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Copy file name to clipboardExpand all lines: articles/ai-foundry/how-to/connections-add.md
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@@ -10,7 +10,7 @@ ms.custom:
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- build-2024
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- ignite-2024
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ms.topic: how-to
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ms.date: 05/08/2025
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ms.date: 07/08/2025
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ms.reviewer: sgilley
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ms.author: sgilley
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author: sdgilley
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| Azure Data Lake Storage Gen 2 || Azure Data Lake Storage Gen2 is a set of capabilities dedicated to big data analytics, built on Azure storage. |
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| Azure Content Safety || Azure AI Content Safety is a service that detects potentially unsafe content in text, images, and videos. |
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| Azure OpenAI || Azure OpenAI is a service that provides access to OpenAI's models including the GPT-4o, GPT-4o mini, GPT-4, GPT-4 Turbo with Vision, GPT-3.5-Turbo, DALLE-3 and Embeddings model series with the security and enterprise capabilities of Azure. |
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| Serverless Model |✓| Serverless Model connections allow you to [serverless API deployment](deploy-models-serverless.md). |
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| Serverless Model |✅| Serverless Model connections allow you to [serverless API deployment](deploy-models-serverless.md). |
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| Microsoft OneLake || Microsoft OneLake provides open access to all of your Fabric items through Azure Data Lake Storage (ADLS) Gen2 APIs and SDKs.<br/><br/>In Azure AI Foundry portal, you can set up a connection to your OneLake data using a OneLake URI. You can find the information that Azure AI Foundry requires to construct a __OneLake Artifact URL__ (workspace and item GUIDs) in the URL on the Fabric portal. For information about the URI syntax, see [Connecting to Microsoft OneLake](/fabric/onelake/onelake-access-api). |
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| API key || API Key connections handle authentication to your specified target on an individual basis. |
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| Custom || Custom connections allow you to securely store and access keys while storing related properties, such as targets and versions. Custom connections are useful when you have many targets that, or cases where, you wouldn't need a credential to access. LangChain scenarios are an example where you would use custom service connections. Custom connections don't manage authentication, so you have to manage authentication on your own. |
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::: zone-end
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::: zone pivot="fdp-project"
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| Service connection type | Preview | Required for Standard Agent deployment | Description |
| Azure AI Search ||✓| Azure AI Search is an Azure resource that supports information retrieval over your vector and textual data stored in search indexes. |
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| Azure Storage ||✓| Azure Storage is a cloud storage solution for storing unstructured data like documents, images, videos, and application installers. |
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| Azure Cosmos DB |✓|✓| Azure Cosmos DB is a globally distributed, multi-model database service that offers low latency, high availability, and scalability across multiple geographical regions. |
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| Azure AI Search ||✅| Azure AI Search is an Azure resource that supports information retrieval over your vector and textual data stored in search indexes. |
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| Azure Storage ||✅| Azure Storage is a cloud storage solution for storing unstructured data like documents, images, videos, and application installers. |
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| Azure Cosmos DB |✅|✅| Azure Cosmos DB is a globally distributed, multi-model database service that offers low latency, high availability, and scalability across multiple geographical regions. |
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| Azure OpenAI ||| Azure OpenAI is a service that provides access to OpenAI's models including the GPT-4o, GPT-4o mini, GPT-4, GPT-4 Turbo with Vision, GPT-3.5-Turbo, DALLE-3, and Embeddings model series with the security and enterprise capabilities of Azure. |
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| Application Insights ||| Azure Application Insights is a service within Azure Monitor that enables developers and DevOps teams to automatically detect performance anomalies, diagnose issues, and gain deep insights into application usage and behavior through powerful telemetry and analytics tools. |
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| API key ||| API Key connections handle authentication to your specified target on an individual basis. |
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| Custom ||| Custom connections allow you to securely store and access keys while storing related properties, such as targets and versions. Custom connections are useful when you have many targets or cases where you wouldn't need a credential to access. LangChain scenarios are a good example where you would use custom service connections. Custom connections don't manage authentication, so you have to manage authentication on your own. |
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| Serverless Model | ✓ || Serverless Model connections allow you to serverless API deployment. |
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| Azure Databricks | ✓ | | Azure Databricks connector allows you to connect your Azure AI Foundry Agents to Azure Databricks to access workflows and Genie Spaces during runtime. It supports three connection types - __Jobs__, __Genie__, and __Other__. You can pick the Job or Genie space you want associated with this connection while setting up the connection in the Foundry UI. You can also use the Other connection type and allow your agent to access workspace operations in Azure Databricks. Authentication is handled through Microsoft Entra ID for users or service principals. For examples of using this connector, see [Jobs](https://github.com/Azure-Samples/AI-Foundry-Connections/blob/main/src/samples/python/sample_agent_adb_job.py) and [Genie](https://github.com/Azure-Samples/AI-Foundry-Connections/blob/main/src/samples/python/sample_agent_adb_genie.py). Note: Usage of this connection is available only via the Foundry SDK in code and is integrated into agents as a FunctionTool (please see the samples above for details). Usage of this connection in AI Foundry Playground is currently not supported.|
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| Serverless Model | ✅ || Serverless Model connections allow you to serverless API deployment. |
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| Azure Databricks | ✅ | | Azure Databricks connector allows you to connect your Azure AI Foundry Agents to Azure Databricks to access workflows and Genie Spaces during runtime. It supports three connection types - __Jobs__, __Genie__, and __Other__. You can pick the Job or Genie space you want associated with this connection while setting up the connection in the Foundry UI. You can also use the Other connection type and allow your agent to access workspace operations in Azure Databricks. Authentication is handled through Microsoft Entra ID for users or service principals. For examples of using this connector, see [Jobs](https://github.com/Azure-Samples/AI-Foundry-Connections/blob/main/src/samples/python/sample_agent_adb_job.py) and [Genie](https://github.com/Azure-Samples/AI-Foundry-Connections/blob/main/src/samples/python/sample_agent_adb_genie.py). Note: Usage of this connection is available only via the Foundry SDK in code and is integrated into agents as a FunctionTool (please see the samples above for details). Usage of this connection in AI Foundry Playground is currently not supported.|
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## Agent knowledge tool connections
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To learn more about Agent Knowledge tools, see [Knowledge tool overview](https://aka.ms/AgentToolOverviewDoc).
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