A self-healing system is an always-on operation running 24/7. Self-healing systems can prevent software problems by addressing causes before they turn into problems which impact service. A self-healing enterprise should have predictability to detect signals for potential issues, isolate those issues with precision, determine root causes and resolve them automatically before they lead to service disruption or degradation. All of this is enabled and enhanced by AI-driven autonomous IT operations software.
Self-healing systems have foresight allowing them to predict where issues might arise in the future, saving IT teams both time and expensive resources. Self-healing enterprises can capture value from three drivers by elevating user experience, optimizing resources and ensuring business continuity.
A self-healing enterprise can record material improvements in its customer experience compared to its peers. Self-healing systems can reduce unplanned outages leading to improvement of brand perception and protection. They can also eliminate performance issues from the online user journey. Finally, high transaction businesses such as e-commerce, banking, telecommunications and pay per use services can increase their customer acquisition by reducing user abandonment.
A self-healing organization can be created in three steps. First, once implemented, AI can learn the ins and outs of capacity models and then maintain them. It can determine underutilized or overutilized software components and adjust to the environment and its context. AI can simulate expected workload changes based on growth projections. This first stage is commonly referred to as projected healing with use of AI-assisted prevention.
Second, AI predicts issues by proactively analyzing software modules to look for early warning signals. This analysis highlights the most important performance metrics and includes forensics data helping triage the cause of early warning signals. These analyses inform proactive healing actions e.g., adjusting system configurations or writing additional scripts to automatically heal the issues. This second stage is commonly referred to as proactive self-healing.
Third, autonomous self-healing augments all the capabilities from the first two levels, adds independent action. At this stage, an enterprise can execute the entire healing cycle automatically by detecting warning signals, predicting problems and rectifying the issues which caused the warning signals in the fi
By Nitin Kumar, CMC, CMAA
Keywords: AI, Digital Disruption, Digital Transformation