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Question #:1 - [Deployment and Testing]
The ABC organization has a financial application built on Pega Platform™. ABC wants to extend this application to other regions in a short period of time, by deploying a large development team. As it is a very sensitive application, ABC wants to have a proper review process to ensure delivery of quality code by the team. What are the two approaches that can help ensure that proper quality check-in gates are in place to achieve this requirement? (Choose Two)
Dedicate a separate ruleset for each team.
Implement rule changes in separate ruleset versions.
Reject the code deployment to higher environments if the compliance score does not meet the Center of Excellence-specified threshold value.
Implement a rule check-in approval process.
Answer: C D
Explanation
Comprehensive and Detailed Explanation From Exact Extract:
Pega’s deployment and testing best practices, as outlined in Pega Academy’s and the Deployment Mission Pega , emphasize quality control through governance processes like Certified Lead System Architect Study Guide compliance scoring and check-in approvals, especially for sensitive applications with large development teams.
Option A (Incorrect): Dedicating a separate ruleset for each team organizes development but does not inherently enforce quality check-in gates. It supports modularity but lacks direct quality assurance, per the module. Ruleset Management
Option B (Incorrect): Using separate ruleset versions supports versioning but does not ensure quality through review or compliance checks. It is aconfiguration practice, not a quality gate, as noted in the guidelines. Application Development
:
Option C (Correct): Rejecting deployments to higher environments (e.g., QA, production) if the compliance score falls below a Center of Excellence threshold ensures that only high-quality code progresses. Pega’s Guardrail Compliance Score evaluates adherence to best practices, making this a robust quality gate, as documented in the module. Deployment Pipeline
Option D (Correct): Implementing a rule check-in approval process requires developers to submit rules for review before check-in, ensuring code quality through peer or senior developer oversight. This is a standard governance practice in Pega, per the section in Pega Community. Rule Check-in Approval
Pega Academy: (covers compliance scoring and governance). Deployment Mission
Pega Community: and (details on quality gates). Rule Check-in Approval Guardrail Compliance Score
Pega Certified Lead System Architect Study Guide (v23): Section on (emphasizes Deployment and Testing quality assurance).
Question #:2 - [Pega Platform Architecture]
You are a Pega developer working on a large-scale application. You need to manage different settings that control the behavior of your application. These settings need to be easily configurable by production users, should be able to vary between different environments, and should be packaged with the application when it is migrated. Which Pega feature is the most appropriate to use in this scenario?
Configuration Sets
Dynamic System Settings
Rule System Settings
Application Settings
Answer: D
Explanation
Comprehensive and Detailed Explanation From Exact Extract:
Pega’s configuration management features, as outlined in Pega Academy’s and Lead System Architect Mission the , provide various options for managing application Pega Certified Lead System Architect Study Guide settings. Application Settings are specifically designed for environment-specific, user-configurable settings that are packaged with the application during migration.
Option A (Incorrect): Configuration Sets are used for managing test configurations in Pega’s testing framework, not for runtime application behavior settings, per the module. Testing Configuration
A.
B. C.
D.
Option B (Incorrect): Dynamic System Settings (DSS) are system-wide settings managed by administrators, not easily configurable by production users. They are not packaged with the application, as noted in the guidelines. System Configuration
Option C (Incorrect): Rule System Settings is not a standard Pega feature. The term may confuse with DSS or other rule types, but it does not apply here, per the module. Configuration Management
Option D (Correct): Application Settings are rule-based, user-configurable settings that can vary by environment (e.g., via ruleset versioning) and are packaged with the application during migration. They are ideal for production user access, as documented in the section of Pega Application Settings Community.
: Pega Academy: (covers configuration options). Lead System Architect Mission
Pega Community: (details on user-configurable settings). Application Settings
Pega Certified Lead System Architect Study Guide (v23): Section on (emphasizes Pega Platform Architecture Application Settings for configuration).
Question #:3 - [Security Design]
ABC is an insurance company that provides quotes to its customers. Customers submit insurance quote requests through the ABC company website. The insurance workflow exposes a web embed to the ABC company website; the web embed uses custom bearer authentication. What are the primary uses of a custom bearer token? (Choose Two)
To authorize the level of access that a user has to a resource.
To encrypt data sent over the network.
To authenticate a user for multiple requests over a period of time.
To authenticate a user for a single request.
Answer: A C
Explanation
Comprehensive and Detailed Explanation From Exact Extract:
Pega’s authentication mechanisms, as outlined in Pega Academy’s and the Security Mission Pega Certified , include bearer tokens for securing API and web embed interactions. Lead System Architect Study Guide
Bearer tokens are used to authenticate and authorize users for multiple requests within a session.
Option A (Correct): A custom bearer token authorizes the level of access a user has to resources (e.g., specific API endpoints or reports) by including accessscope in the token payload. This is a primary use, as documented in the section of Pega Community. Bearer Token Authentication
Option B (Incorrect): Bearer tokens do not encrypt data; encryption is handled by protocols like HTTPS. Tokens carry authentication data, per the module. Web Security
Option C (Correct): Bearer tokens authenticate a user for multiple requests over a period (e.g., session duration), reducing the need for repeated logins. This is a key feature, as noted in theAuthentication guidelines.Mechanisms
Option D (Incorrect): Bearer tokens are designed for multiple requests, not single requests. Singlerequest authentication is typically handled by other mechanisms, per theToken-Based Authentication module.
: Pega Academy: (covers bearer token authentication). Security Mission
Pega Community: (details on token uses). Bearer Token Authentication
Pega Certified Lead System Architect Study Guide (v23): Section on (emphasizes token-based Security Design security).
Question #:4 - [Data Modeling]
A multinational corporation operates several warehouses around the world. Due to varying regional regulations, market demands, and operational hours, the specifics of each warehouse, including its manager, location, and working hours, differ significantly. To streamline logistics and inventory management, employees must identify and interact with their nearest warehouse as part of their operational duties. Oversight of warehouse listings is maintained by a centralized logistics management team. What is the most suitable strategy for managing the warehouse details?
Adopt a data-instance-last design pattern for handling requests related to warehouse management, with tasks assigned to the logistics management team.
Integrate a work queue widget into the logistics management team’s dashboard that assigns them the responsibility of updating and managing warehouse information.
Employ a data-instance-first design pattern and provide a user interface for the logistics team to oversee warehouse details, with responsibilities allocated to the logistics management team.
Construct a dedicated portal for warehouse management, accessible only to the logistics management team, and implement a data-instance-only design pattern.
Answer: C
Explanation
Comprehensive and Detailed Explanation From Exact Extract:
Pega’s data modeling principles, as outlined in Pega Academy’s and the Data Modeling Mission Pega Certified , emphasize structuring data to support operational efficiency and Lead System Architect Study Guide centralized management. The data-instance-first design pattern is ideal when data instances (e.g., warehouse records) are the primary context for interactions, ensuring accessibility and manageability.
Option A (Incorrect): The data-instance-last pattern prioritizes case or process instances over data instances, which is unsuitable here since warehouse details are the primary focus, not derived from cases. This contradicts Pega’s data modeling best practices, per the module. Data Design Patterns
Option B (Incorrect): A work queue widget for updating warehouse information addresses task assignment but does not define how warehouse data is structured or managed. It is a UI solution, not a data modeling strategy, as noted in the guidelines. User Interface Design
Option C (Correct): The data-instance-first design pattern prioritizes warehouse data instances, allowing employees to query and interact with them (e.g., finding the nearest warehouse) while the logistics team manages details via a dedicated UI. This ensures centralized oversight and aligns with Pega’s best practices for data-centric applications, as documented in the section of Pega Data Modeling Community.
Option D (Incorrect): A data-instance-only pattern implies no case or process context, which is impractical for managing warehouse details that require updates and oversight. A portal is a UI solution, not a data modeling strategy, per the module. Data Design
: Pega Academy: (covers data-instance-first pattern). Data Modeling Mission
Pega Community: (details on data-centric design). Data Modeling Patterns
Pega Certified Lead System Architect Study Guide (v23): Section on (emphasizes data instance Data Modeling prioritization).
Question #:5 - [Integration]
U+ Bank has a customer service application that processes customer complaints. Now, after three years in production, the operations manager needs historical reports on resolved cases. The reports should be sent in near real-time. The data warehouse has exposed a REST API to receive the data, and the reports are then generated from the data warehouse. Which two of the following options could you use to create an ideal design solution for posting the data to the data warehouse? (Choose Two)
Read data with data flows, which source data by using a dataset and then output the data to a utility that synchronously posts the data to the data warehouse. For in-flight cases, on resolution of the case, configure the system to post the data to the data warehouse over REST.
Prepare an extract rule and extract the data of already-resolved cases, and then load it into the data warehouse for reporting. For in-flight cases, on resolution of a case, configure the system to post the data to the data warehouse over REST.
C. D. Read data with data flows, which source data by using a dataset and then output the data to a utility that posts the data to the queue processor, which then posts the data tothe data warehouse over REST. For inflight cases, on resolution of a case, reuse a queue processor that you created.
Run a one-time utility that browses all the resolved-cases data, and then asynchronously posts the data to the data warehouse. For in-flight cases, on resolution of a case, configure the system to synchronously post the data to the data warehouse over REST.
Answer: B C
Explanation
Comprehensive and Detailed Explanation From Exact Extract:
Pega’s integration capabilities, as outlined in Pega Academy’s and the Integration Mission Pega Certified Lead , provide multiple approaches for sending data to external systems like a data System Architect Study Guide warehouse via REST APIs. The solution must balance efficiency, scalability, and near real-time requirements for both historical and in-flight case data.
Option A (Incorrect): Using data flows to source data and synchronously post to the data warehouse is inefficient for near real-time reporting. Synchronous REST calls can introduce latency and performance issues, especially for large datasets. Pega recommends asynchronous processing for integration tasks to ensure scalability, as noted in the module.Integration
Option B (Correct): Using an extract rule to process already-resolved cases is ideal for historical data. Extract rules (part of Pega’s Business Intelligence Exchange, BIX) are designed to efficiently export large volumes of data to external systems like data warehouses. For in-flight cases, posting data via REST on case resolution ensures near real-time updates. This approach aligns with Pega’s best practices for data extraction and integration, per the module. BIX Configuration
Option C (Correct): Data flows sourcing data via a dataset and outputting to a queue processor for REST posting is a scalable, asynchronous solution for historical data. Queue processors handle high volumes efficiently, and reusing the same queue processor for in-flight case resolutions ensures consistency and near real-time updates. This is supported by theData Flow and Queue Processor sections in Pega Community.
Option D (Incorrect): A one-time utility for historical data is not sustainable for ongoing reporting needs, as it lacks automation. Additionally, synchronous posting for in-flight cases risks performance bottlenecks, which contradicts Pega’s asynchronous integration recommendations, per theIntegration .Mission
: Pega Academy: (covers REST integration and BIX). Integration Mission
Pega Community: and (details on data extraction and Business Intelligence Exchange (BIX) Queue Processor asynchronous posting).
Pega Certified Lead System Architect Study Guide (v23): Section on (emphasizes scalable data Integration transfer).
Question #:6 - [Pega Platform Architecture]
A software development company is planning to deploy its application for a new client. The client has unique security concerns and requires full control over their resources. Which architecture would be most suitable for this scenario, considering customization, security, and performance?
Design with the multitenancy architecture.
Define an architecture that uses single tenancy.
Blueprint the application architecture with shared tenancy.
Design with the architecture that defines isolated tenancy.
Answer: B
Explanation
Comprehensive and Detailed Explanation From Exact Extract:
Pega’s deployment architectures, as taught in Pega Academy’s and the Lead System Architect Mission Pega , include multitenancy, single tenancy, and variations like shared Certified Lead System Architect Study Guide or isolated tenancy. Single tenancy is preferred when clients require full control over resources, security, and customization.
Option A (Incorrect): Multitenancy allows multiple clients to share the same Pega instance, which reduces resource control and may compromise security due to shared infrastructure. This is unsuitable for a client with unique security concerns, per the module. Pega Cloud Architecture
Option B (Correct): Single tenancy provides a dedicated Pega instance for the client, ensuring full control over resources, security configurations, and performance optimizations. This aligns with the client’s need for customization and security, as documented in the section of Deployment Architecture Pega Community.
Option C (Incorrect): Shared tenancy, a form of multitenancy, involves multiple clients sharing resources, which limits control and increases security risks. This is not ideal for the client’s requirements, per the guidelines. Pega Platform Architecture
Option D (Incorrect): “Isolated tenancy” is not a standard Pega term. While it may imply a form of single tenancy, single tenancy is the precise and recognized architecture for dedicated resource control, as clarified in the module. Deployment Options
: Pega Academy: (covers deployment architectures). Lead System Architect Mission
Pega Community: (details on single vs. multitenancy). Pega Cloud Deployment Options
Pega Certified Lead System Architect Study Guide (v23): Section on (emphasizes Pega Platform Architecture single tenancy for security).
Question #:7 - [Application Design]
Which two of the following business use cases require the case-instance-first design pattern for implementation in Pega applications? (Choose Two)
In a sports competition management system, users must be assigned to an existing sports competition case to provide a final score.
In an event management system, event schedule preparation involves an approval process after a monthly schedule calendar is prepared.
In a healthcare management system, a patient’s medical history is captured before processing diagnostic needs and scheduling an appointment with a specialist.
In an e-commerce platform, customers can browse products and add them to their cart prior to proceeding to the checkout and billing process.
Answer: A C
Explanation
Comprehensive and Detailed Explanation From Exact Extract:
The case-instance-first design pattern in Pega, as described in Pega Academy’sApplication Design Mission and the , is used when a case instance must exist before Pega Certified Lead System Architect Study Guide related actions or data updates occur, ensuring that all actions are tied to a specific case context.
Option A (Correct): In a sports competition management system, assigning users to an existing competition case to provide a score requires the case-instance-first pattern. The competition case must exist to provide the context for scoring, aligning with Pega’s case-centric design, per theCase Design module.
Option B (Incorrect): Event schedule preparation with an approval process does not strictly require a case-instance-first pattern. The schedule could be managed as a data object or standalone process, not necessarily tied to a pre-existing case, as noted in the guidelines. Process Design
Option C (Correct): Capturing a patient’s medical history before diagnostics and scheduling requires a case-instance-first pattern. The patient case provides the context for storing history and coordinating subsequent actions, a common healthcare use case, per the module. Healthcare Application Design
Option D (Incorrect): Browsing products and adding to a cart does not require a case instance until checkout. These actions are typically data-driven (e.g., cart as a data object), not case-driven, per theEguidelines. commerce Design
:
Pega Academy: (covers case-instance-first pattern). Application Design Mission
Pega Community: (details on case-centric use cases). Case Design Patterns
Pega Certified Lead System Architect Study Guide (v23): Section on (emphasizes case- Application Design driven design).
Question #:8 - [Integration]
Every day at 1 AM, all the ATM transactions at ABC Bank from the previous day are shared with the head office of the bank. All ATM machines perform this data sharing. ABC Bank uses this information to validate transactions and balance all the ledgers. If any discrepancy is identified, a dispute resolution flow initiates to investigate the root cause and resolve the dispute. ABC Bank has 1 million ATMs for which transactions need to be analyzed for discrepancies. Which one of the following is the optimal solution for gathering the transaction information from all the ATMs?
D.
The ATM machines generate an Excel file of all the transactions and place it in a NAS directory. Pega workflow processes the files using an Advanced agent.
The ATM machines generate an Excel file of all the transactions and place it in a NAS directory. Pega workflow processes the files using a Queue Processor.
The ATM machines generate an Excel file of all the transactions and place it in a NAS directory. Pega workflow processes the files using a Job Scheduler.
The ATM machines generate an Excel file of all the transactions and place it in a NAS directory. Pega workflow processes the files using a Data Set of type File, and feeds the files into a Data Flow.
Answer: D
Explanation
Comprehensive
Pega’s integration and data processing capabilities, as taught in Pega Academy’s and Integration Mission Lead , emphasize scalable, automated solutions for handling large datasets. For processing System Architect Mission high-volume ATM transaction data, the solution must support efficient file ingestion and processing.
Option A (Incorrect): Advanced agents are legacy components and not recommended for high-volume data processing due to their limited scalability and lack of fault tolerance. Pega discourages their use for new implementations, per the module. Asynchronous Processing
Option B (Incorrect): Queue Processors are designed for processing individual items or events, not bulk file ingestion. Processing millions of transactions fromExcel files via Queue Processors would be inefficient and resource-intensive, as noted in the section. Queue Processor
Option C (Incorrect): Job Schedulers are used for recurring tasks but are not optimized for processing large files directly. They lack the native file-handling capabilities of Data Sets and Data Flows, making them suboptimal, per the module. Job Scheduler Configuration
:
Option D (Correct): Using a File Data Set to ingest Excel files from a NAS directory and feeding them into a Data Flow is the optimal solution. File Data Sets are designed for bulk file processing, and Data Flows efficiently handle large volumes of data, such as millions of ATM transactions. This approach supports scalability and automation, aligning with Pega’s best practices in theData Set and Data Flow modules.
Pega Academy: (covers File Data Sets and Data Flows). Integration Mission
Pega Community: and (details on file ingestion and processing). Data Set – File Type Data Flow Configuration
Pega Certified Lead System Architect Study Guide (v23): Section on (emphasizes scalable data Integration processing).
Question
#:9 - [Application Design]
What is the best approach for implementing limited-availability-and-concurrency design patterns?
Manage the limited resources by using the lock on the instance (data or case); once locked, Pega Platform automatically manages the concurrency.
Use a data instance approach to represent each incoming request for consuming limited available resources. Handle requests with flags to manage resource locks and availability. Processing techniques in Pega Platform manage concurrency.
Create a case instance for each request that represents consuming limited available resources. Case management features in Pega Platform automatically manage locks and concurrency.
Circumstance the rule resolution algorithm to fit the requirements of the business use case; Pega Platform automatically manages the limited availability and concurrency.
Answer: A
Explanation
Comprehensive and Detailed Explanation From Exact Extract:
Pega’s design patterns for limited availability and concurrency, as taught in Pega Academy’sApplication and the , leverage Pega’s built-in locking Design Mission Pega Certified Lead System Architect Study Guide mechanisms to manage resource contention efficiently. Locking is the standard approach for ensuring concurrency control in scenarios like booking limited seats.
Option A (Correct): Using instance locking (e.g., optimistic or pessimistic locking) on data or case instances is the best approach. Pega Platform automatically manages concurrency by ensuring only one user or process can modify a locked instance, preventing conflicts. This is a core feature, as documented in the section of Pega Community. Locking Mechanisms
:
Option B (Incorrect): Using data instances with flags to manage locks and availability is overly complex and error-prone. Pega’s native locking mechanisms are more robust and eliminate the need for custom flag-based logic, per the module. Concurrency Design
Option C (Incorrect): While case instances can use locking, creating a case for each request is unnecessary unless the request requires a full case lifecycle. For simple resource allocation, data instance locking is sufficient, as noted in the guidelines. Case Design
Option D (Incorrect): Circumstancing the rule resolution algorithm does not address concurrency or availability. Circumstancing is for rule specialization, not resource management, per theRule Resolution module.
Pega Academy: (covers concurrency and locking patterns). Application Design Mission
Pega Community: (details on instance locking). Locking Mechanisms
Pega Certified Lead System Architect Study Guide (v23): Section on (emphasizes locking Application Design for concurrency).
Question #:10 - [Work Delegation and Asynchronous Processing]
What is the main difference between a Data Flow and a Queue Processor?
Queue Processors can process a single item immediately, while Data Flows cannot.
Data Flows can process data asynchronously, while Queue Processors cannot.
Data Flows can be scheduled to run at specific times, while Queue Processors cannot.
Queue Processors can process large volumes of data, while Data Flows cannot.
Answer: A
Explanation
Comprehensive and Detailed Explanation From Exact Extract:
Pega’s asynchronous processing tools, including Data Flows and Queue Processors, serve distinct purposes, as explained in Pega Academy’s and the Lead System Architect Mission Pega Certified Lead System Architect . Data Flows are designed for processing large datasets, often in batches, while Queue Processors Study Guide handle individual items with immediate or queued processing.
Option A (Correct): Queue Processors can process a single item immediately (e.g., via Standard or Dedicated queues), making them suitable for real-time, event-driven tasks. Data Flows, however, are
designed for processing streams or batches of data and do not handle single items with the same immediacy. This distinction is highlighted in the section of Pega Data Flow vs. Queue Processor Community.
Option B (Incorrect): Both Data Flows and Queue Processors can process data asynchronously. Data Flows support asynchronous batch processing, and Queue Processors handle queued tasks asynchronously, making this statement false, per the module. Asynchronous Processing
Option C (Incorrect): Data Flows are not typically scheduled to run at specific times; they are triggered by data sources or events. Job Schedulers, not Data Flows, are used for scheduled tasks. Queue Processors also run based on queue triggers, not schedules, as noted in theData Flow module.Configuration
Option D (Incorrect): Data Flows are specifically designed to process large volumes of data, such as in analytics or ETL processes, while Queue Processors are better suited for smaller, individual tasks. This makes the statement incorrect, per the . Lead System Architect Mission
: Pega Academy: (covers Data Flows and Queue Processors). Lead System Architect Mission
Pega Community: (details on processing differences). Data Flow vs. Queue Processor
Pega Certified Lead System Architect Study Guide (v23): Section onWork Delegation and Asynchronous (emphasizes processing capabilities). Processing
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