Introduction
This article delves into the AI Studio offerings, providing an in-depth exploration of its architecture components, such as the AI Studio Hub, AI Studio Project, and associated Azure resources.
AI Studio offers a seamless experience for AI developers and data scientists to create, assess, and deploy AI models using a web portal, SDK, or CLI. It leverages the features and services of various Azure offerings.
Azure AI Studio Architecture Components
The primary AI Studio resources, including the hub and project, are built on Azure Machine Learning. Additionally, the hub and project utilize other resources like Azure OpenAI, Azure AI services, and Azure AI Search.
![Azure AI]()
AI Studio Hub
The hub is the primary resource in AI Studio. It is managed by the Azure resource provider Microsoft.MachineLearningServices/workspaces and categorized as a Hub resource. It offers the following features.
- Data upload and artifact storage
- Hub-scoped connections to Azure services, including Azure OpenAI, Azure AI services, and Azure AI Search
- Base model endpoints for Azure OpenAI, Speech, and Vision
- Compute resources
- Security and governance
AI Studio Project
A project is a subordinate resource to the hub. It is managed by the Azure resource provider Microsoft.MachineLearningServices/workspaces and classified as a Project resource. Projects inherit the hub's connections and compute resources. When a new project is created from the hub, it adopts the hub's security settings. The project includes the following features.
- Groups of components such as datasets, models, and indexes
- An isolated data container (within the storage inherited from the hub)
- Project-scoped connections, such as access to data stored in a separate Azure Storage account
- Open-source model deployments from the catalog and fine-tuned model endpoints
Associated Azure resources
You can create an Azure AI hub in Azure AI Studio either on the Manage page or during the process of creating a new project on the Build page. When you create a hub, an AI hub resource is established in your Azure subscription within the resource group you specify, offering a collaborative workspace for AI development.
In addition to the core AI hub resource, other supporting Azure resources are created, including.
- A Storage account for securely storing data for your AI projects
- A Key Vault for securing credentials used to access external resources and other sensitive information
- A Container Registry for storing Docker images used by your AI solutions
- An Application Insights resource for recording usage and performance metrics
- An Azure OpenAI Service resource that provides generative AI models for your applications
Summary
This article has provided a comprehensive understanding of the Azure AI Studio Architecture, including its core features and capabilities. Azure AI Studio consolidates functionalities from Azure Machine Learning, Azure OpenAI service, and various other Azure AI services to establish a unified workspace. Here, developers can seamlessly collaborate with data scientists and other stakeholders to develop AI solutions.
Hope you have enjoyed reading this article!!
Happy Learning!