Creating Azure AI resources is a fundamental skill for Azure AI Engineers. Azure AI resources are cloud-based services that enable developers to build intelligent applications using pre-built AI capabilities. To create these resources, you typically use the Azure portal, Azure CLI, PowerShell, or A…Creating Azure AI resources is a fundamental skill for Azure AI Engineers. Azure AI resources are cloud-based services that enable developers to build intelligent applications using pre-built AI capabilities. To create these resources, you typically use the Azure portal, Azure CLI, PowerShell, or ARM templates. The process begins by signing into your Azure subscription and navigating to the Azure portal. From there, you select 'Create a resource' and search for the specific AI service you need, such as Azure Cognitive Services, Azure Machine Learning, or Azure OpenAI Service. When configuring an Azure AI resource, you must specify several key parameters. First, choose your subscription and resource group, which helps organize and manage related resources together. Next, select the region where your resource will be deployed, considering factors like latency, compliance requirements, and service availability. You also need to provide a unique name for your resource and select the appropriate pricing tier based on your expected usage and budget. For Cognitive Services, you can create either a multi-service resource that provides access to multiple AI capabilities under a single endpoint and key, or single-service resources dedicated to specific functionalities like Computer Vision, Speech, or Language services. Security considerations are essential when creating AI resources. You should configure authentication using keys or Azure Active Directory, set up virtual networks for network isolation, and implement managed identities where possible. Additionally, enabling diagnostic logging helps monitor usage and troubleshoot issues. After creation, you receive endpoint URLs and access keys needed to integrate the AI services into your applications. Best practices include storing these credentials securely in Azure Key Vault, implementing proper access controls using Role-Based Access Control, and monitoring resource usage through Azure Monitor to optimize costs and performance.
Creating Azure AI Resources
Why is Creating Azure AI Resources Important?
Creating Azure AI resources is fundamental to building any AI solution on the Microsoft Azure platform. Understanding how to properly provision, configure, and manage these resources is essential for the AI-102 exam because it forms the foundation upon which all Azure AI services operate. Proper resource creation ensures optimal performance, cost management, security compliance, and scalability of your AI solutions.
What are Azure AI Resources?
Azure AI resources are cloud-based services that provide artificial intelligence capabilities. These include:
• Azure AI Services (formerly Cognitive Services) - A multi-service resource that provides access to multiple AI capabilities under a single endpoint and key • Single-service resources - Individual resources for specific services like Computer Vision, Language, Speech, etc. • Azure OpenAI Service - Resources for accessing GPT models and other OpenAI capabilities • Azure Machine Learning workspaces - Resources for custom ML model development and deployment
How Resource Creation Works
Methods of Creation:
1. Azure Portal - The graphical interface where you can create resources through a guided wizard 2. Azure CLI - Command-line tool using commands like az cognitiveservices account create 3. Azure PowerShell - Using cmdlets like New-AzCognitiveServicesAccount 4. ARM Templates - JSON-based infrastructure as code for repeatable deployments 5. Bicep - A domain-specific language that compiles to ARM templates 6. REST API - Programmatic creation through Azure Resource Manager API
Key Configuration Options:
• Subscription - The Azure subscription to bill the resource against • Resource Group - Logical container for organizing related resources • Region - The geographic location where the resource is deployed • Pricing Tier - Determines capabilities, limits, and costs (Free, Standard, Premium) • Network Settings - Public access, private endpoints, or virtual network integration • Managed Identity - System-assigned or user-assigned identities for secure authentication
Multi-Service vs Single-Service Resources
Multi-service resource: • One endpoint and key for multiple services • Simplified management and billing • Good for solutions using multiple AI capabilities
Single-service resource: • Dedicated endpoint for one specific service • Required for certain services like Custom Vision training • Better for tracking usage of individual services • Some features require single-service resources
Exam Tips: Answering Questions on Creating Azure AI Resources
1. Know the pricing tiers - Understand that Free tier has limitations on transactions per second and total calls. Questions often test whether you know when to upgrade to Standard tier.
2. Understand regional availability - Not all services are available in all regions. Be aware that you should select regions based on data residency requirements and service availability.
3. Remember authentication methods - Resources can use subscription keys or Azure Active Directory (Microsoft Entra ID) authentication. Know when each is appropriate.
4. Multi-service vs single-service decisions - When a question mentions needing to track billing per service separately, single-service resources are preferred. When simplicity is emphasized, multi-service is the answer.
5. Network security questions - If a question mentions restricting access to specific networks or compliance requirements, look for answers involving private endpoints or virtual network service endpoints.
6. Infrastructure as Code - Questions about repeatable deployments or DevOps scenarios typically require ARM templates or Bicep as the answer.
7. Resource naming - Resource names must be unique within the Azure region and follow naming conventions. Names affect the endpoint URL.
8. Key rotation - Azure AI resources have two keys to allow rotation with zero downtime. Understand this concept for security-related questions.
9. Managed Identity preference - When questions involve secure access patterns, managed identities are generally preferred over storing keys in configuration.