Lead Image © nikkikii, 123RF.com

Lead Image © nikkikii, 123RF.com

Rethinking RAID (on Linux)

Madam, I'm mdadm

Article from ADMIN 62/2021
Configure redundant storage arrays to boost overall data access throughput while maintaining fault tolerance.

Often, you find yourself attempting to eke out a bit more performance from the computer system you are attempting to either build or recycle, usually with limited funds at your disposal. Sure, you can tamper with the CPU or even memory settings, but if the I/O hitting the system needs to touch the underlying storage devices, those CPU tunings will make little to no difference.

In previous articles, I have shared methods by which one can boost write and read performance to slower disk devices by leveraging both solid state drives (SSD) and dynamic random access memory (DRAM) as a cache [1]. This time, I will instead shift focus to a unique way you can configure redundant storage arrays so that you not only boost overall data access throughput but also maintain fault tolerance. The following examples center around a multiple-device redundant array of inexpensive (or independent) disks (MD RAID) in Linux and its userland utility mdadm [2].

Conventional wisdom has always dictated that spreading I/O load across more disk drives instead of bottlenecking a single drive does help significantly when increasing one's workload. For instance, if instead of writing to a single disk drive you split the I/O requests and write that same amount of data in a stripe across multiple drives (e.g., RAID0), you are reducing the amount of work that a single drive must perform to accomplish the same task. For magnetic spinning disks (i.e., hard disk drives, HDDs), the advantages should be more noticeable. The time it takes to seek across a medium introduces latency, and with randomly accessed I/O patterns, the I/O throughput suffers as a result on a single drive. A striped approach does not solve all the problems, but it does help a bit.

In this article, I look at something entirely different. I spend more time focusing on increasing read throughput

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