Reiki: Serviceability Architecture and Approach for Reduction and Management of Product Service Incidents

There is a significant number of IT failures per year because parts fail, products are used in ways they were not designed for, and humans make errors in using products. These failures result in incidents that product vendors service as a part of the warranty or contracts. Incidents incur significant costs for servicing them, including call centers, parts, and field engineers. Some of the major problems include lack of coherent incident information, leading to inaccurate service diagnosis and inability to forecast failures. At the same time, technology has evolved. Hardware is generally more reliable, failures are moving from hardware to firmware, software, and applications. The scale effect limits human operator engagement, prevents centralized approaches, and expands automation. Traditional ways of handling incidents are not appropriate any more. In this paper we present a set of tools and approaches that enable unified serviceability with self-healing, automated learning, and an analysis engine. Unified serviceability with self-healing results in clean incident data and it reduces criticality of incidents into deferred maintenance. Automated learning produces empirically proven actionable knowledge enabling cost reduction of automated incident resolution. Using clean data and actionable knowledge, the analysis engine helps predict failures and determine trends, resulting in preventive maintenance. Collectively, preventive and deferred maintenance and automated incident service significantly reduce the costs. This way we have aligned incidents cost with the technology trends.