This paper looks back at the analysis that has been done for the drive wear-out issue on for the different E-series array systems running at different customers’ sites and uses that data to give more specific guidance on thresholds for a preemptive drive removal. Motivation of DHM: Customers with old ventage or Refurbished drive replacement may experience a data loss event and continues to see a high drive failure rate >5% AFR (Annual Failure Rate). Storage vendors expect to see high fallout rates across the hard drive population as they age.

For the last eight years Backblaze has collected daily operational data from the hard drives in our data centers. This includes daily SMART statistics from over 250,000 hard drives, and SSDs, totaling nearly two exabytes of storage, and totaling over 200 million data points. We'll use this data to examine the following: - the lifetime failure statistics for all the hard drives we have ever used. - how has temperature effects the failure rate of hard drives. - a comparison the failure rates of helium filled hard drives versus air-filled hard drives.

Delivering high throughput and/or high IO rates while minimizing command execution latency is a common problem to many storage applications. Achieving low command latency to implement a responsive system is often not compatible with high performance. The ATA NCQ IO priority feature set, supported today by many SATA hard-disks, provides a coarse solution to this problem. Commands that require a low latency can be assigned a high priority, while background disk accesses are assigned a normal priority level.

Data is growing at an exponential pace and the need to manage this data at the core and edge is a multi-facet problem. New innovative methods to ensure data availability & utilization of the resources that store this data are being developed. Storage device health monitoring & utilization is one such issue. Developing models to predict drive degradation while using machine learning principles is highly desirable. A recent Google blog described the machine learning techniques being used to promote & improve drive maintenance of their fleet.

SATA multi-actuator drives appear as a single drive to the system stack, yet all IO is addressed to LBA ranges on each actuator. Linux IO schedulers must be aware of this geometry via log pages in ATA Command Set –5 and then optimize behavior to ensure that actuators are kept busy. Legacy IO scheduler behavior can lead to underutilized actuators, delayed IO completion resulting in poor performance.

Applications desire for higher IOPS & bandwidth is driving innovations at the hardware level. This requires software stack awareness to harness the benefits. Multi-actuator drives represent the next big innovation in performance.