Yes, Amazon Bedrock integrates with other AWS services to support application workflows, enabling developers to build end-to-end AI-powered solutions. Bedrock’s API-driven design allows it to work seamlessly with compute services like AWS Lambda, storage services like Amazon S3, and orchestration tools like Step Functions. This integration is achieved through standard AWS SDKs, APIs, and event-driven architectures, giving developers flexibility in designing workflows that combine generative AI with existing AWS resources.
For example, you can invoke Bedrock’s foundation models from an AWS Lambda function, process the output, and store results in Amazon S3. A common use case involves using Lambda to handle user input (e.g., a prompt submitted via an API Gateway), send it to Bedrock for text generation, and save the response to an S3 bucket for auditing or later analysis. Bedrock’s responses can also trigger downstream actions, such as sending notifications via Amazon SNS or updating a DynamoDB table. For complex workflows, Step Functions can coordinate multiple steps—like preprocessing data with AWS Glue, invoking Bedrock, and logging results to CloudWatch—while maintaining state and error handling.
Additionally, Bedrock supports security and monitoring integrations. IAM roles govern access to Bedrock APIs, ensuring least-privilege permissions when connecting to other services. Inputs and outputs can be encrypted using AWS KMS, and CloudTrail logs API activity for compliance. Developers can also stream Bedrock usage metrics to CloudWatch to monitor costs or performance. While Bedrock doesn’t provide direct, out-of-the-box connectors (e.g., a dedicated S3 export button), its programmatic API allows straightforward integration with any AWS service using standard SDKs, making it adaptable to existing infrastructure.