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Author: dlepow

articles/api-management/genai-gateway-capabilities.md

@@ -19,9 +19,9 @@ While generative AI services and their APIs provide powerful capabilities for un
 
 ## Challenges in managing generative AI APIs
 
-One of the main resources you have in Azure OpenAI Service is tokens. Azure OpenAI assigns quota for your model deployments expressed in tokens-per-minute (TPM) which is then distributed across your model consumers - for example, different applications, developer teams, departments within the company, etc.
+One of the main resources you have in Azure OpenAI Service is tokens. Azure OpenAI Service assigns quota for your model deployments expressed in tokens-per-minute (TPM) which is then distributed across your model consumers - for example, different applications, developer teams, departments within the company, etc.
 
-Azure makes it easy to connect a single app to Azure OpenAI Service. Your intelligent application connects to Azure OpenAI Service directly using an API key with a TPM limit configured directly on the model deployment level. However, when you start growing your application portfolio, you are presented with multiple apps calling single or even multiple Azure OpenAI Service endpoints deployed as pay-as-you-go or [Provisioned Throughput Units](../ai-services/openai/concepts/provisioned-throughput.md) (PTU) instances. That comes with certain challenges: 
+Azure makes it easy to connect a single app to Azure OpenAI Service: you can connect directly using an API key with a TPM limit configured directly on the model deployment level. However, when you start growing your application portfolio, you are presented with multiple apps calling single or even multiple Azure OpenAI Service endpoints deployed as pay-as-you-go or [Provisioned Throughput Units](../ai-services/openai/concepts/provisioned-throughput.md) (PTU) instances. That comes with certain challenges: 
 
 * How is token usage tracked across multiple applications? Can cross charges be calculated for multiple applications/teams that use Azure OpenAI Service models? 
 * How do you ensure that a single app doesn't consume the whole TPM quota, leaving other apps with no option to use Azure OpenAI Service models? 
@@ -95,9 +95,14 @@ In API Management, enable semantic caching by using Azure Redis Enterprise or an
 * [Azure API Management (APIM) - Azure Open AI Sample (Node.js)](https://github.com/Azure-Samples/genai-gateway-apim)
 * [Python sample code for using Azure OpenAI with API Management](https://github.com/Azure-Samples/openai-apim-lb/blob/main/docs/sample-code.md)
 
+## Architecture and design considerations
+
+* [GenAI gateway reference architecture using API Management](/ai/playbook/technology-guidance/generative-ai/dev-starters/genai-gateway/reference-architectures/apim-based)
+* [Designing and implementing a gateway solution with Azure OpenAI resources](/ai/playbook/technology-guidance/generative-ai/dev-starters/genai-gateway/)
+* [Use a gateway in front of multiple Azure OpenAI deployments or instances](/azure/architecture/ai-ml/guide/azure-openai-gateway-multi-backend)
+
 ## Related content
 
 * [Blog: Introducing GenAI capabilities in Azure API Management](https://techcommunity.microsoft.com/t5/azure-integration-services-blog/introducing-genai-gateway-capabilities-in-azure-api-management/ba-p/4146525)
-* [Designing and implementing a gateway solution with Azure OpenAI resources](/ai/playbook/technology-guidance/generative-ai/dev-starters/genai-gateway/)
 * [Smart load balancing for OpenAI endpoints and Azure API Management](https://techcommunity.microsoft.com/t5/fasttrack-for-azure/smart-load-balancing-for-openai-endpoints-and-azure-api/ba-p/3991616)
 * [Authenticate and authorize access to Azure OpenAI APIs using Azure API Management](api-management-authenticate-authorize-azure-openai.md)