Moved SDK include

Author: s-polly

articles/machine-learning/known-issues/application-sharing-policy-not-supported.md

@@ -13,11 +13,11 @@ ms.custom: known-issue
 
 # Known issue  - The ApplicationSharingPolicy property isn't supported for compute instances
 
+[!INCLUDE [dev v2](../includes/machine-learning-dev-v2.md)]
+
 Configuring the `applicationSharingPolicy` property for a compute instance has no effect as that property isn't supported
 
 
-[!INCLUDE [dev v2](../includes/machine-learning-dev-v2.md)]
-
 **Status:** Open
 
 **Problem area:** Compute

articles/machine-learning/known-issues/compute-a10-sku-not-supported.md

@@ -13,11 +13,12 @@ ms.custom: known-issue
 
 # Known issue  - Provisioning error when creating a compute instance with A10 SKU
 
+[!INCLUDE [dev v2](../includes/machine-learning-dev-v2.md)]
+
 While trying to create a compute instance with A10 SKU, you'll encounter a provisioning error.
 
 :::image type="content" source="media/compute-a10-sku-not-supported/ci-a10.png" alt-text="A screenshot showing the provisioning error message.":::
 
-[!INCLUDE [dev v2](../includes/machine-learning-dev-v2.md)]
 
 **Status:** Open
 

articles/machine-learning/known-issues/compute-idleshutdown-bicep.md

@@ -13,13 +13,12 @@ ms.custom: known-issue, devx-track-bicep
 
 # Known issue  - Idleshutdown property in Bicep template causes error
 
+[!INCLUDE [dev v2](../includes/machine-learning-dev-v2.md)]
+
 When creating an Azure Machine Learning compute instance through Bicep compiled using [MSBuild/NuGet](../../azure-resource-manager/bicep/msbuild-bicep-file.md), using the `idleTimeBeforeShutdown` property as described in the API reference [Microsoft.MachineLearningServices workspaces/computes API reference](/azure/templates/microsoft.machinelearningservices/workspaces/computes?pivots=deployment-language-bicep) results in an error.
 
 
 
-[!INCLUDE [dev v2](../includes/machine-learning-dev-v2.md)]
-
-
 **Status:** Open
 
 

articles/machine-learning/known-issues/compute-slowness-terminal-mounted-path.md

@@ -13,11 +13,9 @@ ms.custom: known-issue
 
 # Known issue  - Slowness in compute instance terminal from a mounted path
 
-While using the compute instance terminal inside a mounted path of a data folder, any commands executed from the terminal result in slowness. This issue is restricted to the terminal; running the commands from SDK using a notebook works as expected.
-
-
 [!INCLUDE [dev v2](../includes/machine-learning-dev-v2.md)]
-<!--- Choose the correct include --->
+
+While using the compute instance terminal inside a mounted path of a data folder, any commands executed from the terminal result in slowness. This issue is restricted to the terminal; running the commands from SDK using a notebook works as expected.
 
 **Status:** Open
 

articles/machine-learning/known-issues/inferencing-invalid-certificate.md

@@ -13,12 +13,11 @@ ms.custom: known-issue
 
 # Known issue  - Invalid certificate error during deployment with an AKS cluster
 
+[!INCLUDE [sdk v1](../includes/machine-learning-sdk-v1.md)]
+
 During machine learning deployments using an AKS cluster, you may receive an invalid certificate error, such as `{"code":"BadRequest","statusCode":400,"message":"The request is invalid.","details":[{"code":"KubernetesUnaccessible","message":"Kubernetes error: AuthenticationException. Reason: InvalidCertificate"}],`
 
 
-
-[!INCLUDE [sdk v1](../includes/machine-learning-sdk-v1.md)]
-
 **Status:** Open
 
 **Problem area:** Inferencing

articles/machine-learning/known-issues/inferencing-updating-kubernetes-compute-appears-to-succeed.md

@@ -13,11 +13,11 @@ ms.custom: known-issue
 
 # Known issue  - Existing Kubernetes compute can't be updated with `az ml compute attach` command
 
-Updating a Kubernetes attached compute instance using the `az ml attach` command appears to succeed but doesn't.
- 
 
 [!INCLUDE [dev v2](../includes/machine-learning-dev-v2.md)]
 
+Updating a Kubernetes attached compute instance using the `az ml attach` command appears to succeed but doesn't.
+ 
 **Status:** Open
 
 **Problem area:** Inferencing

articles/machine-learning/known-issues/jupyter-r-kernel-not-starting.md

@@ -13,10 +13,9 @@ ms.custom: known-issue
 
 # Known issue  - Jupyter R Kernel doesn't start in new compute instance images 
 
-When trying to launch an R kernel in JupyterLab or a notebook in a new compute instance, the kernel fails to start with `Error: .onLoad failed in loadNamespace()`
-
 [!INCLUDE [dev v2](../includes/machine-learning-dev-v2.md)]
 
+When trying to launch an R kernel in JupyterLab or a notebook in a new compute instance, the kernel fails to start with `Error: .onLoad failed in loadNamespace()`
 
 **Status:** Open
 

articles/machine-learning/known-issues/workspace-move-compute-instance-same-name.md

@@ -13,11 +13,10 @@ ms.custom: known-issue
 
 # Known issue  - Creating compute instance after a workspace move results in an Etag conflict error.
 
-After a moving a workspace to a different subscription or resource group, creating a compute instance with the same name as a previous compute instance will fail with an Etag conflict error.
+[!INCLUDE [dev v2](../includes/machine-learning-dev-v2.md)]
 
+After a moving a workspace to a different subscription or resource group, creating a compute instance with the same name as a previous compute instance will fail with an Etag conflict error.
 
-[!INCLUDE [dev v2](../includes/machine-learning-dev-v2.md)]
-<!--- Choose the correct include --->
 
 **Status:** Open