Book Image

Monitoring Elasticsearch

By : Dan Noble, Pulkit Agrawal, Mahmoud Lababidi
Book Image

Monitoring Elasticsearch

By: Dan Noble, Pulkit Agrawal, Mahmoud Lababidi

Overview of this book

ElasticSearch is a distributed search server similar to Apache Solr with a focus on large datasets, a schema-less setup, and high availability. This schema-free architecture allows ElasticSearch to index and search unstructured content, making it perfectly suited for both small projects and large big data warehouses with petabytes of unstructured data. This book is your toolkit to teach you how to keep your cluster in good health, and show you how to diagnose and treat unexpected issues along the way. You will start by getting introduced to ElasticSearch, and look at some common performance issues that pop up when using the system. You will then see how to install and configure ElasticSearch and the ElasticSearch monitoring plugins. Then, you will proceed to install and use the Marvel dashboard to monitor ElasticSearch. You will find out how to troubleshoot some of the common performance and reliability issues that come up when using ElasticSearch. Finally, you will analyze your cluster’s historical performance, and get to know how to get to the bottom of and recover from system failures. This book will guide you through several monitoring tools, and utilizes real-world cases and dilemmas faced when using ElasticSearch, showing you how to solve them simply, quickly, and cleanly.
Table of Contents (15 chapters)
Monitoring Elasticsearch
About the Author
About the Reviewers

Setting up Marvel

See Chapter 2, Installation and the Requirements for Elasticsearch, for instructions on how to install the Marvel Agent and the Marvel Kibana dashboard.

Marvel stores its metrics data inside Elasticsearch. It is possible to store these metrics alongside production data in the same Elasticsearch cluster; however, this is inadvisable because:

  • Marvel's data indices can grow quite large and, in a production setting, you won't want these indices affecting the performance of your primary cluster.

  • If the primary cluster is experiencing issues, having Marvel on a separate cluster will allow you to more easily diagnose those issues.

  • If Marvel is running on a normal data node, it can inadvertently be configured to collect data on its own metrics indices. For example, if you log in to the Marvel dashboard and start querying the Marvel indices, these queries will then be logged back to the Marvel indices. This is probably not the intended behavior.

For these reasons, this chapter covers...