Demonstrates automated Bedrock batch inference triggered by S3 file uploads, orchestrated via EventBridge rules. Implemented using AWS CDK.
This pattern creates an S3 bucket to store the input and output of the batch inference job.
It also creates an EventBridge rule that is triggered when a batch inference input file is uploaded.
When the EventBridge rule is triggered, it uses an AWS-managed Lambda function (created automatically by the AwsApi target) to call the Bedrock createModelInvocationJob API.
This Lambda function creates a new Bedrock batch inference job with the specified model and the uploaded input file.
The output of the batch inference job is stored in the same S3 bucket.
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Clone repo
git clone https://github.com/aws-samples/serverless-patterns/cd serverless-patterns/s3-bedrock-batch-inference-cdkDeploy
python3 -m venv .source ./bin/activatepip3 install -r requirements.txtexport AWS_REGION=us-west-2cdk deploy --parameters ModelARN=<ARN of the model>Testing
Upload the sample input file:
aws s3 cp model_input/input.jsonl s3://{S3 bucket name}/input/Check batch inference job status:
aws bedrock list-model-invocation-jobs | jq '.invocationJobSummaries[] | {jobArn, status, submitTime}'Once completed (30+ minutes), check results in S3 bucket under 'output' prefix
Cleanup
Empty the S3 bucket:
aws s3 rm s3://{S3 bucket name} --recursiveDelete the stack:
cdk destroyCreated by:
