If you’ve done or read anything relating to manufacturing or heavy industries (such as transportation or energy) in recent years, you’ve no doubt come across the term “digital twin.” It’s typically defined as a faithful, detailed digital model of a real-world system or process – anything from a consumer product prototype to an entire factory or telecommunications network.
Well, over the last few months, I have been having some interesting discussions with customers and prospects about the “digital twin” concept, explaining how ignio, Digitate’s flagship AIOps platform, fits into the larger digital twin ecosystem.
The short answer: ignio is far more than what the “digital twin” term encompasses. I could almost call it a “digital genie” for its ability to step in and fulfill its owner’s wishes.
As for the full answer… read on.
Digital models make great testing grounds
The advantage of a digital twin is that you can make changes to the virtual version of the system and examine the outcome. It’s a quicker, cheaper, lower-stakes way to test those changes than making them in the physical version. (This parallels software’s move towards agile development, with its smaller, faster feedback loops.)
And the latest generation, smart digital twins, aren’t just passive simulations waiting for a human to set them going. Drawing on AI and machine learning, they can predict outcomes and even make suggestions to fix problems or improve processes. That can help with anything from shrinking the carbon footprint of a future office building to teaching robots how to navigate around a new factory without colliding.
Many of a digital twin’s benefits apply to ignio as well. Our intelligent automation solution, powered by our proprietary AI algorithms, is designed to self-manage IT environments.
Like a digital twin, ignio has the capability to represent an IT environment accurately (mapped via its unique “blueprint” function). It can predict incidents, offer ways to prevent them, and even suggest improvements when permanently resolving a problem requires a change in the IT environment’s design/architecture.
Only digital-to-digital can close the loop seamlessly
However, ignio has an incredible advantage over the digital twin paradigm: ignio can directly self-heal the IT environment because both ignio’s predictive model and the IT environments it operates on exist in the same digital world.
Let me emphasize this point. A classic digital twin is solely a representation of a chunk of physical reality. It can be very accurate in emulating and predicting behavior of mechanical components, whether a jet engine or a human heart.
However, this digital representation isn’t a closed loop. To stay current, it needs a steady flow of data. Plus, whatever changes you want to incorporate into the original, you have to make yourself. That introduces both delay and the possibility of error, which in turn reduces the digital twin’s speed and agility. And that limits its value, because the ability to respond quickly and nimbly is a key success factor in today’s highly volatile business environment.
Not just a tabletop model
By contrast, IT production environments exist only in a digital reality. Yes, they contain physical components – servers, cables, routers, switches, desktop computers, mobile devices, and much more. But those only come alive when connected by the digital components of software and data flows. And when humans view an IT landscape through a screen, the operations they’re viewing are made up of the same 0s and 1s as the images.
This is the major advantage of ignio as a digital twin for IT operations. ignio not only accurately represents and predicts conditions in a given IT environment, it can directly and seamlessly modify them.
For example, the ignio Event Management solution can predict a CPU or memory shortage. It can then automatically draw on the instructions it was installed with to increase CPU or memory before they run out. The ability to directly act on the original is a huge advantage over many digital twins, which are basically sophisticated model train sets.
ignio’s possibilities for managing complex IT environments are endless. Its mapping or blueprinting function lets ignio understand how various IT solutions in each landscape interact. Its observability capacity allows efficient and effective monitoring of the IT environment, and machine learning built into offerings such as Event Management, ignio AIOps, and ignio AI. Workload Management will not just predict how that IT environment will behave but prevent failures from happening.
Rightly seen, ignio is not just a digital “twin” but a wiser “mentor” leading the IT environment to a healthier existence.
The AI built into ignio does not mean that humans will lose control of IT. ignio remains a software platform controlled by knowledgeable IT staff. It frees precious IT resources from repetitive tasks that mere machines, empowering them to make better use of their time, energy, and expertise.
If you are interested in learning more about ignio, please contact your Technical Account Manager. Or if you are not a customer yet, please visit our website and ask for a demo.
