Finding Correlation and Predicting System Behavior in Large IT Infrastructure
Modern IT development infrastructure has a large number of components that must be monitored, for instance servers and network components. Various system-metrics (build time, CPU utilization, queries time etc.) are gathered to monitor system performance. In practice, it is extremely difficult for a system administrator to observe a correlation between several systemmetrics and predict a target system-metric based on highly correlated system-metrics without machine learning support.
The experiments were performed on development logs at Ericsson. There were many system-metrics available in the system. Our goal is use machine learning techniques to find correlation between buildtime and other system-metrics and predict its trends in the future.
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