MLFlow

tl; dr; A combinator governance component that provides a hosted MLFlow server, a model repository and experiment tracker.

Introduction
Test Drive
Usage

Introduction

MLFlow is an open-source model registry and experiment tracker. Data scientists leverage this hosted service to store the results of their experiments and persist final artifacts like model parameters and weights.

This provides a centralised catalogue of models and experiments, which is useful for organizational purposes and sharing work.

MLFlow also comes with limited serving capabilities, although that is not it's core aim.

Test Drive

The fastest way to get started is to use the test drive functionality provided by TestFaster. Click on the "Launch Test Drive" button below (opens a new window).

:computer: Launch Test Drive :computer:

Usage

Prerequisites

Start by preparing your Kubernetes cluster using one of the infrastructure components or use your own cluster.

Component Usage

module "mlflow" {
  source  = "combinator-ml/mlflow/k8s"
  # Optional settings go here
}

See the full configuration options below.

Requirements

Name	Version
terraform	>= 0.14
helm	>= 2.0.0
kubernetes	>= 2.0.0

Providers

Name	Version
helm	>= 2.0.0
kubernetes	>= 2.0.0

Modules

No Modules.

Resources

Name
helm_release
kubernetes_secret

Inputs

Name	Description	Type	Default	Required
name_prefix	Prefix to be used when naming the different components.	`string`	`"combinator"`	no
namespace	The namespace to install into.	`string`	`"mlflow"`	no

Outputs

No output.

combinator-ml / terraform-k8s-mlflow

readme