Deploying an ElasticSearch 2.x cluster on Ubuntu 16.04 LTS

(Jason Bayton) #1

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1. What is Elasticsearch? Elasticsearch is a free, open source, distributed search engine based on Apache Lucene. Elasticsearch boasts being able to take the overwhelming complexity of Lucene and present it in a simple to use, cross-platform product providing communication through a REST API over HTTP. Elasticsearch integrates with various solutions to provide in-depth search, analysis and manipulation of data. 1.1. Why a cluster? As a standalone server Elasticsearch will work well in smaller or development environments. For production environments however for improved stability, scalability and performance a cluster is very much recommended. As demand grows, adding additional servers is simple and straightforward. 2. The environment 2.1. Hardware Before getting started, note that the resources used in this guide are vastly lower than those recommended by Elastic for running ElasticSearch in production. Although CPU is less of a concern for ElasticSearch, memory is very important; on production environments at least 8GB of RAM is recommended, preferably 16GB or even 32GB due to the potential workloads of the ElasticSearch cluster. Similarly, plenty of SSD or 15K drive storage is also recommended. As the following takes place in a lab environment, the cluster will see nothing near a workload requiring that amount of resource. Before deploying a production cluster however, please read and follow the ElasticSearch minimum hardware guide here. For this guide, I’ll be using three Ubuntu 16.04 LTS servers in a master-data-data configuration. This type of setup scales well for performance, but it is not resilient to failure. In order to…