From ad04f2d1eb9c99e6b3c39be52c33a4e803d22b09 Mon Sep 17 00:00:00 2001 From: Brad Micklea <7644938+bmicklea@users.noreply.github.com> Date: Tue, 24 Sep 2024 11:56:23 -0400 Subject: [PATCH] Update compatibility list (#484) * Update compatibility list * fix typo in Quay --- docs/src/docs/modelkit/compatibility.md | 49 +++++++++++++++++++------ 1 file changed, 37 insertions(+), 12 deletions(-) diff --git a/docs/src/docs/modelkit/compatibility.md b/docs/src/docs/modelkit/compatibility.md index d308ef31..02b401b2 100644 --- a/docs/src/docs/modelkit/compatibility.md +++ b/docs/src/docs/modelkit/compatibility.md @@ -1,41 +1,66 @@ # Compatible Tools -ModelKit packages can be pushed to any OCI-compliant registry, whether in the cloud, on-premises, or locally. This makes ModelKits easy to find because they're in the same place as the rest of your containers and artifacts. It also makes them easy to control since the registry already includes authentication and authorization. +ModelKit packages can be pushed to any OCI 1.1-compliant registry, whether in the cloud, on-premises, or locally. This makes ModelKits easy to find because they're in the same place as the rest of your application's containers and artifacts. It also makes them easy to control since the registry already includes authentication and authorization. ModelKits themselves use standards like JSON, YAML, and TAR files so whatever MLOps or DevOps tools you're using...they'll work with ModelKits. A few examples in alphabetical order: -* Amazon SageMaker, EKS, EC2, ECR, Fargate, Lambda, S3, etc... -* Azure ML, AKS, Cloud, Container Registry, etc... +* Amazon SageMaker +* Amazon Elastic Kubernetes Service (EKS) +* Amazon Elastic Compute Cloud (EC2) +* Amazon Elastic Container Registry (ECR) +* Amazon Fargate +* Amazon Lambda +* Amazon S3 +* Argo CD +* Azure ML +* Azure Kubernetes Service (AKS) +* Azure Cloud +* Azure Container Registry * Circle CI * Clear ML * Comet ML * Databricks * DataRobot * Domino -* Docker and Docker Hub +* Docker +* Docker Hub * DvC -* Git and Git LFS +* Git +* Git LFS * GitHub * GitLab -* Google Vertex, GKS, GCP, Artifact Registry, etc... +* Google Vertex +* Google Kubernetes Service (GKS) +* Google Container Platform (GCP) +* Google Artifact Registry * Hugging Face -* IBM Cloud, Cloud Container Registry +* IBM Cloud +* IBM Cloud Container Registry +* Jenkins CI/CD * JFrog Artifactory * Jupyter notebooks -* Kubernetes / Kserve +* Kubernetes +* Kserve +* Marimo * MLFlow +* ModelScan * Neptune.ai -* NVIDIA Triton, Run.ai, etc... +* NVIDIA Triton and Run.ai * OctoML * Prefect -* Quay.io * Ray -* Red Hat OpenShift, OpenShift AI, Quay, InstructLab, etc... +* Red Hat InstructLab +* Red Hat OpenShift +* Red Hat OpenShift AI +* Red Hat Quay.io * Seldon +* Sonatype Nexus * Tensorflow Hub * VMware * Weights & Biases * ZenML -If you've tried using Kit with your favorite tool and are having trouble, please open an issue in our GitHub repository. \ No newline at end of file +If you've tried using Kit with your favorite tool and are having trouble, please [open an issue](https://github.com/jozu-ai/kitops/issues/new/choose) in our GitHub repository. + +If you've used KitOps with a product or project we've missed, please open a pull request updating this file.