detect and debug a problem is critical. In this chapter, we will discuss the two most important tools we can use to discover what's happening in a production cluster processing a high number of requests. The first tool is logs, which help us to understand what's happening within a single request, while the other tool is metrics, which categorizes the aggregated performance of the system.

The following topics will be covered in this chapter:

  • Observability of a live system
  • Setting up logs
  • Detecting problems through logs
  • Setting up metrics
  • Being proactive

By the end of this chapter, you'll know how to add logs so that they are available to detect problems and how to add and plot metrics and understand the differences between both of them.

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