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When you have Watson Studio, Watson Knowledge Catalog, or Watson Machine Learning provisioned as services in your IBM Cloud account, you can see the events in the IBM Cloud Activity Tracker.
View events in the Activity Tracker in the same IBM Cloud region that you provisioned your services, except for the Tokyo (AP North) region. Events for services that you provision in the Tokyo region are sent to the Activity Tracker in the Sydney region.
Allocate the lock for the modeler flow to the user.
pm-20.modeler-flow-preview.create
Preview a node in a modeler flow.
pm-20.modeler-output.delete
Delete a modeler flow output.
pm-20.spark-kernels.receive
Get the list of Spark kernels.
pm-20.spark-kernel.delete
Delete a Spark kernel.
pm-20.projects.receive
Get the list of projects in which a modeler flow can be created.
pm-20.project-name.receive
Get the name of the project.
pm-20.project-role.receive
Get the project role of the current user.
pm-20.project-compute-services.receive
Get the compute services of the project.
pm-20.project-container.receive
Get the container of the project.
pm-20.project-storage-type.receive
Get the storage type of the project.
Event for model visualization in Watson Studio
Action
Description
pm-20.model.visualize
Visualize model output. The model output can have a single model, ensemble models, or a time-series model. The visualization type can be single, auto, or time-series. This visualization type is in requestedData section.
Events for Watson Machine Learning training assets
Action
Description
pm-20.training.authenticate
Authenticate user.
pm-20.training.authorize
Authorize user.
pm-20.training.list
List all of training.
pm-20.training.get
Get one training.
pm-20.training.create
Start a training.
pm-20.training.delete
Stop a training.
Events for Watson Machine Learning repository assets
The deployment events are tracked for these Watson Machine Learning repository assets:
Asset type
Description
wml_model
Represents a machine learning model asset.
wml_model_definition
Represents the code that is used to train one or more models.
wml_pipeline
Represents a hybrid-pipeline, a SparkML pipeline or a sklearn pipeline that is represented as a JSON document that is used to train one or more models.
wml_experiment
Represents the assets that capture a set of wml_pipeline or wml_model_definition assets that are trained at the same time on the same data set.
wml_function
Represents a Python function (code is packaged in a compressed file) that will be deployed as online deployment in Watson Machine Learning. This code needs to contain a score(…) python function.
wml_training_definition
Represents the training metadata necessary to start a training job.
wml_deployment_job_definition
Represents the deployment metadata information to create a batch job in WML. This asset type contains the same metadata that is used by the /ml/v4/deployment_jobs endpoint. When you submit batch deployment jobs, you can either provide the job definition inline or reference a job definition in a query parameter.
These activities are tracked for each asset type:
Action
Description
pm-20.<asset_type>.list
List all of the specified asset type.
pm-20.<asset_type>.create
Create one of the specified asset types.
pm-20.<asset_type>.delete
Delete one of the specified asset types.
pm-20.<asset_type>.update
Update a specified asset type.
pm-20.<asset_type>.read
View a specified asset type.
pm-20.<asset_type>.add
Add a specified asset type.
Events for Master Data Management
Action
Description
mdm-oc.data.read
Read access operations on the Data microservice.
mdm-oc.data.write
Write access operations on the Data microservice.
mdm-oc.data.manage
Manage operations on the Data microservice.
mdm-oc.matching.read
Read access operations on the Matching microservice.
mdm-oc.matching.write
Write access operations on the Matching microservice.
mdm-oc.matching.manage
Manage access operations on the Matching microservice.
mdm-oc.model.read
Read access operations on the Model microservice.
mdm-oc.model.write
Write access operations on the Model microservice.
mdm-oc.model.manage
Manage operations on the Model microservice.
mdm-oc.configurator.read
Read access operations on the Configuration microservice.
mdm-oc.configurator.manage
Manage operations on the Configuration microservice.
mdm-oc.pairs-analysis.read
Read access operations on the Pair Analysis microservice.
mdm-oc.pairs-analysis.write
Write access operations on the Pair Analysis microservice.
mdm-oc.job.read
Read access operations on the Jobs microservice.
mdm-oc.job.write
Write access operations on the Jobs microservice.
mdm-oc.matching.datasteward
Data stewards access operations on the Job Analysis microservice.