Amazon OpenSearch Serverless

Deliver search and log analytics without provisioning and adjusting resources

Amazon OpenSearch Serverless is a serverless option in Amazon OpenSearch Service. As a developer, you can use OpenSearch Serverless to run petabyte-scale workloads without configuring, managing, and scaling OpenSearch clusters. You get the same interactive millisecond response times as OpenSearch Service with the simplicity of a serverless environment.

What is Amazon OpenSearch Serverless? (01:35)


Get started in seconds

Use familiar open-source ingestion and pipelines without having to change your applications.

Scale on demand

OpenSearch Serverless automatically provisions and continually adjusts to get fast data ingestion rates and millisecond response times during changing usage patterns and demand.

Improve costs

Pay only for what you use by automatically scaling resources to provide the right amount of capacity for your application—without impacting data ingestion.

Store and search vector embeddings

Power your generative artificial intelligence (AI) applications with simple, scalable, and high-performing vector search. 

Use cases

Flex with variable workloads

Scale application resources seamlessly without having to preconfigure needed compute power and memory.

Meet sensitive service-level agreements (SLAs)

Pre-initialize application resources and achieve response times in seconds.

Create development and test environments

Quickly create development and test environments, automatically scale with unpredictable usage, and deliver products to market faster.

Build ML-augmented search experiences

Generate more precise and accurate search results by colocating vector and text search to power your generative AI applications.

Customers and partners

  • riskCanvas
  • riskCanvas is a subsidiary of Genpact. It is a SaaS product offering for a financial crime compliance solution that uses cutting-edge big data, automation, and machine learning technologies to deliver compliance, efficiency, and automation to its clients.

    “riskCanvas’ entity-centric monitoring incorporates transaction monitoring, external enrichment, watchlist screening, and negative news to automatically assess risk and alert only for high-risk customers, hugely reducing the effort to meet regulatory compliance requirements. This requires significant and varied analytic processing that often experiences spikey and unpredictable data load. We are excited about Amazon OpenSearch Serverless, which will scale automatically to meet the data ingestion and analytic processing requirements of our workloads and then scale back down as demand decreases to reduce costs drastically—all with no reengineering or maintenance impact.” 

    Ryan Skousen, Chief Technology Officer (riskCanvas) and Vice President of Technology, Genpact Financial Crimes 

  • SmugMug
  • SmugMug is one of the world's leading photographer-focused communities.

    “SmugMug has used AWS search services since 2011 to power search for our customers' photos and albums. Over time, and through generations of AWS search technology, the amount of undifferentiated heavy lifting has decreased, costs have decreased, and performance and search capabilities have improved. Amazon OpenSearch Serverless automatically scales to meet demand, further decreasing the operational work required to keep our searches fast and helping us lower our overall cost. With Amazon OpenSearch Serverless, we can now expand our OpenSearch use cases to build new features to thrill our customers.”

    Andrew Shieh, Principal Engineer, SmugMug and Flickr

  • Valtix
  • Valtix helps organizations protect workloads in public cloud deployments with a cloud-based network security platform delivered as a service.

    “We are currently using many OpenSearch clusters for our security intelligence database. Our engineering team is responsible for the ongoing maintenance to scale and tune these clusters periodically. With Amazon OpenSearch Serverless, this infrastructure management is handled automatically, freeing up our Engineering team to focus on delivering value for our customers. And since Amazon OpenSearch Serverless automatically scales to meet demand, we do not have to provision a large cluster for our peak load use, so we only have to pay for the resources we actually use.”

    Praveen Patnala, Cofounder and Vice President of Engineering, Valtix

  • Kaizen Analytix
  • Kaizen Analytix is a leading provider of analytics products and business insights solutions that help clients increase revenues, reduce costs, and maximize margins.

    Kaizen Analytix
    “At Kaizen Analytix, we are constantly looking for ways to leverage cloud platforms for analytics projects to reduce costs and increase productivity without sacrificing performance. We are excited about Amazon OpenSearch Serverless, which will enable our customers to meet unpredictable traffic peaks without compromising on performance or managing any OpenSearch infrastructure, while only paying for the resources they use.“

    Sujit Singh, Managing Director, Kaizen Analytix

  • SquareShift
  • SquareShift provides Amazon OpenSearch Service consulting, implementation, and support services.

    “At SquareShift, we pride ourselves in building scalable and cost-effective cloud solutions for our customers. We are excited to support our customers with the new serverless option in Amazon OpenSearch Service. We have customers where search traffic sometimes bursts from low hundreds to millions of user queries per minute during specific events. The new serverless option will help our customers meet unpredictable traffic peaks without compromising performance because Amazon OpenSearch Serverless will seamlessly scale resources to match our workload demands.”

    Aananth Solaiyappan, CEO,

  • Mission Cloud
  • Mission Cloud Services accelerates enterprise cloud transformation by delivering a differentiated suite of agile cloud-managed services and consulting.

    Mission Cloud
    “At Mission Cloud, we believe that the cloud is the greatest business transformation tool of our time, capable of turning an unrealistic or impractical goal into an achievable reality. OpenSearch is critical for a variety of use cases with customers utilizing it for external and internal products. The new serverless option in Amazon OpenSearch Service will help us build solutions for our customers that enable them to support peak traffic without large fixed investment, and without having to think about managing the infrastructure.”

    Ryan Ries, Practice Lead, Data Science & Engineering, Mission Cloud



Introduction to Amazon OpenSearch Serverless

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Get hands on with Amazon OpenSearch Serverless

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Log analytics the easy way with Amazon OpenSearch Serverless

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re:Invent 2022: Provision and scale OpenSearch resources with serverless

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Demo: Searching with Amazon OpenSearch Serverless

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Demo: Log analytics with Amazon OpenSearch Service

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What is a vector database?

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Q: What is Amazon OpenSearch Serverless?
Amazon OpenSearch Serverless is a new serverless option for OpenSearch Service. OpenSearch Serverless provides a streamlined experience that removes the need for you to provision, configure, and tune clusters. The benefits of OpenSearch Serverless are as follows:

  • Automatic provisioning and scaling to provide consistently fast data ingestion rates and millisecond response times during changing usage patterns and application demand.
  • Support for production workloads with redundancy for AZ outages and infrastructure failures.
  • Same data durability as Amazon S3.
  • Pay only for the resources consumed by your workload

Q: How does OpenSearch Serverless relate to the OpenSearch project?
The OpenSearch Serverless core components are powered by the open-source OpenSearch project that includes a search engine, OpenSearch, and a visualization interface, OpenSearch Dashboards.

Q: When should I choose managed clusters instead of the serverless option?
OpenSearch Serverless helps you run various log analytics and search workloads. You might, however, prefer to use the OpenSearch Service managed clusters when you need tight control over cluster configuration or specific customizations. With managed clusters, you can choose your preferred instances and have more control of configuration such as data-sharding strategy. This might be critical for use cases that fall outside the typical patterns supported by OpenSearch Serverless. Also, OpenSearch Serverless currently does not support advanced features or plugins such as alerting, anomaly detection, or kNN. You can use the managed clusters for these features until OpenSearch Serverless adds support for them.

Q: How do I get started with OpenSearch Serverless?
To get started, select the OpenSearch Serverless option under Amazon OpenSearch Service and create new collections, a logical grouping of indexes that work together to support a workload. You can use the command line interface (CLI), AWS SDK, or the AWS Management Console to create collections. OpenSearch Serverless supports the same ingest and query APIs as the OpenSearch open-source suite. So you can continue using your existing clients and streaming ingestion pipelines such as Amazon Kinesis Data Firehose, Kafka, Logstash, Fluent Bit, and Fluentd. When your data is in OpenSearch Serverless, you can interactively analyze and visualize your data using the serverless OpenSearch Dashboards.

Q: How does OpenSearch Serverless work with other AWS services?
OpenSearch Serverless integrates seamlessly with AWS KMS, IAM, AWS billing, CloudWatch, CloudFormation, and CloudTrail.

Q: Which security features does OpenSearch Serverless support?
OpenSearch Serverless is an enhanced security feature by default. All data is encrypted at rest with a collection-level option for you to use either a service managed key or assign your own key through AWS KMS. Access to the collections is controlled through IAM, VPC security group, and SAML 2.0. OpenSearch Serverless supports hierarchical data access policies where you can configure policies at the account, collection, and index levels. You can also configure role-based access control for your collections and indexes.

Q: When does OpenSearch Serverless scale up, and when does it scale down?
When the system resources such as CPU, memory, and disk limits in the ingestion or search nodes are breached or it notices hot shards processing large amounts of read or write requests, OpenSearch Serverless horizontally scales out nodes in response to increased workload demand. Similarly, when the resource utilization falls below a certain threshold, OpenSearch Serverless will automatically and gradually scale in the resources without impacting the performance

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