Salesforce MuleSoft-Integration-Architect-I Exam With Confidence Using Practice Dumps

MuleSoft customers often favor a MuleSoft-hosted Anypoint Platform runtime plane over a customer-hosted runtime for the following reasons:

Reduced time-to-market for the first application (C): Using a MuleSoft-hosted runtime plane accelerates the deployment process because MuleSoft manages the infrastructure, allowing customers to focus on developing and deploying their applications quickly. This leads to faster time-to-market for the initial application and subsequent updates.

Reduced IT operations effort (E): By leveraging a MuleSoft-hosted environment, customers offload the operational responsibilities, such as infrastructure maintenance, updates, and scalability management, to MuleSoft. This reduces the IT operations workload and allows internal teams to focus on more strategic initiatives.

In contrast, other options like reduced application latency and increased application throughput are not directly influenced by whether the runtime plane is MuleSoft-hosted or customer-hosted.

References

MuleSoft Anypoint Platform Documentation

MuleSoft Hosted vs. Customer Hosted Deployment Guides

When a Mule application uses batch job scope to process large datasets and is deployed on multiple CloudHub workers without persistence queues enabled, the following scenario occurs if a worker crashes:

Batch Job Scope: Batch jobs are designed to handle large datasets by splitting the work into records and processing them in parallel.

Non-Persistent Queues: When persistence is not enabled, the state of the batch processing is not stored persistently. This means that if a worker crashes, the state of the in-progress batch job is lost.

Worker Crash Consequence:

When a worker crashes, the records that were being processed by that worker are not tracked persistently.

As a result, when another worker (or the same worker after a restart) picks up the job, it does not have the previous state information.

This leads to the batch job starting from the beginning and reprocessing all records from scratch, causing duplicate processing of records that were already processed before the crash.

This behavior can cause issues such as duplicate data in Salesforce CRM and inefficiencies in processing.

References

MuleSoft Batch Processing

MuleSoft CloudHub Workers

To efficiently handle the invocation of vendor applications and retry requests that generate timeout errors, the most performant way is:

Scatter-Gather Scope: Use a Scatter-Gather scope to invoke each vendor application in parallel. This approach allows the API to send requests to both vendors simultaneously, reducing overall processing time.

Until-Successful Scope: Inside each route of the Scatter-Gather scope, use an Until-Successful scope to handle retries. The Until-Successful scope will retry the request in case of timeout errors until the request succeeds or the maximum retry limit is reached.

This combination ensures that the API can handle intermittent network issues efficiently while minimizing redundant transactions and maximizing performance.

References

MuleSoft Documentation on Scatter-Gather Scope

MuleSoft Documentation on Until-Successful Scope and Error Handling