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Merge pull request #145 from microsoft/psl-re-use-log-analytic-update
docs: Added use-log-analytic file and updated links and replaced content
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‎docs/CustomizingAzdParameters.md

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| `AZURE_ENV_MODEL_NAME` | string | `gpt-4o` | Set the Model Name (allowed values: gpt-4o). |
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| `AZURE_ENV_MODEL_VERSION` | string | `2024-08-06` | Set the Azure model version (allowed values: 2024-08-06) |
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| `AZURE_ENV_MODEL_CAPACITY` | integer | `200` | Set the Model Capacity (choose a number based on available GPT model capacity in your subscription). |
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| `AZURE_ENV_LOG_ANALYTICS_WORKSPACE_ID` | string | `<Existing Workspace Id>` | Set this if you want to reuse an existing Log Analytics Workspace instead of creating a new one. |
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| `AZURE_ENV_LOG_ANALYTICS_WORKSPACE_ID` | string | Guide to get your [Existing Workspace ID](/docs/re-use-log-analytics.md) | Set this if you want to reuse an existing Log Analytics Workspace instead of creating a new one. |
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| `AZURE_ENV_IMAGETAG` | string | `latest` | Set the Image tag Like (allowed values: latest, dev, hotfix) |
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| `AZURE_ENV_JUMPBOX_SIZE` | string | `Standard_DS2_v2` | Specifies the size of the Jumpbox Virtual Machine. Set a custom value if `enablePrivateNetworking` is `true`. |
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---
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```bash
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azd env set AZURE_LOCATION westus2
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```
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```

‎docs/DeploymentGuide.md

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➡️ To ensure sufficient quota is available in your subscription, please follow **[Quota check instructions guide](../docs/quota_check.md)** before you deploy the solution.
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| [![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/microsoft/Modernize-your-Code-Solution-Accelerator) | [![Open in Dev Containers](https://img.shields.io/static/v1?style=for-the-badge&label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/microsoft/Modernize-your-Code-Solution-Accelerator) |
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|---|---|
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### **Configurable Deployment Settings**
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When you start the deployment, most parameters will have **default values**, but you can update the following settings by following the steps [here](../docs/CustomizingAzdParameters.md):
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## Deployment Options & Steps
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| **Setting** | **Description** | **Default value** |
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|----------------------------------|------------------------------------------------------------------------------------------------------|----------------------------|
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| **Azure Region** | The region where resources will be created. | East US |
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| **Resource Prefix** | Prefix for all resources created by this template. This prefix will be used to create unique names for all resources. The prefix must be unique within the resource group. | azdtemp |
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| **AI Location** | Location for all AI services resources. This location can be different from the resource group location. | japaneast |
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| **Capacity** | Configure capacity for **gpt-4o**. | 200 |
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| **Model Deployment Type** | Change the Model Deployment Type (allowed values: Standard, GlobalStandard). | GlobalStandard |
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| **Model Name** | Set the Model Name (allowed values: gpt-4o). | gpt-4o |
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| **Model Version** | Set the Azure model version (allowed values: 2024-08-06). | 2024-08-06 |
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| **Image Tag** | Set the Image tag (allowed values: latest, dev, hotfix). | latest |
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| **Existing Log analytics workspace** | To reuse the existing Log analytics workspace Id. | `<Existing Workspace Id>` |
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This accelerator can be configured to use authentication.
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* To use authentication the installer must have the rights to create and register an application identity in their Azure environment.
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After installation is complete, follow the directions in the [App Authentication](../docs/AddAuthentication.md) document to enable authentication.
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* Note: If you enable authentication, all processing history and current processing will be performed for your specific user. Without authentication, all batch history from the tool will be visible to all users.
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### [Optional] Quota Recommendations
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By default, the **GPT model capacity** in deployment is set to **5k tokens**.
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> **We recommend increasing the capacity to 200k tokens for optimal performance.**
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To adjust quota settings, follow these [steps](../docs/AzureGPTQuotaSettings.md)
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### Deployment Options & Steps
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### Sandbox or WAF Aligned Deployment Options
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The [`infra`](../infra) folder contains the [`main.bicep`](../infra/main.bicep) Bicep script, which defines all Azure infrastructure components for this solution.
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- Select **`true`** to deploy a **WAF-aligned, production-ready environment**
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- Select **`false`** to deploy a **lightweight sandbox/dev environment**
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-
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> [!TIP]
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> Always review and adjust parameter values (such as region, capacity, security settings and log analytics workspace configuration) to match your organization’s requirements before deploying. For production, ensure you have sufficient quota and follow the principle of least privilege for all identities and role assignments.
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### Deployment Steps
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Pick from the options below to see step-by-step instructions for: GitHub Codespaces, VS Code Dev Containers, Local Environments, and Bicep deployments.
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| [![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/microsoft/Modernize-your-Code-Solution-Accelerator) | [![Open in Dev Containers](https://img.shields.io/static/v1?style=for-the-badge&label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/microsoft/Modernize-your-Code-Solution-Accelerator) |
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|---|---|
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<details>
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<summary><b>Deploy in GitHub Codespaces</b></summary>
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[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/microsoft/Modernize-your-Code-Solution-Accelerator)
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2. Accept the default values on the create Codespaces page
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3. Open a terminal window if it is not already open
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4. Continue with the [deploying steps](#deploying)
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4. Continue with the [deploying steps](#deploying-with-azd)
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</details>
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3. In the VS Code window that opens, once the project files show up (this may take several minutes), open a terminal window.
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4. Continue with the [deploying steps](#deploying)
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4. Continue with the [deploying steps](#deploying-with-azd)
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</details>
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3. Open the project folder in your terminal or editor.
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4. Continue with the [deploying steps](#deploying).
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4. Continue with the [deploying steps](#deploying-with-azd).
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</details>
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### Deploying
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<br/>
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Consider the following settings during your deployment to modify specific settings:
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<details>
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<Summary><b>Configurable Deployment Settings</b></Summary>
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When you start the deployment, most parameters will have **default values**, but you can update the following settings by following the steps [here](../docs/CustomizingAzdParameters.md):
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| **Setting** | **Description** | **Default value** |
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|----------------------------------|------------------------------------------------------------------------------------------------------|----------------------------|
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| **Azure Region** | The region where resources will be created. | East US |
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| **Resource Prefix** | Prefix for all resources created by this template. This prefix will be used to create unique names for all resources. The prefix must be unique within the resource group. | azdtemp |
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| **AI Location** | Location for all AI services resources. This location can be different from the resource group location. | japaneast |
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| **Capacity** | Configure capacity for **gpt-4o**. | 200 |
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| **Model Deployment Type** | Change the Model Deployment Type (allowed values: Standard, GlobalStandard). | GlobalStandard |
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| **Model Name** | Set the Model Name (allowed values: gpt-4o). | gpt-4o |
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| **Model Version** | Set the Azure model version (allowed values: 2024-08-06). | 2024-08-06 |
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| **Image Tag** | Set the Image tag (allowed values: latest, dev, hotfix). | latest |
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| **Existing Log analytics workspace** | To reuse the existing Log analytics workspace Id. | `<Existing Workspace Id>` |
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This accelerator can be configured to use authentication.
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* To use authentication the installer must have the rights to create and register an application identity in their Azure environment.
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After installation is complete, follow the directions in the [App Authentication](../docs/AddAuthentication.md) document to enable authentication.
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* Note: If you enable authentication, all processing history and current processing will be performed for your specific user. Without authentication, all batch history from the tool will be visible to all users.
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</details>
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<details>
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<Summary><b> Quota Recommendations </b></Summary>
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By default, the **GPT model capacity** in deployment is set to **5k tokens**.
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> **We recommend increasing the capacity to 200k tokens for optimal performance.**
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To adjust quota settings, follow these [steps](../docs/AzureGPTQuotaSettings.md)
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</details>
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<details>
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<summary><b>Reusing an Existing Log Analytics Workspace</b></summary>
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Guide to get your [Existing Workspace ID](/docs/re-use-log-analytics.md)
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</details>
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### Deploying with AZD
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Once you've opened the project in [Codespaces](#github-codespaces) or in [Dev Containers](#vs-code-dev-containers) or [locally](#local-environment), you can deploy it to Azure following the following steps.
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```
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4. Select a subscription from your Azure account, and select a location which has quota for all the resources.
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* This deployment will take *6-9 minutes* to provision the resources in your account and set up the solution with sample data.
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* If you get an error or timeout with deployment, changing the location can help, as there may be availability constraints for the resources.

‎docs/images/re_use_log/logAnalytics.png

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‎docs/images/re_use_log/logAnalyticsJson.png

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‎docs/images/re_use_log/logAnalyticsList.png

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‎docs/re-use-log-analytics.md

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[← Back to *DEPLOYMENT* guide](https://github.com/microsoft/Modernize-your-code-solution-accelerator/blob/psl-re-use-log-analytic-update/docs/DeploymentGuide.md#deployment-options--steps)
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# Reusing an Existing Log Analytics Workspace
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To configure your environment to use an existing Log Analytics Workspace, follow these steps:
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---
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### 1. Go to Azure Portal
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Go to https://portal.azure.com
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### 2. Search for Log Analytics
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In the search bar at the top, type "Log Analytics workspaces" and click on it and click on the workspace you want to use.
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![alt text](../docs/images/re_use_log/logAnalyticsList.png)
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### 3. Copy Resource ID
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In the Overview pane, Click on JSON View
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![alt text](../docs/images/re_use_log/logAnalytics.png)
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Copy Resource ID that is your Workspace ID
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![alt text](../docs/images/re_use_log/logAnalyticsJson.png)
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### 4. Set the Workspace ID in Your Environment
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Run the following command in your terminal
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```bash
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azd env set AZURE_ENV_LOG_ANALYTICS_WORKSPACE_ID '<Existing Log Analytics Workspace Id>'
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```
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Replace `<Existing Log Analytics Workspace Id>` with the value obtained from Step 3.
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### 5. Continue Deployment
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Proceed with the next steps in the [deployment guide](https://github.com/microsoft/Modernize-your-code-solution-accelerator/blob/psl-re-use-log-analytic-update/docs/DeploymentGuide.md#deployment-options--steps).

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