Last updated on 22nd Sep 2020, Artciles, Blog
Amazon Elasticsearch Service (Amazon ES) is a managed service that makes it easy to deploy, operate, and scale Elasticsearch clusters in the AWS Cloud. Elasticsearch is a popular open-source search and analytics engine for use cases such as log analytics, real-time application monitoring, and clickstream analysis.
AWS Elasticsearch Features
AWS Elasticsearch has various features and each of them introduces some unique functionality. A list of AWS Elasticsearch is as follows
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- It provides access control on AWS Identity and Access Management (IAM).
- The data is encrypted and offers node-to-node encryption.
- AWS Elasticsearch provides security at different levels, which are field-level, document-level, and index-level.
- For Kibana (which is a data visualization tool), it offers HTTP basic authentication.
- AWS Elasticsearch offers flexibility to its users, e.g., to improve the search results, it provides custom packages.
- AWS Elasticsearch provides SQL support to integrate with BI applications (Business Intelligence Application).
- AWS Elasticsearch is highly scalable as it provides up to 3PB attached storage to hold the data.
- Besides that, it supports UltraWarm storage to store read-only data. UltraWarm storage is a cost-effective way to store huge data.
- With AWS Elasticsearch, we can configure various CPU, memory, and storage capacity.
- One of the most important features is, it provides an automated snapshot facility to take backup of Amazon ES domains and restore them. In this, the backup and restore process is done automatically.
- There are various geographical locations (called Regions and Availability Zones) provided by AWS Elasticsearch for your resources.
- It allows allocating the nodes across two or three Availability zones in the same AWS Region.
- To offload the cluster management tasks, it offers dedicated master nodes.
Integration with popular Services
- AWS Elasticsearch can be integrated with several other popular services, like integrate with Kibana for data visualization.
- To monitor the Amazon ES domain metrics and to set the alarms, it is integrated with Amazon CloudWatch.
- To load the streaming data into Amazon Elasticsearch, it integrates with different Amazon services, which are – Amazon DynamoDB, Amazon S3, and Amazon Kinesis.
- AWS Elasticsearch integrates with AWS CloudTrail for auditing configuration API calls to Amazon Elasticsearch domains.
- In case your data exceeds the certain thresholds, it alerts the users from Amazon SNS.
Limitations of AWS Elasticsearch
Along with several advantages, there are few limitations of AWS Elasticsearch, which are as follows
- It allows the users to launch their domain within a VPC or use a public endpoint. Although both actions are not allowed to be performed together in it.
- AWS Elasticsearch provides a free tier only for 12 months; means it is not free. After 12 months of signup, you have to pay for using it.
Advantages of AWS Elasticsearch
The Main Benefits of AWS Elasticsearch is that
1. Used easily: By using AWS Elasticsearch, One can easily post the production-ready ElasticSearch cluster within a fraction of seconds. There is no need to worry about Installation, Provisioning infrastructure, and maintenance of Elasticsearch software. All the services in the Amazon ElasticSearch are fully managed where time can be saved for failure recovery, backup, software patching and monitoring.
2. Supports Open Source APIs and Tools:
Probably, it gives them direct access to the ElasticSearch Open-Source API without any requirement of new software or else programming skills. It supports Logstash which is an open source data ingestion, loading tools, and transformation. It also supports Kibana which is the open-source visualization tool.
One can easily set up with secure access to Amazon ElasticSearch Service from the VPC for perfect maintenance of VPC and Amazon ElasticSearch Service within the AWS network itself. At regular intervals, it applies security patches and keeps the domain up to date to enhance performance with ease.
4. Highly Available:
It is mostly designed to be a high availability using awareness of various zones which is between the data of two availability zones in the same region itself. The services can also monitor the regular health of clusters and replicate the failure nodes in an automatic way.
5. Tightly Integrated with Other AWS Service:
The AWS ElasticSearch services deliver built-in integrations with AWS services that probably include Kinesis Firehose, Amazon the CloudWatch Logs and AWS IOT for seamless data ingestion.
6. Easily Scalable:
Amazon ElasticSearch services can monitor various clusters through Amazon CloudWatch metrics with ease. It can also resize the cluster up or down through certain clicks in the AWS Management console and single API call.
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