Imagine you’re about to build something amazing with Azure AI. Before you dive into writing code or training models, there’s one big question: how do you set up your AI resources? This step might feel like just a checkbox, but it’s the foundation of how your application will scale, perform, and even stay within budget.
Let’s walk through the key things you should consider.
Getting Started with Resources
When you use Azure AI services, the first step is to create one or more AI resources in your Azure subscription. You can spin them up easily through the Azure portal, CLI, Bicep, or ARM templates. Once they’re ready, you can connect to them directly through APIs and SDKs. For some services, like Custom Vision, Azure even gives you a web-based interface to train and test models without writing code.
Centralized or Standalone?
Here’s where choices come in. For small projects, standalone resources like Azure AI Vision or Azure AI Language might be enough. They often come with free tiers so you can experiment without worrying about costs. Each standalone service has its own endpoint and keys, making them secure and independent.
But if your application needs multiple AI capabilities, say OpenAI for text generation, Speech for voice, and Vision for images, you may want a multi-service resource. It bundles several AI services into one, simplifying management and access. This becomes especially powerful in larger projects where shared resources and cost tracking are critical.
Watch Out for the Icons
In the Azure portal, you might notice two resource types with similar names. Always look for the Azure AI services icon, which includes the latest AI offerings like OpenAI and Content Understanding. The older Cognitive Services option still exists but doesn’t support these newer tools.
Regional Availability
Not all AI services are available in every Azure region. Some models, especially in Azure OpenAI, are restricted to specific regions. Before provisioning, check the product availability tables to avoid surprises.
Cost Matters
Azure AI services run on a pay-as-you-go model. Different services have different pricing models, so it’s worth spending a few minutes with the pricing documentation or the Azure pricing calculator. This ensures your great idea won’t come with an unexpected bill.
The Takeaway
Provisioning resources might sound like an admin task, but it shapes how smoothly your AI journey goes. Choosing between standalone or multi-service, checking regions, and planning costs can save you from headaches later. With the right setup, you’re free to focus on what really matters—building intelligent solutions that make an impact.
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