Choose storage by access pattern and performance

First ask how the application reads and writes data: object API, shared filesystem, or block device. Performance tuning cannot repair the wrong interface. Record the clients, location, locking, durability, recovery, and growth requirements before choosing a service.

Then measure request size and pattern, IOPS, throughput, and latency. IOPS counts operations while throughput counts bytes, so small random requests and large sequential scans hit different limits. S3 supports object workloads, EFS supplies elastic shared POSIX, and EBS supplies zonal block volumes with type-specific performance.

No tuning can make an object API a native POSIX namespace or make one block device the stated multi-client filesystem.

Different datasets in one application may need different storage. Separate durable objects, shared files, database blocks, and reproducible scratch. S3 scales object APIs and parallel/multipart patterns. EFS provides elastic shared POSIX; choose modes from measurement. EBS is AZ block, and its volume and compute path must meet the required IOPS, throughput, and latency. Instance store is temporary local scratch/cache.

FSx for Lustre fits high-performance parallel file workloads and S3 integration. EFS remains a simpler general-purpose elastic shared POSIX option when measurement meets the target. EC2 instance store is temporary host-local block storage suited to buffers, caches, and reproducible scratch; its data can disappear with relevant instance lifecycle or disk failure and must not hold the only database copy.

Put durable random block data on a tested EBS and EC2 path. Benchmark real request size, queue depth, instance limits, volume limits, and failure headroom rather than treating a provisioned number as application proof.

For hybrid data, the network is part of the storage design. Calculate a lower bound before promising a migration window. DataSync moves data among supported on-premises and AWS storage. Storage Gateway presents supported file, volume, or tape interfaces with local caching. Neither changes the target access semantics.

Use S3 for durable objects and estimate the DataSync transfer window; evaluate IOPS, throughput, locality, growth, and durability separately. Two hundred decimal terabytes equals 1,600,000 gigabits.

At a perfect 2 Gbps, the theoretical lower bound is 800,000 seconds, about 9.26 days; overhead, retries, and contention make reality longer. Parallelism cannot exceed the physical bottleneck. Use S3 for elastic object growth, benchmark the render filesystem at required concurrency, and retain Storage Gateway only when an on-premises protocol interface is itself required. Performance acceptance should report workload shape with the number.

A result without request size, concurrency, cache state, dataset size, and failure placement cannot be compared with the target. Repeat tests after removing a storage path or compute host, verify scratch reconstruction, and measure transfer checkpoints so an interruption does not turn a nine-day lower bound into an unplanned restart. Growth planning differs by service.

Object storage expands without resizing a volume, while block and provisioned file systems can require capacity or throughput changes. Monitor consumed bytes, burst or throughput credits where relevant, queue depth, and time to scale. Leave enough margin for recovery and maintenance, because a benchmark at full nominal capacity provides no room for a failed path or catch-up work.