Merge pull request #2491 from mrbullwinkle/mrb_01_24_2025_deployment_types

[Azure OpenAI] Deployment types SKUs for code

Author: prmerger-automator[bot]

articles/ai-services/openai/how-to/deployment-types.md

@@ -7,7 +7,7 @@ author: mrbullwinkle
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: how-to
-ms.date: 07/11/2024
+ms.date: 01/24/2025
 ms.author: mbullwin
 ---
 
@@ -39,6 +39,8 @@ For any [deployment type](/azure/ai-services/openai/how-to/deployment-types) lab
 > [!IMPORTANT]
 > Data stored at rest remains in the designated Azure geography, while data may be processed for inferencing in any Azure OpenAI location. [Learn more about data residency](https://azure.microsoft.com/explore/global-infrastructure/data-residency/).
 
+**SKU name in code:** `GlobalStandard`
+
 Global deployments are available in the same Azure OpenAI resources as non-global deployment types but allow you to leverage Azure's global infrastructure to dynamically route traffic to the data center with best availability for each request.  Global standard provides the highest default quota and eliminates the need to load balance across multiple resources.  
 
 Customers with high consistent volume may experience greater latency variability. The threshold is set per model. See the [quotas page to learn more](./quota.md).  For applications that require the lower latency variance at large workload usage, we recommend purchasing provisioned throughput.
@@ -48,6 +50,8 @@ Customers with high consistent volume may experience greater latency variability
 > [!IMPORTANT]
 > Data stored at rest remains in the designated Azure geography, while data may be processed for inferencing in any Azure OpenAI location. [Learn more about data residency](https://azure.microsoft.com/explore/global-infrastructure/data-residency/).
 
+**SKU name in code:** `GlobalProvisionedManaged`
+
 Global deployments are available in the same Azure OpenAI resources as non-global deployment types but allow you to leverage Azure's global infrastructure to dynamically route traffic to the data center with best availability for each request. Global provisioned deployments provide reserved model processing capacity for high and predictable throughput using Azure global infrastructure.  
 
 ## Global batch
@@ -57,6 +61,8 @@ Global deployments are available in the same Azure OpenAI resources as non-globa
 
 [Global batch](./batch.md) is designed to handle large-scale and high-volume processing tasks efficiently. Process asynchronous groups of requests with separate quota, with 24-hour target turnaround, at [50% less cost than global standard](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/). With batch processing, rather than send one request at a time you send a large number of requests in a single file. Global batch requests have a separate enqueued token quota avoiding any disruption of your online workloads.  
 
+**SKU name in code:** `GlobalBatch`
+
 Key use cases include:
 
 * **Large-Scale Data Processing:** Quickly analyze extensive datasets in parallel.
@@ -74,9 +80,12 @@ Key use cases include:
 * **Marketing and Personalization:** Generate personalized content and recommendations at scale.
 
 ## Data zone standard
+
 > [!IMPORTANT]
 > Data stored at rest remains in the designated Azure geography, while data may be processed for inferencing in any Azure OpenAI location within the Microsoft specified data zone. [Learn more about data residency](https://azure.microsoft.com/explore/global-infrastructure/data-residency/).
 
+**SKU name in code:** `DataZoneStandard`
+
 Data zone standard deployments are available in the same Azure OpenAI resource as all other Azure OpenAI deployment types but allow you to leverage Azure global infrastructure to dynamically route traffic to the data center within the Microsoft defined data zone with the best availability for each request. Data zone standard provides higher default quotas than our Azure geography-based deployment types. 
 
 Customers with high consistent volume may experience greater latency variability. The threshold is set per model. See the [Quotas and limits](/azure/ai-services/openai/quotas-limits#usage-tiers) page to learn more. For workloads that require low latency variance at large volume, we recommend leveraging the provisioned deployment offerings. 
@@ -86,23 +95,31 @@ Customers with high consistent volume may experience greater latency variability
 > [!IMPORTANT]
 > Data stored at rest remains in the designated Azure geography, while data may be processed for inferencing in any Azure OpenAI location within the Microsoft specified data zone.[Learn more about data residency](https://azure.microsoft.com/explore/global-infrastructure/data-residency/).
 
+**SKU name in code:** `DataZoneProvisionedManaged`
+
 Data zone provisioned deployments are available in the same Azure OpenAI resource as all other Azure OpenAI deployment types but allow you to leverage Azure global infrastructure to dynamically route traffic to the data center within the Microsoft specified data zone with the best availability for each request. Data zone provisioned deployments provide reserved model processing capacity for high and predictable throughput using Azure infrastructure within the Microsoft specified data zone.  
 
 ## Data zone batch
 
 > [!IMPORTANT]
 > Data stored at rest remains in the designated Azure geography, while data may be processed for inferencing in any Azure OpenAI location within the Microsoft specified data zone. [Learn more about data residency](https://azure.microsoft.com/explore/global-infrastructure/data-residency/).
+ 
+**SKU name in code:** `DataZoneBatch`
 
 Data zone batch deployments provide all the same functionality as [global batch deployments](./batch.md) while allowing you to leverage Azure global infrastructure to dynamically route traffic to only data centers within the Microsoft defined data zone with the best availability for each request. 
 
 ## Standard
 
+**SKU name in code:** `Standard`
+
 Standard deployments provide a pay-per-call billing model on the chosen model. Provides the fastest way to get started as you only pay for what you consume. Models available in each region as well as throughput may be limited.  
 
 Standard deployments are optimized for low to medium volume workloads with high burstiness. Customers with high consistent volume may experience greater latency variability.
 
 ## Provisioned
 
+**SKU name in code:** `ProvisionedManaged`
+
 Provisioned deployments allow you to specify the amount of throughput you require in a deployment. The service then allocates the necessary model processing capacity and ensures it's ready for you. Throughput is defined in terms of provisioned throughput units (PTU) which is a normalized way of representing the throughput for your deployment. Each model-version pair requires different amounts of PTU to deploy and provide different amounts of throughput per PTU. Learn more from our [Provisioned throughput concepts article](../concepts/provisioned-throughput.md).
 
 ### How to disable access to global deployments in your subscription