How to build a digital twin that stays fast, safe, and scalable

What if a system could mirror its complete state, predict issues before they occur, and simulate future behavior using live data? This is the foundation of digital twins: virtual models that remain continuously in sync with real systems to support visibility, analysis, and decision-making.

A digital twin first emerged as a virtual copy of a real-world object, like a machine or a building. But now, the idea has gained traction. People use digital twins for more than just physical objects. They also use them for things like software, cloud services, or any kind of complex system.

No matter what it’s used for, the main idea stays the same: