Containers built to be used with Kubeflow for Data Science
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Updated
Dec 5, 2024 - Dockerfile
Containers built to be used with Kubeflow for Data Science
Kubeflow MLOps pipeline using GitHub Actions
A Golang replacement for the Kubeflow Jupyter Web APIs / Un remplacement Golang pour les API de Web de Jupyter, partie de Kubeflow
Jupyter Notebooks to be used with Advanced Analytics Workspace platform
Vault plugin which will provision multi-user keys for Minio
Applications leveraged by Statistics Canada, ready to launch on Kubernetes using Helm.
Kustomize installation manifests for Kubeflow
Profiles controller for the fine grained control of Kubeflow
Assists with monitoring and managing Kubernetes resource spend
Proposal for the implementation of Protected B workloads in the Advanced Analytics Workspace
Containers to be used for general purpose Data Science
MLFlow Operator generated via KubeBuilder to enable managing multiple MLFlow installs
Scan all Kubeflow pipelines for exposed secrets
Kubeflow deployment powered by ArgoCD
Terraform for Azure Kubernetes Service configuration (DAaaS) (Public)
Experimental containers to be used with Kubeflow for a Desktop experience
Manage storage mounts with Goofys / Gérez les montages automatisé avec Goofys
DAaaS AAW Toleration Injector / Injecteur de Toleration pour ADS EAA
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