You're reading from Docker for Developers Develop and run your application with Docker containers using DevOps tools for continuous delivery

Product type Paperback

Published in Sep 2020

Publisher Packt

ISBN-13 9781789536058

Length 468 pages

Edition 1st Edition

Tools

Docker

Concepts

Containerization

Authors (3):

Richard Bullington-McGuire

Michael Schwartz

Andrew K. Dennis

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Table of Contents (21) Chapters

Preface

1. Section 1: An Introduction to Docker – Containers and Local Development

2. Chapter 1: Introduction to Docker FREE CHAPTER

3. Chapter 2: Using VirtualBox and Docker Containers for Development

4. Chapter 3: Sharing Containers Using Docker Hub

5. Chapter 4: Composing Systems Using Containers

6. Section 2: Running Docker in Production

7. Chapter 5: Alternatives for Deploying and Running Containers in Production

8. Chapter 6: Deploying Applications with Docker Compose

9. Chapter 7: Continuous Deployment with Jenkins

10. Chapter 8: Deploying Docker Apps to Kubernetes

11. Chapter 9: Cloud-Native Continuous Deployment Using Spinnaker

12. Chapter 10: Monitoring Docker Using Prometheus, Grafana, and Jaeger

13. Chapter 11: Scaling and Load Testing Docker Applications

14. Section 3: Docker Security – Securing Your Containers

15. Chapter 12: Introduction to Container Security

16. Chapter 13: Docker Security Fundamentals and Best Practices

17. Chapter 14: Advanced Docker Security – Secrets, Secret Commands, Tagging, and Labels

18. Chapter 15: Scanning, Monitoring, and Using Third-Party Tools

19. Chapter 16: Conclusion – End of the Road, but not the Journey

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Application performance monitoring with Jaeger

We are now going to take a brief tour of Jaeger to see how it can be used for performance monitoring in a microservices architecture. One of the key problems faced when implementing performance and error tracking in a microservice architecture versus a monolithic application is that a microservices architecture is inherently a distributed environment.

Early attempts at solving this problem, such as OpenCensus (https://opencensus.io/tracing/), suffered from disparate terminology and approaches and incompatible systems. To solve this problem, the performance monitoring community created the OpenTracing API.

Understanding the OpenTracing API

The OpenTracing project (https://opentracing.io/) is designed to allow engineers to add performance-monitoring features to their projects using a common API specification that is non-vendor specific.

Some of the key features of OpenTracing that realize this goal are as follows: