Western Digital Technologies, Inc.

Donald Penza

Timothy G Lieber

Robert Lester

Austin Striegel

Evan Richardson

Jared Tesone

An approach to identifying poorly performing data storage devices (DSDs) in a data storage system, such as hard disk drives (HDDs) and/or solid-state drives (SSDs), involves retrieving and evaluating a respective set of log pages, such as SCSI Log Sense counters, from each of multiple DSDs. Based on each respective set of log pages, a value for a Quality of Service (QoS) metric is determined for each respective DSD, where each QoS value represents an average percentage of bytes processed without the respective DSD performing an autonomous error correction. In response to a particular DSD reaching a predetermined threshold QoS value, an in-situ repair may be determined for the particular DSD or the particular DSD may be added to a list of candidate DSDs for further examination, which may include an FRPH examination for suitably configured DSDs.

Use of error correction-based metric for identifying poorly performing data storage devices

An approach to identifying problematic data storage devices, such as hard disk drives (HDDs), in a data storage system involves retrieving and evaluating a respective recovery log, such as a media error section of a device status log, from each of multiple HDDs. Based on each recovery log, a value for a Full Recoveries Per Hour (FRPH) metric is determined for each read-write head of each respective HDD. Generally, the FRPH metric characterizes the amount of time a head has spent performing recovery operations. In response to a particular head FRPH reaching a pre-determined threshold value, an in-situ repair can be determined for the HDD in which the head operates. Similarly, in the context of solid-state drives (SSDs), a latency metric is determinable based on time spent waiting on resolving input/output (IO) request collisions, on which an in-situ repair can be based.

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Rochester, MN, United States of America

Donald Penza