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Monitoring Docker

Monitoring Docker

By : Russ McKendrick
4.6 (5)
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Monitoring Docker

Monitoring Docker

4.6 (5)
By: Russ McKendrick

Overview of this book

This book will show you how monitoring containers and keeping a keen eye on the working of applications helps improve the overall performance of the applications that run on Docker. With the increased adoption of Docker containers, the need to monitor which containers are running, what resources they are consuming, and how these factors affect the overall performance of the system has become the need of the moment. This book covers monitoring containers using Docker's native monitoring functions, various plugins, as well as third-party tools that help in monitoring. Well start with how to obtain detailed stats for active containers, resources consumed, and container behavior. We also show you how to use these stats to improve the overall performance of the system. Next, you will learn how to use SysDig to both view your containers performance metrics in real time and record sessions to query later. By the end of this book, you will have a complete knowledge of how to implement monitoring for your containerized applications and make the most of the metrics you are collecting
Table of Contents (10 chapters)
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9
Index

Some scenarios


To look at which type of monitoring you might want to implement for your container-based applications, we should work through a few different example configurations that your container-based applications could be deploying into. First, let's remind ourselves about Pets, Cattle, Chickens, and Snowflakes.

Pets, Cattle, Chickens, and Snowflakes

Back in the Chapter 1, Introduction to Docker Monitoring, we spoke about Pets, Cattle, Chickens, and Snowflakes; in that chapter, we described what each term meant when it was applied to modern cloud deployments. Here, we will go into a little more detail about how the terms can be applied to your containers.

Pets

For your containers to be considered a Pet, you will be more than likely to be running either a single or a small number of fixed containers on a designated host.

Each one of these containers could be considered a single point of failure; if any one of them goes down, it will more than likely result in errors for your application...

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