Analysis updated 2026-07-26 · repo last pushed 2024-08-02
Share large machine learning model files alongside application code in a cloud registry.
Distribute datasets or project assets through a registry your team already uses.
Ensure everyone on a team pulls the exact matching version of both code and data files.
Use cloud registries as a general-purpose storage hub for any non-container artifacts.
| maelvls/oras | 00kaku/gallery-slider-block | 04amanrajj/netwatch | |
|---|---|---|---|
| Stars | — | — | 0 |
| Language | — | JavaScript | Rust |
| Last pushed | 2024-08-02 | 2021-05-19 | — |
| Maintenance | Stale | Dormant | — |
| Setup difficulty | moderate | easy | moderate |
| Complexity | 2/5 | 2/5 | 3/5 |
| Audience | ops devops | general | ops devops |
Figures from each repo's GitHub metadata at analysis time.
Requires access to a cloud registry (like AWS ECR, Azure ACR, or GitHub Container Registry) with authentication configured.
ORAS CLI is a tool for moving packages, files, and other digital artifacts in and out of cloud registries. Normally, these registries are used to store container images (the bundled software that runs applications in the cloud), but ORAS lets you use them as a general-purpose storage system for almost anything you need to share or distribute. Here is how it works at a high level. Cloud registries speak a specific language designed for container images. ORAS acts as a translator and shipping service, taking your non-container files, packing them into a format the registry understands, and uploading them. When someone else needs those files, they use the same tool to pull them back down. The registry just sees standard packages going in and out, while you get to use it as a convenient hub for your own project assets. A team building a machine learning model, for example, could use this to share large trained model files alongside their application code. Instead of juggling separate download links or storage accounts, developers could push those model files to the same registry they already use for their application. A colleague pulling the latest application would also pull the exact matching model file, ensuring everyone is working with the right versions. The public documentation for this project lives entirely on its website rather than in the repository itself, so the included files do not go into detail about specific commands or advanced features. However, the project is part of the Cloud Native Computing Foundation, which means it follows community standards and is built to work with the same infrastructure that major cloud platforms already use.
ORAS CLI lets you store and share any files, like ML models or datasets, inside cloud registries that are normally used for container images, so teams can keep all their project assets in one place.
Stale — no commits in 1-2 years (last push 2024-08-02).
The license is not mentioned in the repository description, but as a CNCF project it is typically Apache 2.0 which allows free use for any purpose including commercial.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly ops devops.
This repo across BitVibe Labs
Verify against the repo before relying on details.