Published Release Notes

Alerts for long-running queue processor and job scheduler activities

Pega Platform™ now saves an alert in the performance alert log when a queue processor activity or a scheduled job runs longer than the configured threshold value. Use the alerts to identify potential performance issues with long-running processes.

The alerts are enabled by default. You can change the alerts for dedicated queue processors and job schedulers at the rules level. For standard queue processors, you can also set the threshold value for the Queue-For-Processing command in an activity. You disable the alerts in dynamic system settings.

For more information, see:

• PEGA0117 alert: Long-running queue processor activity
• PEGA0118 alert: Long-running job scheduler activity

Automatic draft off mode for processes in case types

App Studio now supports automatically turning off the draft mode for processes in your case types. Any process that you add to a case type is in draft mode by default so that you can run the case type to check the run-time behavior even if the process contains errors. However, in a production environment, processes in draft mode do not work. To save time and deliver your projects faster, any process that has no errors now automatically switches off draft mode when you save the case type. Additionally, Case Designer now displays a list of errors that processes in your case type include, so that you can quickly locate any issues.

For more information, see Save time and effort with automatic draft off mode for processes in case types (8.5), Draft mode of case processes.

Usability improvements in the Email Manager and Case Manager portals

Pega Email Bot™ customer service representatives (CSRs) working in the Email Manager, Case Manager, or Case Worker portals can now quickly reply to one recipient or to all recipients. CSRs can also view the sentiment analysis of an email (positive, negative, or neutral) for each received email, displaying the sentiment pattern for the entire email thread in a triage case. The email bot improvements add value for CSRs working in the portals and help them save time when responding to user requests.

For more information, see Understanding the email triage process and Replying to customers by email for an email bot.

Enhancing your revision management process with Deployment Manager pipelines

Pega Platform 8.5 offers improved synergy between revision management and the automated deployment process provided by Pega's Deployment Manager 4.8 pipelines. Use Deployment Manager 4.8 to increase the efficiency of business-as-usual application changes and automatize the deployment of revision packages.

For more information, see Managing the business-as-usual changes.

Support for Cloud AutoML topic detection models

In Prediction Studio, you can now connect to topic detection models that you create in Cloud AutoML, Google's cloud-based machine learning service. You can then use the models to categorize and route messages from your customers.

For more information, see Broaden your selection of topic detection models by connecting to third-party services (8.5).

Support for custom topic detection models through an API

In Prediction Studio, you can now connect to your custom topic detection models through an API. You can then use the models to categorize and route messages from your customers.

For more information, see Broaden your selection of topic detection models by connecting to third-party services (8.5).

Default Create stage in a case life cycle

Pega Platform™ now adds a default Create stage to a case life cycle every time you create a new case type, both in App Studio and Dev Studio. The default Create stage includes a view that users interact with to provide initial data before case processing begins. Consequently, you can now easily locate the view to make any necessary changes. In the background, the Create stage makes a case type independent from the starting process, which removes relevant advanced configurations and makes application development faster.

For more information, see Capture initial data faster with the default Create stage (8.5), The Create stage.

Control group configuration for predictions

You can now configure a control group for your predictions in Prediction Studio. Based on the control group, Prediction Studio calculates a lift score for each prediction that you can later use to monitor the success rate of your predictions.

For more information, see Customizing predictions.

Response timeout configuration for predictions

You can now set a response timeout for your predictions in Prediction Studio. By setting a response timeout, you control how Prediction Studio registers customer responses that later serve as feedback data for your predictions.

For more information, see Customizing predictions.

New JWT access token format: Authorized Access Token

Pega Platform™ is changing from using opaque tokens to using JSON Web (JWT) tokens and the JWT access token format: Authorized Access Token (AAT). An AAT enables a client application to validate the server for user permissions and authorizes a specific application to access specific parts of a user’s data.

The major benefits to using the JWT format are:

• The JWT is a self-contained token that has authentication information, expire time information, and other user-defined claims digitally signed.
• A single token can be used with multiple applications.
• The tokens are short-lived and can minimize damage if transport security is compromised, as the token signature is verified.
• As the token is verified with the signature, there is no need to verify against a database, thus reducing latency (usually important for Web APIs).

For more information, see Understanding authorized access tokens.