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---
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title: 'Use the Azure Developer CLI to deploy resources for Azure OpenAI On Your Data'
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titleSuffix: Azure OpenAI
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description: Use this article to learn how to automate resource deployment for Azure OpenAI On Your Data.
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manager: nitinme
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ms.service: azure-ai-openai
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ms.topic: quickstart
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author: aahill
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ms.author: aahi
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ms.date: 04/09/2024
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recommendations: false
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---
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# Use the Azure Developer CLI to deploy resources for Azure OpenAI On Your Data
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Use this article to learn how to automate resource deployment for Azure OpenAI On Your Data. The Azure Developer CLI (`azd`) is an open-source, command-line tool that streamlines provisioning and deploying resources to Azure using a template system. The template contains infrastructure files to provision the necessary Azure OpenAI resources and configurations and includes the completed sample app code.
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## Prerequisites
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- An Azure subscription - <a href="https://azure.microsoft.com/free/cognitive-services" target="_blank">Create one for free</a>.
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- Access granted to Azure OpenAI in the desired Azure subscription.
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Azure OpenAI requires registration and is currently only available to approved enterprise customers and partners. [See Limited access to Azure OpenAI Service](/legal/cognitive-services/openai/limited-access?context=/azure/ai-services/openai/context/context) for more information. You can apply for access to Azure OpenAI by completing the form at <a href="https://aka.ms/oai/access" target="_blank">https://aka.ms/oai/access</a>. Open an issue on this repo to contact us if you have an issue.
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- The Azure Developer CLI [installed](/azure/developer/azure-developer-cli/install-azd) on your machine
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## Clone and initialize the Azure Developer CLI template
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1. For the steps ahead, clone and initialize the template.
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```bash
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azd init --template openai-chat-your-own-data
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```
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2. The `azd init` command prompts you for the following information:
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* Environment name: This value is used as a prefix for all Azure resources created by Azure Developer CLI. The name must be unique across all Azure subscriptions and must be between 3 and 24 characters long. The name can contain numbers and lowercase letters only.
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## Use the template to deploy resources
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1. Sign-in to Azure:
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```bash
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azd auth login
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```
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1. Provision and deploy the OpenAI resource to Azure:
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```bash
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azd up
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```
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`azd` prompts you for the following information:
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* Subscription: The Azure subscription that your resources are deployed to.
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* Location: The Azure region where your resources are deployed.
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> [!NOTE]
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> The sample `azd` template uses the `gpt-35-turbo-16k` model. A recommended region for this template is East US, since different Azure regions support different OpenAI models. You can visit the [Azure OpenAI Service Models](/azure/ai-services/openai/concepts/models) support page for more details about model support by region.
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> [!NOTE]
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> The provisioning process may take several minutes to complete. Wait for the task to finish before you proceed to the next steps.
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1. Click the link `azd` outputs to navigate to the new resource group in the Azure portal. You should see the following top level resources:
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* An Azure OpenAI service with a deployed model
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* An Azure Storage account you can use to upload your own data files
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* An Azure AI Search service configured with the proper indexes and data sources
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## Upload data to the storage account
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`azd` provisioned all of the required resources for you to chat with your own data, but you still need to upload the data files you want to make available to your AI service.
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1. Navigate to the new storage account in the Azure portal.
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1. On the left navigation, select **Storage browser**.
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1. Select **Blob containers** and then navigate into the **File uploads** container.
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1. Click the **Upload** button at the top of the screen.
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1. In the flyout menu that opens, upload _contoso_benefits_document_example.pdf_ file in the root `documents` folder of the example repo.
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> [!NOTE]
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> The search indexer is set to run every 5 minutes to index the data in the storage account. You can either wait a few minutes for the uploaded data to be indexed, or you can manually run the indexer from the search service page.
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## Connect or create an application
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After running the `azd` template and uploading your data, you're ready to start using Azure OpenAI on Your Data. See the [quickstart article](../use-your-data-quickstart.md) for code samples you can use to build your applications.

articles/ai-services/openai/includes/connect-your-data-studio.md

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## Add your data using Azure OpenAI Studio
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> [!TIP]
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> You can [use the Azure Developer CLI](../how-to/azure-developer-cli.md) to programmatically create the resources needed for Azure OpenAI On Your Data
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Navigate to [Azure OpenAI Studio](https://oai.azure.com/) and sign-in with credentials that have access to your Azure OpenAI resource. During or after the sign-in workflow, select the appropriate directory, Azure subscription, and Azure OpenAI resource.
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1. Select the **Bring your own data** tile

articles/ai-services/openai/toc.yml

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href: ./how-to/use-your-data-securely.md
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- name: Deploy and use web apps
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href: ./how-to/use-web-app.md
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- name: Use the Azure Developer CLI
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href: ./how-to/azure-developer-cli.md
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- name: Migrate to OpenAI Python v1.x
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href: ./how-to/migration.md
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- name: Models

articles/aks/supported-kubernetes-versions.md

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# Supported Kubernetes versions in Azure Kubernetes Service (AKS)
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The Kubernetes community releases minor versions roughly every three months. Recently, the Kubernetes community has [increased the support window for each version from nine months to one year](https://kubernetes.io/blog/2020/08/31/kubernetes-1-19-feature-one-year-support/), starting with version 1.19.
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The Kubernetes community [releases minor versions](https://kubernetes.io/releases/) roughly every four months.
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Minor version releases include new features and improvements. Patch releases are more frequent (sometimes weekly) and are intended for critical bug fixes within a minor version. Patch releases include fixes for security vulnerabilities or major bugs.
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[major].[minor].[patch]
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Examples:
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1.17.7
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1.17.8
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1.29.2
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1.29.1
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```
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Each number in the version indicates general compatibility with the previous version:
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* **Minor versions** change when functionality updates are made that are backwards compatible to the other minor releases.
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* **Patch versions** change when backwards-compatible bug fixes are made.
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Aim to run the latest patch release of the minor version you're running. For example, if your production cluster is on **`1.17.7`**, **`1.17.8`** is the latest available patch version available for the *1.17* series. You should upgrade to **`1.17.8`** as soon as possible to ensure your cluster is fully patched and supported.
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Aim to run the latest patch release of the minor version you're running. For example, if your production cluster is on **`1.29.1`** and **`1.29.2`** is the latest available patch version available for the *1.29* minor version, you should upgrade to **`1.29.2`** as soon as possible to ensure your cluster is fully patched and supported.
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## AKS Kubernetes release calendar
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> [!NOTE]
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> Alias minor version requires Azure CLI version 2.37 or above as well as API version 20220401 or above. Use `az upgrade` to install the latest version of the CLI.
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AKS allows you to create a cluster without specifying the exact patch version. When you create a cluster without designating a patch, the cluster runs the minor version's latest GA patch. For example, if you create a cluster with **`1.21`**, your cluster runs **`1.21.7`**, which is the latest GA patch version of *1.21*. If you want to upgrade your patch version in the same minor version, please use [auto-upgrade](./auto-upgrade-cluster.md).
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AKS allows you to create a cluster without specifying the exact patch version. When you create a cluster without designating a patch, the cluster runs the minor version's latest GA patch. For example, if you create a cluster with **`1.29`** and **`1.29.2`** is the latest GA'd patch available, your cluster will be created with **`1.29.2`**. If you want to upgrade your patch version in the same minor version, please use [auto-upgrade](./auto-upgrade-cluster.md).
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"autoScalerProfile": null,
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"currentKubernetesVersion": "1.29.2",
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}
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> AKS uses safe deployment practices which involve gradual region deployment. This means it might take up to 10 business days for a new release or a new version to be available in all regions.
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The supported window of Kubernetes versions on AKS is known as "N-2": (N (Latest release) - 2 (minor versions)), and ".letter" is representative of patch versions.
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The supported window of Kubernetes minor versions on AKS is known as "N-2", where N refers to the latest release, meaning that two previous minor releases are also supported.
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For example, on the day that AKS introduces version 1.29, support is provided for the following versions:
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New minor version | Supported Minor Version List
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1.17.a | 1.17.a, 1.17.b, 1.16.c, 1.16.d, 1.15.e, 1.15.f
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1.29 | 1.29, 1.28, 1.27
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When a new minor version is introduced, the oldest minor version is deprecated and removed. For example, let's say the current supported minor version list is:
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```
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You can use one minor version older or newer of `kubectl` relative to your *kube-apiserver* version, consistent with the [Kubernetes support policy for kubectl](https://kubernetes.io/docs/setup/release/version-skew-policy/#kubectl).
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When you deploy an AKS cluster with Azure portal, Azure CLI, Azure PowerShell, the cluster defaults to the N-1 minor version and latest patch. For example, if AKS supports *1.29.2*, *1.29.1*, *1.28.7*, *1.28.6*, *1.27.11*, and *1.27.10*, the default version selected is *1.28.7*.
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* *1.12.x* -> *1.13.x*: allowed.
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When performing an upgrade from an _unsupported version_ that skips two or more minor versions, the upgrade is performed without any guarantee of functionality and is excluded from the service-level agreements and limited warranty.Clusters running _unsupported version_ has the flexibility of decoupling control plane upgrades with node pool upgrades. However if your version is significantly out of date, we recommend that you re-create the cluster.
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articles/api-management/breaking-changes/workspaces-breaking-changes-june-2024.md

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# Workspaces - breaking changes (June 2024)
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[!INCLUDE [api-management-availability-premium](../../../includes/api-management-availability-premium.md)]
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[!INCLUDE [api-management-availability-premium-dev-standard](../../../includes/api-management-availability-premium-dev-standard.md)]
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## Related content
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See all [upcoming breaking changes and feature retirements](overview.md).
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See all [upcoming breaking changes and feature retirements](overview.md).

articles/azure-arc/vmware-vsphere/quick-start-connect-vcenter-to-arc-using-script.md

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- A resource pool or a cluster with a minimum capacity of 16 GB of RAM and four vCPUs.
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> [!NOTE]
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> Azure Arc-enabled VMware vSphere supports vCenter Server instances with a maximum of 9,500 virtual machines (VMs). If your vCenter Server instance has more than 9,500 VMs, we don't recommend that you use Azure Arc-enabled VMware vSphere with it at this point.

articles/azure-netapp-files/manage-availability-zone-volume-placement.md

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* <a name="file-path-uniqueness"></a> For volumes in different availability zones, Azure NetApp Files allows you to create volumes with the same file path (NFS), share name (SMB), or volume path (dual-protocol). This feature is currently in preview.
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>[!IMPORTANT]
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>Once a volume is created with the same file path as another volume in a different availability zone, the volume has the same level of support as other volumes deployed in the subscription without this feature enabled. For example, if there's an issue with other generally available features on the volume such as snapshots, it's supported because the problem is unrelated to the ability to create volumes with the same file path in different availability zones.
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You need to register the feature before using it for the first time. After registration, the feature is enabled and works in the background. No UI control is required.
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---
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title: Call setup issues - The call setup takes too long
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titleSuffix: Azure Communication Services - Troubleshooting Guide
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description: Learn how to troubleshoot when the call setup takes too long.
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author: sloanster
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ms.author: micahvivion
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services: azure-communication-services
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ms.date: 04/10/2024
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ms.topic: troubleshooting
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ms.service: azure-communication-services
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ms.subservice: calling
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---
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# The call setup takes too long
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When the user makes a call or accepts a call, multiple steps and messages are exchanged between the signaling layer and media transport.
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If the call setup takes too long, it's often due to network issues.
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Another factor that contributes to call setup delay is the stream acquisition delay, which is the time it takes for a browser to get the media stream.
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Additionally, device performance can also affect call setup time. For example, a busy browser may take longer to schedule the API request, resulting in a longer call setup time.
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## How to detect using the SDK
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The application can calculate the delay between when the call is initiated and when it's connected.
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## How to mitigate or resolve
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These issues can affect call setup time because the signaling layer uses a `TCP` connection, and factors such as retransmissions can cause delays.
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Additionally, if the user suspects the delay comes from stream acquisition, they should check their devices. For example, they can choose a different audio input device.

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