使用Serverless构建的Step Function状态机陷入无限重试循环

Question

我正在查看我的serverless.yml上的实现是否错误。据我所知，我的Retry:逻辑已被忽略。

状态机在第二个功能（callTextract，CallTextract状态）上失败，并且状态机在失败时立即再次执行。

由于调用Textract的次数过多而导致另一个错误，从而导致另一个失败，并且循环每秒持续数十次。阻止疯狂的唯一方法是运行sls remove。

这是我的serverless.yml：

service: textract-service

provider:
  name: aws
  runtime: python3.7
  timeout: 10
  region: us-east-1
  cfLogs: true
  environment:
    STATE_MACHINE_ARN: ${self:resources.Outputs.TextractStepFunctions.Value}
  iamRoleStatements:
    - Effect: "Allow"
      Action:
        - "s3:PutObject"
        - "states:*"
      Resource:
        Fn::Join:
          - ""
          - - "the-chumiest-bucketARN or *"
            - ${self:resources.Outputs.TextractStepFunctions.Value}

plugins:
  - serverless-plugin-existing-s3
  - serverless-step-functions
  - serverless-pseudo-parameters
  - serverless-plugin-existing-s3 
layers:
  boto3Layer:
    package:
      artifact: boto3_layer.zip
    allowedAccounts:
      - "*"

functions:
  startTextractStateMachine:
    handler: src/start_textract_state_machine.lambda_handler
    role: roleArn
    layers:
      - {Ref: Boto3LayerLambdaLayer}
    events:
      - existingS3:
          bucket: the-chumiest-bucket
          events:
            - s3:ObjectCreated:*
          rules:
            - prefix: clients/client1/input/
            - suffix: .pdf
  callTextract:
    handler: src/call_textract.lambda_handler
    role: roleArn

    layers:
      - {Ref: Boto3LayerLambdaLayer}
  getTextractOutput:
    handler: src/get_textract_output.lambda_handler
    role: roleArn

    layers:
      - {Ref: Boto3LayerLambdaLayer}
  parseTextractOutput:
    handler: src/parse_textract_output.lambda_handler
    role: roleArn

    layers:
      - {Ref: Boto3LayerLambdaLayer}

stepFunctions:
  stateMachines:
    textractStepFunc:
      name: TextractStepFunctions
      definition:
        Comment: A state machine for the Textract OCR process.
        StartAt: StartTextractStateMachine
        States:
          StartTextractStateMachine:
            Type: Task
            Resource: "arn:aws:lambda:#{AWS::Region}:#{AWS::AccountId}:function:#{AWS::StackName}-startTextractStateMachine"
            Next: CallTextract
            Retry:
              - ErrorEquals:
                - States.ALL
                IntervalSeconds: 1
                MaxAttempts: 1
                BackoffRate: 2
          CallTextract:
            Type: Task
            Resource: "arn:aws:lambda:#{AWS::Region}:#{AWS::AccountId}:function:#{AWS::StackName}-callTextract"
            Next: GetTextractOutput
            Retry:
              - ErrorEquals:
                - States.ALL
                IntervalSeconds: 1
                MaxAttempts: 1
                BackoffRate: 2
          GetTextractOutput:
            Type: Task
            Resource: "arn:aws:lambda:#{AWS::Region}:#{AWS::AccountId}:function:#{AWS::StackName}-getTextractOutput"
            Next: ParseTextractOutput
            Retry:
              - ErrorEquals:
                - States.ALL
                IntervalSeconds: 1
                MaxAttempts: 1
                BackoffRate: 2
          ParseTextractOutput:
            Type: Task
            Resource: "arn:aws:lambda:#{AWS::Region}:#{AWS::AccountId}:function:#{AWS::StackName}-parseTextractOutput"
            Retry:
              - ErrorEquals:
                - States.ALL
                IntervalSeconds: 1
                MaxAttempts: 1
                BackoffRate: 2
            End: true

resources:
  Outputs:
    TextractStepFunctions:
      Description: The ARN of the state machine
      Value:
        Ref: TextractStepFunctions

我以前已经使用GUI控制台在Step Functions机器上实现了相同的代码，没有任何问题，因此问题必须在无服务器实现内。