Data Fusion Technique to Predicting Database Performance Issues

Database (DB) stability is a core component of all IT services. Losses from poor performance and unexpected database failures cost millions for companies and take time to recover. In this paper, we introduce a new formalism for finding insight in DB monitoring data, such as performance, query complexity, and events history to increase the ability of the database administrator to respond on different performance issues. A data fusion technique to predict the probability of a critical state of the DB system is proposed. A case study for sets of time series data before DB shutdown is presented. Testing results conclude that the proposed methodology gives better understanding a combination of data, specific behavior of parameters and their contribution to the current problem.

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