The right storage architecture depends on how the workload accesses data, not on what is already sitting in the data center. Choosing the wrong architecture for a workload creates performance problems that no amount of tuning fully resolves.

• Block storage (SAN) — best for workloads requiring low-latency, high-performance direct disk access: databases, virtualization hosts, transactional applications.
• File storage (NAS) — best for shared file access across many users or systems: home directories, department shares, general-purpose file serving.
• Object storage — best for large volumes of unstructured data accessed less frequently or via application APIs: backups, archives, media, application data at scale.
• A single environment often needs more than one architecture — match each workload individually rather than standardizing on one platform for everything.

• Establish current usage as a baseline, broken out by workload or department where possible.
• Project growth rate using historical trend data, not a flat guess — review at least 6-12 months of usage history where available.
• Set a headroom target (commonly 20-30% free capacity) that triggers a planned expansion before storage runs critically low.
• Re-forecast on a regular cadence (e.g., quarterly) since growth rate can change with new projects or acquisitions.

• Identify IOPS and latency requirements per workload — a transactional database has very different needs than an archive.
• Distinguish between random I/O (typical of databases and VMs) and sequential I/O (typical of backups and large file transfers) when sizing storage.
• Match media type to requirement: NVMe/SSD tiers for latency-sensitive workloads, higher-capacity spinning disk for bulk, less latency-sensitive data.
• Validate performance under realistic concurrent load, not just vendor benchmark figures.

• Choose a RAID level (or equivalent erasure coding) based on the balance of usable capacity, performance, and failure tolerance the workload needs.
• Account for rebuild time and risk of a second failure during rebuild on larger, higher-capacity drives.
• Redundancy within an array is not a backup — maintain a separate backup strategy regardless of RAID/redundancy level.
• Plan for hot spares or rapid replacement parts to minimize the window of reduced redundancy after a drive failure.

• Storage Architecture: SAN, NAS, and Object — /knowledge-center/infrastructure/infrastructure-networking/storage-architecture-san-nas-object
• Virtualization Fundamentals — /knowledge-center/infrastructure/infrastructure-networking/virtualization-fundamentals