Published Release Notes

DCO Compatibility tool is deprecated

The DCO Compatibility tool has been deprecated. Use the Application Guardrails landing page to see the compliance score and any warnings for your application.

For more information, see Application Guardrails landing page.

Security fields in JFrog Artifactory repository rule form removed

The fields in the Security section of the JFrog Artifactory repository rule form, including the Secure protocol field, the Truststore field, and the Keystore field, were not functional in Pega Platform™ 7.3, 7.3.1, and 7.4. This section has been removed from the JFrog Artifactory repository rule form in Pega Platform 8.1.

@java and locatable pages no longer supported

@java and locatable pages are no longer supported. Existing rules that use @java and locatable pages will continue to work; however, changes to these rules cannot be saved unless @java and locatable pages are replaced by supported functionality. Use a rule utility function (RUF) instead of an @java page, and use a data page instead of a locatable page. In addition, Pega Platform™ displays a guardrail warning when you open a rule that uses an @java page or a locatable page.

Use repositories as sources for File data sets

You can configure remote repositories, such as Amazon S3 or JFrog Artifactory, or a local repository, as data sources for File data sets. By referencing an external repository from a File data set, you enable a parallel load from multiple CSV or JSON files, which removes the need for a relational database for transferring data to Pega Platform™ in the cloud.

For more information, see Creating a File data set record for files on repositories and Configuring a remote repository as a source for a File data set.

Managed real-time data flow runs

Pega Platform™ now fully manages the life cycle of real-time data flow runs which helps you save time and reduce maintenance efforts. You no longer need to re-create the runs in every environment and manually pause and restart them after every modification. The application manages such runs by seamlessly implementing your changes and keeping the runs active until they encounter a specified number of errors or until you exclude the runs from the application.

For more information, see Tutorial: Using managed data flow runs and Creating a real-time run for data flows

Troubleshooting offline-enabled applications in a browser

You can now troubleshoot offline-enabled applications by using the Tracer tool and developer tools that are available in a web browser. You can troubleshoot scripts that are running when the application is running, without having to use additional debugging tools.

For more information, see Application debugging using the Tracer tool, Troubleshooting offline-enabled applications with the Tracer tool in a browser, and Offline capability.

Define a taxonomy by using the Prediction Studio interface

Create a topic hierarchy and define keywords for each topic in Prediction Studio faster and more intuitively than by editing a CSV file. If you have already defined a taxonomy in a CSV file, you can import that file and modify existing topics and keywords by using the Prediction Studio interface.

For more information, see Creating-keyword-based topics for discovering keywords and Tutorial: Configuring a topic detection model for discovering keywords.

Role-based workspaces improve productivity

You can now use workspaces to access role-based tools and features. By focusing on the tasks that align with your expertise, you can develop and manage your application more quickly.

For more information about the different types of workspaces, see Workspaces.

Extract summaries from the analyzed text

You can now configure a Text Analyzer rule to extract information-rich blocks of text from the analyzed content and combine them into a comprehensive and coherent summary. By summarizing large documents, such as emails, you can facilitate making business decisions without having to read an entire document. In Text Analyzer rules, you can combine summarization with other types of text analysis, such as topic or entity detection, to extract the full context from a message.

For more information, see Configuring text extraction analysis and Tutorial: Extracting email context with Text Analyzer rules.

Improved performance of decision strategies

Strategy rule performance has been improved through the implementation of a new engine. You can perform single and batch test runs to analyze strategy performance, locate and prevent potential issues, and optimize strategy components. Test runs now support data sets and data flows with multiple key properties. The redesigned Test run panel improves the display of information and highlights the most immediately relevant details.

For more information, see Configuring a single case runs and Configuring a batch case runs.