---
title: Connect to Azure OpenAI
description: This page provides step-by-step instructions for setting up an Azure OpenAI connector for the first time. This connector type enables you to leverage...
url: https://docs-v3-preview.elastic.dev/elastic/docs-content/pull/5399/explore-analyze/ai-features/llm-guides/connect-to-azure-openai
products:
  - Elastic Cloud Serverless
  - Elastic Security
applies_to:
  - Serverless Security projects: Generally available
  - Elastic Stack: Generally available
---

# Connect to Azure OpenAI
This page provides step-by-step instructions for setting up an Azure OpenAI connector for the first time. This connector type enables you to leverage large language models (LLMs) within Kibana. You’ll first need to configure Azure, then configure the connector in Kibana.

## Configure Azure


### Configure a deployment

First, set up an Azure OpenAI deployment:
1. Log in to the Azure console and search for Azure OpenAI.
2. In **Azure AI services**, select **Create**.
3. For the **Project Details**, select your subscription and resource group. If you don’t have a resource group, select **Create new** to make one.
4. For **Instance Details**, select the desired region and specify a name, such as `example-deployment-openai`.
5. Select the **Standard** pricing tier, then click **Next**.
6. Configure your network settings, click **Next**, optionally add tags, then click **Next**.
7. Review your deployment settings, then click **Create**. When complete, select **Go to resource**.

The following video demonstrates these steps (click to watch).
[![azure-openai-configure-deployment-video](https://play.vidyard.com/7NEa5VkVJ67RHWBuK8qMXA.jpg)](https://videos.elastic.co/watch/7NEa5VkVJ67RHWBuK8qMXA?)

### Configure keys

Next, create access keys for the deployment:
1. From within your Azure OpenAI deployment, select **Click here to manage keys**.
2. Store your keys in a secure location.

The following video demonstrates these steps (click to watch).
[![azure-openai-configure-keys-video](https://play.vidyard.com/cQXw96XjaeF4RiB3V4EyTT.jpg)](https://videos.elastic.co/watch/cQXw96XjaeF4RiB3V4EyTT?)

### Configure a model

Now, set up the Azure OpenAI model:
1. From within your Azure OpenAI deployment, select **Model deployments**, then click **Manage deployments**.
2. On the **Deployments** page, select **Create new deployment**.
3. Under **Select a model**, choose `gpt-4o` or `gpt-4 turbo`.
4. Set the model version to "Auto-update to default".
   <important>
   The models available to you depend on [region availability](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability). For best results, use `GPT-4o 2024-05-13` with the maximum Tokens-Per-Minute (TPM) capacity. For more information on how different models perform for different tasks, refer to the [Large language model performance matrix](https://docs-v3-preview.elastic.dev/elastic/docs-content/pull/5399/solutions/security/ai/large-language-model-performance-matrix).
   </important>
5. Under **Deployment type**, select **Standard**.
6. Name your deployment.
7. Slide the **Tokens per Minute Rate Limit** to the maximum. The following example supports 80,000 TPM, but other regions might support higher limits.
8. Click **Create**.

The following video demonstrates these steps (click to watch).
[![azure-openai-configure-model-video](https://play.vidyard.com/PdadFyV1p1DbWRyCr95whT.jpg)](https://videos.elastic.co/watch/PdadFyV1p1DbWRyCr95whT?)

## Configure Elastic AI Assistant

Finally, configure the connector in Kibana:
1. Log in to Kibana.
2. Find the **Connectors** page in the navigation menu or use the [global search field](https://docs-v3-preview.elastic.dev/elastic/docs-content/pull/5399/explore-analyze/find-and-organize/find-apps-and-objects). Then click **Create Connector**, and select **OpenAI**.
3. Give your connector a name to help you keep track of different models, such as `Azure OpenAI (GPT-4 Turbo v. 0125)`.
4. For **Select an OpenAI provider**, choose **Azure OpenAI**.
5. Update the **URL** field. We recommend doing the following:
   1. Navigate to your deployment in Azure AI Studio and select **Open in Playground**. The **Chat playground** screen displays.
2. Select **View code**, then from the drop-down, change the **Sample code** to `Curl`.
3. Highlight and copy the URL without the quotes, then paste it into the **URL** field in Kibana.
4. (Optional) Alternatively, refer to the [API documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai/reference) to learn how to create the URL manually.
6. Under **API key**, enter one of your API keys.
7. Click **Save & test**, then click **Run**.

Your LLM connector is now configured. The following video demonstrates these steps (click to watch).
[![azure-openai-configure-model-video](https://play.vidyard.com/RQZVcnXHokC3RcV6ZB2pmF.jpg)](https://videos.elastic.co/watch/RQZVcnXHokC3RcV6ZB2pmF?)