AWS Elasticsearch service intends to help you deploy, scale & operate Elasticsearch over the AWS cloud. If you already have a clean and crisp knowledge of the concepts of Elasticsearch, then you are definitely willing to get started with it. But, it is important for you to know the right approach steps to ensure that you get the job done efficiently.
Elasticsearch is counted as the most popular and preferable open-source analytics and search engine. It is preferred for a set of use cases that includes clickstream analytics, real-time application monitoring, and log analytics. Setting up and configuring the AWS Elasticsearch domain is quite easy and convenient. You will need just a few minutes over the AWS Management Console for creating your domain.
There is more to it that you must know about Amazon Elasticsearch, and this article intends to help you with a detailed definition of Elasticsearch.
Elasticsearch is an open-source database tool that can be easily deployed and operated. It is used for the analytic purpose and searching your logs and data in general. Basically, it is a NoSQL database to store the unstructured data in document format. Besides from that, if we talk about AWS Elasticsearch, it is like the Amazon which is easier as a service to create it in the clouds. You can use it for various purposes not only for online poor checking your logs or data, but you can also connect it to your cloud watch and use it for modeling after creating the AWS Elasticsearch.
Benefits of AWS Elasticsearch:
1) High-end Performance:
Elasticsearch comes with a distributed nature that gives it the potential to support parallel processing of larger volumes of data. Along with that, the high-end performance of AWS Elasticsearch also supports a quick finding of the best matches as per the queries given by you.
2) Availability of Diverse Plugins and Tools:
Elasticsearch has built-in integration with Kibana, a visualization tool. Along with visualization, this tool is also supportive of reporting aspects. Elasticsearch is also integrated onto Logstash and Beats for enabling you with the transformation of load & source data into the Elasticsearch cluster.
3) Application Deployment is Easy with Elasticsearch:
Elasticsearch offers support for diverse languages that include PHP, Node.js, Python, Ruby, and others. Hence, the wide range of support indicates an easy deployment of the application over the platform.
4)Near Real-Time Application:
Some of the Elasticsearch operations include reading or writing of data. Moreover, it takes less than a second over the platform. Therefore, this property allows you to use Elasticsearch for all of the use cases that need near real-time monitoring, such as anomaly detection or application monitoring.
5)Faster Time to Value:
Elasticsearch offers REST-based APIs with a simple HTTP interface. Therefore, it uses schema-free JSON documents, which makes it easy for the users to get started with Elasticsearch quickly to build dedicated applications for specified use cases.
6)Tight Integration with other AWS Services
Elasticsearch services intend to offer built-in and tight integrations with all of the other AWS services. Some of such AWS services include Kinesis Firehose, AWS IoT, CloudWatch Logs, and others. Moreover, this integration potential allows Elasticsearch to execute seamless data ingestion.
7) Easily usable
In Amazon Elasticsearch, all the services are fully managed, and this makes it easy to use. We can save time for backup, failure recovery, software patching, and monitoring. The users of AWS Elasticsearch can post the production-ready Elasticsearch cluster using AWS Elasticsearch within a few seconds. They do not need to worry about the installation and maintenance of Elasticsearch software.
8) Highly Secure
All of the users can easily set up secure access to the Amazon Elasticsearch Service from VPC. Furthermore, it allows perfect maintenance of Amazon Elasticsearch service and VPC within the network of AWS. At regular intervals, it automatically applies security patches for enhancing the performance of the domain and keeping it up to date.
Limitations of AWS Elasticsearch
Along with several advantages, there are few limitations of Amazon 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.
Amazon Elastic search provides free tier only for 12 months; means it is not free. After 12 months of signup, you have to pay for using it.
AWS Elastic Search Features
Elasticsearch has various features and each of them introduces some unique functionality. AWS Elasticsearch features are as follows –
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 from that, it supports for 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 back up of Amazon ES domains and restore them. In this, backup and restore process is done automatically.
There are various geographical locations (called Regions and Availability Zones) is 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.
e) Integration with popular Services
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.