Valid MCPA-Level-1-Maintenance Exam Q&A PDF MCPA-Level-1-Maintenance Dump is Ready (Updated 81 Questions)
Exam Questions and Answers for MCPA-Level-1-Maintenance Study Guide
NEW QUESTION 28
An API implementation is updated. When must the RAML definition of the API also be updated?
- A. When the API implementation is optimized to improve its average response time
- B. When the API implementation changes the structure of the request or response messages
- C. When the API implementation changes from interacting with a legacy backend system deployed on-premises to a modern, cloud-based (SaaS) system
- D. When the API implementation is migrated from an older to a newer version of the Mule runtime
Answer: B
Explanation:
When the API implementation changes the structure of the request or response messages
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>> RAML definition usually needs to be touched only when there are changes in the request/response schemas or in any traits on API.
>> It need not be modified for any internal changes in API implementation like performance tuning, backend system migrations etc..
NEW QUESTION 29
An organization makes a strategic decision to move towards an IT operating model that emphasizes consumption of reusable IT assets using modern APIs (as defined by MuleSoft).
What best describes each modern API in relation to this new IT operating model?
- A. Each modem API must be treated like a product and designed for a particular target audience (for instance, mobile app developers)
- B. Each modern API must be REST and HTTP based
- C. Each modern API must be easy to consume, so should avoid complex authentication mechanisms such as SAML or JWT D
- D. Each modern API has its own software development lifecycle, which reduces the need for documentation and automation
Answer: A
Explanation:
Explanation
Correct Answers:
1. Each modern API must be treated like a product and designed for a particular target audience (for instance mobile app developers)
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NEW QUESTION 30
Which of the following best fits the definition of API-led connectivity?
- A. API-led connectivity is not just an architecture or technology but also a way to organize people and processes for efficient IT delivery in the organization
- B. API-led connectivity is a 3-layered architecture covering Experience, Process and System layers
- C. API-led connectivity is a technology which enabled us to implement Experience, Process and System layer based APIs
Answer: A
Explanation:
API-led connectivity is not just an architecture or technology but also a way to organize people and processes for efficient IT delivery in the organization.
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NEW QUESTION 31
An API experiences a high rate of client requests (TPS) vwth small message paytoads. How can usage limits be imposed on the API based on the type of client application?
- A. Use a cross-origin resource sharing (CORS) policy to limit resource sharing between client applications, configured by the client application type
- B. Use an SLA-based rate limiting policy and assign a client application to a matching SLA tier based on its type
- C. Use a rate limiting policy and a client ID enforcement policy, each configured by the client application type
- D. Use a spike control policy that limits the number of requests for each client application type
Answer: B
Explanation:
Use an SLA-based rate limiting policy and assign a client application to a matching SLA tier
based on its type.
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>> SLA tiers will come into play whenever any limits to be imposed on APIs based on client type
NEW QUESTION 32
A company wants to move its Mule API implementations into production as quickly as possible. To protect access to all Mule application data and metadata, the company requires that all Mule applications be deployed to the company's customer-hosted infrastructure within the corporate firewall. What combination of runtime plane and control plane options meets these project lifecycle goals?
- A. Manually provisioned customer-hosted runtime plane and MuleSoft-hosted control plane
- B. MuleSoft-hosted runtime plane and customer-hosted control plane
- C. Manually provisioned customer-hosted runtime plane and customer-hosted control plane
- D. iPaaS provisioned customer-hosted runtime plane and MuleSoft-hosted control plane
Answer: C
Explanation:
Manually provisioned customer-hosted runtime plane and customer-hosted control plane
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There are two key factors that are to be taken into consideration from the scenario given in the question.
>> Company requires both data and metadata to be resided within the corporate firewall
>> Company would like to go with customer-hosted infrastructure.
Any deployment model that is to deal with the cloud directly or indirectly (Mulesoft-hosted or Customer's own cloud like Azure, AWS) will have to share atleast the metadata.
Application data can be controlled inside firewall by having Mule Runtimes on customer hosted runtime plane. But if we go with Mulsoft-hosted/ Cloud-based control plane, the control plane required atleast some minimum level of metadata to be sent outside the corporate firewall.
As the customer requirement is pretty clear about the data and metadata both to be within the corporate firewall, even though customer wants to move to production as quickly as possible, unfortunately due to the nature of their security requirements, they have no other option but to go with manually provisioned customer-hosted runtime plane and customer-hosted control plane.
NEW QUESTION 33
A retail company is using an Order API to accept new orders. The Order API uses a JMS queue to submit orders to a backend order management service. The normal load for orders is being handled using two (2) CloudHub workers, each configured with 0.2 vCore. The CPU load of each CloudHub worker normally runs well below 70%. However, several times during the year the Order API gets four times (4x) the average number of orders. This causes the CloudHub worker CPU load to exceed 90% and the order submission time to exceed 30 seconds. The cause, however, is NOT the backend order management service, which still responds fast enough to meet the response SLA for the Order API. What is the MOST resource-efficient way to configure the Mule application's CloudHub deployment to help the company cope with this performance challenge?
- A. Permanently increase the size of each of the two (2) CloudHub workers by at least four times (4x) to one (1) vCore
- B. Permanently increase the number of CloudHub workers by four times (4x) to eight (8) CloudHub workers
- C. Use a vertical CloudHub autoscaling policy that triggers on CPU utilization greater than 70%
- D. Use a horizontal CloudHub autoscaling policy that triggers on CPU utilization greater than 70%
Answer: D
Explanation:
Use a horizontal CloudHub autoscaling policy that triggers on CPU utilization greater than
70%
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The scenario in the question is very clearly stating that the usual traffic in the year is pretty well handled by the existing worker configuration with CPU running well below 70%. The problem occurs only "sometimes" occasionally when there is spike in the number of orders coming in.
So, based on above, We neither need to permanently increase the size of each worker nor need to permanently increase the number of workers. This is unnecessary as other than those "occasional" times the resources are idle and wasted.
We have two options left now. Either to use horizontal Cloudhub autoscaling policy to automatically increase the number of workers or to use vertical Cloudhub autoscaling policy to automatically increase the vCore size of each worker.
Here, we need to take two things into consideration:
1. CPU
2. Order Submission Rate to JMS Queue
>> From CPU perspective, both the options (horizontal and vertical scaling) solves the issue. Both helps to bring down the usage below 90%.
>> However, If we go with Vertical Scaling, then from Order Submission Rate perspective, as the application is still being load balanced with two workers only, there may not be much improvement in the incoming request processing rate and order submission rate to JMS queue. The throughput would be same as before.
Only CPU utilization comes down.
>> But, if we go with Horizontal Scaling, it will spawn new workers and adds extra hand to increase the throughput as more workers are being load balanced now. This way we can address both CPU and Order Submission rate.
Hence, Horizontal CloudHub Autoscaling policy is the right and best answer.
NEW QUESTION 34
A code-centric API documentation environment should allow API consumers to investigate and execute API client source code that demonstrates invoking one or more APIs as part of representative scenarios.
What is the most effective way to provide this type of code-centric API documentation environment using Anypoint Platform?
- A. Create API Notebooks and include them in the relevant Anypoint Exchange entries
- B. Make relevant APIs discoverable via an Anypoint Exchange entry
- C. Enable mocking services for each of the relevant APIs and expose them via their Anypoint Exchange entry
- D. Ensure the APIs are well documented through their Anypoint Exchange entries and API Consoles and share these pages with all API consumers
Answer: A
Explanation:
Create API Notebooks and Include them in the relevant Anypoint exchange entries
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>> API Notebooks are the one on Anypoint Platform that enable us to provide code-centric API documentation
NEW QUESTION 35
An API implementation is deployed to CloudHub.
What conditions can be alerted on using the default Anypoint Platform functionality, where the alert conditions depend on the end-to-end request processing of the API implementation?
- A. When a particular API client invokes the API too often within a given time period
- B. When the response time of API invocations exceeds a threshold
- C. When the API receives a very high number of API invocations
- D. When the API is invoked by an unrecognized API client
Answer: B
Explanation:
When the response time of API invocations exceeds a threshold
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>> Alerts can be setup for all the given options using the default Anypoint Platform functionality
>> However, the question insists on an alert whose conditions depend on the end-to-end request processing of the API implementation.
>> Alert w.r.t "Response Times" is the only one which requires end-to-end request processing of API implementation in order to determine if the threshold is exceeded or not.
NEW QUESTION 36
When could the API data model of a System API reasonably mimic the data model exposed by the corresponding backend system, with minimal improvements over the backend system's data model?
- A. When there is an existing Enterprise Data Model widely used across the organization
- B. When the corresponding backend system is expected to be replaced in the near future
- C. When the System API can be assigned to a bounded context with a corresponding data model
- D. When a pragmatic approach with only limited isolation from the backend system is deemed appropriate
Answer: D
Explanation:
When a pragmatic approach with only limited isolation from the backend system is deemed appropriate.
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General guidance w.r.t choosing Data Models:
>> If an Enterprise Data Model is in use then the API data model of System APIs should make use of data types from that Enterprise Data Model and the corresponding API implementation should translate between these data types from the Enterprise Data Model and the native data model of the backend system.
>> If no Enterprise Data Model is in use then each System API should be assigned to a Bounded Context, the API data model of System APIs should make use of data types from the corresponding Bounded Context Data Model and the corresponding API implementation should translate between these data types from the Bounded Context Data Model and the native data model of the backend system. In this scenario, the data types in the Bounded Context Data Model are defined purely in terms of their business characteristics and are typically not related to the native data model of the backend system. In other words, the translation effort may be significant.
>> If no Enterprise Data Model is in use, and the definition of a clean Bounded Context Data Model is considered too much effort, then the API data model of System APIs should make use of data types that approximately mirror those from the backend system, same semantics and naming as backend system, lightly sanitized, expose all fields needed for the given System API's functionality, but not significantly more and making good use of REST conventions.
The latter approach, i.e., exposing in System APIs an API data model that basically mirrors that of the backend system, does not provide satisfactory isolation from backend systems through the System API tier on its own.
In particular, it will typically not be possible to "swap out" a backend system without significantly changing all System APIs in front of that backend system and therefore the API implementations of all Process APIs that depend on those System APIs! This is so because it is not desirable to prolong the life of a previous backend system's data model in the form of the API data model of System APIs that now front a new backend system.
The API data models of System APIs following this approach must therefore change when the backend system is replaced.
On the other hand:
>> It is a very pragmatic approach that adds comparatively little overhead over accessing the backend system directly
>> Isolates API clients from intricacies of the backend system outside the data model (protocol, authentication, connection pooling, network address, ...)
>> Allows the usual API policies to be applied to System APIs
>> Makes the API data model for interacting with the backend system explicit and visible, by exposing it in the RAML definitions of the System APIs
>> Further isolation from the backend system data model does occur in the API implementations of the Process API tier
NEW QUESTION 37
A Mule application exposes an HTTPS endpoint and is deployed to three CloudHub workers that do not use static IP addresses. The Mule application expects a high volume of client requests in short time periods. What is the most cost-effective infrastructure component that should be used to serve the high volume of client requests?
- A. An API proxy
- B. The CloudHub shared load balancer
- C. A customer-hosted load balancer
- D. Runtime Manager autoscaling
Answer: B
Explanation:
The CloudHub shared load balancer
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The scenario in this question can be split as below:
>> There are 3 CloudHub workers (So, there are already good number of workers to handle high volume of requests)
>> The workers are not using static IP addresses (So, one CANNOT use customer load-balancing solutions without static IPs)
>> Looking for most cost-effective component to load balance the client requests among the workers.
Based on the above details given in the scenario:
>> Runtime autoscaling is NOT at all cost-effective as it incurs extra cost. Most over, there are already 3 workers running which is a good number.
>> We cannot go for a customer-hosted load balancer as it is also NOT most cost-effective (needs custom load balancer to maintain and licensing) and same time the Mule App is not having Static IP Addresses which limits from going with custom load balancing.
>> An API Proxy is irrelevant there as it has no role to play w.r.t handling high volumes or load balancing.
So, the only right option to go with and fits the purpose of scenario being most cost-effective is - using a CloudHub Shared Load Balancer.
NEW QUESTION 38
An API has been updated in Anypoint exchange by its API producer from version 3.1.1 to 3.2.0 following accepted semantic versioning practices and the changes have been communicated via the APIs public portal.
The API endpoint does NOT change in the new version. How should the developer of an API client respond to this change?
- A. The API producer should be contacted to understand the change to existing functionality
- B. The API producer should be requested to run the old version in parallel with the new one
- C. The API client code only needs to be changed if it needs to take advantage of the new features
- D. The API clients need to update the code on their side and need to do full regression
Answer: C
NEW QUESTION 39
What is true about automating interactions with Anypoint Platform using tools such as Anypoint Platform REST APIs, Anypoint CU, or the Mule Maven plugin?
- A. API policies can be applied to the Anypoint Platform APIs so that ONLY certain LOBs have access to specific functions
- B. Anypoint Platform APIs can ONLY automate interactions with CloudHub, while the Mule Maven plugin is required for deployment to customer-hosted Mule runtimes
- C. By default, the Anypoint CLI and Mule Maven plugin are NOT included in the Mule runtime, so are NOT available to be used by deployed Mule applications
- D. Access to Anypoint Platform APIs and Anypoint CU can be controlled separately through the roles and permissions in Anypoint Platform, so that specific users can get access to Anypoint CLI white others get access to the platform APIs
Answer: C
Explanation:
By default, the Anypoint CLI and Mule Maven plugin are NOT included in the Mule runtime, so are NOT available to be used by deployed Mule applications
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>> We CANNOT apply API policies to the Anypoint Platform APIs like we can do on our custom written API instances. So, option suggesting this is FALSE.
>> Anypoint Platform APIs can be used for automating interactions with both CloudHub and customer-hosted Mule runtimes. Not JUST the CloudHub. So, option opposing this is FALSE.
>> Mule Maven plugin is NOT mandatory for deployment to customer-hosted Mule runtimes. It just helps your CI/CD to have smoother automation. But not a compulsory requirement to deploy. So, option opposing this is FALSE.
>> We DO NOT have any such special roles and permissions on the platform to separately control access for some users to have Anypoint CLI and others to have Anypoint Platform APIs. With proper general roles/permissions (API Owner, Cloudhub Admin etc..), one can use any of the options (Anypoint CLI or Platform APIs). So, option suggesting this is FALSE.
Only TRUE statement given in the choices is that - Anypoint CLI and Mule Maven plugin are NOT included in the Mule runtime, so are NOT available to be used by deployed Mule applications.
Maven is part of Studio or you can use other Maven installation for development.
CLI is convenience only. It is one of many ways how to install app to the runtime.
These are definitely NOT part of anything except your process of deployment or automation.
NEW QUESTION 40
What are 4 important Platform Capabilities offered by Anypoint Platform?
- A. API Design and Development, API Deprecation, API Versioning, API Consumer Engagement
- B. API Versioning, API Runtime Execution and Hosting, API Invocation, API Consumer Engagement
- C. API Design and Development, API Runtime Execution and Hosting, API Versioning, API Deprecation
- D. API Design and Development, API Runtime Execution and Hosting, API Operations and Management, API Consumer Engagement
Answer: D
Explanation:
API Design and Development, API Runtime Execution and Hosting, API Operations and Management, API Consumer Engagement
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>> API Design and Development - Anypoint Studio, Anypoint Design Center, Anypoint Connectors
>> API Runtime Execution and Hosting - Mule Runtimes, CloudHub, Runtime Services
>> API Operations and Management - Anypoint API Manager, Anypoint Exchange
>> API Consumer Management - API Contracts, Public Portals, Anypoint Exchange, API Notebooks
NEW QUESTION 41
What Mule application can have API policies applied by
Anypoint Platform to the endpoint exposed by that Mule application?
A) A Mule application that accepts requests over HTTP/1.x
B) A Mule application that accepts JSON requests over TCP but is NOT required to provide a response
C) A Mute application that accepts JSON requests over WebSocket
D) A Mule application that accepts gRPC requests over HTTP/2
- A. Option B
- B. Option D
- C. Option A
- D. Option C
Answer: C
Explanation:
Option A
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>> Anypoint API Manager and API policies are applicable to all types of HTTP/1.x APIs.
>> They are not applicable to WebSocket APIs, HTTP/2 APIs and gRPC APIs
NEW QUESTION 42
How are an API implementation, API client, and API consumer combined to invoke and process an API?
- A. The ApI client creates an API consumer, which sends API invocations to an API such that they are processed by an API implementation
- B. The ApI consumer creates an API client, which sends API invocations to an API such that they are processed by an API implementation
- C. The API client creates an API consumer, which receives API invocations from an API such that they are processed for an API implementation
- D. The API consumer creates an API implementation, which receives API invocations from an API such that they are processed for an API client
Answer: B
Explanation:
The API consumer creates an API client, which sends API invocations to an API such that they are processed by an API implementation
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Terminology:
>> API Client - It is a piece of code or program the is written to invoke an API
>> API Consumer - An owner/entity who owns the API Client. API Consumers write API clients.
>> API - The provider of the API functionality. Typically an API Instance on API Manager where they are managed and operated.
>> API Implementation - The actual piece of code written by API provider where the functionality of the API is implemented. Typically, these are Mule Applications running on Runtime Manager.
NEW QUESTION 43
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