HPC and technical computing environments require the collection, storage, and transmission of large-scale datasets. To meet these demands, datacenter architects must consider how increasing storage capacity over time will affect HPC workloads, performance, and system availability.
While many enterprises have looked to scale-up NAS to meet their storage needs, this approach can lead to data islands that make it difficult to share data. Distributed, scale-out storage was developed to get around the technology limitations of scale-up NAS architectures.
A traditional scale-up NAS system has a limited fixed amount of controllers, cache, and drive slots. When it reaches capacity, the customer must either upgrade to a larger system, or acquire another system. Alternatively, organizations also acquire platforms that are larger than current requirements to ensure bandwidth and disk space is available for future expansion. If expansion does not occur within the near future, or, is less than capacity forecasts, the resources provided by the large platform are simply wasted — and at high cost. As the amount of unstructured data grows to drive innovation and discovery, organizations are learning that new approaches, such as scale-out NAS, are needed to manage.
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