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Optional: Configuring the Adaptive Decision Manager service for Pega Cloud Services

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The Adaptive Decision Manager (ADM) service provides predictions of customer behavior by creating adaptive models based on customer responses to your offers. With adaptive models, you can ensure that your next-best-action decisions are always relevant and based on the latest customer behavior.

The following dynamic system settings control the ADM service:

decision/monitoring/daysToKeepData
This setting determines how much time elapses before Pega Platform automatically deletes a snapshot from your repository. By default, Pega Platform deletes snapshots with a time stamp older than 180 days.
admmart/snapshotAtEveryUpdate
By enabling this setting, you can configure the ADM service to take snapshots every time the model is updated. If the setting is disabled, the default system behavior is to take adaptive model data snapshots at intervals that are determined by the ADM snapshot agent schedule, typically every night.
  1. In the navigation panel of Dev Studio, click Records SysAdmin Dynamic System Settings .

  2. To change how much time elapses before Pega Platform automatically deletes a snapshot from your repository, change the value of the decision/monitoring/daysToKeepData dynamic system setting.

  3. To configure the ADM service to take snapshots every time the model is updated, add the admmart/snapshotAtEveryUpdate dynamic system setting:

    If you enable this option for a prolonged period, the increased number of snapshots might cause database space issues.
    1. On the Dynamic System Settings tab, click Create.

    2. On the New tab, enter a short description of the dynamic system setting.

      Take snapshots at every model update
    3. In the Owning Ruleset field, enter Pega-DecisionEngine.

    4. In the Setting Purpose field, enter admmart/snapshotAtEveryUpdate.

    5. Click Create and open.

    6. On the Settings tab, in the Value field, enter true, and then click Save.

      The admmart/snapshotAtEveryUpdate setting is added to the list. The ADM service starts taking adaptive model data snapshots every time the model is updated.
  4. To revert to the default snapshot schedule, disable the admmart/snapshotAtEveryUpdate dynamic system setting:

    1. On the Dynamic System Settings tab, click the admmart/snapshotAtEveryUpdate setting.

    2. On the Settings tab, in the Value field, enter false, and then click Save.

  • Configuring the Adaptive Decision Manager service for on-premises environments

    Enable the prediction of customer behavior by configuring the Adaptive Decision Manager (ADM) service. The ADM service creates adaptive models and updates them in real time based on incoming customer responses to your offers. With adaptive models, you can ensure that your next-best-action decisions are always relevant and based on the latest customer behavior.

  • Adaptive Decision Manager service

    The Adaptive Decision Manager (ADM) creates and updates adaptive models by processing customer responses in real time. By including adaptive models in your next-best-actions strategies, you can make better decisions for your business based on accurately predicted customer behavior.

  • Enabling decision management services

    Decision management services comprise the technical foundation of decision management. Learn more about decision management services and how to enable them to fully benefit from next-best-action strategies and other decision management features in Pega Platform.

  • Pega-DecisionEngine agents

    The Pega-DecisionEngine agents support Decision Management operations.

  • Model management

    On the Model Management landing page, you can manage adaptive models that were run and predictive models with responses. You can view the performance of individual models and the number of their responses, or perform various maintenance activities, such as clearing, deleting, and updating models.

  • Adaptive model details

    On the Model Management landing page, you can access details about the adaptive models that were executed (such as the number of recorded responses, last update time, and so on). The models are generated as a result of running a decision strategy that contains an Adaptive Model shape.

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