PEGACPLSA88V1 Exam Dumps - Pegasystems Certified Lead System Architect (CLSA) Questions and Answers

Activities and functions in Pega share certain common features which are vital for their flexibility and maintainability.

Parameterization: Both activities and functions can be parameterized, allowing them to accept input values when they are invoked. This makes them reusable in different contexts by simply changing the parameters.

Versioning: Both activities and functions support versioning. This means you can maintain different versions of an activity or function, which is useful for keeping track of changes and ensuring compatibility with different versions of the application.

References: Pega Platform documentation on activities and functions.

ProductionApp 01.01CustomerApp 07.01ServiceApp 01.01EmployeeApp 01.01MyEnterpriseApp 01.02PegaRULES 07.10

To troubleshoot chronic performance issues in a cloud-based production application, you can use the following techniques:

Performance Alerts and Exceptions in PDC: Review the alerts and exceptions in Pega Predictive Diagnostic Cloud (PDC). PDC provides real-time monitoring and insights into performance issues.

Performance Alerts and Exceptions using PLA: Use the Pega Log Analyzer (PLA) to review alerts and exceptions. PLA helps in identifying and diagnosing performance bottlenecks by analyzing log files.

References:

Pega Predictive Diagnostic Cloud (PDC)

Pega Log Analyzer (PLA)

Pega's Center-out business architecture involves:

Case Management Feature (A):

Utilizing case management allows organizations to manage, automate, and improve work processes efficiently. This ensures that every step in the Microjourney®—a complete customer interaction or process—is executed correctly and consistently.

DX API Synchronization (C):

Pega's DX API helps in keeping the front-end channels and back-end logic in sync. This avoids the creation of silos, ensuring seamless and consistent interaction across different channels.

References:

Pega's Center-out Business Architecture Overview

Pega Documentation on Case Management

Pega DX API Documentation

Rule Configuration:

Set the availability of the data transform rule to "Blocked".

Testing with Previous Versions:

This allows you to save and check in the record despite validation errors and lets previous versions of the rule execute during testing.

 Node Association: To control which nodes in a cluster an agent runs on, you need to associate the agent with specific node types. This ensures that the agent runs only on the nodes that match the specified type.

 Configuration: In the agent rule configuration, specify the node type under the "Node" settings. This allows for precise control over the agent's execution environment.

References:

Pega Academy: Configuring Agents for Node Types

Pega Documentation: Agent Configuration and Node Types

 The decision table provided in the question lists rules for segmenting customers based on their credit score and average balance.

 For a customer with a credit score of 240 and an average balance of 35000:

The first rule checks if the credit score is >= 400 and < 600, and average balance >= 30000. This rule doesn't apply as the credit score is 240.

The second rule checks if the credit score is >= 200 and < 400, and average balance >= 20000. This rule applies since the credit score is 240 and average balance is 35000.

 According to this rule, the result is "Fair".

 Therefore, the label returned for a customer with a credit score of 240 and an average balance of 35000 is "Fair".

 Indexing: Adding indexes to columns involved in equality comparisons can significantly improve query performance by reducing the need for full table scans.

 Implementation: Identify the columns frequently used in WHERE clauses and create indexes for these columns in the database. This optimization reduces query execution time and enhances overall application performance.

References:

Pega Academy: Database Optimization Techniques

Pega Documentation: Indexing Database Tables

Max Attempts: The maximum number of retry attempts set is 4.

Initial Delay: The initial delay before the first retry attempt is 2 minutes.

Delay Factor: The delay factor is set to 2, which means the delay doubles with each retry.

Calculating Delays:

First attempt fails, delay before second attempt = Initial delay = 2 minutes.

Second attempt fails, delay before third attempt = Initial delay * Delay factor = 2 minutes * 2 = 4 minutes.

Third attempt fails, delay before fourth attempt = 4 minutes * Delay factor = 4 minutes * 2 = 8 minutes.

Delay Between Attempts: The question specifically asks for the delay between the second and third attempt, which is calculated as 8 minutes.

References:

Pega documentation on queue processor configuration.

Pega Platform 8.x help files related to processing retries and delay factors.

 Setting pxThread.isWebMashup:

In the pyDefault Data Transform for a case, setting pxThread.isWebMashup to True ensures that App Studio users see the same views displayed by a Mashup interface.

 Associated Privilege Visibility Conditions:

Using associated privilege visibility conditions allows App Studio users to view and configure sections only shown to external personas at design time.

 References:

Pega documentation on Mashup interface development in App Studio outlines these practices to ensure seamless integration and development.

 Therefore, the correct answers are:

B. In the pyDefault Data Transform for a case, set pxThread.isWebMashup to True by using an Application Setting. App Studio users then see the same views that are displayed by a Mashup interface when it is configured to use the Create a case option.

C. Use associated privilege visibility conditions. At design time, an App Studio user is able to view and configure sections that are only shown to external personas.