acrolinx fixes

Author: aahill

articles/ai-services/openai/how-to/provisioned-throughput-onboarding.md

@@ -15,20 +15,20 @@ recommendations: false
 Use this article to learn about calculating and understanding costs associated with PTU. For an overview of the provisioned throughput offering, see [What is provisioned throughput?](../concepts/provisioned-throughput.md). When you're ready to sign up for the provisioned throughput offering, see the [getting started guide](./provisioned-get-started.md).
 
 > [!NOTE]
-> In function calling and agent use cases, token usage can be variable. You should understand your expected Tokens Per Minute (TPM) usage in detail prior to migrating workloads to PTU.
+> In function calling and agent use cases, token usage can be variable. You should understand your expected Tokens Per Minute (TPM) usage in detail before migrating workloads to PTU.
 
 ## Provisioned throughput units
 
-Provisioned throughput units (PTUs) are generic units of model processing capacity that you can use to size provisioned deployments to achieve the required throughput for processing prompts and generating completions.   Provisioned throughput units are granted to a subscription as quota. Each quota is specific to a region and defines  the maximum number of PTUs that can be assigned to deployments in that subscription and region.
+Provisioned throughput units (PTUs) are generic units of model processing capacity that you can use to size provisioned deployments to achieve the required throughput for processing prompts and generating completions.  Provisioned throughput units are granted to a subscription as quota. Each quota is specific to a region and defines  the maximum number of PTUs that can be assigned to deployments in that subscription and region.
 
 ## Understanding provisioned throughput billing
 
-Azure OpenAI [Provisioned](../how-to/deployment-types.md#provisioned), [Data Zone Provisioned](../how-to/deployment-types.md#data-zone-provisioned) (also known as regional), and [Global Provisioned](../how-to/deployment-types.md#global-provisioned) are purchased on-demand at an hourly basis based on the number of deployed PTUs, with substantial term discount available via the purchase of [Azure Reservations](#azure-reservations-for-azure-openai-provisioned-deployments).   
+Azure OpenAI [Provisioned](../how-to/deployment-types.md#provisioned), [Data Zone Provisioned](../how-to/deployment-types.md#data-zone-provisioned) (also known as regional), and [Global Provisioned](../how-to/deployment-types.md#global-provisioned) are purchased on-demand at an hourly basis based on the number of deployed PTUs, with substantial term discount available via the purchase of [Azure Reservations](#azure-reservations-for-azure-openai-provisioned-deployments).  
 
 The hourly model is useful for short-term deployment needs, such as validating new models or acquiring capacity for a hackathon.  However, the discounts provided by the Azure Reservation for Azure OpenAI Provisioned, Data Zone Provisioned, and Global Provisioned are considerable and most customers with consistent long-term usage will find a reserved model to be a better value proposition. 
 
 > [!NOTE]
-> Azure OpenAI Provisioned customers onboarded prior to the August self-service update use a purchase model called the Commitment model.  These customers can continue to use this older purchase model alongside the Hourly/reservation purchase model.  The Commitment model is not available for new customers or [certain new models](../concepts/provisioned-migration.md#supported-models-on-commitment-payment-model) introduced after August 2024.  For details on the Commitment purchase model and options for coexistence and migration, please see the [Azure OpenAI Provisioned August Update](../concepts/provisioned-migration.md).
+> Azure OpenAI Provisioned customers onboarded prior to the August self-service update use a purchase model called the Commitment model. These customers can continue to use this older purchase model alongside the Hourly/reservation purchase model. The Commitment model is not available for new customers or [certain new models](../concepts/provisioned-migration.md#supported-models-on-commitment-payment-model) introduced after August 2024. For details on the Commitment purchase model and options for coexistence and migration, see the [Azure OpenAI Provisioned August Update](../concepts/provisioned-migration.md).
 
 
 ## Model independent quota
@@ -57,7 +57,7 @@ Provisioned, Data Zone Provisioned, and Global Provisioned deployments are charg
 
 If a deployment exists for a partial hour, it will receive a prorated charge based on the number of minutes it was deployed during the hour.  For example, a deployment that exists for 15 minutes during an hour will receive 1/4th the hourly charge.  
 
-If the deployment size is changed, the costs of the deployment will adjust to match the new number of PTUs.   
+If the deployment size is changed, the costs of the deployment will adjust to match the new number of PTUs.  
 
 :::image type="content" source="../media/provisioned/hourly-billing.png" alt-text="A diagram showing hourly billing." lightbox="../media/provisioned/hourly-billing.png":::
 
@@ -66,10 +66,10 @@ Paying for provisioned, data zoned provisioned, and global provisioned deploymen
 Customers that require long-term usage of provisioned, data zoned provisioned, and global provisioned deployments, however, might pay significantly less per month by purchasing a term discount via [Azure Reservations](#azure-reservations-for-azure-openai-provisioned-deployments) as discussed later in the article. 
 
 > [!IMPORTANT]
-> It is not recommended to scale production deployments according to incoming traffic and pay for them purely on an hourly basis. There are two reasons for this:
+> It's not recommended to scale production deployments according to incoming traffic and pay for them purely on an hourly basis. There are two reasons for this:
 > * The cost savings achieved by purchasing Azure Reservations for Azure OpenAI Provisioned, Data Zone Provisioned, and Global Provisioned are significant, and it will be less expensive in many cases to maintain a deployment sized for full production volume paid for via a reservation than it would be to scale the deployment with incoming traffic.
-> * Having unused provisioned quota (PTUs) does not guarantee that capacity will be available to support an increase in the size of the deployment when required. Quota limits the maximum number of PTUs that can be deployed, but it is not a capacity guarantee. Provisioned capacity for each region and model dynamically changes throughout the day and might not be available when required. As a result, it is recommended to maintain a permanent deployment to cover your traffic needs (paid for via a reservation).
-> Charges for deployments on a deleted resource will continue until the resource is purged.  To prevent this, delete a resource’s deployment before deleting the resource.  For more information, see [Recover or purge deleted Azure AI services resources](../../recover-purge-resources.md). 
+> * Having unused provisioned quota (PTUs) doesn't guarantee that capacity will be available to support an increase in the size of the deployment when required. Quota limits the maximum number of PTUs that can be deployed, but it isn't a capacity guarantee. Provisioned capacity for each region and model dynamically changes throughout the day and might not be available when required. As a result, it's recommended to maintain a permanent deployment to cover your traffic needs (paid for via a reservation).
+> Charges for deployments on a deleted resource will continue until the resource is purged. To prevent this, delete a resource’s deployment before deleting the resource. For more information, see [Recover or purge deleted Azure AI services resources](../../recover-purge-resources.md). 
 
 ## How much throughput per PTU you get for each model
 The amount of throughput (measured in tokens per minute or TPM) a deployment gets per PTU is a function of the input and output tokens in a given minute. 
@@ -78,7 +78,7 @@ Generating output tokens requires more processing than input tokens. For the mod
 
 To help with simplifying the sizing effort, the following table outlines the TPM-per-PTU for the specified models. To understand the impact of output tokens on the TPM-per-PTU limit, use the 3 input token to 1 output token ratio. 
 
-For a detailed understanding of how different ratios of input and output tokens impact the throughput your workload needs, see the [Azure OpenAI capacity calculator](https://ai.azure.com/resource/calculator). The table also shows Service Level Agreement (SLA) Latency Target Values per model.  For more information about the SLA for Azure OpenAI Service, see the [Service Level Agreements (SLA) for Online Services page](https://www.microsoft.com/licensing/docs/view/Service-Level-Agreements-SLA-for-Online-Services?lang=1)
+For a detailed understanding of how different ratios of input and output tokens impact the throughput your workload needs, see the [Azure OpenAI capacity calculator](https://ai.azure.com/resource/calculator). The table also shows Service Level Agreement (SLA) Latency Target Values per model. For more information about the SLA for Azure OpenAI Service, see the [Service Level Agreements (SLA) for Online Services page](https://www.microsoft.com/licensing/docs/view/Service-Level-Agreements-SLA-for-Online-Services?lang=1)
 
 
 |Topic| **gpt-4o**   | **gpt-4o-mini**  | **o1**|
@@ -90,7 +90,7 @@ For a detailed understanding of how different ratios of input and output tokens
 |Input TPM per PTU |2,500|37,000|230|
 |Latency Target Value |25 Tokens Per Second|33 Tokens Per Second|25 Tokens Per Second|
 
-For a full list see the [Azure OpenAI Service in Azure AI Foundry portal calculator](https://ai.azure.com/resource/calculator).
+For a full list, see the [Azure OpenAI Service in Azure AI Foundry portal calculator](https://ai.azure.com/resource/calculator).
 
 ## Determining the number of PTUs needed for a workload
 
@@ -157,26 +157,26 @@ Discounts on top of the hourly usage price can be obtained by purchasing an Azur
 
     * All subscriptions in a billing account 
 
-* New reservations can be purchased to cover the same scope as existing reservations, to allow for discounting of new provisioned deployments.  The scope of existing reservations can also be updated at any time without penalty, for example to cover a new subscription. 
+* New reservations can be purchased to cover the same scope as existing reservations, to allow for discounting of new provisioned deployments. The scope of existing reservations can also be updated at any time without penalty, for example to cover a new subscription. 
 
 * Reservations for Global, Data Zone, and Regional deployments aren't interchangeable. You need to purchase a separate reservation for each deployment type. 
 
-* Reservations can be canceled after purchase, but credits are limited.   
+* Reservations can be canceled after purchase, but credits are limited.  
 
 * If the size of provisioned deployments within the scope of a reservation exceeds the amount of the reservation, the excess is charged at the hourly rate. For example, if deployments amounting to 250 PTUs exist within the scope of a 200 PTU reservation, 50 PTUs will be charged on an hourly basis until the deployment sizes are reduced to 200 PTUs, or a new reservation is created to cover the remaining 50. 
 
 * Reservations guarantee a discounted price for the selected term.  They don't reserve capacity on the service or guarantee that it will be available when a deployment is created. It's highly recommended that customers create deployments prior to purchasing a reservation to prevent from over-purchasing a reservation. 
 
 > [!IMPORTANT] 
-> * Capacity availability for model deployments is dynamic and changes frequently across regions and models.  To prevent you from purchasing a reservation for more PTUs than you can use, create deployments first, and then purchase the Azure Reservation to cover the PTUs you have deployed.  This best practice will ensure that you can take full advantage of the reservation discount and prevent you from purchasing a term commitment that you cannot use. 
+> * Capacity availability for model deployments is dynamic and changes frequently across regions and models. To prevent you from purchasing a reservation for more PTUs than you can use, create deployments first, and then purchase the Azure Reservation to cover the PTUs you have deployed. This best practice will ensure that you can take full advantage of the reservation discount and prevent you from purchasing a term commitment that you cannot use. 
 >
-> * The Azure role and tenant policy requirements to purchase a reservation are different than those required to create a deployment or Azure OpenAI resource.  Verify authorization to purchase reservations in advance of needing to do so. See Azure OpenAI [Provisioned reservation documentation](https://aka.ms/oai/docs/ptum-reservations) for more details.
+> * The Azure role and tenant policy requirements to purchase a reservation are different than those required to create a deployment or Azure OpenAI resource. Verify authorization to purchase reservations in advance of needing to do so. See Azure OpenAI [Provisioned reservation documentation](https://aka.ms/oai/docs/ptum-reservations) for more details.
 
 ## Important: sizing Azure OpenAI provisioned reservations
 
-The PTU amounts in reservation purchases are independent of PTUs allocated in quota or used in deployments. It's possible to purchase a reservation for more PTUs than you have in quota, or can deploy for the desired region, model, or version.   Credits for over-purchasing a reservation are limited, and customers must take steps to ensure they maintain their reservation sizes in line with their deployed PTUs.  
+The PTU amounts in reservation purchases are independent of PTUs allocated in quota or used in deployments. It's possible to purchase a reservation for more PTUs than you have in quota, or can deploy for the desired region, model, or version. Credits for over-purchasing a reservation are limited, and customers must take steps to ensure they maintain their reservation sizes in line with their deployed PTUs. 
 
-The best practice is to always purchase a reservation after deployments have been created.  This prevents purchasing a reservation and then finding out that the required capacity isn't available for the desired region or model. 
+The best practice is to always purchase a reservation after deployments have been created. This prevents purchasing a reservation and then finding out that the required capacity isn't available for the desired region or model. 
 
 
 Reservations for Global, Data Zone, and Regional deployments aren't interchangeable. You need to purchase a separate reservation for each deployment type.
@@ -187,7 +187,7 @@ To assist customers with purchasing the correct reservation amounts. The total n
 
 Managing Azure Reservations 
 
-After a reservation is created, it is a best practice monitor it to ensure it is receiving the usage you're expecting.  This can be done via the Azure Reservation Portal or Azure Monitor.  Details on these articles and others can be found here: 
+After a reservation is created, it is a best practice monitor it to ensure it is receiving the usage you're expecting. This can be done via the Azure Reservation Portal or Azure Monitor. Details on these articles and others can be found here: 
 
 * [View Azure reservation utilization](/azure/cost-management-billing/reservations/reservation-utilization) 
 * [View Azure Reservation purchase and refund transactions](/azure/cost-management-billing/reservations/view-purchase-refunds)