hub-component.yaml

---
version: 1
kind: component
meta:
  name: sagemaker
  title: sagemaker
  brief: SageMaker Pipeline
  description: >
    Amazon SageMaker is a complete machine learning workflow service for developing, training, and deploying models.  SageMaker Pipeline template provides automation for the build and deployment of machine learning models on SageMaker. This template provides a full implementation of ML pipeline and includes Jupyter notebooks showing how to create, launch, stop, and track the progress of workflows using python and Amazon Alexa.
  category: App Stack
  version: 1.0.0
  maturity: beta
  license: Apache
  source:
    dir: ../../components/sagemaker

requires:
  - aws
provides:
  - sagemaker

parameters:
  - name: dns.domain
    env: DOMAIN_NAME
  - name: terraform.bucket.name
    env: STATE_BUCKET
  - name: terraform.bucket.region
    env: STATE_REGION

  - name: component.sagemaker
    parameters:
    - name: version
      value: 1.0.0
    - name:  name
      value: sagemaker-build
      env:   COMPONENT_NAME
    - name: ConfigFramework
      value: BYOD
      env:   CONFIG_FRAMEWORK
    - name: NoteBookInstanceType
      value: ml.t2.medium
      env:   NOTEBOOK_INSTANCE_TYPE
    - name: ExternalGithubRepo
      value: USE_CODECOMMIT_REPO
      env:   EXTERNAL_GITHUB_REPO

templates:
  kind: mustache
  files:
    - "*.template"
outputs:
  - name: component.sagemaker.NoteBookInstance.url
    brief: AWS Console url of your sagemaker notebook instance
    fromTfVar: NoteBookInstance
  - name: component.sagemaker.NoteBookUrl.url
    brief: URL of your Jupyter notebook
    fromTfVar: NoteBookUrl