要实现Pipelines的EventBridge触发，您需要通过AWS Step Functions的有限状态机来触发AWS SageMaker Pipelines。如果您使用一个不同的触发器来触发Pipelines，比如S3对象被创建，或者为了进行调试而手动触发，则EventBridge可能无法触发Pipelines。

以下是一个示例，在有限状态机中使用Lambda函数作为中间步骤来实现Pipelines触发：

{
  "Comment": "A SageMaker Pipeline triggered by CloudWatch Event Rule",
  "StartAt": "Step1",
  "States": {
    "Step1": {
      "Type": "Task",
      "Resource": "arn:aws:lambda:REGION:ACCOUNT_ID:function:LAMBDA_FUNCTION_NAME",
      "Next": "Step2"
    },
    "Step2": {
      "Type": "Task",
      "Resource": "arn:aws:states:::sagemaker:createPipeline",
      "Parameters": {
        "PipelineDefinition": {
          "Version": 1.0,
          "PipelineParameters": [
            {
              "Name": "InstanceType",
              "Value": "ml.t2.medium"
            }
          ],
          "Steps": [
            {
              "Name": "Step1",
              "Action": {
                "AlgorithmSpecification": {
                  "trainingInputMode": "File",
                  "trainingImage": "IMAGE_URI",
                  "metricDefinitions": [
                    {
                      "Name": "validation:accuracy",
                      "Regex": "validation:accuracy=([0-9\\.]+)"
                    }
                  ]
                },
                "InputDataConfig": [
                  {
                    "DataSource": {
                      "S3DataSource": {
                        "S3DataType": "S3Prefix",
                        "S3Uri": "s3://BUCKET_NAME/INPUT_DATA",
                        "S3DataDistributionType": "FullyReplicated"
                      }
                    },
                    "ChannelName": "train"
                  }
                ],
                "OutputDataConfig": {
                  "S3OutputPath": "s3://BUCKET_NAME/OUTPUT_PREFIX"
                },
                "ResourceConfig": {
                  "InstanceCount": 1,
                  "InstanceType": "ml.t2.medium",
                  "VolumeSizeInGB": 10
                },
                "RoleArn": "ROLE_ARN",
                "StoppingCondition": {
                  "MaxRuntimeInSeconds": 900
                }
              },
              "Type": "Training",
              "Inputs": [
                {
                  "Name": "InputData",
                  "OutputName": "train",
                  "S3Input": {
                    "S3Uri": "s3