Tag: Azure OpenAI
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Azure OpenAI Distillation and Stored Completions (Azure Gen AI Series, Part 17)
Capture production traffic with store=True, then distill a small Azure OpenAI model that answers like a flagship. The workflow, the real costs, and the traffic volume where it pays off.
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Fine-Tuning Azure OpenAI, from SFT to DPO and RFT (Azure Gen AI Series, Part 16)
SFT, DPO, and RFT on Azure OpenAI: which models take which method, what the training and hosting actually cost, and how to read the loss curve before you deploy.
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Calling Azure OpenAI Models with REST, the SDKs, and the Responses API (Azure Gen AI Series, Part 11)
Azure gives you three ways to call a model, and they are not interchangeable. How Chat Completions, the Responses API, and raw REST differ, and when to pick each on the v1 path.
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Azure OpenAI Entra ID Authentication, Managed Identities, and Encryption (Azure Gen AI Series, Part 10)
Move Azure OpenAI off static API keys to Microsoft Entra ID and managed identities, disable local auth without locking yourself out, and know when customer-managed keys are worth the cost.
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Azure OpenAI Private Link and VNet Isolation (Azure Gen AI Series, Part 9)
Private networking for Azure OpenAI, done in the right order: private endpoints, the DNS zones that make them work, when a managed VNet earns its keep, and the On Your Data trap that closes every call.
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Azure OpenAI Regions, Quotas, and Data Zones (Azure Gen AI Series, Part 8)
Azure OpenAI quota is a grid: per region, per subscription, per model, per deployment type. Here are the real 2026 numbers, the new quota tiers, how data zones change residency, and the two commands I run before promising any capacity.
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Azure OpenAI Deployment Types, Standard vs PTU vs Batch (Azure Gen AI Series, Part 6)
Standard, provisioned throughput units, and Batch are the three ways to bill an Azure OpenAI deployment. How to pick with a utilization break-even, size PTUs, and use spillover so you are not throttled or overpaying.
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Azure OpenAI vs Foundry vs Azure Machine Learning, and Which One Your Project Belongs In (Azure Gen AI Series, Part 5)
Azure OpenAI, Microsoft Foundry, and Azure Machine Learning look interchangeable and are not. A practical guide to which resource your project belongs in, and how to move between them without a rebuild.
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Azure OpenAI in Foundry Models, and How to Choose One (Azure Gen AI Series, Part 3)
Azure OpenAI in Foundry Models is the set of OpenAI models you deploy inside a Foundry resource. Here is which models you get in 2026, how to pick one, and how the call goes out with the v1 API.
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Azure AI Foundry Platform and Foundry Projects Explained (Azure Gen AI Series, Part 2)
Microsoft renamed Azure AI Foundry and rebuilt it around one resource, projects, and a single SDK. Here is what the platform is, how projects work, and your first API call against it.
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Azure Generative AI Stack, End to End (Azure Gen AI Series, Part 1)
The whole Azure generative AI stack in one map: Azure AI Foundry, the model catalog, the three deployment types that decide your bill, retrieval, agents, and the compute underneath. Where to start and what to skip.
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About the Author
Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
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