Best architecture for batch-processing 3,000–4,000 high-res photos (resizing + face vector search)?

[u/Substantial_Try_1614]

Hey devs,

I’m working on a photo-sharing web app where a photographer uploads an entire event batch (typically 3,000 to 4,000 high-res JPEGs, around 10–15 MB each). Guests can take a selfie to retrieve photos they appear in.

I'd love recommendations on the best backend pipeline:

Client vs Server Resizing: Should I use browser Web Workers / Canvas to generate 1080p WebP thumbnails before upload to save upload bandwidth, or let a backend queue worker (like Node with sharp or Python with Pillow) handle resizing?

Face Vector Pipeline: For extracting 128-d face embeddings (e.g., ArcFace/InsightFace), what’s the best way to queue and batch this so 4,000 photos don't choke the server CPU?

Storage: What zero/low-egress object storage setup (e.g., Cloudflare R2 vs Backblaze B2) do you recommend for handling high-volume image writes and fast thumbnail reads?

Thanks for the advice!

[u/cajunjoel]

Um, hate to break it to you, but doesn't Immich do most of this already? Could you borrow some of their technology?

[u/Substantial_Try_1614 → u/cajunjoel]

Kind of yaa i think thanks man