How We Saved $500,000 Per Year by Rolling Our Own “S3” Miedwar Meshbesher 12 min read · Oct 19, 2025 -- Listen Share
tl;dr
Press enter or click to view image in full size Camera → N3 → S3 Fallback
We used S3 as a landing zone for Nanit’s video processing pipeline (baby sleep-state inference), but at thousands of uploads/second, S3’s PutObject request fees dominated costs. Worse, S3’s auto-cleanup (Lifecycle rules) has a 1-day minimum; we paid for 24 hours of storage on objects processed in ~2 seconds. We built N3, a Rust-based in-memory landing zone that eliminates both issues, using S3 only as an overflow buffer.
Result: meaningful cost reduction (~$0.5M/year).
Part 1: Background
High-Level Overview of Our Video Processing Pipeline
Cameras record video chunks (configurable duration).
(configurable duration). For each chunk, the camera requests an S3 presigned URL from the Camera Service and uploads directly to S3 .
from the and uploads . An AWS Lambda posts the object key to an SQS FIFO queue (sharded by baby_uid).
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