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Merge pull request #214776 from Blackmist/patch-42
Update how-to-deploy-managed-online-endpoints.md
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articles/machine-learning/how-to-deploy-managed-online-endpoints.md

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@@ -19,11 +19,6 @@ ms.custom: how-to, devplatv2, ignite-fall-2021, cliv2, event-tier1-build-2022, s
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[!INCLUDE [sdk v2](../../includes/machine-learning-sdk-v2.md)]
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> [!IMPORTANT]
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> SDK v2 is currently in public preview.
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> The preview version is provided without a service level agreement, and it's not recommended for production workloads. Certain features might not be supported or might have constrained capabilities.
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> For more information, see [Supplemental Terms of Use for Microsoft Azure Previews](https://azure.microsoft.com/support/legal/preview-supplemental-terms/).
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Learn how to use an online endpoint to deploy your model, so you don't have to create and manage the underlying infrastructure. You'll begin by deploying a model on your local machine to debug any errors, and then you'll deploy and test it in Azure.
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You'll also learn how to view the logs and monitor the service-level agreement (SLA). You start with a model and end up with a scalable HTTPS/REST endpoint that you can use for online and real-time scoring.

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