Deploy a serverless semantic search API with zero baseline compute cost using Lambda and OpenSearch Serverless NextGen (scale-to-zero).
This pattern deploys an Amazon API Gateway REST API backed by three AWS Lambda functions that perform semantic, lexical, and hybrid search against an Amazon OpenSearch Serverless NextGen collection.
Amazon OpenSearch Serverless NextGen scales compute to zero when idle and provisions in approximately 10 seconds when traffic arrives. Combined with Lambda's own scale-to-zero, the entire stack incurs zero compute cost when not in use.
Embeddings are generated server-side by an OpenSearch ML model connected to Amazon Bedrock (Amazon Titan Text Embeddings V2) — Lambda functions send and receive plain text only.
A hybrid search pipeline applies min-max score normalization to combine BM25 (lexical) and k-NN (semantic) results with configurable weights.
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Clone repo
git clone https://github.com/aws-samples/serverless-patterns/cd serverless-patterns/apigw-lambda-opensearch-serverless-nextgenDeploy
sam buildsam deploy --guidedTesting
See the GitHub repo for detailed testing instructions.
Cleanup
Delete the stack:
sam delete --stack-name STACK_NAME.Created by:
