What kind of workloads benefit from a file system designed for random I/O?

Workloads that benefit from a file system designed for random I/O are typically those that require quick access to small chunks of data spread throughout a large data set rather than reading or writing large contiguous blocks of data. Boot volumes are a prime example of this type of workload. When a machine starts, it needs to access many different files and pieces of data that are not necessarily located near each other on disk. This makes quick random access essential for optimal performance during the boot process.

In contrast, streaming video workloads typically involve large, sequential file operations, which are not as dependent on random I/O capabilities. Data warehouses often focus on bulk data processing and may favor sequential I/O for aggregate queries, while log processing can also be more sequential as logs are often written in a linear fashion—making random I/O less critical in those contexts. Thus, boot volumes exemplify a workload that fundamentally relies on the strengths of a file system designed for random I/O.