Mulesoft MCPA-LEVEL-1-MAINTENANCE Exam Questions & Answers

Correct Answer: C

Create API Notebooks and Include them in the relevant Anypoint exchange entries ***************************************** >> API Notebooks are the one on Anypoint Platform that enable us to provide code-centric API documentation : https://docs.mulesoft.com/exchange/to-use-api-notebook

Correct Answer: A

Search Anypoint exchange for a suitable existing fallback API, and then implement invocations to this fallback API in addition to the order API *****************************************

>> It is not ideal and good approach, until unless there is a pre-approved agreement with the API clients that they will receive a HTTP 3xx temporary redirect status code and they have to implement fallback logic their side to call another API.

>> Creating separate entry of same Order API in API manager would just create an another instance of it on top of same API implementation. So, it does NO GOOD by using clone od same API as a fallback API. Fallback API should be

ideally a different API implementation that is not same as primary one.

>> There is NO option currently provided by Anypoint HTTP Connector that allows us to invoke a fallback API when we receive certain HTTP status codes in response. The only statement TRUE in the given options is to Search Anypoint

exchange for a suitable existing fallback API, and then implement invocations to this fallback API in addition to the order API.

Correct Answer: D

Increase the size of the CloudHub worker(s) *****************************************

The key details that we can take out from the given scenario are:

>> API implementation uses a database bulk insert command to submit all the purchase data to a database

>> JDBC driver processes the data into a set of several temporary disk files on the CloudHub worker

>> Sometimes a request fails and the logs show a message indicating an out-of-file-space message

Based on above details:

>> Both auto-scaling options does NOT help because we cannot set auto-scaling rules based on error messages. Auto-scaling rules are kicked-off based on CPU/Memory usages and not due to some given error or disk space issues. >>

Increasing the number of CloudHub workers also does NOT help here because the reason for the failure is not due to performance aspects w.r.t CPU or Memory. It is due to disk-space.

>> Moreover, the API is doing bulk insert to submit the received batch data. Which means, all data is handled by ONE worker only at a time. So, the disk space issue should be tackled on "per worker" basis. Having multiple workers does not

help as the batch may still fail on any worker when disk is out of space on that particular worker. Therefore, the right way to deal this issue and resolve this is to increase the vCore size of the worker so that a new worker with more disk space

will be provisioned.