Predictive Analytics for Storage Management Using Time-Series Forecasting Techniques

摘要

Storage availability and performance are key to enterprise private cloud deployments. Artificial Intelligence algorithms provides significant opportunity for addressing the storage management challenges. The idea of going beyond automation of routine storage management tasks and adding intelligence to solve the challenging problems on performance management is getting more adoption in the industry. In this paper, we provide AI based solutions to two key problems in storage management - congestion detection and load balancing.