diff --git a/sample/sagemaker/2017-07-24/service-2.json b/sample/sagemaker/2017-07-24/service-2.json
index 9b5c96fb..ceebcbf2 100644
--- a/sample/sagemaker/2017-07-24/service-2.json
+++ b/sample/sagemaker/2017-07-24/service-2.json
@@ -4435,7 +4435,7 @@
       "type":"string",
       "max":2048,
       "min":1,
-      "pattern":"^arn:aws(-cn|-us-gov)?:sagemaker:[a-z0-9\\-]{9,16}:[0-9]{12}:algorithm/[\\S]{1,2048}$"
+      "pattern":"^arn:aws(-cn|-us-gov|-iso-f)?:sagemaker:[a-z0-9\\-]{9,16}:[0-9]{12}:algorithm/[\\S]{1,2048}$"
     },
     "AlgorithmImage":{
       "type":"string",
@@ -6077,6 +6077,14 @@
         "Descending"
       ]
     },
+    "AutoMountHomeEFS":{
+      "type":"string",
+      "enum":[
+        "Enabled",
+        "Disabled",
+        "DefaultAsDomain"
+      ]
+    },
     "AutoParameter":{
       "type":"structure",
       "required":[
@@ -7306,7 +7314,7 @@
     "ClusterInstanceGroupSpecifications":{
       "type":"list",
       "member":{"shape":"ClusterInstanceGroupSpecification"},
-      "max":20,
+      "max":100,
       "min":1
     },
     "ClusterInstancePlacement":{
@@ -7646,7 +7654,7 @@
       "type":"string",
       "max":2048,
       "min":1,
-      "pattern":"^arn:aws(-cn|-us-gov)?:sagemaker:[a-z0-9\\-]{9,16}:[0-9]{12}:code-repository/[\\S]{1,2048}$"
+      "pattern":"^arn:aws(-cn|-us-gov|-iso-f)?:sagemaker:[a-z0-9\\-]{9,16}:[0-9]{12}:code-repository/[\\S]{1,2048}$"
     },
     "CodeRepositoryContains":{
       "type":"string",
@@ -8018,7 +8026,7 @@
         },
         "Environment":{
           "shape":"EnvironmentMap",
-          "documentation":"<p>The environment variables to set in the Docker container.</p> <p>The maximum length of each key and value in the <code>Environment</code> map is 1024 bytes. The maximum length of all keys and values in the map, combined, is 32 KB. If you pass multiple containers to a <code>CreateModel</code> request, then the maximum length of all of their maps, combined, is also 32 KB.</p>"
+          "documentation":"<p>The environment variables to set in the Docker container. Don't include any sensitive data in your environment variables.</p> <p>The maximum length of each key and value in the <code>Environment</code> map is 1024 bytes. The maximum length of all keys and values in the map, combined, is 32 KB. If you pass multiple containers to a <code>CreateModel</code> request, then the maximum length of all of their maps, combined, is also 32 KB.</p>"
         },
         "ModelPackageName":{
           "shape":"VersionedArnOrName",
@@ -10871,7 +10879,7 @@
         },
         "Environment":{
           "shape":"TransformEnvironmentMap",
-          "documentation":"<p>The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.</p>"
+          "documentation":"<p>The environment variables to set in the Docker container. Don't include any sensitive data in your environment variables. We support up to 16 key and values entries in the map.</p>"
         },
         "TransformInput":{
           "shape":"TransformInput",
@@ -20918,7 +20926,7 @@
     "ImageArn":{
       "type":"string",
       "max":256,
-      "pattern":"^arn:aws(-[\\w]+)*:sagemaker:.+:[0-9]{12}:image/[a-z0-9]([-.]?[a-z0-9])*$"
+      "pattern":"^arn:aws(-[\\w]+)*:sagemaker:.+:[0-9]{12}:image/[a-zA-Z0-9]([-.]?[a-zA-Z0-9])*$"
     },
     "ImageBaseImage":{
       "type":"string",
@@ -28158,7 +28166,7 @@
       "type":"string",
       "max":2048,
       "min":1,
-      "pattern":"^arn:aws(-cn|-us-gov)?:sagemaker:[a-z0-9\\-]{9,16}:[0-9]{12}:model-package/[\\S]{1,2048}$"
+      "pattern":"^arn:aws(-cn|-us-gov|-iso-f)?:sagemaker:[a-z0-9\\-]{9,16}:[0-9]{12}:model-package/[\\S]{1,2048}$"
     },
     "ModelPackageArnList":{
       "type":"list",
@@ -28268,7 +28276,7 @@
       "type":"string",
       "max":2048,
       "min":1,
-      "pattern":"^arn:aws(-cn|-us-gov)?:sagemaker:[a-z0-9\\-]{9,16}:[0-9]{12}:model-package-group/[\\S]{1,2048}$"
+      "pattern":"^arn:aws(-cn|-us-gov|-iso-f)?:sagemaker:[a-z0-9\\-]{9,16}:[0-9]{12}:model-package-group/[\\S]{1,2048}$"
     },
     "ModelPackageGroupSortBy":{
       "type":"string",
@@ -32283,7 +32291,7 @@
       "type":"string",
       "max":2048,
       "min":1,
-      "pattern":"^arn:aws(-cn|-us-gov)?:sagemaker:[a-z0-9\\-]{9,16}:[0-9]{12}:project/[\\S]{1,2048}$"
+      "pattern":"^arn:aws(-cn|-us-gov|-iso-f)?:sagemaker:[a-z0-9\\-]{9,16}:[0-9]{12}:project/[\\S]{1,2048}$"
     },
     "ProjectEntityName":{
       "type":"string",
@@ -35307,7 +35315,7 @@
     "StudioLifecycleConfigArn":{
       "type":"string",
       "max":256,
-      "pattern":"arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:studio-lifecycle-config/.*"
+      "pattern":"^(arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:studio-lifecycle-config/.*|None)$"
     },
     "StudioLifecycleConfigContent":{
       "type":"string",
@@ -39092,6 +39100,10 @@
         "StudioWebPortalSettings":{
           "shape":"StudioWebPortalSettings",
           "documentation":"<p>Studio settings. If these settings are applied on a user level, they take priority over the settings applied on a domain level.</p>"
+        },
+        "AutoMountHomeEFS":{
+          "shape":"AutoMountHomeEFS",
+          "documentation":"<p>Indicates whether auto-mounting of an EFS volume is supported for the user profile. The <code>DefaultAsDomain</code> value is only supported for user profiles. Do not use the <code>DefaultAsDomain</code> value when setting this parameter for a domain.</p>"
         }
       },
       "documentation":"<p>A collection of settings that apply to users in a domain. These settings are specified when the <code>CreateUserProfile</code> API is called, and as <code>DefaultUserSettings</code> when the <code>CreateDomain</code> API is called.</p> <p> <code>SecurityGroups</code> is aggregated when specified in both calls. For all other settings in <code>UserSettings</code>, the values specified in <code>CreateUserProfile</code> take precedence over those specified in <code>CreateDomain</code>.</p>"
diff --git a/src/sagemaker_core/main/code_injection/shape_dag.py b/src/sagemaker_core/main/code_injection/shape_dag.py
index 5c324fa8..0a250f6b 100644
--- a/src/sagemaker_core/main/code_injection/shape_dag.py
+++ b/src/sagemaker_core/main/code_injection/shape_dag.py
@@ -14416,6 +14416,7 @@
                 "shape": "StudioWebPortalSettings",
                 "type": "structure",
             },
+            {"name": "AutoMountHomeEFS", "shape": "AutoMountHomeEFS", "type": "string"},
         ],
         "type": "structure",
     },
diff --git a/src/sagemaker_core/main/resources.py b/src/sagemaker_core/main/resources.py
index 759cda84..3d0ac679 100644
--- a/src/sagemaker_core/main/resources.py
+++ b/src/sagemaker_core/main/resources.py
@@ -26434,7 +26434,7 @@ def create(
             model_client_config: Configures the timeout and maximum number of retries for processing a transform job invocation.
             max_payload_in_mb: The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB.  The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify the MaxConcurrentTransforms parameter, the value of (MaxConcurrentTransforms \* MaxPayloadInMB) also cannot exceed 100 MB. For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.
             batch_strategy: Specifies the number of records to include in a mini-batch for an HTTP inference request. A record  is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.  To enable the batch strategy, you must set the SplitType property to Line, RecordIO, or TFRecord. To use only one record when making an HTTP invocation request to a container, set BatchStrategy to SingleRecord and SplitType to Line. To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to MultiRecord and SplitType to Line.
-            environment: The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
+            environment: The environment variables to set in the Docker container. Don't include any sensitive data in your environment variables. We support up to 16 key and values entries in the map.
             data_capture_config: Configuration to control how SageMaker captures inference data.
             data_processing: The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
             tags: (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
diff --git a/src/sagemaker_core/main/shapes.py b/src/sagemaker_core/main/shapes.py
index 876a16d1..cbff1687 100644
--- a/src/sagemaker_core/main/shapes.py
+++ b/src/sagemaker_core/main/shapes.py
@@ -3055,7 +3055,7 @@ class ContainerDefinition(Base):
     model_data_url: The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3 path is required for SageMaker built-in algorithms, but not if you use your own algorithms. For more information on built-in algorithms, see Common Parameters.   The model artifacts must be in an S3 bucket that is in the same region as the model or endpoint you are creating.  If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provide. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.  If you use a built-in algorithm to create a model, SageMaker requires that you provide a S3 path to the model artifacts in ModelDataUrl.
     model_data_source: Specifies the location of ML model data to deploy.  Currently you cannot use ModelDataSource in conjunction with SageMaker batch transform, SageMaker serverless endpoints, SageMaker multi-model endpoints, and SageMaker Marketplace.
     additional_model_data_sources: Data sources that are available to your model in addition to the one that you specify for ModelDataSource when you use the CreateModel action.
-    environment: The environment variables to set in the Docker container. The maximum length of each key and value in the Environment map is 1024 bytes. The maximum length of all keys and values in the map, combined, is 32 KB. If you pass multiple containers to a CreateModel request, then the maximum length of all of their maps, combined, is also 32 KB.
+    environment: The environment variables to set in the Docker container. Don't include any sensitive data in your environment variables. The maximum length of each key and value in the Environment map is 1024 bytes. The maximum length of all keys and values in the map, combined, is 32 KB. If you pass multiple containers to a CreateModel request, then the maximum length of all of their maps, combined, is also 32 KB.
     model_package_name: The name or Amazon Resource Name (ARN) of the model package to use to create the model.
     inference_specification_name: The inference specification name in the model package version.
     multi_model_config: Specifies additional configuration for multi-model endpoints.
@@ -3856,6 +3856,7 @@ class UserSettings(Base):
     custom_posix_user_config: Details about the POSIX identity that is used for file system operations.
     custom_file_system_configs: The settings for assigning a custom file system to a user profile. Permitted users can access this file system in Amazon SageMaker Studio.
     studio_web_portal_settings: Studio settings. If these settings are applied on a user level, they take priority over the settings applied on a domain level.
+    auto_mount_home_efs: Indicates whether auto-mounting of an EFS volume is supported for the user profile. The DefaultAsDomain value is only supported for user profiles. Do not use the DefaultAsDomain value when setting this parameter for a domain.
     """
 
     execution_role: Optional[str] = Unassigned()
@@ -3875,6 +3876,7 @@ class UserSettings(Base):
     custom_posix_user_config: Optional[CustomPosixUserConfig] = Unassigned()
     custom_file_system_configs: Optional[List[CustomFileSystemConfig]] = Unassigned()
     studio_web_portal_settings: Optional[StudioWebPortalSettings] = Unassigned()
+    auto_mount_home_efs: Optional[str] = Unassigned()
 
 
 class RStudioServerProDomainSettings(Base):