awsai mlPractitioner

Unlocking AI Potential with Amazon OpenSearch Serverless

5 min read AWS BlogMay 28, 2026Reviewed for accuracy

Practitioner — Hands-on experience recommended

In the rapidly evolving landscape of AI applications, the need for scalable, efficient search capabilities is paramount. Amazon OpenSearch Serverless addresses this need by providing a fully managed search and vector engine specifically designed for building AI agents. This service allows you to focus on developing your applications without worrying about the underlying infrastructure.

The next generation of OpenSearch Serverless is built to scale dynamically, handling requests from zero to thousands per second and back to zero when idle. This elasticity translates to up to 60% cost savings compared to traditional OpenSearch Service clusters that require provisioning for peak capacity. You can create resources in seconds and enjoy scaling capacity up to 20 times faster than previous iterations. Key configuration parameters include maximum and minimum indexing and search capacities, measured in OpenSearch Compute Units (OCUs). For instance, you can set the maximum indexing capacity to 10 OCUs and the minimum to 0, allowing for flexible resource management.

In production, you’ll want to take advantage of the collection and collection group features. A collection can be created for search and vector search, while a collection group can contain multiple collections, inheriting generation settings. This setup is crucial for organizing your data efficiently. The next generation of Amazon OpenSearch Serverless is generally available today, making it a timely option for developers looking to enhance their AI applications with robust search capabilities.

Key takeaways

→Leverage OpenSearch Serverless for scalable AI applications with dynamic resource management.
→Utilize OpenSearch Compute Units (OCUs) to optimize indexing and search capacities.
→Create collection groups to efficiently manage multiple collections and their settings.

Why it matters

This service significantly reduces operational overhead and costs, allowing teams to focus on building AI capabilities rather than managing infrastructure. The ability to scale rapidly is crucial for applications that experience variable workloads.

Code examples

Bash

1aws opensearchserverless create-collection-group \
2    --name channy-nextgen-group \
3    --standby-replicas ENABLED \
4    --generation NEXTGEN \
5    --description "My NextGen collection group" \
6    --capacity-limits '{\
7        "maxIndexingCapacityInOCU": 10,\
8        "maxSearchCapacityInOCU": 10,\
9        "minIndexingCapacityInOCU": 0,\
10        "minSearchCapacityInOCU": 0\
11    }' \
12    --region "us-east-1"

Bash

1aws opensearchserverless create-collection \
2    --name channy-nextgen-collection \
3    --type SEARCH \
4    --collection-group-name channy-nextgen-group \
5    --standby-replicas ENABLED \
6    --description "My collection in NextGen group" \
7    --region "us-east-1"