Amazon Elasticsearch: An Introduction


4 min read

Amazon Elasticsearch: An Introduction

Hi Everyone👋, welcome again🤗. In my last post, I gave a brief introduction to AWS, its meaning, and its benefits. I hope you learned from it. If you have not read the post, please go back to my last post and check it out. Today, I would be explaining Amazon Elasticsearch.

What is Elasticsearch? Elasticsearch is an open-source, RESTful, distributed search and analytics engine built on Apache Lucene. It is the search engine that powers log analytics.

How does it work? We have the ELK stack that we use when working with Elasticsearch. It is an Acronym for Elasticsearch, Logstash and, Kibana. First, you send data in the form of JSON documents to Elasticsearch using the API or ingestion tools such as Logstash. After this, Elasticsearch automatically stores the original documents and adds a searchable reference to the documents in the cluster’s index. You can then search and retrieve the documents using the Elasticsearch API. You can also use Kibana, an open-source visualization tool, with Elasticsearch to visualize your data and build interactive dashboards. In summary:

  • Elasticsearch: is a distributed, JSON-based search and analytics engine designed for horizontal scalability, maximum reliability, and easy management.

  • Logstash: is a simple tool for transforming and streaming data in Elasticsearch and,

  • Kibana: is an easy-to-use tool for visualization of data in Elasticsearch.

The benefits of Amazon Elasticsearch include:

  1. Easy to use: When using AWS Elasticsearch, you can deploy a production-ready Elasticsearch cluster in minutes. It simplifies time-consuming management tasks such as software patching, failure recovery, backups, and monitoring.

  2. It is Open: AWS Elasticsearch gives direct access to the Elasticsearch Open-Source API. It is fully compatible with the open-source Elasticsearch API, for all codes and applications.

  3. Secure: AWS Elasticsearch provides secure Elasticsearch clusters with AWS identity and management policies(IAM).

  4. Available: It proves high availability using zone awareness which replicates data between two zones.

  5. AWS Integrated: It integrates with Amazon kinesis firehose, AWS IOT, Amazon cloud watch Logs for seamless data ingestion, AWS CloudTrail for auditing, AWS Identity and access management(IAM) for security, and AWS CloudFormation for cloud orchestration.

  6. Scalable: It can scale clusters from a single node up to 20 nodes. You can configure the clusters to meet performance requirements by selecting from a range of instance types and storage options.

This is a basic introduction to Amazon Elasticsearch. In my next post, I would write on how to get started with Amazon Elasticsearch. Watch out for it👀. Do not forget to react to my post❤, add comments✍, and subscribe to my newsletter🏤.