Book Image

The DevOps 2.1 Toolkit: Docker Swarm

By : Viktor Farcic
Book Image

The DevOps 2.1 Toolkit: Docker Swarm

By: Viktor Farcic

Overview of this book

Viktor Farcic's latest book, The DevOps 2.1 Toolkit: Docker Swarm, takes you deeper into one of the major subjects of his international best seller, The DevOps 2.0 Toolkit, and shows you how to successfully integrate Docker Swarm into your DevOps toolset. Viktor shares with you his expert knowledge in all aspects of building, testing, deploying, and monitoring services inside Docker Swarm clusters. You'll go through all the tools required for running a cluster. You'll travel through the whole process with clusters running locally on a laptop. Once you're confident with that outcome, Viktor shows you how to translate your experience to different hosting providers like AWS, Azure, and DigitalOcean. Viktor has updated his DevOps 2.0 framework in this book to use the latest and greatest features and techniques introduced in Docker. We'll go through many practices and even more tools. While there will be a lot of theory, this is a hands-on book. You won't be able to complete it by reading it on the metro on your way to work. You'll have to read this book while in front of the computer and get your hands dirty.
Table of Contents (22 chapters)
Title Page
Credits
About the Author
www.PacktPub.com
Customer Feedback
Preface
11
Embracing Destruction: Pets versus Cattle

Choosing the right database to store system metrics


In The DevOps 2.0 Toolkit, I argued against "traditional" monitoring tools like Nagios (https://www.nagios.org/) and Icinga (https://www.icinga.org/). Instead, we chose to use Elasticsearch for both the logs and the system metrics. In the previous chapter, I reiterated the choice for using Elasticsearch as the logging solution. Can we extend its usage by storing metrics? Yes, we can. Should we do that? Should we use it as a place to store system metrics? Are there better solutions? The biggest problem with Elasticsearch, if used as a database to store system metrics, is that it is not a time series type of database. Logs benefit greatly from Elasticsearch ability to perform free text search and store data in an unstructured way. However, for system metrics, we might take advantage of a different type of data storage. We need a time series database.

Time series databases are designed around optimized ways to store and retrieve time series...