Availability of enterprise IT systems – an expert-based Bayesian model

Ensuring the availability of enterprise IT systems is a challenging task. The factors that can bring systems down are numerous, and their impact on various system architectures is difficult to predict. At the same time, maintaining high availability is crucial in many applications, ranging from control systems in the electric power grid, over electronic trading systems on the stock market to specialized command and control systems for military and civilian purposes. The present paper describes a Bayesian decision support model, designed to help enterprise IT systems decision makers evaluate the consequences of their decisions by analyzing various scenarios. The model is based on expert elicitation from 50 academic experts on IT systems availability, obtained through an electronic survey. The Bayesian model uses a leaky Noisy-OR method to weigh together the expert opinions on 16 factors affecting systems availability. Using this model, the effect of changes to a system can be estimated beforehand, providing decision support for improvement of enterprise IT systems availability. Keywords-Systems availability, High availability, Downtime, Bayesian networks, Noisy-OR, Expert elicitation