pipelines

Creates, updates, deletes, gets or lists a pipelines resource.

Overview

Name	pipelines
Type	Resource
Id	aws.iotsitewise.pipelines

Fields

The following fields are returned by SELECT queries:

describe_pipeline

Name	Datatype	Description
computations	array	A list of compute nodes forming a pipeline DAG.
created_at	string (date-time)	The time the pipeline was created, in Unix epoch time.
description	string	The description of the pipeline. (pattern: <code>[^\u0000-\u001F\u007F]+</code>)
environment_variables	object	The environment variables shared across all compute nodes in the pipeline.
pipeline_arn	string	The ARN of the pipeline. (pattern: <code>^arn:aws(-cn|-us-gov)?:[a-zA-Z0-9-:/_.]+$</code>)
pipeline_name	string	Reusable resource name with alphanumeric, hyphen, and underscore characters. (pattern: <code>[a-zA-Z0-9_-]+</code>)
status	object	The current lifecycle status of the pipeline.
updated_at	string (date-time)	The time the pipeline was last updated, in Unix epoch time.
version	string	The version of the pipeline. (pattern: <code>^(0|([1-9]{1}\d*))$</code>)
workspace_name	string	The name of the workspace. (pattern: <code>^[a-zA-Z0-9_-]+$</code>)

list_pipelines

Name	Datatype	Description
created_at	string (date-time)	The time the pipeline was created, in Unix epoch time.
description	string	The description of the pipeline. (pattern: <code>[^\u0000-\u001F\u007F]+</code>)
pipeline_arn	string	The ARN of the pipeline. (pattern: <code>^arn:aws(-cn|-us-gov)?:[a-zA-Z0-9-:/_.]+$</code>)
pipeline_name	string	Reusable resource name with alphanumeric, hyphen, and underscore characters. (pattern: <code>[a-zA-Z0-9_-]+</code>)
status	object	The current lifecycle status of the pipeline.
updated_at	string (date-time)	The time the pipeline was last updated, in Unix epoch time.
version	string	The version of the pipeline. (pattern: <code>^(0|([1-9]{1}\d*))$</code>)

Methods

The following methods are available for this resource:

Name	Accessible by	Required Params	Optional Params	Description
describe_pipeline	select	workspace_name, pipeline_name, region	version	Retrieves detailed information about a specific pipeline in a workspace.
list_pipelines	select	workspace_name, region	nextToken, maxResults	Lists pipelines in a workspace. To get complete details about a pipeline, use DescribePipeline.
create_pipeline	insert	workspace_name, region, pipelineName, computations		Creates a new pipeline in the specified workspace. A pipeline defines a directed acyclic graph (DAG) of compute nodes, where each node references a task and can declare dependencies on other nodes. Cyclic dependencies are not allowed. Nodes without dependencies run in parallel, while nodes with dependencies wait for all upstream nodes to complete successfully before starting. You can set environment variables at the pipeline level that are shared across all compute nodes, and override them at the individual compute node level.
update_pipeline	update	workspace_name, pipeline_name, region		Updates an existing pipeline in the specified workspace. Only the fields provided in the request are updated; fields not included in the request are preserved unchanged. You can update the pipeline description, environment variables, and the list of compute nodes independently.
delete_pipeline	delete	workspace_name, pipeline_name, region		Deletes a pipeline from the specified workspace. A pipeline cannot be deleted if it has any active executions. Wait for all executions to complete before attempting to delete the pipeline, or use CancelPipelineExecution to stop a running execution.
cancel_pipeline_execution	exec	workspace_name, pipeline_name, pipeline_execution_id, region		Cancels a pipeline execution in the specified workspace. If the execution is not in a terminal state (such as NOT_STARTED or RUNNING), it transitions to CANCELLING and asynchronously to CANCELLED. This operation is idempotent: calling it on an execution that is already CANCELLING or CANCELLED returns success with the current state. Calling it on a terminal execution (SUCCEEDED or FAILED) returns a conflict error. You can optionally provide a reason; it is returned in the stateDetails field when you describe the execution.
start_pipeline_execution	exec	workspace_name, pipeline_name, region		Starts execution of a pipeline in the specified workspace. Each compute node runs according to the DAG dependency order defined in the pipeline. Nodes without dependencies start immediately, while dependent nodes wait for all upstream nodes to complete successfully. You can provide runtime environment variable overrides that take the highest priority in the environment variable hierarchy, without modifying the pipeline definition.

Parameters

Parameters can be passed in the WHERE clause of a query. Check the Methods section to see which parameters are required or optional for each operation.

Name	Datatype	Description
pipeline_execution_id	string	The unique identifier of the pipeline execution.
pipeline_name	string	The name of the pipeline to execute.
region	string	AWS region (default: us-east-1)
workspace_name	string	The name of the workspace containing the pipeline.
maxResults	integer	The maximum number of results to return for each paginated request. Default: 50.
nextToken	string	The token to be used for the next set of paginated results.
version	string	The version number of the pipeline to retrieve. If not specified, returns the latest version.

SELECT examples

describe_pipeline

Retrieves detailed information about a specific pipeline in a workspace.

SELECT
computations,
created_at,
description,
environment_variables,
pipeline_arn,
pipeline_name,
status,
updated_at,
version,
workspace_name
FROM aws.iotsitewise.pipelines
WHERE workspace_name = '{{ workspace_name }}' -- required
AND pipeline_name = '{{ pipeline_name }}' -- required
AND region = '{{ region }}' -- required
AND version = '{{ version }}'
;

list_pipelines

Lists pipelines in a workspace. To get complete details about a pipeline, use DescribePipeline.

SELECT
created_at,
description,
pipeline_arn,
pipeline_name,
status,
updated_at,
version
FROM aws.iotsitewise.pipelines
WHERE workspace_name = '{{ workspace_name }}' -- required
AND region = '{{ region }}' -- required
AND nextToken = '{{ nextToken }}'
AND maxResults = '{{ maxResults }}'
;

INSERT examples

create_pipeline

Creates a new pipeline in the specified workspace. A pipeline defines a directed acyclic graph (DAG) of compute nodes, where each node references a task and can declare dependencies on other nodes. Cyclic dependencies are not allowed. Nodes without dependencies run in parallel, while nodes with dependencies wait for all upstream nodes to complete successfully before starting. You can set environment variables at the pipeline level that are shared across all compute nodes, and override them at the individual compute node level.

INSERT INTO aws.iotsitewise.pipelines (
pipelineName,
description,
environmentVariables,
computations,
tags,
clientToken,
workspace_name,
region
)
SELECT 
'{{ pipelineName }}' /* required */,
'{{ description }}',
'{{ environmentVariables }}',
'{{ computations }}' /* required */,
'{{ tags }}',
'{{ clientToken }}',
'{{ workspace_name }}',
'{{ region }}'
RETURNING
pipeline_arn,
pipeline_name,
status,
version
;

Manifest

# Description fields are for documentation purposes
- name: pipelines
props:
  - name: workspace_name
    value: "{{ workspace_name }}"
    description: Required parameter for the pipelines resource.
  - name: region
    value: "{{ region }}"
    description: Required parameter for the pipelines resource.
  - name: pipelineName
    value: "{{ pipelineName }}"
    description: |
      Reusable resource name with alphanumeric, hyphen, and underscore characters.
  - name: description
    value: "{{ description }}"
  - name: environmentVariables
    value: "{{ environmentVariables }}"
    description: |
      Map of environment variables for container configuration
  - name: computations
    description: |
      A list of compute nodes forming a pipeline DAG.
    value:
      - computeNodeName: "{{ computeNodeName }}"
        taskName: "{{ taskName }}"
        environmentVariables: "{{ environmentVariables }}"
        dependsOn: "{{ dependsOn }}"
  - name: tags
    value: "{{ tags }}"
  - name: clientToken
    value: "{{ clientToken }}"

UPDATE examples

update_pipeline

Updates an existing pipeline in the specified workspace. Only the fields provided in the request are updated; fields not included in the request are preserved unchanged. You can update the pipeline description, environment variables, and the list of compute nodes independently.

UPDATE aws.iotsitewise.pipelines
SET 
description = '{{ description }}',
environmentVariables = '{{ environmentVariables }}',
computations = '{{ computations }}'
WHERE 
workspace_name = '{{ workspace_name }}' --required
AND pipeline_name = '{{ pipeline_name }}' --required
AND region = '{{ region }}' --required
RETURNING
status,
version;

DELETE examples

delete_pipeline

Deletes a pipeline from the specified workspace. A pipeline cannot be deleted if it has any active executions. Wait for all executions to complete before attempting to delete the pipeline, or use CancelPipelineExecution to stop a running execution.

DELETE FROM aws.iotsitewise.pipelines
WHERE workspace_name = '{{ workspace_name }}' --required
AND pipeline_name = '{{ pipeline_name }}' --required
AND region = '{{ region }}' --required
;

Lifecycle Methods

cancel_pipeline_execution

Cancels a pipeline execution in the specified workspace. If the execution is not in a terminal state (such as NOT_STARTED or RUNNING), it transitions to CANCELLING and asynchronously to CANCELLED. This operation is idempotent: calling it on an execution that is already CANCELLING or CANCELLED returns success with the current state. Calling it on a terminal execution (SUCCEEDED or FAILED) returns a conflict error. You can optionally provide a reason; it is returned in the stateDetails field when you describe the execution.

EXEC aws.iotsitewise.pipelines.cancel_pipeline_execution 
@workspace_name='{{ workspace_name }}' --required, 
@pipeline_name='{{ pipeline_name }}' --required, 
@pipeline_execution_id='{{ pipeline_execution_id }}' --required, 
@region='{{ region }}' --required 
@@json=
'{
"reason": "{{ reason }}"
}'
;

start_pipeline_execution

Starts execution of a pipeline in the specified workspace. Each compute node runs according to the DAG dependency order defined in the pipeline. Nodes without dependencies start immediately, while dependent nodes wait for all upstream nodes to complete successfully. You can provide runtime environment variable overrides that take the highest priority in the environment variable hierarchy, without modifying the pipeline definition.

EXEC aws.iotsitewise.pipelines.start_pipeline_execution 
@workspace_name='{{ workspace_name }}' --required, 
@pipeline_name='{{ pipeline_name }}' --required, 
@region='{{ region }}' --required 
@@json=
'{
"executionEnvironmentVariableOverrides": "{{ executionEnvironmentVariableOverrides }}", 
"executionPriority": {{ executionPriority }}, 
"clientToken": "{{ clientToken }}"
}'
;