Update provisioned-reservation-update.md

Author: sydneemayers

articles/ai-services/openai/concepts/provisioned-reservation-update.md

@@ -45,27 +45,27 @@ In addition to the updates for the hourly payment model, new Azure Reservations
 | Provisioned | `ProvisionedManaged`  | Provisioned Managed Regional |
 
 > [!IMPORTANT]
-> Azure Reservations for Azure OpenAI Provisioned offers are not interchangeable across deployment types. The Azure Reservation purchased must match the provisioned deployment type. If the Azure Reservation purchased does not match the provisioned deployment type, the provisioned deployment will default to the hourly payment model until a matching Azure Reservation product is purchased. For more information, see the [Azure Reservations for Azure OpenAI Service Provisioned guidance](https://aka.ms/oai/docs/ptum-reservations).
+> Azure Reservations for Azure OpenAI provisioned offers are not interchangeable across deployment types. The Azure Reservation purchased must match the provisioned deployment type. If the Azure Reservation purchased does not match the provisioned deployment type, the provisioned deployment will default to the hourly payment model until a matching Azure Reservation product is purchased. For more information, see the [Azure Reservations for Azure OpenAI Service Provisioned guidance](https://aka.ms/oai/docs/ptum-reservations).
 
 ## Migrating existing deployments to Global or Data zone provisioned
-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).
+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).
 
-Two approaches are available for customers to migrate from provisioned deployments to Global or Data zone provisioned deployments. 
+Two approaches are available for customers to migrate from provisioned deployments to global or data zone provisioned deployments. 
 
 ### Zero downtime migration 
 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 coexist multiple deployments to shift traffic over. The process to migrate a provisioned deployment using the zero downtime migration approach is as follows:
-- Create a new deployment using the `GlobalProvisionedManaged` or `DataZoneProvisionedManaged` deployment types in the target Azure OpenAI resource.
-- Transition traffic from the existing `ProvisionedManaged` deployment type to the newly created `GlobalProvisionedManaged` or `DataZoneProvisionedManaged` deployment until all traffic is offloaded from the existing `ProvisionedManaged` deployment.
-- Once traffic is migrated over to the new deployment, validate that there are no inference requests being processed on the previous `ProvisionedManaged` deployment by ensuring the Azure OpenAI Requests metric ([see Monitor Azure OpenAI](https://aka.ms/aoai/docs/monitor-azure-openai) for more details on this metric) does not show any API calls made within 5-10 minutes of the inference traffic being migrated over to the new deployment.
-- Once you confirm that no inference calls have been made on the previous `ProvisionedManaged` deployment, delete the `ProvisionedManaged` deployment. 
+- Create a new deployment using the global or data zone provisioned deployment types in the target Azure OpenAI resource.
+- 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.
+- 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).
+- Once you confirm that no inference calls have been made, delete the regional provisioned deployment.
 
 ### Migration with downtime 
-The migration with downtime approach involves migrating existing provisioned deployments to Global or Data zone provisioned deployments while stopping any exisitng 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 migration a provisioned deployment using the migration with downtime approach is as follows:
-- Validate that there are no inference requests being processed on the previous `ProvisionedManaged` deployment by ensuring the Azure OpenAI Requests metric ([see Monitor Azure OpenAI](https://aka.ms/aoai/docs/monitor-azure-openai) for more details on this metric) does not show any API calls made within the last 5-10 minutes.
-- Once you confirm that no inference calls have been made on your `ProvisionedManaged` deployment, delete the `ProvisionedManaged` deployment.
-- Create a new deployment using the `GlobalProvisionedManaged` or `DataZoneProvisionedManaged` deployment types in the target Azure OpenAI resource.
-- Once your new deployment has succeeded, you may resume inference traffic on the new `GlobalProvisionedManaged` or `DataZoneProvisionedManaged` deployment.
+The migration with downtime approach involves migrating existing provisioned deployments to global or data zone provisioned deployments while stopping any exisitng 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:
+- 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).
+- Once you confirm that no inference calls have been made, delete the regional provisioned deployment.
+- Create a new deployment using the global or data zone deployment types in the target Azure OpenAI resource.
+- Once your new deployment has succeeded, you may resume inference traffic on the new global or data zone deployment.
 
 ## How do I migrate my existing Azure Reservation to the new Azure Reservation products?
-As noted above, Azure Reservation products for Azure OpenAI Service provisioned will be specific to the provisioned deployment type. If the Azure Reservation purhcased 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 may 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/oai/docs/ptum-reservations).
+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 may 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/oai/docs/ptum-reservations).