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Audit and observe compute instance version GA release
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articles/machine-learning/azure-machine-learning-ci-image-release-notes.md

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Main updates provided with each image version are described in the below sections.
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## April 7, 2023
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Version: `23.04.07`
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Main changes:
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- `Azure Machine Learning SDK` to version `1.49.0`
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- `Certifi` updated to `2022.9.24`
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- `.Net` updated from `3.1` (EOL) to `6.0`
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- `Pyspark` update to `3.3.1` (mitigating log4j 1.2.17 and common-text-1.6 vulnerabilities)
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- Default `intellisense` to Python `3.10` on the CI
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- Bug fixes and stability improvements
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Main environment specific updates:
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- `Azureml_py38` environment is now the default.
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## January 19, 2023
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Version: `23.01.19`
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articles/machine-learning/how-to-create-manage-compute-instance.md

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* *Microsoft.MachineLearningServices/workspaces/computes/write*
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* *Microsoft.MachineLearningServices/workspaces/checkComputeNameAvailability/action*
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### Audit and observe compute instance version
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## Audit and observe compute instance version
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Once a compute instance is deployed, it does not get automatically updated. Microsoft [releases](azure-machine-learning-ci-image-release-notes.md) new VM images on a monthly basis. To understand options for keeping recent with the latest version, see [vulnerability management](concept-vulnerability-management.md#compute-instance).
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To keep track of whether an instance's operating system version is current, you could query its version using the Studio UI. In your workspace in Azure Machine Learning studio, select Compute, then select compute instance on the top. Select a compute instance's compute name to see its properties including the current operating system. Enable 'audit and observe compute instance os version' under the previews management panel to see these preview properties.
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To keep track of whether an instance's operating system version is current, you could query its version using the CLI, SDK or Studio UI.
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Administrators can use [Azure Policy](policy-reference.md) definitions to audit instances that are running on outdated operating system versions across workspaces and subscriptions. The following is a sample policy:
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# [Studio UI](#tab/azure-studio)
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```json
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{
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"mode": "All",
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"policyRule": {
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"if": {
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"allOf": [
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{
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"field": "type",
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"equals": "Microsoft.MachineLearningServices/workspaces/computes"
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},
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{
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"field": "Microsoft.MachineLearningServices/workspaces/computes/computeType",
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"equals": "ComputeInstance"
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},
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{
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"field": "Microsoft.MachineLearningServices/workspaces/computes/osImageMetadata.isLatestOsImageVersion",
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"equals": "false"
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}
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]
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},
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"then": {
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"effect": "Audit"
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}
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}
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}
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In your workspace in Azure Machine Learning studio, select Compute, then select compute instance on the top. Select a compute instance's compute name to see its properties including the current operating system.
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# [Python SDK](#tab/python)
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[!INCLUDE [sdk v2](../../includes/machine-learning-sdk-v2.md)]
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```python
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from azure.ai.ml.entities import ComputeInstance, AmlCompute
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# Display operating system version
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instance = ml_client.compute.get("myci")
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print instance.os_image_metadata
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```
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For more information on the classes, methods, and parameters used in this example, see the following reference documents:
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* [`AmlCompute` class](/python/api/azure-ai-ml/azure.ai.ml.entities.amlcompute)
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* [`ComputeInstance` class](/python/api/azure-ai-ml/azure.ai.ml.entities.computeinstance)
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# [Azure CLI](#tab/azure-cli)
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[!INCLUDE [cli v2](../../includes/machine-learning-cli-v2.md)]
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```azurecli
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az ml compute show --name "myci"
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```
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---
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IT administrators can use [Azure Policy](./../governance/policy/overview.md) to monitor the inventory of instances across workspaces in Azure Policy compliance portal. Assign the built-in policy [Audit Azure Machine Learning Compute Instances with an outdated operating system](https://ms.portal.azure.com/#view/Microsoft_Azure_Policy/PolicyDetailBlade/definitionId/%2Fproviders%2FMicrosoft.Authorization%2FpolicyDefinitions%2Ff110a506-2dcb-422e-bcea-d533fc8c35e2) on an Azure subscription or Azure management group scope.
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## Next steps
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* [Access the compute instance terminal](how-to-access-terminal.md)

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