Amazon Elasticsearch Service is a fully managed service that makes it easy to deploy, secure, and run Elasticsearch cost effectively at scale. We can build, monitor, and troubleshoot our applications using the tools we love, at the scale we need. The service provides support for open source Elasticsearch APIs, managed Kibana, integration with Logstash and other AWS services, and built-in alerting and SQL querying. Amazon Elasticsearch Service let us pay only for what we use – there are no upfront costs or usage requirements. With Amazon Elasticsearch Service, we get the ELK stack we need, without the operational overhead.
Benefits
Easy to deploy and manage
With Amazon Elasticsearch Service we can deploy our Elasticsearch cluster in minutes. The service simplifies management tasks such as hardware provisioning, software installation and patching, failure recovery, backups, and monitoring. To monitor our clusters, Amazon Elasticsearch service includes built-in event monitoring and alerting so we can get notified on changes to our data to proactively address any issues.
Highly scalable and available
Amazon Elasticsearch Service let us store up to 3 PB of data in a single cluster, enabling us to run large log analytics workloads via a single Kibana interface. We can easily scale our cluster up or down via a single API call or a few clicks in the AWS console. Amazon Elasticsearch Service is designed to be highly available using multi-AZ deployments, which allows us to replicate data between three Availability Zones in the same region.
Highly secure
For our data in Elasticsearch Service, we can achieve network isolation with Amazon VPC, encrypt data at-rest and in-transit using keys we create and control through AWS KMS, and manage authentication and access control with Amazon Cognito and AWS IAM policies. Amazon Elasticsearch Service is also HIPAA eligible, and compliant with PCI DSS, SOC, ISO, and FedRamp standards to help us meet industry-specific or regulatory requirements.
Cost-effective
With Amazon Elasticsearch Service, we pay only for the resources we consume. We can select on-demand pricing with no upfront costs or long-term commitments, or achieve significant cost savings via our Reserved Instance pricing. As a fully managed service, Amazon Elasticsearch Service further lowers our total cost of operations by eliminating the need for a dedicated team of Elasticsearch experts to monitor and manage our clusters.
Use cases
Application monitoring
Store, analyze, and correlate application and infrastructure log data to find and fix issues faster and improve application performance. Enable trace data analysis for our distributed applications to quickly identify performance issues. You can receive automated alerts if our application is underperforming, enabling us to proactively address any issues. An online travel company, for example, we can use Amazon Elasticsearch Service to analyze logs from its applications to identify and resolve performance bottlenecks or availability issues, ensuring streamlined booking experience.
Security information and event management (SIEM)
Centralize and analyze logs from disparate applications and systems across our network for real-time threat detection and incident management. A telecom company, for example, can use Amazon Elasticsearch Service with Kibana to quickly index, search, and visualize logs from its routers, applications, and other devices to find and prevent security threats such as data breaches, unauthorized login attempts, DoS attacks, and fraud.
Search
Provide a fast, personalized search experience for our applications, websites, and data lake catalogs, allowing our users to quickly find relevant data. For example, a real estate business can use Amazon Elasticsearch Service to help its consumers find homes in their desired location, in a certain price range from among millions of real-estate properties. We get access to all of Elasticsearch’s search APIs, supporting natural language search, auto-completion, faceted search, and location-aware search.
Infrastructure monitoring
Collect logs and metrics from our servers, routers, switches, and virtualized machines to get a comprehensive visibility into our infrastructure, reducing mean time to detect (MTTD) and resolve (MTTR) issues and lowering system downtime. A gaming company, for example, we can use Amazon Elasticsearch Service to monitor and analyze server logs to identify any server performance issues that could lead to application downtime.
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