To integrate Amazon Bedrock with AWS Step Functions and EventBridge for AI-driven workflows, you can use AWS Lambda as a bridge between services. Bedrock provides API access to foundation models, which you can invoke via Lambda functions. Step Functions then orchestrates the workflow by chaining Lambda calls, data processing, and error handling. EventBridge acts as the event bus to trigger workflows based on external events (e.g., file uploads to S3). This setup lets you automate multi-step processes, such as processing user inputs with AI, storing results, or triggering downstream actions.
For example, imagine a document-processing workflow:
- A Step Function state machine starts when a file is uploaded to an S3 bucket (detected via EventBridge).
- A Lambda function calls Bedrock’s API to summarize the document.
- Another Lambda function saves the summary to DynamoDB. Step Functions handles retries if Bedrock’s API returns throttling errors, and EventBridge can notify downstream services (e.g., SNS for email alerts) when the workflow completes. You define the workflow logic in Step Functions’ Amazon States Language (ASL), specifying dependencies between Lambda invocations and Bedrock calls. Use IAM roles to grant Step Functions and Lambda permissions to access Bedrock and other services.
To connect EventBridge, create a rule that matches specific events (e.g., s3:ObjectCreated). The rule triggers the Step Function via its ARN or through a Lambda function that validates input data. For time-based workflows, use EventBridge Schedules to invoke Bedrock periodically. For monitoring, leverage CloudWatch Metrics and Logs to track API latency, errors, and workflow execution times. If you need low-latency responses, use Step Functions’ Express Workflows for faster execution. Always encrypt data in transit (TLS for Bedrock APIs) and at rest (KMS for S3/DynamoDB) to meet security requirements. Test workflows locally using the AWS SAM CLI or Step Functions’ visual editor to catch logic errors early.