LATEST MCPA-LEVEL-1 TEST CAMP | MCPA-LEVEL-1 TRAINING FOR EXAM

Latest MCPA-Level-1 Test Camp | MCPA-Level-1 Training For Exam

Latest MCPA-Level-1 Test Camp | MCPA-Level-1 Training For Exam

Blog Article

Tags: Latest MCPA-Level-1 Test Camp, MCPA-Level-1 Training For Exam, MCPA-Level-1 Exam Bible, MCPA-Level-1 Latest Test Prep, MCPA-Level-1 Valid Real Exam

If you want to be a more successful person and become the best, the first step you need to take is to have our MCPA-Level-1 exam questions. Get an internationally certified MCPA-Level-1 certificate to prove your strength. This is the best way. Your strength and efficiency will really bring you more job opportunities. And our MCPA-Level-1 study braindumps will help you pass the exam easily and get the certification for sure.

The MCPA-Level-1 certification exam is a comprehensive test that evaluates a candidate's understanding of the Anypoint Platform. MCPA-Level-1 exam covers a wide range of topics, including application network, API-led connectivity, data transformation, and deployment strategies. MCPA-Level-1 exam also tests the candidate's ability to design and develop efficient and scalable integration solutions using MuleSoft's Anypoint Platform.

MuleSoft MCPA-Level-1 Certification is an excellent certification for architects and developers who want to demonstrate their skills and expertise in the MuleSoft Anypoint Platform. MuleSoft Certified Platform Architect - Level 1 certification not only validates their skills but also provides access to MuleSoft's community and resources. If you are looking to advance your career in MuleSoft, the MCPA-Level-1 certification is a great place to start.

>> Latest MCPA-Level-1 Test Camp <<

MCPA-Level-1 Pass4sure Guide & MCPA-Level-1 Exam Preparation & MCPA-Level-1 Study Materials

Laziness will ruin your life one day. It is time to have a change now. Although we all love cozy life, we must work hard to create our own value. Then our MCPA-Level-1 training materials will help you overcome your laziness. Study is the best way to enrich your life. On one hand, you may learn the newest technologies in the field with our MCPA-Level-1 Study Guide to help you better adapt to your work, and on the other hand, you will pass the MCPA-Level-1 exam and achieve the certification which is the symbol of competence.

MuleSoft Certified Platform Architect - Level 1 Sample Questions (Q64-Q69):

NEW QUESTION # 64
What condition requires using a CloudHub Dedicated Load Balancer?

  • A. When cross-region load balancing is required between separate deployments of the same Mule application
  • B. When custom DNS names are required for API implementations deployed to customer-hosted Mule runtimes
  • C. When server-side load-balanced TLS mutual authentication is required between API implementations and API clients
  • D. When API invocations across multiple CloudHub workers must be load balanced

Answer: C

Explanation:
When server-side load-balanced TLS mutual authentication is required between API implementations and API clients
*****************************************
Fact/ Memory Tip: Although there are many benefits of CloudHub Dedicated Load balancer, TWO important things that should come to ones mind for considering it are:
>> Having URL endpoints with Custom DNS names on CloudHub deployed apps
>> Configuring custom certificates for both HTTPS and Two-way (Mutual) authentication.
Coming to the options provided for this question:
>> We CANNOT use DLB to perform cross-region load balancing between separate deployments of the same Mule application.
>> We can have mapping rules to have more than one DLB URL pointing to same Mule app. But vicevera (More than one Mule app having same DLB URL) is NOT POSSIBLE
>> It is true that DLB helps to setup custom DNS names for Cloudhub deployed Mule apps but NOT true for apps deployed to Customer-hosted Mule Runtimes.
>> It is true to that we can load balance API invocations across multiple CloudHub workers using DLB but it is NOT A MUST. We can achieve the same (load balancing) using SLB (Shared Load Balancer) too. We DO NOT necessarily require DLB for achieve it.
So the only right option that fits the scenario and requires us to use DLB is when TLS mutual authentication is required between API implementations and API clients.


NEW QUESTION # 65
What best explains the use of auto-discovery in API implementations?

  • A. It enables Anypoint Studio to discover API definitions configured in Anypoint Platform
  • B. It makes API Manager aware of API implementations and hence enables it to enforce policies
  • C. It enables Anypoint Analytics to gain insight into the usage of APIs
  • D. It enables Anypoint Exchange to discover assets and makes them available for reuse

Answer: B

Explanation:
Correct answer: It makes API Manager aware of API implementations and hence enables it to enforce policies.
*****************************************
>> API Autodiscovery is a mechanism that manages an API from API Manager by pairing the deployed application to an API created on the platform.
>> API Management includes tracking, enforcing policies if you apply any, and reporting API analytics.
>> Critical to the Autodiscovery process is identifying the API by providing the API name and version.
References:
https://docs.mulesoft.com/api-manager/2.x/api-auto-discovery-new-concept
https://docs.mulesoft.com/api-manager/1.x/api-auto-discovery
https://docs.mulesoft.com/api-manager/2.x/api-auto-discovery-new-concept


NEW QUESTION # 66
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 a pragmatic approach with only limited isolation from the backend system is deemed appropriate
  • D. When there is an existing Enterprise Data Model widely used across the organization

Answer: C

Explanation:
When a pragmatic approach with only limited isolation from the backend system is deemed appropriate.
*****************************************
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 systemand 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 # 67
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 is migrated from an older to a newer version of the Mule runtime
  • 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 changes the structure of the request or response messages

Answer: D


NEW QUESTION # 68
A manufacturing company has deployed an API implementation to CloudHub and has not configured it to be automatically restarted by CloudHub when the worker is not responding.
Which statement is true when no API Client invokes that API implementation?

  • A. No alert on the API invocations and APT implementation can be raised
  • B. Alerts on the APT invocation and API implementation can be raised
  • C. No alert on the API invocations is raised but alerts on the API implementation can be raised
  • D. Alerts on the API invocations are raised but no alerts on the API implementation can be raised

Answer: C

Explanation:
When an API implementation is deployed on CloudHub without configuring automatic restarts in case of worker non-responsiveness, MuleSoft's monitoring and alerting behavior is as follows:
* API Invocation Alerts:
* If no clients are invoking the API, there will be no invocation alerts triggered, as alerts related to invocations depend on actual client requests.
* Implementation-Level Alerts:
* Even without invocation, CloudHub can still monitor the state of the API implementation. If the worker becomes unresponsive, an alert related to the API implementation's health or availability could still be raised.
* Why Option C is Correct:
* This option correctly identifies that no invocation-related alerts would be triggered in the absence of client requests, while implementation-level alerts could still be generated based on the worker's state.
ReferencesFor additional information, check MuleSoft documentation on CloudHub monitoring and alert configurations to understand worker status alerts versus invocation alerts.


NEW QUESTION # 69
......

The money you have invested on updating yourself is worthwhile. The knowledge you have learned is priceless. You can obtain many useful skills on our MCPA-Level-1 study guide, which is of great significance in your daily work. Never feel sorry to invest yourself. Our MCPA-Level-1 Exam Materials deserve your choice. If you still cannot make decisions, you can try our free demo of the MCPA-Level-1 training quiz.

MCPA-Level-1 Training For Exam: https://www.actualvce.com/MuleSoft/MCPA-Level-1-valid-vce-dumps.html

Report this page