Azure Virtual Machines

Every service eventually needs somewhere to run code. Buying physical servers means guessing capacity up front, spending capital early, and waiting far too long when traffic spikes. It also means you own patching, hardware failures, power, cooling, and replacement cycles.

Before cloud infrastructure, teams had to buy hardware, rack it, cable it, and wait weeks to expand. Virtualization changed that by allowing multiple isolated servers to share the same physical machine. Cloud providers then turned that virtualization layer into an on-demand service, and VMs became the most direct form of 'rent a server instead of owning one'.

Azure VMs run on top of a hypervisor, the software layer that divides one physical machine into many isolated virtual ones. You choose a machine family, an image, disks, and network placement, then Azure boots the instance inside a subnet with security rules around it. A single VM is really a bundle of compute, storage, networking, and availability choices working together.

Virtual Machines and App Service both run application code, but the control surface is different. A VM gives you operating system access, kernel-level changes, and custom middleware at the cost of patching and operations work. App Service removes much of that infrastructure work, but it also narrows how much of the host you can control.

Virtual Machines fit situations where operating system control is part of the job. Migrating existing Windows workloads, installing custom middleware, or running GPU-backed training jobs are common examples. They are common starting points, but they also require an operations model that can absorb patching, security updates, and host-level troubleshooting.