Microsoft Azure

Microsoft Azure is Microsoft’s cloud computing platform. It rents out virtual machines, storage, databases, and AI services over the internet, on a pay-as-you-go basis, across a global network of datacenters that Microsoft builds and maintains. Launched in 2010, Azure now offers more than 200 products and services and is used by 95% of Fortune 500 companies. For AI developers, Azure matters because it hosts Azure OpenAI Service and Azure AI Foundry, the managed platforms most enterprise generative AI applications run on.

How Microsoft Azure works

Azure delivers cloud computing in four forms, letting you choose how much of the underlying infrastructure you manage yourself.

• Infrastructure as a service (IaaS): you rent raw virtual machines and storage, and manage the operating system and software yourself, similar to running your own server without owning the hardware.
• Platform as a service (PaaS): Azure manages the underlying infrastructure, so you deploy code directly without configuring servers, useful for web apps and databases.
• Software as a service (SaaS): fully managed applications, like Microsoft 365, run on Azure’s infrastructure with no setup required from the user.
• Serverless functions: Azure Functions run your code only when triggered by an event, and you pay only for the compute time actually used.
• AI services: Azure OpenAI Service gives developers API access to GPT and DALL·E models with enterprise-grade security, while Azure AI Foundry adds tools for building, evaluating, and governing AI agents.
• Billing: every service is metered, so you pay per hour, per gigabyte, or per request, with discounts available for reserved capacity.

What you can build with Microsoft Azure

• Enterprise chatbots and copilots: connect Azure OpenAI Service to your company’s data to build assistants that answer questions using your own documents and records.
• Document intelligence pipelines: use Azure AI to extract structured data from claims, contracts, or invoices, cutting down manual data entry work.
• Production web applications: deploy an app on Azure App Service or Azure Kubernetes Service, backed by Azure SQL Database, scaling automatically as traffic grows.
• Hybrid cloud systems: extend an existing on-premises Windows Server or Active Directory setup into the cloud without rebuilding your identity and access management from scratch.
• Real-time voice and translation tools: build multilingual customer support or live-event translation using Azure’s realtime speech and transcription models.
• Custom AI agents: use Azure AI Foundry to build, test, and deploy agents that automate tasks like customer support summarization or claims processing.