How to scale GenAI apps built on Azure AI services
Blog post from Portkey
Azure AI services are increasingly popular for enterprises diving into generative AI, with Azure OpenAI experiencing significant growth and being utilized by over half of the Fortune 500 companies. The Azure AI ecosystem offers access to powerful models like GPT-4, along with features critical for businesses, such as data privacy, regional deployment, and safety controls. The introduction of Azure AI Foundry and Azure AI content safety enhances the framework, offering extensive model access and reliable safety measures. However, scaling AI applications on Azure presents challenges, including cost management, governance, and developer velocity, especially when teams rely on multiple Azure subscriptions to isolate budgets and monitor usage. Portkey emerges as a solution by providing a centralized control layer that integrates seamlessly with Azure's infrastructure, enabling observability, cost control, and safe AI operations while supporting tools like the OpenAI C# SDK and Microsoft's Semantic Kernel. It allows enterprises to manage AI workloads efficiently without the need for numerous subscriptions, offering features like virtual keys for consumption management, role-based access control, and real-time analytics, thus facilitating innovation and operational efficiency in Azure's AI landscape.
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