Distribution-spec Alternatives

distribution-spec reviews and mentions

• Scaling Spin Apps With KEDA
  6 projects | dev.to | 20 Dec 2024

  Spin Apps are packaged and distributed as OCI artifacts. By leveraging OCI artifacts, Spin Apps can be distributed using any registry that implements the Open Container Initiative Distribution Specification (a.k.a. “OCI Distribution Spec”).

• Day 3: What is Docker and why should I care?
  7 projects | dev.to | 3 Dec 2024

  Docker is a company that maintains the Docker software and also offers a cloud service to run Docker containers in the cloud. They run DockerHub, which is a platform to store share and run Docker images. The actual standard for Docker containers is called OCI (Open Container Initiative). Because Docker is based on OCI there are many other tools that can interact with Docker containers, like Podman or Lima. If you want to go really deep, I really recommend reading the OCI specification! It's long but super interesting.

• Kubernetes and Cloud Native Associate (KCNA) Exam Guide
  18 projects | dev.to | 30 Nov 2024

  Open Container Initiative

• A Very Deep Dive Into Docker Builds
  3 projects | dev.to | 25 Nov 2024

  So performance cannot be said to be better with Docker, why choose Docker then? Better reasons are that you can strip down a Docker image much easier than an OS. This is critical for us due to security requirements. While Python requires a lot of OS features, the majority of the OS is still bloat. Every piece of bloat is a potential attack vector (each of these unused components might have one or more CVEs that we need to patch, even though we don't even use that software). Another reason is that the build process of Docker is much simpler to manage. There are tools such as Packer that allow similar processes for VMs, but these are not as standardized as the open container initiative (OCI - which Docker adheres to).

• serverless-registry: A Docker registry backed by Workers and R2
  11 projects | news.ycombinator.com | 5 Sep 2024

  If you are a CloudFlare employee reading this, you should get involved with the OCI Distribution group that develops the standards for the registry: https://github.com/opencontainers/distribution-spec

• Docker Containers | Linux Namespaces | Container Isolation
  5 projects | dev.to | 10 Aug 2024

  What makes containers useful is the tooling that surrounds it. For these labs, we will be using Docker, which has been a widely adopted tool for using containers to build applications. Docker provides developers and operators with a friendly interface to build, ship and run containers on any environment with a Docker engine. Because Docker client requires a Docker engine, an alternative is to use Podman, which is a deamonless container engine to develop, manage and run OCI containers and is able to run containers as root or in rootless mode. For those reasons, we recommend Podman but because of adoption, this lab still uses Docker.

• Using S3 as a Container Registry
  8 projects | news.ycombinator.com | 12 Jul 2024

  The OCI Distribution Spec is not great.

  > According to the specification, a layer push must happen sequentially: even if you upload the layer in chunks, each chunk needs to finish uploading before you can move on to the next one.

  As far as I've tested with DockerHub and GHCR, chunked upload is broken anyways, and clients upload the image as a whole. The spec also promotes `Content-Range` value formats that do not match the RFC7233 format.

  Another gripe of mine is that they missed the opportunity to standardize pagination of listing tags, because they accidentally deleted some text from the standard [1]. Now different registries roll their own.

  [1] https://github.com/opencontainers/distribution-spec/issues/4...

• A step-by-step guide to building an MLOps pipeline
  7 projects | dev.to | 4 Jun 2024

  One of the main reasons teams struggle to build and maintain their MLOps pipelines are vendor specific packaging. As a model is handed off between data science teams, app development teams, and SRE/DevOps teams, the teams are required to repackage the model to work with their unique toolset. This is tedious, and stands in contrast to well adopted development processes where teams have standardized on the use of containers to ensure that project definitions, dependencies, and artifacts are shared in a consistent format. KitOps is a robust and flexible tool that addresses these exact shortcomings in the MLOps pipeline. It packages the entire ML project in an OCI-compliant artifact called a ModelKit. It is uniquely designed with flexible development attributes to accommodate ML workflows. They present more convenient processes for ML development than DevOps pipelines. Some of these benefits include:

• A Brief History Of Serverless
  10 projects | dev.to | 13 May 2024

  Internally, Google used a platform called Borg which is still used by Google to this day. It also served as the basis for Kubernetes. Borg is a container-based platform whose goal was to allow developers to focus on code, not infrastructure. Google has an entire infrastructure team to manage the datacenters. This system came out circa 2004. This predates the advent of modern OCI Containers by about a decade.

• The transitory nature of MLOps: Advocating for DevOps/MLOps coalescence
  2 projects | dev.to | 25 Mar 2024

  Back in 2013, a little company called Docker made it really easy to start using containers to package up applications. A big key to their success was the OCI (you can learn about that here), an industry wide initiative to have standards around how we package up our applications. Because of OCI standards, we have hundreds (maybe thousands?) of tools that can be combined to manage and deploy applications. So why aren’t we using this for packaging up Notebooks and AI models as well? It would make deploying, sharing, and managing our models easier for everyone involved.

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  coderabbit.ai | 30 Apr 2025

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