Bad Sector Prediction

By analyzing S.M.A.R.T. attributes and performance metrics, aSAN can predict disks that are likely to develop bad sectors. This enables proactive replacement during planned maintenance windows, transforming storage maintenance from a reactive to a predictive model and preventing unplanned outages.

Capacity Prediction

Using historical consumption data, aSAN forecasts future storage capacity needs. It provides administrators with advance warning of when the cluster will exhaust its available space, allowing for timely procurement and expansion, thereby avoiding service interruptions due to full storage.

SSD Lifetime Prediction

The system continuously monitors SSD health parameters, such as wear level and total bytes written, to estimate the remaining usable life of each drive. This prediction allows for the planned, preemptive replacement of SSDs before they fail, safeguarding against data loss and the performance impact of a sudden SSD failure.

Data Self-Balancing

aSAN automatically redistributes data across the cluster when new nodes or disks are added, or when significant data deletion creates imbalance. The goal is to maintain even utilization of storage capacity and I/O load across all devices, preventing hotspots and ensuring optimal performance without manual intervention.

SkyOPS

Integrated within the HCI platform, SkyOPS is an AIOps engine that provides intelligent operational management for the storage layer. It offers capabilities such as risk prediction, continuous optimization recommendations, and real-time monitoring, assisting IT teams in proactively identifying and resolving potential storage-related issues.