AWS News Blog
Announcing Amazon OpenSearch Service which Supports OpenSearch 1.0
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Developers embrace open-source software for many reasons. One of the most important reasons is the freedom to use that software where and how they want. On January 21, 2021, Elastic NV announced that they would change their software licensing strategy. After Elasticsearch version 7.10.2 and Kibana 7.10.2, they will not release new versions of Elasticsearch and Kibana under the permissive 2.0 version of the Apache License (ALv2). Instead, Elastic NV is releasing Elasticsearch and Kibana under the Elastic license, with source code available under the Elastic License or Server Side Public License (SSPL). These licenses are not open source and do not offer users the same freedom.
For this reason, we decided to create and maintain OpenSearch, a community-driven, open-source fork from the last ALv2 version of Elasticsearch and Kibana. We are making a long-term investment in the OpenSearch project and recently released version 1.0.
OpenSearch provides a highly scalable system for providing fast access and response to large volumes of data with an integrated visualization tool, OpenSearch Dashboards, that makes it easy for users to explore their data. OpenSearch and OpenSearch Dashboards were originally derived from Elasticsearch 7.10.2 and Kibana 7.10.2. Like Elasticsearch and Apache Solr, OpenSearch is powered by the Apache Lucene search library.
Announcing Amazon OpenSearch Service
Today we bring you Amazon OpenSearch Service, and we will continue to deliver the same experiences without any negative impact to ongoing operations, development methodology, or business use.
Amazon OpenSearch Service offers a choice of open-source engines to deploy and run, including the currently available 19 versions of ALv2 Elasticsearch 7.10 and earlier and OpenSearch 1.0. We will continue to support and maintain the ALv2 Elasticsearch versions with security and bug fixes. We will deliver all-new features and functionality through OpenSearch and OpenSearch Dashboards. Amazon OpenSearch Service APIs will be backward-compatible with the existing service APIs, so there is no need for you to update your current client code or applications. We will keep clients of OpenSearch compatible with open source.
To get started, in the AWS Management Console, choose Create a domain. In Step 1: Choose deployment type, select OpenSearch 1.0 (latest).
We recommend OpenSearch 1.0 if you are deploying a new cluster and want access to the latest features and enhancements. OpenSearch 1.0 is compatible with the open-source Elasticsearch 7.10 APIs and most clients.
Upgrading to OpenSearch 1.0
Amazon OpenSearch Service offers a seamless in-place upgrade path from existing Elasticsearch 6.x and 7.x managed clusters to OpenSearch. To upgrade a domain to OpenSearch 1.0 in the AWS Management Console, choose the domain that you want to upgrade, choose Actions, and then select Upgrade domain.
Next, you can select a version to upgrade to OpenSearch 1.0 for your existing domain without creating a separate domain and migrating your data.
The upgrade process is irreversible. It can’t be paused or canceled. During an upgrade, you can’t make configuration changes to the domain. Before you start an upgrade, you can perform the pre-upgrade checks for issues that can block an upgrade and take a snapshot of the cluster by selecting Check upgrade eligibility.
Amazon OpenSearch Services starts the upgrade, which can take from 15 minutes to several hours to complete. To learn more, see Upgrading Amazon OpenSearch Service domains and the rest of the Amazon OpenSearch Service Developer Guide.
OpenSearch Features
OpenSearch provides the following features:
| Features | Description |
| Advanced Security | Offers encryption, authentication, authorization, and auditing features. They include integrations with Active Directory, LDAP, SAML, Kerberos, JSON web tokens, and more. OpenSearch also provides fine-grained, role-based access control to indices, documents, and fields. |
| SQL Query Syntax | Provides the familiar SQL query syntax. Use aggregations, group by, and where clauses to investigate your data. Read data as JSON documents or CSV tables so you have the flexibility to use the format that works best for you. |
| Reporting | Schedule, export, and share reports from dashboards, saved searches, alerts, and visualizations. |
| Anomaly Detection | Use machine learning anomaly detection based on the Random Cut Forest (RCF) algorithm to automatically detect anomalies as your data is ingested. Combine with alerting to monitor data in near real time and send alert notifications automatically. |
| Index Management | Define custom policies to automate routine index management tasks, such as rollover and delete, apply them to indices and index patterns, and transforms. |
| Performance Analyzer and RCA Framework | Query numerous cluster performance metrics and aggregations. Use PerfTop, the command line interface (CLI) to quickly display and analyze those metrics. Use the root cause analysis (RCA) framework to investigate performance and reliability issues in clusters. |
| Asynchronous Search | Run complex queries without worrying about the query timing out with Asynchronous Search queries running in the background. Track query progress and retrieve partial results as they become available. |
| Trace Analytics | Ingest and visualize OpenTelemetry data for distributed applications. Visualize the flow of events between these applications to identify performance problems. |
| Alerting | Automatically monitor data and send alert notifications to stakeholders. With an intuitive interface and a powerful API, easily set up, manage, and monitor alerts. Craft highly specific alert conditions using OpenSearch’s full query language and scripting capabilities. |
| k-NN search | Using machine learning, run the nearest neighbor search algorithm on billions of documents across thousands of dimensions with the same ease as running any regular OpenSearch query. Use aggregations and filter clauses to further refine similarity search operations. k-NN similarity search powers use cases such as product recommendations, fraud detection, image and video search, related document search, and more. |
| Piped Processing Language | Provides a familiar query syntax with a comprehensive set of commands delimited by pipes (|) to query data. |
| Dashboard Notebooks | Combine dashboards, visualizations, text, and more to provide context and detailed explanations when analyzing data. |
OpenSearch 1.0 supports three new features that are not available in the existing Elasticsearch versions supported on Amazon OpenSearch Service: Transforms, Data Streams, and Notebooks in OpenSearch Dashboards.
To engage with the OpenSearch community, we welcome pull requests through GitHub to fix bugs, improve performance and stability, or add new features. You can leave feedback in the OpenSearch community forum.
Now Available
Amazon Elasticsearch Service is available now. For more information, see the Amazon OpenSearch Service page.
You can send feedback to the AWS forum for Amazon OpenSearch Service or through your usual AWS Support contacts.
— Channy