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Copy file name to clipboardExpand all lines: articles/app-service/troubleshoot-diagnostic-logs.md
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| Log Name| Log type | Windows | Windows Container | Linux | Linux Container | Description |
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|-|-|-|-|-|-|-|
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| App Service Console Logs | AppServiceConsoleLogs | Java SE & Tomcat | Yes | Yes | Yes | Standard output and standard error |
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| App Service Console Logs | AppServiceConsoleLogs | Java SE & Tomcat | Yes | Yes | Yes | Standard output and standard error <sup>3</sup> |
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| HTTP logs | AppServiceHTTPLogs | Yes | Yes | Yes | Yes | Web server logs |
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| App Service Environment Platform Logs | AppServiceEnvironmentPlatformLogs | Yes | N/A | Yes | Yes | App Service Environment: scaling, configuration changes, and status logs|
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| Access Audit Logs | AppServiceAuditLogs | Yes | Yes | Yes | Yes | Login activity via FTP and Kudu |
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| Site Content Change Audit Logs | AppServiceFileAuditLogs | Yes | Yes | TBA | TBA | File changes made to the site content; **only available for Premium tier and above** |
Copy file name to clipboardExpand all lines: articles/azure-monitor/logs/log-excel.md
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> [!NOTE]
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> Because Excel is a local client application, local hardware and software limitations impact it's performance and ability to process large sets of data.
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## Prerequisites
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To integrate Log Analytics and Excel, you need:
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-[Excel](https://www.microsoft.com/en-us/microsoft-365/excel) local client application.
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- A Log Analytics workspace that has some data. If needed, [create a diagnostic setting to send data to a Log Analytics workspace](../essentials/create-diagnostic-settings.md).
1.**Create and run your query** in Log analytics as you normally would. Don’t worry if you hit the number of records limitation in the user interface. We recommend you use relative dates - like the ‘ago’ function or the UI time picker - so Excel refreshes the right set of data.
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2.**Export Query** - Once you are happy with the query and its results, export the query to M using Log Analytics **Export to Power BI (M query)** menu choice under the *Export* menu:
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:::image type="content" source="media/log-excel/export-query.png" alt-text="Log Analytics query with the data and export option" border="true":::
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:::image type="content" source="media/log-excel/export-query.png" alt-text="Screenshot of Log Analytics query with the data and export option." border="true":::
Once the[prerequisite](../prerequisites-resources.md) steps are complete, and you have a cluster pool deployed, continue to use the Azure portal to create a Spark cluster.
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You can use the Azure portal to create an Apache Spark cluster in cluster pool. You then create a Jupyter Notebook and use it to run Spark SQL queries against Apache Hive tables.
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Once the[subscription prerequisites](../prerequisites-subscription.md) and [resource prerequisites](../prerequisites-resources.md)steps are complete, and you have a cluster pool deployed, continue to use the Azure portal to create a Spark cluster.
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You can use the Azure portal to create an Apache Spark cluster in cluster pool. You can then create a Jupyter Notebook and use it to run Spark SQL queries against Apache Hive tables.
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1. In the Azure portal, type cluster pools, and select cluster pools to go to the cluster pools page. On the cluster pools page, select the cluster pool in which you can add a new Spark cluster.
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1. On the specific cluster pool page, click **+ New cluster**.
Copy file name to clipboardExpand all lines: articles/machine-learning/how-to-network-isolation-model-catalog.md
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# Use Model Catalog collections with workspace managed virtual network
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In this article, you learn how you can use the various collections in the Model Catalog within an isolated network.
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In this article, you learn how to use the various collections in the Model Catalog within an isolated network.
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Workspace [managed virtual network](./how-to-network-isolation-planning.md) is the recommended way to support network isolation with the Model Catalog. It provides easily configuration to secure your workspace. After you enable managed virtual network in the workspace level, resources related to workspace in the same virtual network, will use the same network setting in the workspace level. You can also configure the workspace to use private endpoint to access other Azure resources such as Azure OpenAI. Furthermore, you can configure FQDN rule to approve outbound to non-Azure resources, whose relevance you learn in the rest of this article. See [how to Workspace managed network isolation](./how-to-managed-network.md) to enable workspace managed virtual network.
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Workspace [managed virtual network](./how-to-network-isolation-planning.md) is the recommended way to support network isolation with the Model Catalog. It provides easily configuration to secure your workspace. After you enable managed virtual network in the workspace level, resources related to workspace in the same virtual network, will use the same network setting in the workspace level. You can also configure the workspace to use private endpoint to access other Azure resources such as Azure OpenAI. Furthermore, you can configure FQDN rule to approve outbound to non-Azure resources, which is required to use some of the collections in the Model Catalog. See [how to Workspace managed network isolation](./how-to-managed-network.md) to enable workspace managed virtual network.
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The creation of the managed virtual network is deferred until a compute resource is created or provisioning is manually started. You can use following command to manually trigger network provisioning.
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```bash
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*[ExpressRoute](https://azure.microsoft.com/products/expressroute/) - Connects on-premises networks into the cloud over a private connection. Connection is made using a connectivity provider.
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*[Azure Bastion](/azure/bastion/bastion-overview) - In this scenario, you create an Azure Virtual Machine (sometimes called a jump box) inside the virtual network. You then connect to the VM using Azure Bastion. Bastion allows you to connect to the VM using either an RDP or SSH session from your local web browser. You then use the jump box as your development environment. Since it is inside the virtual network, it can directly access the workspace.
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3. Since the workspace managed virtual network can access internet in this configuration, you can work with all the Collections in the Model Catalog from within the workspace.
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## Workspace managed virtual network to allow only approved outbound
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Since the workspace managed virtual network can access internet in this configuration, you can work with all the Collections in the Model Catalog from within the workspace.
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1. Configure a workspace with managed virtual network to allow only approved outbound by following the steps listed [here](./how-to-managed-network.md#configure-a-managed-virtual-network-to-allow-only-approved-outbound).
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2. If you choose to set the public network access to the workspace to disabled, you can connect to the workspace using one of the methods as listed in Scenario 1.
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## Workspace managed virtual network to allow only approved outbound
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1. Configure a workspace by following [Workspace managed network isolation](./how-to-managed-network.md#configure-a-managed-virtual-network-to-allow-only-approved-outbound). In step 3 of the tutorial when selecting **Workspace managed outbound access**, select **Allow Only Approved Outbound**.
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2. If you set the public network access to the workspace to disabled, you can connect to the workspace using one of the methods as listed [in step 2 of the allow internet outbound section of this tutorial](#workspace-managed-virtual-network-to-allow-internet-outbound).
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3. The workspace manages virtual network is set to an allow only configuration. You must add a corresponding user-defined outbound rule to allow all the relevant FQDNs.
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1. Follow this link for a list of FQDNs required for the [Curated by Azure AI collection](#language-models-in-curated-by-azure-ai-collection).
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2. Follow this link for a list of FQDNs required for the [Hugging Face collection](#work-with-hugging-face-collection).
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## Work with open source models curated by Azure Machine Learning
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Workspace managed virtual network to allow only approved outbound uses a Service Endpoint Policy to Azure Machine Learning managed storage accounts, to help access the models in the collections curated by Azure Machine Learning in an out-of-the-box manner. This mode of workspace configuration also has default outbound to Microsoft Container Registry where the docker image used to deploy the models is present.
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Workspace managed virtual network to allow only approved outbound uses a Service Endpoint Policy to Azure Machine Learning managed storage accounts, to help access the models in the collections curated by Azure Machine Learning in an out-of-the-box manner. This mode of workspace configuration also has default outbound to the Microsoft Container Registry that contains the docker image used to deploy the models.
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### Language models in 'Curated by Azure AI' collection
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Today, these models involve dynamic installation of dependencies at runtime. Therefore, users should add user defined outbound rules for the following FQDNs at the workspace level:
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These models involve dynamic installation of dependencies at runtime. To add a user defined outbound rule, follow step four of
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To use the Curated by Azure AI collection, users should add user defined outbound rules for the following FQDNs at the workspace level:
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*`*.anaconda.org`
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*`*.anaconda.com`
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*`*.pytorch.org`
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*`pytorch.org`
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Follow Step 4 in the [managed virtual network tutorial](./how-to-managed-network.md#configure-a-managed-virtual-network-to-allow-only-approved-outbound) to add the corresponding user-defined outbound rules.
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> [!WARNING]
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> FQDN outbound rules are implemented using Azure Firewall. If you use outbound FQDN rules, charges for Azure Firewall are included in your billing. For more information, see [Pricing](./how-to-managed-network.md#pricing).
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*`cdn-lfs.huggingface.co`
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*`cdn.auth0.com`
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Follow Step 4 in the [managed virtual network tutorial](./how-to-managed-network.md#configure-a-managed-virtual-network-to-allow-only-approved-outbound) to add the corresponding user-defined outbound rules.
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