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

Cluster requirements

The requirements for your cluster—the number of nodes and the hardware specifications of each node—depend on several factors, including the following:

  • Total volume of data

  • Data ingest rate

  • Average record size

  • Data mapping

  • Types of queries being run

  • System performance requirements

There's no one size fits all formula to determine cluster requirements for a given Elasticsearch use case. The best approach is to meticulously test performance while changing variables, such as shard size, the number of nodes in the cluster, and hardware configurations until an optimal solution is found. This section focuses on high-level guidelines to consider when configuring your cluster.

It's a good idea to run at least three nodes in a production environment and to set data replication to 1, which asks Elasticsearch to maintain one copy of each shard in the cluster. This configuration will ensure that if a node goes down, your cluster won't lose any data.

Elasticsearch tends to be more memory intensive...