A rapidly expanding research division is rolling out a deep analysis platform that processes large data sets at unpredictable intervals. The application requires a high number of input/output operations and data encryption. It must also stay operational during spikes in demand and confirm that data is retained for compliance requirements. Which option meets these criteria?
Object-based resources with encryption that emphasize long-term archival over responsiveness
HPC nodes with ephemeral storage that do not keep data beyond processing cycles
Local drives with limited encryption and minimal data retention capability
Block-based storage with encryption and compute nodes configured for high IOPS
A block-based resource with encryption, provisioned for high IOPS, and paired with load-balanced compute nodes can handle unpredictable bursts, ensure sensitive data is secure, and maintain the necessary throughput. An ephemeral-only approach is not designed for compliance-focused retention. A platform focused on object-based storage does not emphasize high IOPS, which is important for compute-intensive tasks. A dedicated HPC (High-Performance Computing) environment with ephemeral storage meets certain performance criteria but does not align well with regulatory data retention needs.
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Why isn't object-based storage suitable for high IOPS tasks?