QUESTION: 141

One of the backend systems involved by the API implementation enforces rate limits on the number of request a particle client can make.
Both the back-end system and API implementation are deployed to several non-production environments including the staging environment and to a particular production environment. Rate limiting of the back-end system applies to all non-production environments. The production environment however does not have any rate limiting.
What is the cost-effective approach to conduct performance test of the API implementation in the non-production staging environment?

Including logic within the API implementation that bypasses in locations of the back-end system in the staging environment and invoke a Mocking service that replicates typical back-end system responses
Then conduct performance test using this API implementation
Use MUnit to simulate standard responses from the back-end system.
Then conduct performance test to identify other bottlenecks in the system
Create a Mocking service that replicates the back-end system's production performance characteristics
Then configure the API implementation to use the mocking service and conduct the performance test
Conduct scaled-down performance tests in the staging environment against rate-limiting back- end system. Then upscale performance results to full production scale

Answer(s): C

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QUESTION: 142

A system API EmployeeSAPI is used to fetch employee's data from an underlying SQL database. The architect must design a caching strategy to query the database only when there is an update to the employees stable or else return a cached response in order to minimize the number of redundant transactions being handled by the database.
What must the architect do to achieve the caching objective?

Use an On Table Row on employees table and call invalidate cache Use an object store caching strategy and expiration interval to empty
Use a Scheduler with a fixed frequency every hour triggering an invalidate cache flow Use an object store caching strategy and expiration interval to empty
Use a Scheduler with a fixed frequency every hour triggering an invalidate cache flow Use an object store caching strategy and set expiration interval to 1-hour
Use an on table rule on employees table call invalidate cache and said new employees data to cache
Use an object store caching strategy and set expiration interval to 1-hour

Answer(s): A

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QUESTION: 143

A leading bank implementing new mule API.
The purpose of API to fetch the customer account balances from the backend application and display them on the online platform the online banking platform. The online banking platform will send an array of accounts to Mule API get the account balances.
As a part of the processing the Mule API needs to insert the data into the database for auditing purposes and this process should not have any performance related implications on the account balance retrieval flow
How should this requirement be implemented to achieve better throughput?

Implement the Async scope fetch the data from the backend application and to insert records in the Audit database
Implement a for each scope to fetch the data from the back-end application and to insert records into the Audit database
Implement a try-catch scope to fetch the data from the back-end application and use the Async scope to insert records into the Audit database
Implement parallel for each scope to fetch the data from the backend application and use Async scope to insert the records into the Audit database

Answer(s): D

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QUESTION: 144

A Mule application is built to support a local transaction for a series of operations on a single database. The mule application has a Scatter-Gather scope that participates in the local transaction.
What is the behavior of the Scatter-Gather when running within this local transaction?

Execution of all routes within Scatter-Gather occurs in parallel Any error that occurs inside Scatter-Gather will result in a roll back of all the database operations
Execution of all routes within Scatter-Gather occurs sequentially Any error that occurs inside Scatter-Gather will be handled by error handler and will not result in roll back
Execution of all routes within Scatter-Gather occurs sequentially Any error that occurs inside Scatter-Gather will result in a roll back of all the database operations
Execution of all routes within Scatter-Gather occurs in parallel Any error that occurs inside Scatter-Gather will be handled by error handler and will not result in roll back

Answer(s): A

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