2024 Updated MuleSoft MCPA-Level-1-Maintenance Dumps PDF - Want To Pass MCPA-Level-1-Maintenance Fast
MCPA-Level-1-Maintenance Practice Exam Dumps - 99% Marks In MuleSoft Exam
The MCPA-Level-1-Maintenance Certification Exam consists of multiple-choice questions that test the candidate's knowledge of MuleSoft runtime fabric, deployment, architecture and troubleshooting. MCPA-Level-1-Maintenance exam covers a range of topics including managing MuleSoft APIs, optimizing application performance, troubleshooting MuleSoft applications, and monitoring MuleSoft applications using various tools. Successful candidates will have demonstrated their ability to manage complex MuleSoft applications, deploy and configure MuleSoft runtime fabric and troubleshoot issues that may arise. Overall, the MCPA-Level-1-Maintenance Certification Exam is an essential credential for any MuleSoft platform architect looking to advance their career and increase their value to organizations that use MuleSoft integrations.
NEW QUESTION # 45
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 an IP blacklist policy to all APIs; the blacklist will Include all bad actors
- B. Shut out bad actors by using HTTPS mutual authentication for all API invocations
- C. Apply a Header injection and removal policy that detects the malicious data before it is used
- 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 # 46
How can the application of a rate limiting API policy be accurately reflected in the RAML definition of an API?
- A. By refining the response definitions by adding the x-ratelimit-* response headers with description, type, and example
- B. By refining the response definitions by adding the out-of-the-box Anypoint Platform rate-limit-enforcement securityScheme with description, type, and example
- C. By refining the request definitions by adding a remaining Requests query parameter with description, type, and example
- D. By refining the resource definitions by adding a description of the rate limiting policy behavior
Answer: A
Explanation:
By refining the response definitions by adding the x-ratelimit-* response headers with description, type, and example
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References:
https://docs.mulesoft.com/api-manager/2.x/rate-limiting-and-throttling#response-headers
https://docs.mulesoft.com/api-manager/2.x/rate-limiting-and-throttling-sla-based-policies#response-headers
NEW QUESTION # 47
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 the majority of the applications in the application network are cloud based
- D. When various teams responsible for creating APIs are new to integration and hence need extensive training
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 # 48
Due to a limitation in the backend system, a system API can only handle up to 500 requests per second. What is the best type of API policy to apply to the system API to avoid overloading the backend system?
- A. Spike control
- B. HTTP caching
- C. Rate limiting - SLA based
- D. Rate limiting
Answer: A
Explanation:
Spike control
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>> First things first, HTTP Caching policy is for purposes different than avoiding the backend system from overloading. So this is OUT.
>> Rate Limiting and Throttling/ Spike Control policies are designed to limit API access, but have different intentions.
>> Rate limiting protects an API by applying a hard limit on its access.
>> Throttling/ Spike Control shapes API access by smoothing spikes in traffic.
That is why, Spike Control is the right option.
NEW QUESTION # 49
What is typically NOT a function of the APIs created within the framework called API-led connectivity?
- A. They provide an additional layer of resilience on top of the underlying backend system, thereby insulating clients from extended failure of these systems.
- B. They can compose data from various sources and combine them with orchestration logic to create higher level value.
- C. They reduce the dependency on the underlying backend systems by helping unlock data from backend systems In a reusable and consumable way.
- D. They allow for innovation at the user Interface level by consuming the underlying assets without being aware of how data Is being extracted from backend systems.
Answer: A
Explanation:
They provide an additional layer of resilience on top of the underlying backend system, thereby insulating clients from extended failure of these systems.
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In API-led connectivity,
>> Experience APIs - allow for innovation at the user interface level by consuming the underlying assets without being aware of how data is being extracted from backend systems.
>> Process APIs - compose data from various sources and combine them with orchestration logic to create higher level value
>> System APIs - reduce the dependency on the underlying backend systems by helping unlock data from backend systems in a reusable and consumable way.
However, they NEVER promise that they provide an additional layer of resilience on top of the underlying backend system, thereby insulating clients from extended failure of these systems.
https://dzone.com/articles/api-led-connectivity-with-mule
NEW QUESTION # 50
What is the most performant out-of-the-box solution in Anypoint Platform to track transaction state in an asynchronously executing long-running process implemented as a Mule application deployed to multiple CloudHub workers?
- A. Redis distributed cache
- B. java.util.WeakHashMap
- C. Persistent Object Store
- D. File-based storage
Answer: C
Explanation:
Persistent Object Store
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>> Redis distributed cache is performant but NOT out-of-the-box solution in Anypoint Platform
>> File-storage is neither performant nor out-of-the-box solution in Anypoint Platform
>> java.util.WeakHashMap needs a completely custom implementation of cache from scratch using Java code and is limited to the JVM where it is running. Which means the state in the cache is not worker aware when running on multiple workers. This type of cache is local to the worker. So, this is neither out-of-the-box nor worker-aware among multiple workers on cloudhub. https://www.baeldung.com/java-weakhashmap
>> Persistent Object Store is an out-of-the-box solution provided by Anypoint Platform which is performant as well as worker aware among multiple workers running on CloudHub. https://docs.mulesoft.com/object-store/ So, Persistent Object Store is the right answer.
NEW QUESTION # 51
A company requires Mule applications deployed to CloudHub to be isolated between non-production and production environments. This is so Mule applications deployed to non-production environments can only access backend systems running in their customer-hosted non-production environment, and so Mule applications deployed to production environments can only access backend systems running in their customer-hosted production environment. How does MuleSoft recommend modifying Mule applications, configuring environments, or changing infrastructure to support this type of per-environment isolation between Mule applications and backend systems?
- A. Create non-production and production environments in different Anypoint Platform business groups
- B. Create separate Anypoint VPCs for non-production and production environments, then configure connections to the backend systems in the corresponding customer-hosted environments
- C. Modify properties of Mule applications deployed to the production Anypoint Platform environments to prevent access from non-production Mule applications
- D. Configure firewall rules in the infrastructure inside each customer-hosted environment so that only IP addresses from the corresponding Anypoint Platform environments are allowed to communicate with corresponding backend systems
Answer: B
Explanation:
Create separate Anypoint VPCs for non-production and production environments, then configure connections to the backend systems in the corresponding customer-hosted environments.
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>> Creating different Business Groups does NOT make any difference w.r.t accessing the non-prod and prod customer-hosted environments. Still they will be accessing from both Business Groups unless process network restrictions are put in place.
>> We need to modify or couple the Mule Application Implementations with the environment. In fact, we should never implements application coupled with environments by binding them in the properties. Only basic things like endpoint URL etc should be bundled in properties but not environment level access restrictions.
>> IP addresses on CloudHub are dynamic until unless a special static addresses are assigned. So it is not possible to setup firewall rules in customer-hosted infrastrcture. More over, even if static IP addresses are assigned, there could be 100s of applications running on cloudhub and setting up rules for all of them would be a hectic task, non-maintainable and definitely got a good practice.
>> The best practice recommended ), is to have your Anypoint VPCs
seperated for Prod and Non-Prod and perform the VPC peering or VPN tunneling for these Anypoint VPCs to respective Prod and Non-Prod customer-hosted environment networks.
NEW QUESTION # 52
What API policy would be LEAST LIKELY used when designing an Experience API that is intended to work with a consumer mobile phone or tablet application?
- A. IPwhitellst
- B. Client ID enforcement
- C. OAuth 2.0 access token enforcement
- D. JSON threat protection
Answer: A
Explanation:
IP whitelist
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>> OAuth 2.0 access token and Client ID enforcement policies are VERY common to apply on Experience APIs as API consumers need to register and access the APIs using one of these mechanisms
>> JSON threat protection is also VERY common policy to apply on Experience APIs to prevent bad or suspicious payloads hitting the API implementations.
>> IP whitelisting policy is usually very common in Process and System APIs to only whitelist the IP range inside the local VPC. But also applied occassionally on some experience APIs where the End User/ API Consumers are FIXED.
>> When we know the API consumers upfront who are going to access certain Experience APIs, then we can request for static IPs from such consumers and whitelist them to prevent anyone else hitting the API.
However, the experience API given in the question/ scenario is intended to work with a consumer mobile phone or tablet application. Which means, there is no way we can know all possible IPs that are to be whitelisted as mobile phones and tablets can so many in number and any device in the city/state/country/globe.
So, It is very LEAST LIKELY to apply IP Whitelisting on such Experience APIs whose consumers are typically Mobile Phones or Tablets.
NEW QUESTION # 53
Which of the following best fits the definition of API-led connectivity?
- A. API-led connectivity is a technology which enabled us to implement Experience, Process and System layer based APIs
- B. API-led connectivity is a 3-layered architecture covering Experience, Process and System layers
- C. 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
Answer: C
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 # 54
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. Client ID enforcement
- B. Auth 2 token enforcement
- C. SLA-based rate limiting
- D. IPwhitelist
Answer: C
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 # 55
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 # 56
What Mule application deployment scenario requires using Anypoint Platform Private Cloud Edition or Anypoint Platform for Pivotal Cloud Foundry?
- A. When regulatory requirements mandate on-premises processing of EVERY data item, including meta-data
- B. When ALL backend systems in the application network are deployed in the organization's intranet
- C. When it Is required to make ALL applications highly available across multiple data centers
- D. When it is required that ALL APIs are private and NOT exposed to the public cloud
Answer: A
Explanation:
When regulatory requirements mandate on-premises processing of EVERY data item, including meta-data.
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We need NOT require to use Anypoint Platform PCE or PCF for the below. So these options are OUT.
>> We can make ALL applications highly available across multiple data centers using CloudHub too.
>> We can use Anypoint VPN and tunneling from CloudHub to connect to ALL backend systems in the application network that are deployed in the organization's intranet.
>> We can use Anypoint VPC and Firewall Rules to make ALL APIs private and NOT exposed to the public cloud.
Only valid reason in the given options that requires to use Anypoint Platform PCE/ PCF is - When regulatory requirements mandate on-premises processing of EVERY data item, including meta-data.
NEW QUESTION # 57
What is a typical result of using a fine-grained rather than a coarse-grained API deployment model to implement a given business process?
- A. A decrease in the number of connections within the application network supporting the business process
- B. A higher number of discoverable API-related assets in the application network
- C. A better response time for the end user as a result of the APIs being smaller in scope and complexity
- D. An overall tower usage of resources because each fine-grained API consumes less resources
Answer: B
Explanation:
A higher number of discoverable API-related assets in the application network.
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>> We do NOT get faster response times in fine-grained approach when compared to coarse-grained approach.
>> In fact, we get faster response times from a network having coarse-grained APIs compared to a network having fine-grained APIs model. The reasons are below.
Fine-grained approach:
1. will have more APIs compared to coarse-grained
2. So, more orchestration needs to be done to achieve a functionality in business process.
3. Which means, lots of API calls to be made. So, more connections will needs to be established. So, obviously more hops, more network i/o, more number of integration points compared to coarse-grained approach where fewer APIs with bulk functionality embedded in them.
4. That is why, because of all these extra hops and added latencies, fine-grained approach will have bit more response times compared to coarse-grained.
5. Not only added latencies and connections, there will be more resources used up in fine-grained approach due to more number of APIs.
That's why, fine-grained APIs are good in a way to expose more number of resuable assets in your network and make them discoverable. However, needs more maintenance, taking care of integration points, connections, resources with a little compromise w.r.t network hops and response times.
NEW QUESTION # 58
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 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
- B. Create a canonical model that combines the backend and API-led models to simplify and unify data models, and minimize data transformations.
- 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 # 59
In which layer of API-led connectivity, does the business logic orchestration reside?
- A. System Layer
- B. Process Layer
- C. Experience Layer
Answer: B
Explanation:
Process Layer
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>> Experience layer is dedicated for enrichment of end user experience. This layer is to meet the needs of different API clients/ consumers.
>> System layer is dedicated to APIs which are modular in nature and implement/ expose various individual functionalities of backend systems
>> Process layer is the place where simple or complex business orchestration logic is written by invoking one or many System layer modular APIs So, Process Layer is the right answer.
NEW QUESTION # 60
What CANNOT be effectively enforced using an API policy in Anypoint Platform?
- A. Maintaining tamper-proof credentials between APIs
- B. Guarding against Denial of Service attacks
- C. Logging HTTP requests and responses
- D. Backend system overloading
Answer: B
Explanation:
Guarding against Denial of Service attacks
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>> Backend system overloading can be handled by enforcing "Spike Control Policy"
>> Logging HTTP requests and responses can be done by enforcing "Message Logging Policy"
>> Credentials can be tamper-proofed using "Security" and "Compliance" Policies However, unfortunately, there is no proper way currently on Anypoint Platform to guard against DOS attacks.
NEW QUESTION # 61
Which of the below, when used together, makes the IT Operational Model effective?
- A. Create resuable assets, make them discoverable so that LOB teams can self-serve and browse the APIs
- B. Create reusable assets, Do marketing on the created assets across organization, Arrange time to time LOB reviews to ensure assets are being consumed or not
- C. Create reusable assets, Make them discoverable so that LOB teams can self-serve and browse the APIs, Get active feedback and usage metrics
Answer: A
Explanation:
Create reusable assets, Make them discoverable so that LOB teams can self-serve and browse the APIs, Get active feedback and usage metrics.
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Diagram, arrow Description automatically generated
NEW QUESTION # 62
What Anypoint Platform Capabilities listed below fall under APIs and API Invocations/Consumers category?
Select TWO.
- A. API Consumer Engagement
- B. API Runtime Execution and Hosting
- C. API Operations and Management
- D. API Design and Development
Answer: D
Explanation:
Explanation
Correct Answers: API Design and Development and API Runtime Execution and Hosting
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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
Explanation
Correct Answers: API Operations and Management and 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
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NEW QUESTION # 63
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MuleSoft MCPA-Level-1-Maintenance exam is designed for those individuals who have already achieved the MuleSoft Certified Platform Architect - Level 1 certification and wish to maintain their status as a certified professional. MCPA-Level-1-Maintenance exam is intended to test the knowledge and skills of the candidate in the latest MuleSoft platform developments and updates.
Updated Verified MCPA-Level-1-Maintenance Q&As - Pass Guarantee: https://examcollection.prep4king.com/MCPA-Level-1-Maintenance-latest-questions.html
