MuleSoft MCPA-Level-1-Maintenance Daily Practice Exam New 2023 Updated 81 Questions
Use Valid MCPA-Level-1-Maintenance Exam - Actual Exam Question & Answer
The MCPA-Level-1-Maintenance exam focuses on assessing an individual's ability to perform maintenance tasks on the Anypoint Platform. This includes tasks such as upgrading the platform, managing security, troubleshooting issues, and ensuring high availability. MCPA-Level-1-Maintenance exam is designed to ensure that certified architects maintain their expertise and stay up to date with the latest updates and best practices.
Passing the MCPA-Level-1-Maintenance exam validates that the candidate has up-to-date knowledge and skills in designing and developing integration solutions using the Anypoint Platform. It also demonstrates their commitment to maintaining their expertise and staying current with the latest advancements in MuleSoft's technology. Additionally, maintaining their MCPA-Level-1 certification helps professionals stand out in the job market and opens up opportunities for career growth and advancement.
The MCPA-Level-1-Maintenance exam covers several topics related to MuleSoft platform maintenance, including troubleshooting MuleSoft applications, managing and monitoring MuleSoft applications, maintaining MuleSoft components, and upgrading MuleSoft applications. MCPA-Level-1-Maintenance exam also covers topics related to security and performance tuning.
NEW QUESTION # 17
The application network is recomposable: it is built for change because it "bends but does not break"
- A. FALSE
- B. TRUE
Answer: B
Explanation:
Explanation
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>> Application Network is a disposable architecture.
>> Which means, it can be altered without disturbing entire architecture and its components.
>> It bends as per requirements or design changes but does not break
NEW QUESTION # 18
Refer to the exhibit.
What is the best way to decompose one end-to-end business process into a collaboration of Experience, Process, and System APIs?
A) Handle customizations for the end-user application at the Process API level rather than the Experience API level
B) Allow System APIs to return data that is NOT currently required by the identified Process or Experience APIs
C) Always use a tiered approach by creating exactly one API for each of the 3 layers (Experience, Process and System APIs)
D) Use a Process API to orchestrate calls to multiple System APIs, but NOT to other Process APIs
- A. Option A
- B. Option D
- C. Option B
- D. Option C
Answer: C
Explanation:
Allow System APIs to return data that is NOT currently required by the identified Process or Experience APIs.
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>> All customizations for the end-user application should be handled in "Experience API" only. Not in Process API
>> We should use tiered approach but NOT always by creating exactly one API for each of the 3 layers.
Experience APIs might be one but Process APIs and System APIs are often more than one. System APIs for sure will be more than one all the time as they are the smallest modular APIs built in front of end systems.
>> Process APIs can call System APIs as well as other Process APIs. There is no such anti-design pattern in API-Led connectivity saying Process APIs should not call other Process APIs.
So, the right answer in the given set of options that makes sense as per API-Led connectivity principles is to allow System APIs to return data that is NOT currently required by the identified Process or Experience APIs.
This way, some future Process APIs can make use of that data from System APIs and we need NOT touch the System layer APIs again and again.
NEW QUESTION # 19
An organization has created an API-led architecture that uses various API layers to integrate mobile clients with a backend system. The backend system consists of a number of specialized components and can be accessed via a REST API. The process and experience APIs share the same bounded-context model that is different from the backend data model. What additional canonical models, bounded-context models, or anti-corruption layers are best added to this architecture to help process data consumed from the backend system?
- A. Create a canonical model that combines the backend and API-led models to simplify and unify data models, and minimize data transformations.
- B. Create a bounded-context model for every layer and overlap them when the boundary contexts overlap, letting API developers know about the differences between upstream and downstream data models
- C. Create a bounded-context model for the system layer to closely match the backend data model, and add an anti-corruption layer to let the different bounded contexts cooperate across the system and process layers
- D. Create an anti-corruption layer for every API to perform transformation for every data model to match each other, and let data simply travel between APIs to avoid the complexity and overhead of building canonical models
Answer: C
Explanation:
Create a bounded-context model for the system layer to closely match the backend data model, and add an anti-corruption layer to let the different bounded contexts cooperate across the system and process layers
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>> Canonical models are not an option here as the organization has already put in efforts and created bounded-context models for Experience and Process APIs.
>> Anti-corruption layers for ALL APIs is unnecessary and invalid because it is mentioned that experience and process APIs share same bounded-context model. It is just the System layer APIs that need to choose their approach now.
>> So, having an anti-corruption layer just between the process and system layers will work well. Also to speed up the approach, system APIs can mimic the backend system data model.
NEW QUESTION # 20
A company has started to create an application network and is now planning to implement a Center for Enablement (C4E) organizational model. What key factor would lead the company to decide upon a federated rather than a centralized C4E?
- A. When there are a large number of existing common assets shared by development teams
- B. When development is already organized into several independent initiatives or groups
- C. When various teams responsible for creating APIs are new to integration and hence need extensive training
- D. When the majority of the applications in the application network are cloud based
Answer: B
Explanation:
When development is already organized into several independent initiatives or groups
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>> It would require lot of process effort in an organization to have a single C4E team coordinating with multiple already organized development teams which are into several independent initiatives. A single C4E works well with different teams having at least a common initiative. So, in this scenario, federated C4E works well instead of centralized C4E.
NEW QUESTION # 21
Question 10: Skipped
An API implementation returns three X-RateLimit-* HTTP response headers to a requesting API client. What type of information do these response headers indicate to the API client?
- A. A correlation ID that should be sent in the next request
- B. The error codes that result from throttling
- C. The remaining capacity allowed by the API implementation
- D. The HTTP response size
Answer: C
Explanation:
The remaining capacity allowed by the API implementation.
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>> Reference:
https://docs.mulesoft.com/api-manager/2.x/rate-limiting-and-throttling-sla-based-policies#response-headers
NEW QUESTION # 22
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. 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
- 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. Invoke the system API deployed to the primary environment, and if it fails, invoke the system API deployed to the DR environment
Answer: B
Explanation:
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.
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>> The API requirement in the given scenario is to respond in least possible time.
>> The option that is suggesting to first try the API in primary environment and then fallback to API in DR environment would result in successful response but NOT in least possible time. So, this is NOT a right choice of implementation for given requirement.
>> Another option that is suggesting to ONLY invoke API in primary environment and to add timeout and retries may also result in successful response upon retries but NOT in least possible time. So, this is also NOT a right choice of implementation for given requirement.
>> One more option that is suggesting to invoke API in primary environment and API in DR environment in parallel using Scatter-Gather would result in wrong API response as it would return merged results and moreover, Scatter-Gather does things in parallel which is true but still completes its scope only on finishing all routes inside it. So again, NOT a right choice of implementation for given requirement The Correct choice is to invoke the API in primary environment and the API in DR environment parallelly, and using ONLY the first response received from one of them.
NEW QUESTION # 23
An organization has implemented a Customer Address API to retrieve customer address information. This API has been deployed to multiple environments and has been configured to enforce client IDs everywhere.
A developer is writing a client application to allow a user to update their address. The developer has found the Customer Address API in Anypoint Exchange and wants to use it in their client application.
What step of gaining access to the API can be performed automatically by Anypoint Platform?
- A. Request access to the appropriate API Instances deployed to multiple environments using the client application's credentials
- B. Modify the client application to call the API using the client application's credentials
- C. Approve the client application request for the chosen SLA tier
- D. Create a new application in Anypoint Exchange for requesting access to the API
Answer: C
Explanation:
Approve the client application request for the chosen SLA tier
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>> Only approving the client application request for the chosen SLA tier can be automated
>> Rest of the provided options are not valid
NEW QUESTION # 24
An API implementation is being designed that must invoke an Order API, which is known to repeatedly experience downtime.
For this reason, a fallback API is to be called when the Order API is unavailable.
What approach to designing the invocation of the fallback API provides the best resilience?
- A. Create a separate entry for the Order API in API Manager, and then invoke this API as a fallback API if the primary Order API is unavailable
- B. Search Anypoint Exchange for a suitable existing fallback API, and then implement invocations to this fallback API in addition to the Order API
- C. Redirect client requests through an HTTP 307 Temporary Redirect status code to the fallback API whenever the Order API is unavailable
- D. Set an option in the HTTP Requester component that invokes the Order API to instead invoke a fallback API whenever an HTTP 4xx or 5xx response status code is returned from the Order API
Answer: B
Explanation:
Search Anypoint exchange for a suitable existing fallback API, and then implement invocations to this fallback API in addition to the order API
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>> 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.
NEW QUESTION # 25
Refer to the exhibit. An organization is running a Mule standalone runtime and has configured Active Directory as the Anypoint Platform external Identity Provider. The organization does not have budget for other system components.
What policy should be applied to all instances of APIs in the organization to most effecuvelyKestrict access to a specific group of internal users?
- A. Apply an IP whitelist policy; only the specific users' workstations will be in the whitelist
- B. Apply a basic authentication - LDAP policy; the internal Active Directory will be configured as the LDAP source for authenticating users
- C. Apply a client ID enforcement policy; the specific group of users will configure their client applications to use their specific client credentials
- D. Apply an OAuth 2.0 access token enforcement policy; the internal Active Directory will be configured as the OAuth server
Answer: B
Explanation:
Apply a basic authentication - LDAP policy; the internal Active Directory will be configured as the LDAP source for authenticating users.
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>> IP Whitelisting does NOT fit for this purpose. Moreover, the users workstations may not necessarily have static IPs in the network.
>> OAuth 2.0 enforcement requires a client provider which isn't in the organizations system components.
>> It is not an effective approach to let every user create separate client credentials and configure those for their usage.
The effective way it to apply a basic authentication - LDAP policy and the internal Active Directory will be configured as the LDAP source for authenticating users.
NEW QUESTION # 26
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 the API receives a very high number of API invocations
- B. When a particular API client invokes the API too often within a given time period
- C. When the response time of API invocations exceeds a threshold
- D. When the API is invoked by an unrecognized API client
Answer: C
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 # 27
An organization has several APIs that accept JSON data over HTTP POST. The APIs are all publicly available and are associated with several mobile applications and web applications.
The organization does NOT want to use any authentication or compliance policies for these APIs, but at the same time, is worried that some bad actor could send payloads that could somehow compromise the applications or servers running the API implementations.
What out-of-the-box Anypoint Platform policy can address exposure to this threat?
- A. Apply a Header injection and removal policy that detects the malicious data before it is used
- B. Shut out bad actors by using HTTPS mutual authentication for all API invocations
- C. Apply an IP blacklist policy to all APIs; the blacklist will Include all bad actors
- D. Apply a JSON threat protection policy to all APIs to detect potential threat vectors
Answer: D
Explanation:
Apply a JSON threat protection policy to all APIs to detect potential threat vectors
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>> Usually, if the APIs are designed and developed for specific consumers (known consumers/customers) then we would IP Whitelist the same to ensure that traffic only comes from them.
>> However, as this scenario states that the APIs are publicly available and being used by so many mobile and web applications, it is NOT possible to identify and blacklist all possible bad actors.
>> So, JSON threat protection policy is the best chance to prevent any bad JSON payloads from such bad actors.
NEW QUESTION # 28
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 the corresponding backend system is expected to be replaced in the near future
- B. When the System API can be assigned to a bounded context with a corresponding data model
- C. When there is an existing Enterprise Data Model widely used across the organization
- 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 # 29
A set of tests must be performed prior to deploying API implementations to a staging environment. Due to data security and access restrictions, untested APIs cannot be granted access to the backend systems, so instead mocked data must be used for these tests. The amount of available mocked data and its contents is sufficient to entirely test the API implementations with no active connections to the backend systems. What type of tests should be used to incorporate this mocked data?
- A. Integration tests
- B. Performance tests
- C. Unit tests (Whitebox)
- D. Functional tests (Blackbox)
Answer: C
Explanation:
Unit tests (Whitebox)
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NEW QUESTION # 30
A System API is designed to retrieve data from a backend system that has scalability challenges. What API policy can best safeguard the backend system?
- A. IPwhitelist
- B. Auth 2 token enforcement
- C. Client ID enforcement
- D. SLA-based rate limiting
Answer: D
Explanation:
SLA-based rate limiting
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>> Client Id enforement policy is a "Compliance" related NFR and does not help in maintaining the "Quality of Service (QoS)". It CANNOT and NOT meant for protecting the backend systems from scalability challenges.
>> IP Whitelisting and OAuth 2.0 token enforcement are "Security" related NFRs and again does not help in maintaining the "Quality of Service (QoS)". They CANNOT and are NOT meant for protecting the backend systems from scalability challenges.
Rate Limiting, Rate Limiting-SLA, Throttling, Spike Control are the policies that are "Quality of Service (QOS)" related NFRs and are meant to help in protecting the backend systems from getting overloaded.
https://dzone.com/articles/how-to-secure-apis
NEW QUESTION # 31
Version 3.0.1 of a REST API implementation represents time values in PST time using ISO 8601 hh:mm:ss format. The API implementation needs to be changed to instead represent time values in CEST time using ISO
8601 hh:mm:ss format. When following the semver.org semantic versioning specification, what version should be assigned to the updated API implementation?
- A. 3.0.1
- B. 3.1.0
- C. 4.0.0
- D. 3.0.2
Answer: C
Explanation:
4.0.0
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As per semver.org semantic versioning specification:
Given a version number MAJOR.MINOR.PATCH, increment the:
- MAJOR version when you make incompatible API changes.
- MINOR version when you add functionality in a backwards compatible manner.
- PATCH version when you make backwards compatible bug fixes.
As per the scenario given in the question, the API implementation is completely changing its behavior.
Although the format of the time is still being maintained as hh:mm:ss and there is no change in schema w.r.t format, the API will start functioning different after this change as the times are going to come completely different.
Example: Before the change, say, time is going as 09:00:00 representing the PST. Now on, after the change, the same time will go as 18:00:00 as Central European Summer Time is 9 hours ahead of Pacific Time.
>> This may lead to some uncertain behavior on API clients depending on how they are handling the times in the API response. All the API clients need to be informed that the API functionality is going to change and will return in CEST format. So, this considered as a MAJOR change and the version of API for this new change would be 4.0.0
NEW QUESTION # 32
A REST API is being designed to implement a Mule application.
What standard interface definition language can be used to define REST APIs?
- A. AsyncAPI Specification
- B. Web Service Definition Language(WSDL)
- C. OpenAPI Specification (OAS)
- D. YAML
Answer: C
NEW QUESTION # 33
An organization uses various cloud-based SaaS systems and multiple on-premises systems. The on-premises systems are an important part of the organization's application network and can only be accessed from within the organization's intranet.
What is the best way to configure and use Anypoint Platform to support integrations with both the cloud-based SaaS systems and on-premises systems?
A) Use CloudHub-deployed Mule runtimes in an Anypoint VPC managed by Anypoint Platform Private Cloud Edition control plane
B) Use CloudHub-deployed Mule runtimes in the shared worker cloud managed by the MuleSoft-hosted Anypoint Platform control plane
C) Use an on-premises installation of Mule runtimes that are completely isolated with NO external network access, managed by the Anypoint Platform Private Cloud Edition control plane
D) Use a combination of Cloud Hub-deployed and manually provisioned on-premises Mule runtimes managed by the MuleSoft-hosted Anypoint Platform control plane
- A. Option A
- B. Option D
- C. Option B
- D. Option C
Answer: C
Explanation:
Use a combination of CloudHub-deployed and manually provisioned on-premises Mule
runtimes managed by the MuleSoft-hosted Platform control plane.
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Key details to be taken from the given scenario:
>> Organization uses BOTH cloud-based and on-premises systems
>> On-premises systems can only be accessed from within the organization's intranet Let us evaluate the given choices based on above key details:
>> CloudHub-deployed Mule runtimes can ONLY be controlled using MuleSoft-hosted control plane. We CANNOT use Private Cloud Edition's control plane to control CloudHub Mule Runtimes. So, option suggesting this is INVALID
>> Using CloudHub-deployed Mule runtimes in the shared worker cloud managed by the MuleSoft-hosted Anypoint Platform is completely IRRELEVANT to given scenario and silly choice. So, option suggesting this is INVALID
>> Using an on-premises installation of Mule runtimes that are completely isolated with NO external network access, managed by the Anypoint Platform Private Cloud Edition control plane would work for On-premises integrations. However, with NO external access, integrations cannot be done to SaaS-based apps. Moreover CloudHub-hosted apps are best-fit for integrating with SaaS-based applications. So, option suggesting this is BEST WAY.
The best way to configure and use Anypoint Platform to support these mixed/hybrid integrations is to use a combination of CloudHub-deployed and manually provisioned on-premises Mule runtimes managed by the MuleSoft-hosted Platform control plane.
NEW QUESTION # 34
Which of the following sequence is correct?
- A. API Consumer requests access to API >> API Client implementes logic to call an API >> API routes the request to >> API Implementation
- B. API Client implementes logic to call an API >> API Consumer requests access to API >> API routes the request to >> API Implementation
- C. API Consumer implementes logic to call an API >> API Client requests access to API >> API Implementation routes the request to >> API
- D. API Client implementes logic to call an API >> API Consumer requests access to API >> API Implementation routes the request to >> API
Answer: A
Explanation:
API Consumer requests access to API >> API Client implementes logic to call an API >> API routes the request to >> API Implementation
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>> API consumer does not implement any logic to invoke APIs. It is just a role. So, the option stating "API Consumer implementes logic to call an API" is INVALID.
>> API Implementation does not route any requests. It is a final piece of logic where functionality of target systems is exposed. So, the requests should be routed to the API implementation by some other entity. So, the options stating "API Implementation routes the request to >> API" is INVALID
>> The statements in one of the options are correct but sequence is wrong. The sequence is given as "API Client implementes logic to call an API >> API Consumer requests access to API >> API routes the request to
>> API Implementation". Here, the statements in the options are VALID but sequence is WRONG.
>> Right option and sequence is the one where API consumer first requests access to API on Anypoint Exchange and obtains client credentials. API client then writes logic to call an API by using the access client credentials requested by API consumer and the requests will be routed to API implementation via the API which is managed by API Manager.
NEW QUESTION # 35
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. Use a horizontal CloudHub autoscaling policy that triggers on CPU utilization greater than 70%
- B. Permanently increase the size of each of the two (2) CloudHub workers by at least four times (4x) to one (1) vCore
- C. Permanently increase the number of CloudHub workers by four times (4x) to eight (8) CloudHub workers
- D. Use a vertical CloudHub autoscaling policy that triggers on CPU utilization greater than 70%
Answer: A
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 # 36
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