Online Access Free MCPA-Level-1-Maintenance Practice Test

Mule applications that implement a number of REST APIs are deployed to their own subnet that is inaccessible from outside the organization.
External business-partners need to access these APIs, which are only allowed to be invoked from a separate subnet dedicated to partners - called Partner-subnet. This subnet is accessible from the public internet, which allows these external partners to reach it.
Anypoint Platform and Mule runtimes are already deployed in Partner-subnet. These Mule runtimes can already access the APIs.
What is the most resource-efficient solution to comply with these requirements, while having the least impact on other applications that are currently using the APIs?

• A.Redeploy the API implementations to the same servers running the Mule runtimes
• B.Add an additional endpoint to each API for partner-enablement consumption
• C.Duplicate the APIs as Mule applications, then deploy them to the Mule runtimes
• D.Implement (or generate) an API proxy Mule application for each of the APIs, then deploy the API proxies to the Mule runtimes

Traffic is routed through an API proxy to an API implementation. The API proxy is managed by API Manager and the API implementation is deployed to a CloudHub VPC using Runtime Manager. API policies have been applied to this API. In this deployment scenario, at what point are the API policies enforced on incoming API client requests?

• A.At a MuleSoft-hosted load balancer
• B.At the API implementation
• C.At the API proxy
• D.At both the API proxy and the API implementation

A system API has a guaranteed SLA of 100 ms per request. The system API is deployed to a primary environment as well as to a disaster recovery (DR) environment, with different DNS names in each environment. An upstream process API invokes the system API and the main goal of this process API is to respond to client requests in the least possible time. In what order should the system APIs be invoked, and what changes should be made in order to speed up the response time for requests from the process API?

• A.Invoke ONLY the system API deployed to the primary environment, and add timeout and retry logic to avoid intermittent failures
• B.Invoke the system API deployed to the primary environment, and if it fails, invoke the system API deployed to the DR environment
• C.In parallel, invoke the system API deployed to the primary environment and the system API deployed to the DR environment using a scatter-gather configured with a timeout, and then merge the responses
• D.In parallel, invoke the system API deployed to the primary environment and the system API deployed to the DR environment, and ONLY use the first response

Say, there is a legacy CRM system called CRM-Z which is offering below functions:
1. Customer creation
2. Amend details of an existing customer
3. Retrieve details of a customer
4. Suspend a customer

• A.Implement different system APIs named createCustomer, amendCustomer, retrieveCustomer and suspendCustomer as they are modular and has seperation of concerns
• B.Implement different system APIs named createCustomerInCRMZ, amendCustomerInCRMZ, retrieveCustomerFromCRMZ and suspendCustomerInCRMZ as they are modular and has seperation of concerns
• C.Implement a system API named customerManagement which has all the functionalities wrapped in it as various operations/resources

A retail company with thousands of stores has an API to receive data about purchases and insert it into a single database. Each individual store sends a batch of purchase data to the API about every 30 minutes. The API implementation uses a database bulk insert command to submit all the purchase data to a database using a custom JDBC driver provided by a data analytics solution provider. The API implementation is deployed to a single CloudHub worker. The JDBC driver processes the data into a set of several temporary disk files on the CloudHub worker, and then the data is sent to an analytics engine using a proprietary protocol. This process usually takes less than a few minutes. Sometimes a request fails. In this case, the logs show a message from the JDBC driver indicating an out-of-file-space message. When the request is resubmitted, it is successful.
What is the best way to try to resolve this throughput issue?

• A.se a CloudHub autoscaling policy to add CloudHub workers
• B.Use a CloudHub autoscaling policy to increase the size of the CloudHub worker
• C.Increase the number of CloudHub workers
• D.Increase the size of the CloudHub worker(s)