Published Release Notes

More action types on the bottom bar

Pega Infinity Mobile Client™ now provides more flexible bottom bar configuration with a broader choice of actions, so that your apps can be more useful. For example, users can now create work items, open work items, or log out directly from the bottom bar of a mobile app.

For more information, see Configuring the bottom bar.

Support for custom database tables in external Cassandra clusters

Pega Platform™ now supports a connection to external Cassandra clusters through a dedicated Database Table data set, which reduces the need for data ingestion and export. You can use custom tables that you store in your external Cassandra cluster in data flows for accessing and saving data. You can access your custom data model by mapping the model to a Pega Platform class.

For more information, see Connecting to an external Cassandra database through a Database Table data set.

Enhanced data flow performance monitoring

The performance alert log now provides more detailed information about the data flows in your application. You can view performance details for data flows that are currently running and data flow runs that have completed successfully. You can also view a performance summary for data flow runs that are running for too long or have failed.

For more information, see:

• PEGA0082 alert: Dataflow started
• PEGA0083 alert: Dataflow complete
• PEGA0062 alert: Data flow execution time above threshold
• PEGA0072 alert: Data flow run failed

Ability to support advanced device features with Pega Infinity Mobile Client

Pega Infinity Mobile Client™ now provides a development kit that you can use to make mobile apps support advanced device features that are typically available to native applications, for example, an embedded laser scanner or a projector module, and integrate functions of external software solutions, for example, a cloud-based file storage.

For more information about enhancing mobile apps with device feature support, see the documentation for the development module in the latest Pega Infinity Mobile Client distribution package on Digital Delivery.

Support for regular performance alerts

You can now specify how often Pega Platform™ sends you performance alerts about SLA violations in data flow runs. By default, the interval is 5 seconds for single case data flows and 5 minutes for batch and real-time data flows.

The following dynamic system settings control the alert interval:

• Single case runs: dataflow/singlecase/alert/throttleTime
• Batch runs: dataflow/batch/alert/throttleTime
• Real-time runs: dataflow/realtime/alert/throttleTime

For more information, see PEGA0062 alert: Data flow execution time above threshold.

Automatic model training when mapping entities to case properties in Email Bot

You can now initiate automatic feedback to entity models in Pega Email Bot™, during manual mapping of email content to a case property.

To enable automatic feedback, you set the Work-Channel-Triage.pyIsRuntimeFeedback rule to true in Pega Platform™. By default this feature is disabled. Enabling this feature ensures that the email bot is more responsive by automatically copying detected entities, such as names, locations, dates, and ZIP codes, to case type properties of a case type.

For more information, see Email triage, Email channel NLP model and Enabling the NLP model training for the email channel.

Prediction Studio notifications

Prediction Studio now displays notifications when adaptive or predictive models encounter problems. For example, if the performance of a model decreases suddenly, a notification appears, which you can use to immediately investigate the cause of the problem.

For more information, see Accessing Prediction Studio notifications and Prediction Studio notification types.

Production data sampling and migration for decision strategy simulations

Pega Platform™ now supports the sampling and migration of data from the production environment to the simulation environment. The data that is migrated for simulations includes customer details, Adaptive Decision Management information, and interaction history. By running a simulation on that sample data in Pega Marketing™ or Pega Customer Decision Hub™, you can verify how the changes to your decision logic impact the results. You can use that information to optimize and adjust your decision algorithms and processes.

For more information, see Deploying sample production data to a simulation environment for testing.

Integrate text analytics with decision strategies through the Interaction API

The Interaction API provides more context for making next-best-action decisions by integrating text analytics with decision management components such as strategies, propositions, and interaction history. By including natural language processing in your decisioning solution through the Interaction API, you ensure that the next-best-action decisions that you make are more informed and accurate.

For more information, see Customizable Interaction API for text analytics.

Support for machine learning as a service models

In Pega Platform™, you can now run advanced machine learning and artificial intelligence models that you develop in third-party tools. By configuring a connection with an external machine learning as a service provider, such as Google AI Platform, you can use the predictive power of your custom models to improve the predictions in your customer strategies.

For more information, see Connecting to a Machine Learning as a Service model and Configuring a machine learning service connection.