New serverless pattern - eventbridge-scheduler-ai-agent-trigger

eventbridge-scheduler-ai-agent-trigger/README.md

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+# Amazon EventBridge Scheduler to Amazon Bedrock AI Agent
+
+This pattern demonstrates how to trigger an Amazon Bedrock AI Agent on a recurring schedule using Amazon EventBridge Scheduler. An orchestrator Lambda function, invoked by the scheduler, sends a task payload to the Bedrock Agent, which processes the input, generates an execution summary, and persists the result to a DynamoDB table via an action group Lambda.
+
+Learn more about this pattern at Serverless Land Patterns: https://serverlessland.com/patterns/eventbridge-scheduler-ai-agent-trigger
+
+Important: this application uses various AWS services and there are costs associated with these services after the Free Tier usage - please see the [AWS Pricing page](https://aws.amazon.com/pricing/) for details. You are responsible for any AWS costs incurred. No warranty is implied in this example.
+
+## Requirements
+
+* [Create an AWS account](https://portal.aws.amazon.com/gp/aws/developer/registration/index.html) if you do not already have one and log in. The IAM user that you use must have sufficient permissions to make necessary AWS service calls and manage AWS resources.
+* [AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/install-cliv2.html) installed and configured
+* [Git Installed](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
+* [Terraform](https://www.terraform.io/downloads.html) >= 1.0 installed
+
+## Architecture
+
+![Architecture Diagram](Architecture.png)
+
+The pattern deploys the following resources:
+
+1. **Amazon EventBridge Scheduler** – Triggers the orchestrator Lambda on a recurring schedule (default: `rate(1 hour)`).
+2. **Orchestrator Lambda** (Python 3.14) – Receives the scheduler event and invokes the Bedrock Agent with a task payload.
+3. **Amazon Bedrock Agent** – Processes the task payload, generates an execution summary using a foundation model (default: Claude 3 Haiku), and calls the action group.
+4. **Action Group Lambda** (Python 3.14) – Persists execution records to DynamoDB.
+5. **Amazon DynamoDB Table** – Stores task execution records.
+6. **Amazon SQS Dead-Letter Queue** – Captures failed scheduler invocations after retries are exhausted.
+
+## Deployment Instructions
+
+1. Clone the repository:
+    ```
+    git clone https://github.com/aws-samples/serverless-patterns
+    ```
+1. Change directory to the pattern directory:
+    ```
+    cd serverless-patterns/eventbridge-scheduler-ai-agent-trigger
+    ```
+1. Initialize Terraform:
+    ```
+    terraform init
+    ```
+1. Deploy the infrastructure:
+    ```
+    terraform apply -auto-approve
+    ```
+    During the prompts, provide values for:
+    * `aws_region` – AWS region (e.g. `us-east-1`)
+    * `prefix` – Unique prefix for all resource names
+
+1. Note the outputs from the deployment. These contain the resource names and ARNs used for testing.
+
+## How it works
+
+1. EventBridge Scheduler fires on the configured schedule and invokes the orchestrator Lambda with a JSON payload containing `taskType`, `scheduleName`, and `scheduledTime`.
+2. The orchestrator Lambda calls `bedrock-agent-runtime:InvokeAgent` with the payload, targeting the agent alias.
+3. The Bedrock Agent parses the payload, generates an executive summary using the foundation model, and calls the `recordTaskExecution` action group.
+4. The action group Lambda writes the execution record (task ID, type, scheduled time, summary, and recorded timestamp) to the DynamoDB table.
+5. If the scheduler invocation fails after 3 retries, the event is sent to the SQS dead-letter queue.
+
+## Testing
+
+1. Invoke the orchestrator Lambda manually:
+    ```
+    aws lambda invoke \
+      --function-name <prefix>-agent-orchestrator \
+      --payload '{"taskType":"scheduled-report","scheduleName":"manual-test","scheduledTime":"2026-03-13T10:00:00Z"}' \
+      --cli-binary-format raw-in-base64-out \
+      output.json
+    ```
+2. Check the DynamoDB table for the new execution record:
+    ```
+    aws dynamodb scan --table-name <prefix>-agent-task-executions
+    ```
+
+## Cleanup
+
+1. Destroy the stack:
+    ```
+    terraform destroy -auto-approve
+    ```
+1. Confirm all resources have been removed:
+    ```
+    terraform show
+    ```
+----
+Copyright 2026 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+
+SPDX-License-Identifier: MIT-0

eventbridge-scheduler-ai-agent-trigger/api_schema.json

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+{
+  "openapi": "3.0.0",
+  "info": {
+    "title": "Scheduled Task Execution API",
+    "version": "1.0.0",
+    "description": "Actions for recording and retrieving scheduled AI agent task executions"
+  },
+  "paths": {
+    "/record-task-execution": {
+      "post": {
+        "operationId": "recordTaskExecution",
+        "summary": "Record a scheduled task execution in the tracking database",
+        "description": "Persists a task execution record with task ID, type, timestamp, and an AI-generated summary to DynamoDB",
+        "requestBody": {
+          "required": true,
+          "content": {
+            "application/json": {
+              "schema": {
+                "type": "object",
+                "required": [
+                  "taskId",
+                  "taskType",
+                  "scheduledTime",
+                  "executionSummary"
+                ],
+                "properties": {
+                  "taskId": {
+                    "type": "string",
+                    "description": "Unique identifier for this task execution — combine scheduleName and scheduledTime"
+                  },
+                  "taskType": {
+                    "type": "string",
+                    "description": "The category of the scheduled task (e.g. scheduled-report)"
+                  },
+                  "scheduledTime": {
+                    "type": "string",
+                    "description": "ISO 8601 UTC timestamp when the task was scheduled to run"
+                  },
+                  "executionSummary": {
+                    "type": "string",
+                    "description": "AI-generated summary describing the task execution and its outcome"
+                  }
+                }
+              }
+            }
+          }
+        },
+        "responses": {
+          "200": {
+            "description": "Execution recorded successfully",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "type": "object",
+                  "properties": {
+                    "message": { "type": "string" },
+                    "taskId": { "type": "string" },
+                    "recordedAt": { "type": "string" }
+                  }
+                }
+              }
+            }
+          }
+        }
+      }
+    },
+    "/get-last-execution": {
+      "get": {
+        "operationId": "getLastExecution",
+        "summary": "Get the most recent task execution for a given task type",
+        "description": "Retrieves the latest execution record from DynamoDB filtered by task type",
+        "parameters": [
+          {
+            "name": "taskType",
+            "in": "query",
+            "required": true,
+            "schema": { "type": "string" },
+            "description": "Task type to look up (e.g. scheduled-report)"
+          }
+        ],
+        "responses": {
+          "200": {
+            "description": "Last execution found",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "type": "object",
+                  "properties": {
+                    "taskId": { "type": "string" },
+                    "taskType": { "type": "string" },
+                    "scheduledTime": { "type": "string" },
+                    "executionSummary": { "type": "string" },
+                    "recordedAt": { "type": "string" }
+                  }
+                }
+              }
+            }
+          },
+          "404": {
+            "description": "No executions found for the given task type"
+          }
+        }
+      }
+    }
+  }
+}

eventbridge-scheduler-ai-agent-trigger/example-pattern.json

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+{
+  "title": "Trigger AI Agent with Amazon EventBridge Scheduler",
+  "description": "Create a EventBridge scheduler which invokes a Bedrock Agent upon triggering.",
+  "language": "Python",
+  "level": "300",
+  "framework": "Terraform",
+  "introBox": {
+    "headline": "How it works",
+    "text": [
+      "This pattern demonstrates how to trigger an Amazon Bedrock AI Agent on a recurring schedule using Amazon EventBridge Scheduler. An orchestrator AWS Lambda function, invoked by the scheduler, sends a task payload to the Bedrock Agent, which processes the input, generates an execution summary, and persists the result to a DynamoDB table via an action group Lambda. The pattern includes retry logic, a dead-letter queue for failed invocations, and least-privilege IAM policies scoped to the agent alias ARN."
+    ]
+  },
+  "gitHub": {
+    "template": {
+      "repoURL": "https://github.com/aws-samples/serverless-patterns/tree/main/eventbridge-scheduler-ai-agent-trigger",
+      "templateURL": "serverless-patterns/eventbridge-scheduler-ai-agent-trigger",
+      "projectFolder": "eventbridge-scheduler-ai-agent-trigger",
+      "templateFile": "main.tf"
+    }
+  },
+  "resources": {
+    "bullets": [
+      {
+        "text": "Invoke a Lambda function on a schedule",
+        "link": "https://docs.aws.amazon.com/lambda/latest/dg/with-eventbridge-scheduler.html"
+      },
+      {
+        "text": "Allow users to view information about and invoke an agent",
+        "link": "https://docs.aws.amazon.com/bedrock/latest/userguide/security_iam_id-based-policy-examples-agent.html#security_iam_id-based-policy-examples-perform-actions-agent"
+      }
+    ]
+  },
+  "deploy": {
+    "text": [
+      "terraform init",
+      "terraform apply"
+    ]
+  },
+  "testing": {
+    "text": [
+      "See the GitHub repo for detailed testing instructions."
+    ]
+  },
+  "cleanup": {
+    "text": [
+      "terraform destroy",
+      "terraform show"
+    ]
+  },
+  "authors": [
+    {
+      "name": "Rajil Paloth",
+      "image": "https://i.ibb.co/r2TsqGf6/Passport-size.jpg",
+      "bio": "ProServe Delivery Consultant at AWS",
+      "linkedin": "paloth"
+    }
+  ]
+}