sample code for running custom workflow in Intersight Cloud Orchestrator and retrieving the output.
- Kevin Chen
- Intersight
This uses a workflow originally from dCloud demo of Intersight, Getting started with Intersight orchestration V2, the SDK is using the default SaaS platform therefore the workflow is exported from the dCloud demo and re-imported to Intersight.
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Set up a Python virtual environment. Make sure Python 3 is installed in your environment, and if not, you may download Python here. Once Python 3 is installed in your environment, you can activate the virtual environment with the instructions found here.
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Install the requirements with
pip3 install -r requirements.txt -
Generate Intersight API KEY ID and secret on the Intersight dashboard. Follow the latest instructions here on the Intersight API Documentation
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Set up the environment file as per .env example file. The .env file contains credentials used for the code to authenticate with Intersight.
INTERSIGHT_API_KEY_ID = [insert your API KEY ID generated]
INTERSIGHT_API_PRIVATE_KEY = [path to the secret key text file downloaded from Intersight]
Organization_MoId = [The organization ID for your specific Organization on Intersight]
- You can run sampleCode/get_workflows.py to see the history of workflows that has been executed.
$ python sampleCode/get_workflows.py
This will generate an output that lists workflow information such as workflow definition MoId, inputs used, status, etc. The information here can be used for step 6.
- Customise sampleCode/run_workflow.py to run your workflows.
Currently the function refer to a workflow corresponding to my specific demo instance, therefore workflow definition MoId should be modified according to the information collected in step 5.
workflow_definition=WorkflowWorkflowDefinitionRelationship(
class_id="mo.MoRef",
moid="660b69c7696f6e3201f1dc71",
object_type="workflow.WorkflowDefinition"
)- Run the modified python script
$ python sampleCode/run_workflow.py
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