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Post By Admin Last Updated At 2020-06-11
An overview of AWS Elasticsearch

Elasticsearch is an open-source popular search and analytics engine. The AWS Elasticsearch offers different services that help to deploy, secure, and operate various Elasticsearch. Such as log analytics, monitoring applications, and text search, etc. AWS Elasticsearch has some in-built integration such as Amazon VPC, Logstash, Kibana, Amazon Cloudwatch, etc. These platforms are very helpful for changing raw data into meaningful insights. It is done securely with a quick response.

In Elasticsearch there are different search performance metrics to watch such as query load, fetch latency, and query latency. Further, there are two index performance metrics also such as index refresh and index flush. Besides, there are indexing latency and flush latency.

Moreover, Elasticsearch is easy to use API which contains capabilities like scalability, security, and availability of production works.

AWS Elasticsearch performance

AWS Elasticsearch has a cluster that is made up of different nodes. Each node is an individual running instance under Elasticsearch. It also contains a configuration file that denotes the cluster name for each Elasticsearch. Moreover, there are three different types of nodes in Elasticsearch. They are;

  • Client nodes
  • Master eligible nodes
  • Data nodes

Client nodes: If the user sets node.master and to false, then it will end up with a client node. It is meant to work as a load balancer. The Client nodes help the search workload so that the data and master-eligible nodes can perform well in their tasks. Moreover, adding client nodes to the cluster helps to search/index workload easily to get route requests.

Master-eligible nodes: Each of the clusters automatically selects the master node from all other master-eligible nodes. These nodes are helpful to coordinate cluster tasks like creating and removing various indices, segregating shards among nodes, etc. Moreover, a master-eligible node can function as a data node. It’s the biggest advantage of this node.

Data nodes: Usually, every node is a data node. It helps to store data and performs various actions like indexing, searching, etc. In the large clusters, the user can create specifically dedicated data nodes but ensuring that these can handle many data related queries. Besides, these can be done without putting the extra workload on clusters.

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The AWS Elasticsearch provides different kinds of metrics that help to detect various issues and actions to be taken. Some key areas that need to monitor regarding performance are; memory and garbage collection, availability of cluster node and its health, search and index performance, etc. Moreover, there are host-level system metrics, resource errors, etc.

AWS Elasticsearch architecture

The architecture of AWS Elasticsearch includes an idea about various services. This allows creating instances, remove, and change sizes of instance and storage configurations. It contains three different components such as; Logstash, Kibana, and Elasticsearch. Logstash is useful to collect and transfer data to Elasticsearch. Elasticsearch acts as a database that helps to search and analyze the logs.

Moreover, Kibana is useful to visualize data on dashboards that provide quick insight into any documents. The dashboard contains various interactive graphs and diagrams to visualize complex queries. These include maps, charts, tables, etc.

These services are expandable very much. They are useful to monitor the services through Amazon Cloudwatch metrics. Furthermore, it includes different integrations also such as data visualization, Amazon CloudTrail, Amazon Kinesis, Amazon DynamoDB, etc. The services also provide the guarantee of a secure environment and easy integrations. There is an option of accessing IAM control that helps to authenticate Kibana and Data encryption.

Moreover, the AWS Elasticsearch supports the different zones of various geographical locations to provide the availability of services.

Benefits of AWS Elasticsearch

There are many benefits of AWS Elasticsearch. It offers simple REST APIs, HTTP interface along with JSON documents that are schema-free. This search helps to build applications quickly and has the most value for time. It provides high performance in service with different types of complementary tools and plugins. Moreover, it is easy to use and very secure. Using the AWS Elasticsearch, the user can easily post any production-ready cluster within no time. All the services within this are fully managed along with installation, maintenance, and monitoring, patching, and backup of software.

Besides, it provides support to open-source tools and APIs. It gives direct access to these tools without the need for programming knowledge. Such as Kibana, Logstash, etc. Using VPC within the AWS network, one can easily set up secure access to AWS Elasticsearch. It also updates the software regularly and keeps its performance well.

Furthermore, it is highly scalable. It can easily modify cluster using the AWS management console with certain clicks. It also provides a real-time, distributed analytics engine that works robustly. Besides, it offers data durability and various cluster scaling options. It provides advanced security with IAM control.

AWS Elasticsearch pricing

Using AWS Elasticsearch service one can pay for the usage of service only. The payment of service includes the usage hours, data transfer, and Amazon EBS storage. Here, one can start with AWS free tier. It provides free usage of up to 750 hours per month. Additionally, it offers 10 GB per month optional EBS storage. Moreover, it offers an on-demand instance pricing service with live usage. It helps to generate the current usage fee.

Furthermore, it also offers a reserved instance pricing system. The user can reserve instances for a one or three-year term paying a certain amount for service usage. Here the user can save more compared to other on-demand services. Both service instances are identical to each other. Besides, it has a different pricing system for different years or terms of usage.

AWS Elasticsearch Kibana

It is an open-source data visualization tool. This is mostly useful for logging applications and time-series analytics, monitoring, and operations. It offers interactive dashboards with different line graphs, maps, tables, histograms, etc. Moreover, it offers highly interactive charts, filters, mapping support, etc. It is a very powerful and easy visualization tool to get quick results. It s interactive dashboards help to get meaningful insights and many more.

The core uses of this tool under AWS Elasticsearch are as follows.

  • It is useful for analyzing logs that are generated from various servers, devices, and applications.
  • Further, it offers a wide range of charts along with various reports that reflect the value of time and its usage.
  • Its IT operations are always-on monitoring. It captures various server logs. Moreover, it indexes large data and makes it available for analysis.
AWS Elasticsearch Concept

There are different types of concepts available for AWS Elasticsearch and these are as follows. :-

Here, the Amazon/ AWS Elasticsearch domain and Elasticsearch cluster are similar concepts. Besides, domains are the clusters having instance type, settings, count, and storage type that the user mentions. 

This facilitates to build of more than one Elasticsearch indices under the same domain.

Moreover, within Amazon Elasticsearch, to update the domain, blue/green deployment processes are mainly used.

Furthermore, AWS automatically takes care of software updates even if the user does not look at updating. 

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Features of AWS Elasticsearch

There are several useful features that AWS Elasticsearch has. Each of its features represents its unique functionality. Let us discuss each of these AWS ES features in detail.


The AWS Elasticsearch engine is highly-flexible and offers its users to store data with 3PB (petabytes) storage inside. Besides, it has a great feature of UltraWarm Storage that facilitates read-only data with a large storage capacity. This is a cost-effective way for large data storage. Furthermore, users can configure several storage areas, CPU, and memory using AWS ES.


Amazon ES engine offers great flexibility to its users that helps to enhance search results. For this search engine provides them some custom packages also. Moreover, to combine with BI apps, it provides users with SQL support.


When it comes to security, the AWS ES engine offers the best. The Amazon Elasticsearch engine provides data access control on AWS IAM (Identity and Access Management). Further, it takes care of data encryption from node-to-node. It offers security at three different levels such as index-level, field, and document level. 


The most important and reliable feature of AWS ES is its stability. Here it offers an automatic snapshot facility. By this, it takes backup of the AWS Elasticsearch engine domains and restores them securely. Moreover, it provides various geographical locations to its users for resources. Further, it enables the distribution of nodes across availability zones within AWS regions. It also provides some dedicated master nodes to dump some cluster management jobs.

Integration with other services

AWS Elasticsearch has an integration facility with other popular services such as integration with Kibana for data visualization. Moreover, it has integration with the Amazon CloudWatch feature to check the AWS ES domain metrics & to set important alarms. The search engine also combines with AWS CloudTrail to audit configure API calls to AWS Elasticsearch domain.

Furthermore, to load transmitting data into Amazon ES, it combines with several Amazon services. Like kinesis, DynamoDB, etc. There is another important facility that it offers is, it sets an alert through Amazon SNS while data exceeds limits.

Limitations of AWS Elasticsearch

There are certain limitations or cons of an AWS Elasticsearch along with its benefits. These are;-

The AWS ES domain enables its users to start their domain within a VPC (Virtual Pvt Cloud) or through using a public endpoint. Hence, both actions together are not allowed for users to launch their domain. 

Moreover, it offers its free trial facility only for up to 12 months in a year. Beyond this period that users have to go with payment for using it further.

AWS Elasticsearch version

The following versions of AWS ES are currently supporting it.

7.9, 7.8, 7.7, 7.4, 7.1

6.8, 6.7, 6.5, 6.4, 6.3, 6.2, 6.0

5.6, 5.5, 5.3, 5.1



In comparison with earlier versions of Amazon ES, versions 7.x & 6.x offer many powerful features. This makes them faster, more secure, and easier to use for the users of AWS ES. 

The features and highlights of these AWS ES versions are;-

Higher indexing performance 

This feature enhances the throughput of data updates at superior capacity.

Better security

This feature of AWS ES facilitates prevention from complex queries. This may negatively affect the performance and stability of the cluster.

Vega visualizations

Kibana 6.2 and higher versions support this language that facilitates context-aware ES queries to make. Moreover, it offers to integrate several data sources into a single platform. 

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High-level REST-client using Java

Compared to another low-level client, this one provides a more simplified development experience and supports most ES APIs.

Moreover, the features of supported versions of AWS ES are as follows;-

VPC support, the need for HTTPS for all domain traffic, Multiple availability zones, dedicated master nodes, and custom packages. These facilities are inclusive for all the ES domains. There are many other features that support other versions of this search engine. Hence, these are the basic supportive features of an AWS Elasticsearch.


Thus, the above writing provides an overview of AWS Elasticsearch. It offers a wide range of services. These are helpful to use AWS for different purposes. It gives various search and indexing analytics that are useful for the user in different ways. Using AWS Elasticsearch the user can get real-time insights of meaningful data that serve different purposes. This includes a great service offering that changes the scenario of data visualization. This system has many uses that can be altered with other services. It has a vast field of the service community.

To enhance skills in this regard one can opt for AWS Online Training where the aspirants will get practical insights. This learning will help to fill the gaps in various skills and enhances the career successfully.