Nicheloom

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Docker pulls more than it needs to

and how we can fix it

Details

External ID
47267138
Source
HN
Company
—
Product
Docker pulls more than it needs to
Website domain
dockerpull.com
Launched
March 5, 2026
Cohort
—
Upvotes
8
Upvotes percentile
0.491389913899139
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

Hi all!I've built a small tool to visualize how inefficient `docker pull` is, in preparation for standing up a new Docker registry + transport. It's bugged me for a while that updating one dependency with Docker drags along many other changes. It's a huge problem with Docker+robotics. With dozens or hundreds of dependencies, there's no "right" way to organize the layers that doesn't end up invalidating a bunch of layers on a single dependency update - and this is ignoring things like compiled code, embedded ML weights, etc. Even worse, many robotics deployments are on terrible internet, either due to being out in the boonies or due to customer shenanagins. I've been up at 4AM before supporting a field tech who needs to pull 100MB of mostly unchanged Docker layers to 8 robots on a 1Mbps connnection. (and I don't think that robotics is the only industry that runs into this, either - see the ollama example, that's a painful pull)What if Docker were smarter and knew about the files were already on disk? How many copies of `python3.10` do I have floating around `/var/lib/docker`. For that matter, how many copies of it does DockerHub have? A registry that could address and deduplicate at the file level rather than just the layer level is surely cheaper to run.This tool:- Given two docker images, one you have and one you are pulling, finds how much data docker pull would use, as well as how much data is _actually_ required to pull- Shows an estiimate for how much time you will save on various levels of cruddy internet- There's a bunch of examples given of situations where more intelligent pulls would help, but the two image names are free text, feel free to write your own values there and try it out (one at a time though, there's a work queue to analyze new image pairs)The one thing I wish it had but haven't gotten around to fitting in the UI somehow is a visualization of the files that _didn't_ change but are getting pulled anyhow.It was written entirely in Claude Code, which is a new experience for me. I don't know nextjs at all, I don't generally write frontends. I could have written the backend maybe a little slower than Claude, but the frontend would have taken me 4x as long and wouldn't have been as pretty. It helped that I knew what I wanted on the backend, I think.The registry/transport/snapshotter(?) I'm building will allow both sharing files across docker layers on your local machine well as in the registry. There's a bit of prior art with this, but only on the client side. The eStargz format allows splitting apart the metadata for a filesystem and the contents, while still remaining OCI compliant - but it does lazy pulls of the contents, and has no deduplication. I think it could easily compete with other image providers both on cost (due to using less storage and bandwidth...everywhere) as well as speed.If you'd be interested, please reach out.

Enrichment

Theme
macOS utilities and system tools
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
Not AI
Project type
Hobby / open-source project
Normalized one-liner
optimize docker pull efficiency
Manually corrected
False

Could you build this?

Yes This is a focused developer utility that parses standard Docker/OCI image manifests and filesystem layer diffs to visually display duplicate content.

Discussion

9 comments analyzed.

Competitors mentioned: OSTree and casync, Local Arch package caching

Concerns raised: Docker lacks product-market fit and incentivizes inefficiency as central hub, Cannot deduplicate layers after creation without changing digest, Multiple image versions with same tag have different SHAs, Large dependencies merged into single non-shared layers, Slow image downloads on poor connections

Feature requests: Registry-level layer deduplication and reorganization, Better tooling for building layers in efficient format, Improved local caching system comparable to Arch

Competitors

Other products that read as similar to this one — 71 launches clear the similarity bar, closest 8 shown.

Attention rank: #45 of 72 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 120 days after the earliest competitor.

Other launches for this product

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