Storage Math That Survives Procurement

The NAS spec sheet said 100 TB. The OS mounted 90.9 TiB. Somebody signed the PO without checking base-2 vs base-10. These nine converters exist so that somebody isn't you.

TB →PB

1 PB = 1,024 TB. Cold-tier your S3 IA before the next quarterly bill arrives.

TB →PB Scaler →

PB →EB

Crossed 1 PB? Next stop: exabyte. Scale the Ceph cluster before the purchase order lands.

PB →EB Scaler →

GiB vs GB —The 6.9% Lie

Box: 1 TB. OS: 931 GB. Nobody stole 69 GB. It's base-10 vs base-2. Quantify the gap on every drive you buy.

GiB vs GB Analyzer →

Token Count →Storage

1B tokens × 4 bytes = 4 GB raw. Then tokenizer overhead. Then dataset metadata. Size the data lake before the GPUs sit idle.

Token →Storage Estimator →

IOPS →Throughput

10K IOPS × 16K blocks = 160 MB/s ceiling. Your app needs 250 MB/s. You're bottlenecked. Fix it before the DBA pages you.

IOPS →Throughput →

DB Rows →Storage

50M rows. 3 indexes. 200 bytes/row. That's 30 GB before WAL, before replication lag. Size the RDS instance correctly.

Row →Storage Profiler →

Redis RAM Inflation

4 GB JSON on disk. 6— GB in Redis with hashtable-encoding overhead. Model the heap before you hit SWAP at peak traffic.

Redis RAM Profiler →

Video Encoding Optimizer

H.264 vs H.265 vs AV1 vs VP9 —file size, bitrate, and encoding time compared. Content-type presets + CRF reverse calculator. Find the CRF that hits your target file size.

Video Encoding Optimizer →

Parquet vs CSV Compression

150 GB CSV →15 GB Parquet with Snappy. Columnar storage + predicate pushdown. Athena queries drop 10× in cost. S3 bill drops 90%.

Parquet vs CSV Profiler →

KV Cache VRAM Inflation

32K context window. Every 1K tokens burns more VRAM. At long sequences, KV cache dwarfs model weights. Map it before you provision.

KV Cache Profiler →

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