Published Release Notes

Strategies are now available as a condition type in proposition filters

When designing proposition filters, you can now include strategy outcomes as a condition to be evaluated. Select a strategy and specify the component that you want to use as output to include more advanced decisioning in your proposition filters.

For more information, see Enrich your Proposition Filter rules with conditions based on strategy results.

Pega Express methodology in App Studio for successful Microjourneys

App Studio now supports the Pega Express™ methodology to help you visualize the key factors of your Microjourneys™ - case types, personas, and data objects. With Microjourneys, you can analyze and clearly communicate who the parties that interact with your cases are, what channels of communication they use, and what data they need to resolve a case. Associating personas and data objects with case types also helps you manage your development team's workload by using a list of the draft elements that they need to develop.

For more information, see Plan successful microjourneys in App Studio (8.4), Creating a microjourney for customer success.

Upgrade impact

During a Pega Infinity™ upgrade to 8.4 and later, clients using App Studio are asked to update their applications to support use of the Pega Express™ methodology. Without this application update, the Persona landing page and Data objects and integration landing page are empty. For more information, see Pega 8.4 Deep Dive: Pega Express methodology in App Studio.

What steps are required to update the application to be compatible with this change?

In order to utilize the Pega Express methodology in App Studio and use the Inventory page, click Start now to complete the update of your application and add the required rules to it. If you choose to cancel, App Studio continues to work as expected without the Pega Express methodology features; you can click Start now at the top of your application overview page at any time to install the required rules in your application.

Relationships between elements of Microjourneys in application inventory

A new Inventory page in App Studio helps you manage a delivery of your projects by giving you an overview of the elements of your application and how they interact with your Microjourneys™. The new Inventory page lists draft relationships between the case types, personas, and data objects that you want to implement through development. By checking releases that correspond to the items that you need to develop, you can prioritize your work accordingly. 

For more information, see Plan successful microjourneys in App Studio (8.4), Creating a Microjourney for customer success, Managing application inventory.

Upgrade impact

During a Pega Infinity™ upgrade to 8.4 and later, clients using App Studio are asked to update their applications to support use of the Pega Express™ methodology. Without this application update, the Persona landing page and Data objects and integration landing page are empty. For more information, see Pega 8.4 Deep Dive: Pega Express methodology in App Studio.

What steps are required to update the application to be compatible with this change?

In order to utilize the Pega Express methodology in App Studio and use the Inventory page, click Start now to complete the update of your application and add the required rules to it. If you choose to cancel, App Studio continues to work as expected without the Pega Express methodology features; you can click Start now at the top of your application overview page at any time to install the required rules in your application.

Default text analytics model for detecting small talk

Enhance your web chat experience by configuring chatbots to detect small talk. Pega Platform™ provides the default model that is a topic detection model, available for English, German, Spanish, Dutch, Portuguese, Italian, and French.

For more information, see Configure your chatbot for small talk.

Integrate your application with external Kafka clusters

Configure your application to use an external Kafka cluster for managing real-time data. By having an external Stream service provider, you can perform such maintenance tasks as an upgrade or hotfix deployment faster because external nodes do not require restarting.

For more information, see Externally managed Stream service.

Updated architecture of the data flow service

Benefit from improvements to data flow architecture that increase the stability of data flow runs and minimize the need for manual restarting of data flow jobs. Real-time data flows now use improved node rebalancing for better handling of failed or restarted nodes. If the topology changes, batch data flows no longer attempt to pause and resume the run. As such, there are fewer interactions with the database and between the nodes, resulting in the increased resilience of the Data Flow service.

If you are upgrading from a previous version of Pega Platform™, see Changes to the architecture of the Data Flow service for an overview of the changes to the Data Flow service compared to previous versions.

Changes to the architecture of the Data Flow service

In Pega Platform™ 8.4, the architecture of batch and real-time data flows uses improved node handling to increase the stability of data flow runs. As a result, there are fewer interactions with the database and between the nodes, resulting in increased resilience of the Data Flow service.

If you upgrade from a previous version of Pega Plaftorm, see the following list for an overview of the changes in the behavior of the Data Flow service compared to previous versions:

• Responsiveness
• Updates to lifecycle actions
• Starting a run
• Triggering pre- and post-activities
• Selecting a node fail policy
• No service nodes and active runs

Responsiveness

Nodes no longer communicate and trigger each other, but run periodic tasks instead. As such, triggering a new run does not cause the service nodes to immediately start the run. Instead, the run starts a few seconds later. The same applies to user actions such as stopping, starting, and updating the run. The system also processes topology changes as periodic tasks, so it might take a few minutes for new nodes to join runs, or for partitions to redistribute when a node leaves a run.

Updates to lifecycle actions

To make lifecycle actions more intuitive, the Stop action consolidates both the Stop and Pause actions. The Start action consolidates both the Resume and Start actions.

You can resume or restart stopped and failed runs with the Start and Restart actions. The Start action is only available for resumable runs and continues the run from where it stopped. The Restart action causes the run to process from the beginning. Completed runs can only be restarted. If a run completes with failures, you can restart it from the beginning, or process only the errors by using the Reprocess failures action.

Starting a run

New data flow runs have the Initializing status, and start automatically. You no longer need to manually start a new run, so the New status is now removed.

If there are no nodes available to process a run, the run gets the Queued status and waits for an available node.

Triggering pre- and post-activities

The system now triggers pre-activities on a random service node, rather than on the node that triggered the run.

The system triggers post-activities only for runs that complete, fail, or complete with failures. If you manually stop a run with the Stop action, the post-activity does not trigger. However, restarting the run with the Restart action triggers first the post-activity, and then the pre-activity.

You can no longer choose to run pre- and post-activities on all nodes.

Selecting a node fail policy

For resumable runs, you can no longer select a node fail policy. If a node fails, the partitions assigned to that node automatically continue the run on different nodes.

For non-resumable runs, you can choose to restart the partitions assigned to the failed node on different nodes, or to fail the partitions assigned to the failed node.

No service nodes and active runs

If the last data flow node for an in-progress run fails, the run remains in the In Progress state, even if no processing takes place. This behavior results from the fact that data flow architecture now prevents unrelated nodes from affecting runs.

Support for predictive models in PMML version 4.4

Pega Platform™ now supports the import of predictive models in Predictive Model Markup Language (PMML) version 4.4. With this feature, you can import PMML models that use the anomaly detection algorithm.

For a list of all supported PMML models, see Supported models for import. 

Consistent search experience in App Studio

Pega Platform™ now supports a unified search mechanism in App Studio. Instead of manually locating a single item, such as a case type, a channel, or a data object, you can simply use the Search option in the navigation pane. You can also use Search in case types and personas landing pages, to conveniently access the information that you need, for example channels and case types associated with a persona.  

For more information, see Plan your Microjourneys more conveniently in an improved Case Designer (8.5), Creating a Microjourney for customer success.

Automated project estimation in App Studio

App Studio now supports estimating projects in an intuitive and automated way, so that you can plan your work with greater efficiency and accuracy. Estimations include the number of hours that you will need to deliver an application, based on multiple factors such as the delivery methodology, the number and complexity of features to implement, and the number of teams involved. After you provide the required data, the project estimator calculates the expected duration of application development. To share your project estimates outside Pega Platform™, for example with your stakeholders, you can also export estimates to an .xlsx file.

For more information, see Estimate projects automatically in App Studio (8.5), Estimating application development.