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Amazon Bedrock batch inference is a cost-effective solution for high-volume, time-insensitive workloads. However, managing input formatting and job quotas, orchestrating concurrent executions, and handling postprocessing tasks can be challenging. This post introduces a flexible and scalable solution that simplifies the batch inference workflow using AWS Step Functions, AWS CDK, and Amazon S3. The solution handles preprocessing, parallel batch job execution, and postprocessing. It uses a SimpleCoT dataset to demonstrate the use case and covers key architectural considerations for batch processing workflows.

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