Which two statements are true about asynchronous processing?

Comprehensive and Detailed Explanation From Exact Extract:

Pega’s asynchronous processing tools, including Job Schedulers and Queue Processors, are designed for scalability and reliability, as detailed in Pega Academy’sLead System Architect Missionand thePega Certified Lead System Architect Study Guide. Understanding their configuration and behavior across nodes is critical for LSA responsibilities.

Option A (Incorrect): Job Schedulers are associated with specific node types (e.g., BackgroundProcessing) and do not typically support multiple node types for a single scheduler. This ensures dedicated processing, as clarified in theJob Scheduler Configurationmodule.

Option B (Correct): Queue Processors can be associated with multiple node types (e.g., BackgroundProcessing, Stream), allowing them to leverage distributed processing for scalability. This is a key feature for handling high-volume tasks, as documented in theQueue Processorsection of Pega Community.

Option C (Incorrect): Job Schedulers do not use Kafka for throughput. While Pega’s Stream nodes may use Kafka for data flows or event streaming, Job Schedulers rely on Pega’s internal scheduling mechanism, per theAsynchronous Processingmodule.

Option D (Correct): The replication factor in Queue Processors (e.g., via Kafka-based queues in Pega) ensures reliability and fault tolerance by maintaining copies of queued tasks across nodes. This is a standard feature for queue processors, as noted in theQueue Processor Configurationmodule.