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articles/ai-services/openai/concepts/provisioned-migration.md

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@@ -260,6 +260,29 @@ Customers must reach out to their account teams to schedule a managed migration.
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- All commitments in a subscription/region must be migrated at the same time.
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- Needing to coordinate a time for migration with the Microsoft team.
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## Migrating existing deployments to global or data zone provisioned
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Existing customers of provisioned deployments can choose to migrate to global or data zone provisioned deployments to benefit from the lower deployment minimums, granular scale increments, or differentiated pricing available for these deployment types. To learn more about how global and data zone provisioned deployments handle data processing across Azure geographies, see the Azure OpenAI deployment [data processing documentation](https://aka.ms/aoai/docs/data-processing-locations).
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Two approaches are available for customers to migrate from provisioned deployments to global or data zone provisioned deployments.
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### Zero downtime migration
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The zero downtime migration approach allows customers to migrate their existing provisioned deployments to global or data zone provisioned deployments without interrupting the existing inference traffic on their deployment. This migration approach minimizes workload interruptions, but does require a customer to have multiple coexisting deployments while shifting traffic over. The process to migrate a provisioned deployment using the zero downtime migration approach is as follows:
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- Create a new deployment using the global or data zone provisioned deployment types in the target Azure OpenAI resource.
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- Transition traffic from the existing regional provisioned deployment type to the newly created global or data zone provisioned deployment until all traffic is offloaded from the existing regional provisioned deployment.
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- Once traffic is migrated over to the new deployment, validate that there are no inference requests being processed on the previous provisioned deployment by ensuring the Azure OpenAI Requests metric does not show any API calls made within 5-10 minutes of the inference traffic being migrated over to the new deployment. For more information on this metric, [see the Monitor Azure OpenAI documentation](https://aka.ms/aoai/docs/monitor-azure-openai).
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- Once you confirm that no inference calls have been made, delete the regional provisioned deployment.
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### Migration with downtime
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The migration with downtime approach involves migrating existing provisioned deployments to global or data zone provisioned deployments while stopping any existing inference traffic on the original provisioned deployment. This migration approach does not require coexistence of multiple deployments to support but does require workload interruption to complete. The process to migrate a provisioned deployment using the migration with downtime approach is as follows:
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- Validate that there are no inference requests being processed on the previous provisioned deployment by ensuring the Azure OpenAI Requests metric does not show any API calls made within the last 5-10 minutes. For more information on this metric, [see the Monitor Azure OpenAI documentation](https://aka.ms/aoai/docs/monitor-azure-openai).
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- Once you confirm that no inference calls have been made, delete the regional provisioned deployment.
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- Create a new deployment using the global or data zone deployment types in the target Azure OpenAI resource.
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- Once your new deployment has succeeded, you may resume inference traffic on the new global or data zone deployment.
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## How do I migrate my existing Azure Reservation to the new Azure Reservation products?
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Azure Reservations for Azure OpenAI Service provisioned offers are specific to the provisioned deployment type. If the Azure Reservation purchased does not match the provisioned deployment type, the deployment will default to the hourly payment model. If you choose to migrate to global or data zone provisioned deployments, you might need to purchase a new Azure Reservation for these deployments to support additional discounts. For more information on how to purchase a new Azure Reservation or make changes to an existing Azure Reservation, see the [Azure Reservations for Azure OpenAI Service Provisioned guidance](https://aka.ms/aoai/reservation-transition).
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## Managing Provisioned Throughput Commitments
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Provisioned throughput commitments are created and managed by selecting **Management center** in the [Azure AI Foundry portal](https://ai.azure.com/)'s navigation menu > **Quota** > **Manage Commitments**.
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### View and edit an existing resource
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In Azure AI Foundry, select **Management center** > **Quota** > **Provisioned** > **Manage commitments** and select a resource with an existing commitment to view/change it.
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## Migrating existing deployments to global or data zone provisioned
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Existing customers of provisioned deployments can choose to migrate to global or data zone provisioned deployments to benefit from the lower deployment minimums, granular scale increments, or differentiated pricing available for these deployment types. To learn more about how global and data zone provisioned deployments handle data processing across Azure geographies, see the Azure OpenAI deployment [data processing documentation](https://aka.ms/aoai/docs/data-processing-locations).
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Two approaches are available for customers to migrate from provisioned deployments to global or data zone provisioned deployments.
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### Zero downtime migration
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The zero downtime migration approach allows customers to migrate their existing provisioned deployments to global or data zone provisioned deployments without interrupting the existing inference traffic on their deployment. This migration approach minimizes workload interruptions, but does require a customer to have multiple coexisting deployments while shifting traffic over. The process to migrate a provisioned deployment using the zero downtime migration approach is as follows:
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- Create a new deployment using the global or data zone provisioned deployment types in the target Azure OpenAI resource.
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- Transition traffic from the existing regional provisioned deployment type to the newly created global or data zone provisioned deployment until all traffic is offloaded from the existing regional provisioned deployment.
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- Once traffic is migrated over to the new deployment, validate that there are no inference requests being processed on the previous provisioned deployment by ensuring the Azure OpenAI Requests metric does not show any API calls made within 5-10 minutes of the inference traffic being migrated over to the new deployment. For more information on this metric, [see the Monitor Azure OpenAI documentation](https://aka.ms/aoai/docs/monitor-azure-openai).
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- Once you confirm that no inference calls have been made, delete the regional provisioned deployment.
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### Migration with downtime
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The migration with downtime approach involves migrating existing provisioned deployments to global or data zone provisioned deployments while stopping any existing inference traffic on the original provisioned deployment. This migration approach does not require coexistence of multiple deployments to support but does require workload interruption to complete. The process to migrate a provisioned deployment using the migration with downtime approach is as follows:
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- Validate that there are no inference requests being processed on the previous provisioned deployment by ensuring the Azure OpenAI Requests metric does not show any API calls made within the last 5-10 minutes. For more information on this metric, [see the Monitor Azure OpenAI documentation](https://aka.ms/aoai/docs/monitor-azure-openai).
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- Once you confirm that no inference calls have been made, delete the regional provisioned deployment.
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- Create a new deployment using the global or data zone deployment types in the target Azure OpenAI resource.
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- Once your new deployment has succeeded, you may resume inference traffic on the new global or data zone deployment.
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## How do I migrate my existing Azure Reservation to the new Azure Reservation products?
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Azure Reservations for Azure OpenAI Service provisioned offers are specific to the provisioned deployment type. If the Azure Reservation purchased does not match the provisioned deployment type, the deployment will default to the hourly payment model. If you choose to migrate to global or data zone provisioned deployments, you might need to purchase a new Azure Reservation for these deployments to support additional discounts. For more information on how to purchase a new Azure Reservation or make changes to an existing Azure Reservation, see the [Azure Reservations for Azure OpenAI Service Provisioned guidance](https://aka.ms/aoai/reservation-transition).

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