Self healing in artificial intelligence

Self healing in artificial intelligence
Cuneyt Buyukbezci
19 May, 2020

The world has become digitally connected to a degree that few probably ever imagined possible. With the rise of the always connected user and consumer, it can often seem like every business is becoming a software driven organization, open 24/7. The effect of this digitisation is clear -- to stay ahead of the competition digital enterprises must elevate their user experience and eliminate disruptions from their UI flow.

There have been a lot of advances recently in AI-driven autonomous information technology (IT) operations and while these monitoring tools are powerful, there’s a new tool that’s even better -- self-healing software which detects and resolves problems before they ever happen. 

It’s a giant breakthrough, one that offers huge advantages, but any enterprise which wants to update its systems to become self-healing must consider adopting the following tools.

A digital enterprise must have several essential capabilities in order to become self-healing. 

The first of those vital capabilities is a predictive and preventive approach to problem solving. A predictive capability equates to foreseeing issues in advance and knowing what to fix even when there isn’t yet a clear problem. In this model, a system looks at signals and makes a judgment on where there might be a problem in the future.

Such a predictive system is extremely advantageous as it resolves problems before they ever cause congestion or outright failure. The self healing process is fast. However, for it to work correctly there must be a pre-programmed automated action that can be implemented as soon as a bug is discovered. 

Rectifications can happen in several forms. An AI can assist a human technician in taking action, i.e. the machine provides the recipe but the human fixes the problem. Or, AI can take action and rectify the issue of its own accord.

Next up, for a self-healing system to function properly, it needs to have information about each layer in an enterprise stack, from edge to cloud. These layers all ‘talk’ to each other and to function properly a self-healing enterprise must understand how those interactions are architected. For instance, an understanding of the context i.e. seasonality and transactional behavior.

Experience also plays a key role in the functioning of a self healing system. Picture an IT operations expert who has been working in the same environment for years. When part of an application has a performance issue he or she may judge that the degradation is an indication of a problem because last time, in a similar scenario, the degradation was avoided. To perform well, a self healing system must have access to the same historical data points that a human technician does.

Finally, for an organization to fully create a self healing enterprise system it is necessary to have a programme that is capable of autonomously finding a problem and fixing it. Once a self healing system finds the root cause of a problem it should have the capability to propose a solution and subsequently eliminate the issue. 

While a self healing system can find a bug and then have a human technician implement a fix, this tends to be slower than having the system itself resolve the issue.

A self healing system takes any IT operation to a whole new level, one where problems are solved autonomously. Not only does this free up technicians to focus on less menial tasks, but it also speeds up the response time and decreases the chance that a user will experience an interruption in their service. 

It’s a win-win for the consumer and the organization. Self healing enterprises are on the cutting edge of AI implementation. Are you ready to upgrade your network to the next level?

Cuneyt Buyukbezci

Cuneyt Buyukbezci

Cuneyt Buyukbezci is chief marketing officer at Appnomic. The views in this article are his own.