Amazon SageMaker · Arazzo Workflow

Amazon SageMaker Provision Notebook Instance

Version 1.0.0

Create a SageMaker notebook instance and poll it until it is in service.

1 workflow 1 source API 1 provider
View Spec View on GitHub Artificial IntelligenceInferenceMachine-LearningMLOpsTrainingArazzoWorkflows

Provider

amazon-sagemaker

Workflows

provision-notebook-instance
Create a notebook instance and poll it to an in-service state.
Launches a managed Jupyter notebook instance and describes it in a loop until it leaves the Pending state, returning the connection URL and final status.
2 steps inputs: instanceType, notebookInstanceName, roleArn, volumeSizeInGB outputs: notebookInstanceArn, notebookInstanceStatus, url
1
createNotebookInstance
Launch a managed Jupyter notebook instance with the requested instance type, IAM role, and optional storage volume size.
2
pollNotebookInstance
Describe the notebook instance to read its status. Repeat while the status remains Pending and continue once it reaches a terminal state such as InService or Failed.

Source API Descriptions

Arazzo Workflow Specification

Raw ↑
arazzo: 1.0.1
info:
  title: Amazon SageMaker Provision Notebook Instance
  summary: Create a SageMaker notebook instance and poll it until it is in service.
  description: >-
    A common SageMaker development setup flow. The workflow launches a managed
    Jupyter notebook instance with the requested instance type and IAM role,
    then describes the instance and loops while its status remains Pending,
    continuing once the instance reaches a terminal state such as InService or
    Failed. The connection URL is captured for the caller. Each step spells out
    its request inline so the flow can be read and executed without opening the
    underlying OpenAPI description.
  version: 1.0.0
  x-realizes-capability-ids:
  - BC-610.60
  x-capability-derivation:
    method: 'deterministic join: sourceDescriptions -> per-tag OpenAPI -> tag/capability edge. No classification at this step.'
    min_confidence: 0.7
    sources:
    - capability_id: BC-610.60
      capability_name: Artificial Intelligence Management
      spec: amazon-sagemaker-notebook-instances-api-openapi.yml
      confidence: 0.7
    model: Turbo EA Capabilities by Vincent Verdet — Turbo EA, https://github.com/vincentmakes/turbo-ea-capabilities, CC BY 4.0
sourceDescriptions:
- name: notebookInstancesApi
  url: ../openapi/amazon-sagemaker-notebook-instances-api-openapi.yml
  type: openapi
workflows:
- workflowId: provision-notebook-instance
  summary: Create a notebook instance and poll it to an in-service state.
  description: >-
    Launches a managed Jupyter notebook instance and describes it in a loop
    until it leaves the Pending state, returning the connection URL and final
    status.
  inputs:
    type: object
    required:
    - notebookInstanceName
    - instanceType
    - roleArn
    properties:
      notebookInstanceName:
        type: string
        description: A unique name for the notebook instance.
      instanceType:
        type: string
        description: The type of ML compute instance to launch for the notebook.
      roleArn:
        type: string
        description: The ARN of the IAM role SageMaker assumes for the notebook instance.
      volumeSizeInGB:
        type: integer
        description: The size of the ML storage volume to attach, in GB.
  steps:
  - stepId: createNotebookInstance
    description: >-
      Launch a managed Jupyter notebook instance with the requested instance
      type, IAM role, and optional storage volume size.
    operationId: CreateNotebookInstance
    parameters:
    - name: X-Amz-Target
      in: header
      value: SageMaker.CreateNotebookInstance
    requestBody:
      contentType: application/x-amz-json-1.1
      payload:
        NotebookInstanceName: $inputs.notebookInstanceName
        InstanceType: $inputs.instanceType
        RoleArn: $inputs.roleArn
        VolumeSizeInGB: $inputs.volumeSizeInGB
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      notebookInstanceArn: $response.body#/NotebookInstanceArn
  - stepId: pollNotebookInstance
    description: >-
      Describe the notebook instance to read its status. Repeat while the status
      remains Pending and continue once it reaches a terminal state such as
      InService or Failed.
    operationId: DescribeNotebookInstance
    parameters:
    - name: X-Amz-Target
      in: header
      value: SageMaker.DescribeNotebookInstance
    requestBody:
      contentType: application/x-amz-json-1.1
      payload:
        NotebookInstanceName: $inputs.notebookInstanceName
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      notebookInstanceStatus: $response.body#/NotebookInstanceStatus
      url: $response.body#/Url
    onSuccess:
    - name: stillPending
      type: goto
      stepId: pollNotebookInstance
      criteria:
      - context: $response.body
        condition: $.NotebookInstanceStatus == "Pending"
        type: jsonpath
    - name: notebookTerminal
      type: end
      criteria:
      - context: $response.body
        condition: $.NotebookInstanceStatus != "Pending"
        type: jsonpath
  outputs:
    notebookInstanceArn: $steps.createNotebookInstance.outputs.notebookInstanceArn
    notebookInstanceStatus: $steps.pollNotebookInstance.outputs.notebookInstanceStatus
    url: $steps.pollNotebookInstance.outputs.url

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