kfserving #12

Supports: kubernetes

Deploy this charm on Kubernetes with the CLI. Find out how by reading the docs.

Description

KFServing aims to solve production model serving use cases by providing performant, high abstraction interfaces for common ML frameworks like Tensorflow, XGBoost, ScikitLearn, PyTorch, and ONNX.


KFServing Operator

Overview

This charm encompasses the Kubernetes Python operator for KFServing (see CharmHub).

The KFServing operator is a Python script that wrap the latest released version of KFServing, providing lifecycle management and handling events such as install, upgrade, integrate, and remove.

Install

To install KFServing, run:

juju deploy kfserving

For more information, see https://juju.is/docs


Configuration

metrics-port
(string) Metrics port
8080
webhook-port
(string) Webhook port
9443