Capacity forecasting in a backup storage environment
Mark Chamness · 2011
Managing storage growth is painful [1]. When a system exhausts available storage, it is not only an operational inconvenience but also a budgeting nightmare. Many system administrators already have historical data for their systems and thus can predict full capacity events in advance. EMC has developed a capacity forecasting tool for Data Domain systems which has been in production since January 2011. This tool analyses historical data from over 10,000 back-up systems daily, forecasts the future date for full capacity, and sends proactive notifications. This paper describes the architecture of the tool, the predictive model it employs, and the results of the implementation. Tags: storage, predictive modeling, case study, capacity planning, forecasting, machine learning.