Kubeflow

  • Kubeflow Charmers | bundle
  • Cloud
Channel Revision Published
latest/candidate 294 24 Jan 2022
latest/beta 430 30 Aug 2024
latest/edge 423 26 Jul 2024
1.9/stable 432 03 Dec 2024
1.9/beta 420 19 Jul 2024
1.9/edge 431 03 Dec 2024
1.8/stable 414 22 Nov 2023
1.8/beta 411 22 Nov 2023
1.8/edge 413 22 Nov 2023
1.7/stable 409 27 Oct 2023
1.7/beta 408 27 Oct 2023
1.7/edge 407 27 Oct 2023
juju deploy kubeflow --channel latest/edge
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Platform:

This guide presents some Machine learning operations (MLOps) tools integrated in Charmed Kubeflow (CKF). MLOps are a set of practices that automate and simplify ML workflows and deployments.

Katib

Katib is a Kubernetes-native project for automated machine learning (AutoML). Katib supports hyperparameter tuning, early stopping and neural architecture search (NAS).

Katib is agnostic to ML frameworks. It can tune hyperparameters of applications written in any language of the users’ choice and natively supports many ML frameworks, such as TensorFlow, MXNet, PyTorch, XGBoost, and others.

Kubeflow Pipelines

Kubeflow Pipelines (KFP) is a workflow engine that allows specifying tasks and their configuration, environment variables and secrets. Additionally, KFP provides task execution scheduling.

MinIO

MinIO is a secured object storage system. It can be used as a standalone product or as a cloud storage gateway. For cloud use, it provides an AWS S3-compatible API.

MLflow

MLflow is an experiment and model repository that enables model tracking including metadata, training results and model comparison.

Seldon Core

Seldon Core is a platform to deploy ML models on Kubernetes at scale as microservices. It supports REST and gRPC protocols, manual and auto-scaling.