Updated workshop Oct. 2022

assets/deploy-model-dev.yml

@@ -23,7 +23,7 @@ Resources:
   Model:
     Type: "AWS::SageMaker::Model"
     Properties:
-      ModelName: !Sub ${ModelName}-dev-${TrainJobId}
+      ModelName: !Sub ${ModelName}-dev
       PrimaryContainer:
         Image: !Ref ImageRepoUri
         ModelDataUrl: !Sub s3://sagemaker-${AWS::Region}-${AWS::AccountId}/${ModelName}/${ModelName}-${TrainJobId}/output/model.tar.gz
@@ -38,11 +38,11 @@ Resources:
           InstanceType: ml.t2.medium
           ModelName: !GetAtt Model.ModelName
           VariantName: !Sub ${ModelVariant}-${ModelName}
-      EndpointConfigName: !Sub ${ModelName}-dec-${TrainJobId}
+      EndpointConfigName: !Sub ${ModelName}-dec
       KmsKeyId: !Ref KmsKeyId
 
   Endpoint:
     Type: "AWS::SageMaker::Endpoint"
     Properties:
-      EndpointName: !Sub ${ModelName}-dev-${TrainJobId}
-      EndpointConfigName: !GetAtt EndpointConfig.EndpointConfigName
+      EndpointName: !Sub ${ModelName}-dev
+      EndpointConfigName: !GetAtt EndpointConfig.EndpointConfigName

assets/deploy-model-prd.yml

@@ -1,5 +1,6 @@
 Transform: AWS::Serverless-2016-10-31
-Description: Deploy the production Amazon SageMaker Endpoint with Autoscaling, Model Monitoring Schedule and API Gateway Lambda.
+Description: Deploy the production Amazon SageMaker Endpoint with Autoscaling, Model 
+  Monitoring Schedule and API Gateway Lambda.
 Parameters:
   ImageRepoUri:
     Type: String
@@ -23,7 +24,8 @@ Parameters:
     Type: Number
     Description: The metric alarm threshold
   KmsKeyId:
-    Description: AWS KMS key ID used to encrypt data at rest on the ML storage volume attached to endpoint config and S3 data capture.
+    Description: AWS KMS key ID used to encrypt data at rest on the ML storage volume 
+      attached to endpoint config and S3 data capture.
     Type: String
   NotificationArn:
     Description: The arn for notification topic
@@ -81,7 +83,7 @@ Resources:
   Model:
     Type: "AWS::SageMaker::Model"
     Properties:
-      ModelName: !Sub ${ModelName}-prd-${TrainJobId}
+      ModelName: !Sub ${ModelName}-prd
       PrimaryContainer:
         Image: !Ref ImageRepoUri
         ModelDataUrl: !Sub s3://sagemaker-${AWS::Region}-${AWS::AccountId}/${ModelName}/${ModelName}-${TrainJobId}/output/model.tar.gz
@@ -109,13 +111,13 @@ Resources:
         EnableCapture: True
         InitialSamplingPercentage: 100
         KmsKeyId: !Ref KmsKeyId
-      EndpointConfigName: !Sub ${ModelName}-pec-${TrainJobId}
+      EndpointConfigName: !Sub ${ModelName}-pec
       KmsKeyId: !Ref KmsKeyId
 
   Endpoint:
     Type: "AWS::SageMaker::Endpoint"
     Properties:
-      EndpointName: !Sub ${ModelName}-prd-${TrainJobId}
+      EndpointName: !Sub ${ModelName}-prd
       EndpointConfigName: !GetAtt EndpointConfig.EndpointConfigName
 
   ApiFunction:
@@ -189,7 +191,7 @@ Resources:
   PreTrafficLambdaFunction:
     Type: AWS::Serverless::Function
     Properties:
-      FunctionName: !Sub "CodeDeployHook_mlops-${ModelName}-PreTrafficLambdaFunction"
+      FunctionName: !Sub "${ModelName}-PreTrafficLambdaFunction"
       CodeUri: ../api
       Handler: pre_traffic_hook.lambda_handler
       Runtime: python3.7
@@ -221,7 +223,7 @@ Resources:
   PostTrafficLambdaFunction:
     Type: AWS::Serverless::Function
     Properties:
-      FunctionName: !Sub "CodeDeployHook_mlops-${ModelName}-PostTrafficLambdaFunction"
+      FunctionName: !Sub "${ModelName}-PostTrafficLambdaFunction"
       CodeUri: ../api
       Handler: post_traffic_hook.lambda_handler
       Runtime: python3.7
@@ -351,7 +353,7 @@ Resources:
     Properties:
       MaxCapacity: 10
       MinCapacity: 2
-      ResourceId: !Sub endpoint/${ModelName}-prd-${TrainJobId}/variant/${ModelVariant}-${ModelName}
+      ResourceId: !Sub endpoint/${ModelName}-prd/variant/${ModelVariant}-${ModelName}
       RoleARN: !Sub arn:aws:iam::${AWS::AccountId}:role/MLOps
       ScalableDimension: sagemaker:variant:DesiredInstanceCount
       ServiceNamespace: sagemaker
@@ -362,7 +364,7 @@ Resources:
     Properties:
       PolicyName: SageMakerVariantInvocationsPerInstance
       PolicyType: TargetTrackingScaling
-      ResourceId: !Sub endpoint/${ModelName}-prd-${TrainJobId}/variant/${ModelVariant}-${ModelName}
+      ResourceId: !Sub endpoint/${ModelName}-prd/variant/${ModelVariant}-${ModelName}
       ScalableDimension: sagemaker:variant:DesiredInstanceCount
       ServiceNamespace: sagemaker
       TargetTrackingScalingPolicyConfiguration:

pipeline.yml

@@ -183,7 +183,7 @@ Resources:
       RepositoryDescription: !Sub SageMaker safe deployment pipeline for project ${SageMakerProjectName} with id ${SageMakerProjectId}, prefix ${ProjectPrefix} and model name ${ModelName}
       Code:
         S3:
-          Bucket: "S3_BUCKET_NAME"
+          Bucket: !Sub "${AWS::AccountId}-pipelineyaml-bucket"
           Key: "project.zip"
         BranchName: !Ref GitBranch
 
@@ -966,4 +966,4 @@ Outputs:
   KMSKey:
     Value: !Ref KMSKey
   NotificationTopic:
-    Value: !Ref NotificationTopic
+    Value: !Ref NotificationTopic

pipeline_bucket.yml

@@ -0,0 +1,6 @@
+Resources:
+  S3Bucket:
+    Type: 'AWS::S3::Bucket'
+    DeletionPolicy: Retain
+    Properties:
+      BucketName: !Sub "${AWS::AccountId}-pipelineyaml-bucket"