Data driven decision making for application support

This paper discusses the design of a solution to enable data driven decision making for application support. The design proposes a novel standard for logging within applications. The next phase of the design proposes a novel method to use the standardized logs to map the functioning of an application to a finite state automata. The analytics proposed in the design helps understand issues during application processing, assess the impact of issues and quickly take decisions to resolve the issues. Big data analytics and probabilistic models are used on the historical application logs to further predict issues prior to their occurrence, assess the health of application functioning and be able to proactively act on situations that can lead to errors.