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PREDIX Analytics (Orchestration (Configuration (Developing an…

- - - - {
        "analyticName":<string>,
        "analyticVersion":<string>,
        "comment":<string>,
        "orchestrationStepId":<string>,
        "iterations":[<list of Iterations>]
        }
      - Iteration Type
        
        {
        "inputMaps":[<list of PortMaps>],
        "outputMaps":[<list of OutputDataConnectorMaps>],
        "inputModelMaps":[<list of ModelPortMaps>],
        "id":<string>,
        "name":<string>
        }
        
        PortMap Type
        
        {
        "valueSourceType":<string>,
        "fullyQualifiedPortName":<string>
        }
        
        InputConstantMap Type (type of PortMap)
        
        {
        "valueSourceType":<string>,
        "fullyQualifiedPortName":<string>,
        "value":<string>
        }
        
        value Field
        
        Numeric or String value
        
        Parameter and passed in at runtime using customAttribute field of OrchestrationExecution
        
        InputDataConnectorMap Type (type of PortMap)
        
        {
        "valueSourceType":<string>,
        "fullyQualifiedPortName":<string>,
        "fieldId":<string>,
        "dataSourceId":<string>,
        "queryCriteria":<string>,
        "tagNameQuery":<string>
        }
        
        OutputDataConnectorMap Type
        
        {
        "fullyQualifiedPortName":<string>,
        "fieldId":<string>,
        "dataSourceId":<string>,
        "tagNameQuery":<string>
        }
        
        ModelPortMap Type
        
        {
        "modelPortName": <string>,
        "modelName": <string>,
        "modelVersion": <string>
        }
  - - - POST <execution_uri>/api/v2/execution/orchestrations/{orchestrationConfigurationId}/deployment
    - - Used for
        
        Configure dynamic tags in port-to-field map
        
        Customize query criteria attributes in port-to-field map
        
        These custom attributes are also passed to custom data connectors
    - - Single Asset + Asset Group
        
        CREATE the orchestration request body containing the orchestrationConfigurationId
        
        (Optional) PASS Custom Attributes
        
        CREATE an Orchestration Configuration
        
        RUN the orchestration
      - External Data Source
        
        CREATE the orchestration request body containing the orchestrationConfigurationId
        
        RUN the orchestration
        
        CREATE an Orchestration Configuration
      - Time Series Tags
        
        CREATE an Orchestration Configuration
        
        ASSOCIATE each field in the orchestration configuration's port-to-field map with a tag name in the Time Series service.
        
        CREATE the orchestration request body containing the orchestrationConfigurationId
        
        (Optional) PASS Custom Attributes
        
        RUN the orchestration
        
        POST <execution_uri>/api/v2/execution/async
      - One Analytic
        
        Download the sample BPMN workflow
        
        Edit the saved sample BPMN workflow file
        
        <Analytic Catalog Entry Id>
        
        <Analytic Name>
        
        <Analytic Version>
        
        Prepare the input for the demo analytic
        
        Send an orchestration execution request
        
        POST <execution_uri>/api/v2/execution/testrun
  - - - Definition
        
        Format of input and output JSON structure
        
        Port-to-field map
        
        How to get values
        
        Where to write the values
        
        Use fieldId
      - Handle Predix Time Series Data
        
        fieldId is mapped to a Predix Time Series tag id
        
        Process
        
        Orchestration is run for the asset group or a single asset
        
        tagNameQuery exists, use this query to TRANSALTE the fieldId to a time series tag id
        
        tagNameQuery doesn't exist, use the tenant's default tag query
        
        Orchestration is run without an asset identifier
        
        MUST contain a map of fieldId to Predix TIme Series tag ids
      - Handle Persistent and Temporary Data
        
        Identity the data source to be passed by dataSourceId
        
        "Temporary"
        
        Cache the value for use by analytics in the orchestration
        
        Persistent store
        
        Read/Write the value to the persistent storage
    - - Custom tag query - tagNameQuery to override the default tag query value in the port-to-filed map
      - Data source for the tagNameQuery is Predix Asset Service -> tagNameQuery is GEL query
      - tagNameQuery can have 2 parameters
        
        ${ASSET_ID}
        
        ${FIELD_ID}
    - - Use Cases
        
        Sensor data is stored in PostgreSQL DB
        
        Image data is stored in Predix Blobstore + Sensor data is stored in Predix Time Series
        
        Self-learn and produce model data every time it runs
        
        Legacy asset data is stored in PostgreSQL DB + More recent asset data is stored in Predix Asset
      - Custom Data Connector Service
        
        Developing
        
        Requirements
        
        3 must implement APIs
        
        HEALTHCHECK
        
        /api/v1/analytics/customdata/healthcheck
        
        Status 200 response for successful execution
        
        READ
        
        /api/v1/analytics/customdata/read
        
        Status 200 response for successful execution
        
        WRITE
        
        /api/v1/analytics/customdata/write
        
        Status 201 response for successful execution
        
        Secured using custom UAA-based authentication
        
        Without custom credential
        
        Use the same authorization token used during orchestration execution
        
        With custom credentials
        
        A fresh token fetched
        
        Must DEPLOY, RUN, MANAGE in Predix org and space
        
        Must be REACHABLE by the analytics framework via HTTPS
        
        Implementing
        
        DEPLOY it to Predix cloud
        
        CONFIGURE a port-to-field
        
        EXECUTE an orchestration
        
        DEVELOP your Custom Data Connector service
      - Update Runtime with External Data Source Client Credentials
        
        Require update the runtime configuration
        
        Provide the corresponding externalService configuration parameters
      - Limitations
        
        The Custom Data Connector service must be able to authenticate the same token used to run orchestration execution
        
        The READ and WRITE data operations must complete and return within one minute
        
        NOT INVOKE your Custom Data Connector service with custom HTTP header details.
  - - - GET <monitoring_uri>/api/v1/monitoring/orchestrations/{orchestrationRequestId}
    - - GET <analytic-uri>/api/v1/analytic/execution/async/{requestId}/result
    - - COMPLETED
      - FAILED
      - PROCESSING
  - - - With Single Asset | For Asset Group
        
        :fire:　Create the orchestration configuration entry and upload the BPMN and port-to-field artifacts
        
        :red_flag: CREATE the default tag query
        
        Create the port-to-field maps for the analytics in the orchestration
        
        :red_flag: (Optional) CREATE a custom tag query in the port-to-field maps
        
        If using trained analytics
        
        Review the requirements
        
        Upload the trained models for the analytic
        
        Deploy the orchestration workflow file
        
        :star: Validate the structure of the orchestration workflow file and health of referenced analytics
        
        Run the orchestration with the orchestration configuration and asset id
        
        Create the orchestration workflow files
        
        Verify the orchestration execution results status
        
        Understand how to find the URI values and to configure the REST headers for each API
      - Using Predix Time Series Tags
        
        If using trained analytics
        
        REVIEW the requirements
        
        UPLOAD the trained models for the analytic
        
        CREATE the port-to-field maps for the analytics in the orchestration
        
        :star: VALIDATE the structure of the orchestration workflow file and health of reference analytics
        
        :fire: CREATE the orchestration configuration entry and UPLOAD the BPMN and port-to-field artifacts
        
        CREATE the orchestration workflow files
        
        DEPLOY the orchestration workflow file
        
        Understand how to FIND the URI values and to CONFIGURE the REST headers for each API
        
        RUN the orchestration with the tag id map in the request
        
        VEFY the orchestration execution result status
      - Using an External Data Source
        
        Create the port-to-field maps for the analytics in the orchestration
        
        dataSourceId = identity the external data source
        
        :fire: Create the orchestration configuration entry and upload the BPMN and port-to-field artifacts
        
        If using trained analytics
        
        Review the requirements
        
        Upload the trained models for the analytic
        
        :red_flag:　DEVELOP your Custom Connector Service (Java-based reference with PostgreSQL DB) and deploy it to Predix cloud.
        
        :star: Validate the structure of the orchestration file and health of referenced analytics
        
        Deploy the orchestration workflow file
        
        Create the orchestration workflow files
        
        Run the orchestration for analytics using an external data source
        
        Understand how to find the URI values and to configure the REST headers for each API
        
        Verify the orchestration execution results status
    - - Precondition
        
        Hosted in the Analytic Catalog
        
        Deployed the Cloud Foundry
        
        Running
      - API
        
        POST <execution_uri>/api/v2/execution/validation
    - - Create an orchestration configuration entry with the attributes
        
        API: POST <config_uri>/api/v2/config/orchestrations
      - Upload the orchestration workflow file
        
        API: POST <config_uri>/api/v2/config/orchestrations/artifacts
      - Upload the port-to-field map files corresponding to each orchestration step defined in the orchestration workflow
        
        API: POST <config_uri>/api/v2/config/orchestrations/artifacts
    - - API: POST <config_uri>/api/v2/config/orchestrations/defaulttagquery
    - - API: GET <config_uri>/api/v2/config/orchestrations
    - - Delete an orchestration + all the artifacts
        
        API: DELETE <config_uri>/api/v2/config/orchestrations/{id}
      - Delete one artifact attached to an orchestration
        
        API: DELETE <config_uri>/api/v2/config/orchestrations/artifacts/{id}
  - - - RETRIEVE job definitions
      - RETRIEVE job history
      - CREATE
      - UPDATE
      - DELETE
      - ※　Enable/Disable by update job state to Active/Inactive
    - - POST <scheduler_uri>/api/v1/scheduler/jobs
    - - GET <scheduler_uri>/api/v1/scheduler/jobs/{jobId}/history
- - - - {
        "analyticName":<string>,
        "analyticVersion":<string>,
        "comment":[<string>],
        "inputPortDefinitions":[<List of PortDefinition>],
        "inputModelDefinitions":[<List of InputModel>],
        "outputPortDefinitions":[<List of PortDefinition>]
        }
    - - {
        "name" : <String>,
        "description" : <String>,
        "packageName" : <String>,
        "codeLanguage" : <String>,
        "version" : <String>,
        "author" : <String>,
        "inputDataPortDefinitions" : [<List of DataPortDefinition>],
        "constantDataPortDefinitions" : [<List of DataPortDefinition>],
        "outputDataPortDefinitions" : [<List of DataPortDefinition>]
        }
    - - TimeseriesArrayPort
        
        {
        "comment": [<string>],
        "portName": <string>,
        "portType": <string>,
        "variable": <boolean>,
        "columns": [<List of FieldPorts>]
        }
      - CompositePort
        
        {
        "comment":[<string>],
        "portName":<string>,
        "portType":<string>,
        "variable":<boolean>,
        "childrenPorts":[<List of PortDefinition>]
        }
      - FieldPort
        
        {
        "comment":[<string>],
        "portName":<string>,
        "portType":<string>,
        "variable":<boolean>,
        "engUnit":<string>,
        "dataType":<string>,
        "required":<boolean>
        }
      - childrenPorts
    - - { "modelPortName": <string>,
        "comments" : [<string>] }
  - - - Using the UI
        
        Select the Analytics tab to open the Analytics Catalog page
        
        Click New Analytics to open the Analytic Editor
        
        In the Attributes section, provide the follow info
        
        Taxonomy Location (+)
        
        Name (*)
        
        Author(*)
        
        Description (+)
        
        Version(*
        
        Language(*)
        
        Click Select a file to attach in Files pane to upload a file
        
        Java, Matlab -> JAR file
        
        Python -> ZIP file
        
        Click Save
      - Using REST APIs
        
        Update the catalog taxonomy structure for the analytic classification (+)
        
        Create an analytic catalog entry with the attribute for the analytic
        
        Upload the executable to the catalog (max size 250MB)
        
        Validate the analytic runs in the Cloud Foundry environment (deploy, run, retrieve the results)
    - - Synchronously Using the Analytics Catalog
      - Synchronously Using a Direct Call
      - Asynchronously Using a Direct Call
    - - Pagination
      - Sorting
      - Filtering
    - - Promote the validated analytic to a production state so it can be consumed by the Runtime service
      - Optimize the analytics's memory usage, disk usage, and number of instance
      - Restart the previous deployed analytic
  - - - By REST API
        
        Get the list of artifacts attached
        
        GET <catalog_uri>/api/v1/catalog/analytics/{id}/artifacts
        
        Download an artifact by its ID
        
        GET <catalog_uri>/api/v1/catalog/artifacts/{id}/file
      - By UI
    - - Get the list of artifacts attached
      - Update the executable artifact
        
        PUT <catalog_uri>/api/v1/catalog/artifacts/{id}
    - - API
        
        POST <catalog_uri>/api/v1/catalog/artifacts
        
        Multipart/form-data type
        
        file
        
        catalogEntryID
        
        type
        
        executable : executable analytic artifact
        
        Template : analytic template file