stargz-snapshotter
acr
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stargz-snapshotter | acr | |
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10 | 1 | |
1,045 | 163 | |
2.9% | 1.2% | |
8.4 | 5.3 | |
2 days ago | 16 days ago | |
Go | ||
Apache License 2.0 | GNU General Public License v3.0 or later |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
stargz-snapshotter
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Tree-shaking, the horticulturally misguided algorithm
A lazy chunked delivery strategy like used in the k8s stargz-snapshotter[0] project could be effective here, where it only pulls chunks as needed, but it would probably require wasm platform changes.
[0] https://github.com/containerd/stargz-snapshotter
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Show HN: depot.ai – easily embed ML / AI models in your Dockerfile
To optimize build speed, cache hits, and registry storage, we're building each image reproducibly and indexing the contents with eStargz[0]. The image is stored on Cloudflare R2, and served via a Cloudflare Worker. Everything is open source[1]!
Compared to alternatives like `git lfs clone` or downloading your model at runtime, embedding it with `COPY` produces layers that are cache-stable, with identical hash digests across rebuilds. This means they can be fully cached, even if your base image or source code changes.
And for Docker builders that enable eStargz, copying single files from the image will download only the requested files. eStargz can be enabled in a variety of image builders[2], and we’ve enabled it by default on Depot[3].
Here’s an announcement post with more details: https://depot.dev/blog/depot-ai.
We’d love to hear any feedback you may have!
[0] https://github.com/containerd/stargz-snapshotter/blob/main/docs/estargz.md
[1] https://github.com/depot/depot.ai
[2] https://github.com/containerd/stargz-snapshotter/blob/main/docs/integration.md#image-builders
[3] https://depot.dev
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A Hidden Gem: Two Ways to Improve AWS Fargate Container Launch Times
Seekable OCI (SOCI) is a technology open-sourced by AWS that enables containers to launch faster by lazily loading the container image. It’s usually not possible to fetch individual files from gzipped tar files. With SOCI, AWS borrowed some of the design principles from stargz-snapshotter, but took a different approach. A SOCI index is generated separately from the container image and is stored in the registry as an OCI Artifact and linked back to the container image by OCI Reference Types. This means that the container images do not need to be converted, image digests do not change, and image signatures remain valid.
- containerd/stargz-snapshotter: Fast container image distribution plugin with lazy pulling
- EStargz: Lazy pull container images for faster cold starts
- How to optimize the security, size and build speed of Docker images
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Speeding up LXC container pull by up to 3x
This is interesting and seems general purpose. Not merely for container images.
There’s this option for OCI containers which I don’t pretend to understand: https://github.com/containerd/stargz-snapshotter
It is used by containerd and nerdctl. You do have to build the image with it. Images work in OCI compatible registry. By fetching most used files first container can be started before loading is finished. Or so I gather.
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Optimizing Docker image size and why it matters
stargz is a gamechanger for startup time. You might not need to care about image size at all
kubernetes and podmand support it, and docker support is likely coming. It lazy loads the filesystem on start-up, making network requests for things that are needed and therefore can often start up large images very fast.
https://github.com/containerd/stargz-snapshotter
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FOSS News International #2: November 8-145, 2021
containerd/stargz-snapshotter: Fast container image distribution plugin with lazy pulling (github.com)
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Introducing GKE image streaming for fast application startup and autoscaling
Yes, see https://github.com/containerd/stargz-snapshotter
acr
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Introducing GKE image streaming for fast application startup and autoscaling
Microsoft were working on something similar for ACR a few years ago: https://github.com/Azure/acr/blob/main/docs/teleport/README.md it’s a shame this never turned into anything, or at least, not that I’m aware of.
What are some alternatives?
kube-fledged - A kubernetes operator for creating and managing a cache of container images directly on the cluster worker nodes, so application pods start almost instantly
containerd - An open and reliable container runtime
docker-github-runner-linux - Repository for building a self hosted GitHub runner as a ubuntu linux container
soci-snapshotter - A containerd snapshotter plugin which enables standard OCI images to be lazily loaded without requiring a build-time conversion step.
docker-github-runner-windows - Repository for building a self hosted GitHub runner as a windows container
snoop - Snoop — инструмент разведки на основе открытых данных (OSINT world)
private-aks-cluster-terraform-devops - This sample shows how to create a private AKS cluster using Terraform and Azure DevOps
uChmViewer - A fork of Kchmviewer, the best software for viewing .chm (MS HTML help) and .epub eBooks.
Lean and Mean Docker containers - Slim(toolkit): Don't change anything in your container image and minify it by up to 30x (and for compiled languages even more) making it secure too! (free and open source)
veinmind-tools - veinmind-tools 是由长亭科技自研,基于 veinmind-sdk 打造的容器安全工具集
depot.ai - Embed machine learning models in your Dockerfile