MCPA-Level-1試験問題集を提供していますMuleSoft問題
MCPA-Level-1認定ガイドPDFはリアル試験問題で100%カバー率
MuleSoft MCPA-Level-1認定試験は、MuleSoft Anypoint Platformの深い理解を持つことを求められる厳しい試験です。試験は、MuleSoft Anypoint Platformを使用して複雑な統合プロジェクトを設計および実装する能力をテストするように設計されています。試験に合格するためには、MuleSoft Anypoint Platformでの実務経験が必要です。
Mulesoft MCPA-LEVEL-1（Mulesoft Certified Platform Architect-Level 1）認定試験は、MulesoftのAnyPointプラットフォームを使用して統合ソリューションの設計と構築に関する個人の専門知識を評価するために設計されたテストです。この認定は、Mulesoftのプラットフォームを深く理解し、複雑な統合プロジェクトを設計および実装できる経験豊富な建築家向けです。
MCPA-Level-1試験に合格するには、候補者は、クライアントのニーズを満たすMulesoftソリューションを設計および実装する能力を成功裏に実証する必要があります。この試験では、AnyPointプラットフォームアーキテクチャ、統合パターン、API実装、データ統合、展開など、さまざまなトピックについて説明します。 MCPA-LEVEL-1認定は、建築家が潜在的な雇用主、クライアント、および同僚にスキルと知識を実証する優れた方法です。また、アプリケーションの統合と開発の分野でキャリアを前進させたい個人にとっても貴重な資格です。
質問 # 29
When designing an upstream API and its implementation, the development team has been advised to NOT set timeouts when invoking a downstream API, because that downstream API has no SLA that can be relied upon.
This is the only downstream API dependency of that upstream API.
- A. An SLA for the upstream API CANNOT be provided
- B. The invocation of the downstream API will run to completion without timing out
- C. A default timeout of 500 ms will automatically be applied by the Mule runtime in which the upstream API implementation executes
- D. Assume the downstream API runs uninterrupted without crashing. What is the impact of this advice?
- E. A toad-dependent timeout of less than 1000 ms will be applied by the Mule runtime in which the downstream API implementation executes
正解：C
質問 # 30
The implementation of a Process API must change.
What is a valid approach that minimizes the impact of this change on API clients?
- A. Implement the Process API changes in a new API implementation, and have the old API implementation return an HTTP status code 301 - Moved Permanentlyto inform API clients they should be calling the new API implementation.
- B. Update the RAML definition of the current Process API and notify API client developers by sending them links to the updated RAML definition.
- C. Postpone changes until API consumers acknowledge they are ready to migrate to a new Process API or API version.
- D. Implement required changes to the Process API implementation so that, whenever possible, the Process API's RAML definition remains unchanged.
正解：B
解説：
Explanation/Reference:
質問 # 31
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 B
- B. Option C
- C. Option A
- D. Option D
正解：A
解説：
Allow System APIs to return data that is NOT currently required by the identified Process or Experience APIs.
*****************************************
>> 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.
質問 # 32
What API policy would LEAST likely be applied to a Process API?
- A. Rate limiting
- B. Custom circuit breaker
- C. JSON threat protection
- D. Client ID enforcement
正解：B
解説：
Explanation/Reference: https://docs.mulesoft.com/api-manager/2.x/policy-mule3-provided-policies
質問 # 33
When designing an upstream API and its implementation, the development team has been advised to NOT set timeouts when invoking a downstream API, because that downstream API has no SLA that can be relied upon.
This is the only downstream API dependency of that upstream API.
Assume the downstream API runs uninterrupted without crashing. What is the impact of this advice?
- A. The invocation of the downstream API will run to completion without timing out
- B. An SLA for the upstream API CANNOT be provided
- C. A default timeout of 500 ms will automatically be applied by the Mule runtime in which the upstream API implementation executes
- D. A toad-dependent timeout of less than 1000 ms will be applied by the Mule runtime in which the downstream API implementation executes
正解：B
解説：
An SLA for the upstream API CANNOT be provided.
*****************************************
>> First thing first, the default HTTP response timeout for HTTP connector is 10000 ms (10 seconds). NOT
500 ms.
>> Mule runtime does NOT apply any such "load-dependent" timeouts. There is no such behavior currently in Mule.
>> As there is default 10000 ms time out for HTTP connector, we CANNOT always guarantee that the invocation of the downstream API will run to completion without timing out due to its unreliable SLA times.
If the response time crosses 10 seconds then the request may time out.
The main impact due to this is that a proper SLA for the upstream API CANNOT be provided.
質問 # 34
The implementation of a Process API must change.
What is a valid approach that minimizes the impact of this change on API clients?
- A. Implement required changes to the Process API implementation so that whenever possible, the Process API's RAML definition remains unchanged
- B. Implement the Process API changes in a new API implementation, and have the old API implementation return an HTTP status code 301 - Moved Permanently to inform API clients they should be calling the new API implementation
- C. Update the RAML definition of the current Process API and notify API client developers by sending them links to the updated RAML definition
- D. Postpone changes until API consumers acknowledge they are ready to migrate to a new Process API or API version
正解：A
解説：
Implement required changes to the Process API implementation so that, whenever possible, the Process API's RAML definition remains unchanged.
*****************************************
Key requirement in the question is:
>> Approach that minimizes the impact of this change on API clients
Based on above:
>> Updating the RAML definition would possibly impact the API clients if the changes require any thing mandatory from client side. So, one should try to avoid doing that until really necessary.
>> Implementing the changes as a completely different API and then redirectly the clients with 3xx status code is really upsetting design and heavily impacts the API clients.
>> Organisations and IT cannot simply postpone the changes required until all API consumers acknowledge they are ready to migrate to a new Process API or API version. This is unrealistic and not possible.
The best way to handle the changes always is to implement required changes to the API implementations so that, whenever possible, the API's RAML definition remains unchanged.
質問 # 35
A system API is deployed to a primary environment as well as to a disaster recovery (DR) environment, with different DNS names in each environment. A process API is a client to the system API and is being rate limited by the system API, with different limits in each of the environments. The system API's DR environment provides only 20% of the rate limiting offered by the primary environment. What is the best API fault-tolerant invocation strategy to reduce overall errors in the process API, given these conditions and constraints?
- A. Invoke the system API deployed to the primary environment; add timeout and retry logic to the process API to avoid intermittent failures; if it still fails, invoke the system API deployed to the DR environment
- B. In parallel, invoke the system API deployed to the primary environment and the system API deployed to the DR environment; add timeout and retry logic to the process API to avoid intermittent failures; add logic to the process API to combine the results
- C. Invoke the system API deployed to the primary environment; add retry logic to the process API to handle intermittent failures by invoking the system API deployed to the DR environment
- D. Invoke the system API deployed to the primary environment; add timeout and retry logic to the process API to avoid intermittent failures; if it still fails, invoke a copy of the process API deployed to the DR environment
正解：A
解説：
Correct answer: Invoke the system API deployed to the primary environment; add timeout and retry logic to the process API to avoid intermittent failures; if it still fails, invoke the system API deployed to the DR environment
*****************************************
There is one important consideration to be noted in the question which is - System API in DR environment provides only 20% of the rate limiting offered by the primary environment. So, comparitively, very less calls will be allowed into the DR environment API opposed to its primary environment. With this in mind, lets analyse what is the right and best fault-tolerant invocation strategy.
1. Invoking both the system APIs in parallel is definitely NOT a feasible approach because of the 20% limitation we have on DR environment. Calling in parallel every time would easily and quickly exhaust the rate limits on DR environment and may not give chance to genuine intermittent error scenarios to let in during the time of need.
2. Another option given is suggesting to add timeout and retry logic to process API while invoking primary environment's system API. This is good so far. However, when all retries failed, the option is suggesting to invoke the copy of process API on DR environment which is not right or recommended. Only system API is the one to be considered for fallback and not the whole process API. Process APIs usually have lot of heavy orchestration calling many other APIs which we do not want to repeat again by calling DR's process API. So this option is NOT right.
3. One more option given is suggesting to add the retry (no timeout) logic to process API to directly retry on DR environment's system API instead of retrying the primary environment system API first. This is not at all a proper fallback. A proper fallback should occur only after all retries are performed and exhausted on Primary environment first. But here, the option is suggesting to directly retry fallback API on first failure itself without trying main API. So, this option is NOT right too.
This leaves us one option which is right and best fit.
- Invoke the system API deployed to the primary environment
- Add Timeout and Retry logic on it in process API
- If it fails even after all retries, then invoke the system API deployed to the DR environment.
質問 # 36
What is true about where an API policy is defined in Anypoint Platform and how it is then applied to API instances?
- A. The API policy Is defined in API Manager and then automatically applied to ALL API instances
- B. The API policy is defined in API Manager, and then applied to ALL API instances in the specified environment
- C. The API policy Is defined In API Manager for a specific API Instance, and then ONLY applied to the specific API instance
- D. The API policy Is defined In Runtime Manager as part of the API deployment to a Mule runtime, and then ONLY applied to the specific API Instance
正解：C
解説：
The API policy is defined in API Manager for a specific API instance, and then ONLY applied to the specific API instance.
*****************************************
>> Once our API specifications are ready and published to Exchange, we need to visit API Manager and register an API instance for each API.
>> API Manager is the place where management of API aspects takes place like addressing NFRs by enforcing policies on them.
>> We can create multiple instances for a same API and manage them differently for different purposes.
>> One instance can have a set of API policies applied and another instance of same API can have different set of policies applied for some other purpose.
>> These APIs and their instances are defined PER environment basis. So, one need to manage them seperately in each environment.
>> We can ensure that same configuration of API instances (SLAs, Policies etc..) gets promoted when promoting to higher environments using platform feature. But this is optional only. Still one can change them per environment basis if they have to.
>> Runtime Manager is the place to manage API Implementations and their Mule Runtimes but NOT APIs itself. Though API policies gets executed in Mule Runtimes, We CANNOT enforce API policies in Runtime Manager. We would need to do that via API Manager only for a cherry picked instance in an environment.
So, based on these facts, right statement in the given choices is - "The API policy is defined in API Manager for a specific API instance, and then ONLY applied to the specific API instance".
質問 # 37
What is true about API implementations when dealing with legal regulations that require all data processing to be performed within a certain jurisdiction (such as in the USA or the EU)?
- A. They must te deployed to Anypoint Platform runtime planes that are managed by Anypoint Platform control planes, with both planes in the same Jurisdiction
- B. They must ensure ALL data is encrypted both in transit and at rest
- C. They must use a Jurisdiction-local external messaging system such as Active MQ rather than Anypoint MQ
- D. They must avoid using the Object Store as it depends on services deployed ONLY to the US East region
正解：A
解説：
They must be deployed to Anypoint Platform runtime planes that are managed by Anypoint Platform control planes, with both planes in the same Jurisdiction.
*****************************************
>> As per legal regulations, all data processing to be performed within a certain jurisdiction. Meaning, the data in USA should reside within USA and should not go out. Same way, the data in EU should reside within EU and should not go out.
>> So, just encrypting the data in transit and at rest does not help to be compliant with the rules. We need to make sure that data does not go out too.
>> The data that we are talking here is not just about the messages that are published to Anypoint MQ. It includes the apps running, transaction states, application logs, events, metric info and any other metadata. So, just replacing Anypoint MQ with a locally hosted ActiveMQ does NOT help.
>> The data that we are talking here is not just about the key/value pairs that are stored in Object Store. It includes the messages published, apps running, transaction states, application logs, events, metric info and any other metadata. So, just avoiding using Object Store does NOT help.
>> The only option left and also the right option in the given choices is to deploy application on runtime and control planes that are both within the jurisdiction.
質問 # 38
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 C
- C. Option D
- D. Option A
正解：D
質問 # 39
An organization is implementing a Quote of the Day API that caches today's quote.
What scenario can use the GoudHub Object Store via the Object Store connector to persist the cache's state?
- A. When there is one deployment of the API implementation to CloudHub and anottV deployment to a customer-hosted Mule runtime that must share the cache state
- B. When there are three CloudHub deployments of the API implementation to three separate CloudHub regions that must share the cache state
- C. When there is one CloudHub deployment of the API implementation to three CloudHub workers that must share the cache state
- D. When there are two CloudHub deployments of the API implementation by two Anypoint Platform business groups to the same CloudHub region that must share the cache state
正解：A
質問 # 40
How can the application of a rate limiting API policy be accurately reflected in the RAML definition of an API?
- A. By refining the resource definitions by adding a description of the rate limiting policy behavior
- B. By refining the request definitions by adding a remaining Requests query parameter with description, type, and example
- C. By refining the response definitions by adding the out-of-the-box Anypoint Platform rate-limit-enforcement securityScheme with description, type, and example
- D. By refining the response definitions by adding the x-ratelimit-* response headers with description, type, and example
正解：D
解説：
Correct answer: By refining the response definitions by adding the x-ratelimit-* response headers with description, type, and example
*****************************************
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
質問 # 41
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 B
- B. Option C
- C. Option A
- D. Option D
正解：A
解説：
Correct answer: Use a combination of CloudHub-deployed and manually provisioned on-premises Mule runtimes managed by the MuleSoft-hosted Platform control plane.
*****************************************
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.
質問 # 42
A new upstream API Is being designed to offer an SLA of 500 ms median and 800 ms maximum (99th percentile) response time. The corresponding API implementation needs to sequentially invoke 3 downstream APIs of very similar complexity.
The first of these downstream APIs offers the following SLA for its response time: median: 100 ms, 80th percentile: 500 ms, 95th percentile: 1000 ms.
If possible, how can a timeout be set in the upstream API for the invocation of the first downstream API to meet the new upstream API's desired SLA?
- A. No timeout is possible to meet the upstream API's desired SLA; a different SLA must be negotiated with the first downstream API or invoke an alternative API
- B. Do not set a timeout; the Invocation of this API Is mandatory and so we must wait until it responds
- C. Set a timeout of 50 ms; this times out more invocations of that API but gives additional room for retries
- D. Set a timeout of 100 ms; that leaves 400 ms for the other two downstream APIs to complete
正解：D
解説：
Correct answer: Set a timeout of 100ms; that leaves 400ms for other two downstream APIs to complete
*****************************************
Key details to take from the given scenario:
>> Upstream API's designed SLA is 500ms (median). Lets ignore maximum SLA response times.
>> This API calls 3 downstream APIs sequentially and all these are of similar complexity.
>> The first downstream API is offering median SLA of 100ms, 80th percentile: 500ms; 95th percentile: 1000ms.
Based on the above details:
>> We can rule out the option which is suggesting to set 50ms timeout. Because, if the median SLA itself being offered is 100ms then most of the calls are going to timeout and time gets wasted in retried them and eventually gets exhausted with all retries. Even if some retries gets successful, the remaining time wont leave enough room for 2nd and 3rd downstream APIs to respond within time.
>> The option suggesting to NOT set a timeout as the invocation of this API is mandatory and so we must wait until it responds is silly. As not setting time out would go against the good implementation pattern and moreover if the first API is not responding within its offered median SLA 100ms then most probably it would either respond in 500ms (80th percentile) or 1000ms (95th percentile). In BOTH cases, getting a successful response from 1st downstream API does NO GOOD because already by this time the Upstream API SLA of 500 ms is breached. There is no time left to call 2nd and 3rd downstream APIs.
>> It is NOT true that no timeout is possible to meet the upstream APIs desired SLA.
As 1st downstream API is offering its median SLA of 100ms, it means MOST of the time we would get the responses within that time. So, setting a timeout of 100ms would be ideal for MOST calls as it leaves enough room of 400ms for remaining 2 downstream API calls.
質問 # 43
What is a key requirement when using an external Identity Provider for Client Management in Anypoint Platform?
- A. The application network must include System APIs that interact with the Identity Provider
- B. To invoke OAuth 2.0-protected APIs managed by Anypoint Platform, API clients must submit access tokens issued by that same Identity Provider
- C. Single sign-on is required to sign in to Anypoint Platform
- D. APIs managed by Anypoint Platform must be protected by SAML 2.0 policies
正解：B
解説：
https://www.folkstalk.com/2019/11/mulesoft-integration-and-platform.html Explanation:
To invoke OAuth 2.0-protected APIs managed by Anypoint Platform, API clients must submit access tokens issued by that same Identity Provider
*****************************************
>> It is NOT necessary that single sign-on is required to sign in to Anypoint Platform because we are using an external Identity Provider for Client Management
>> It is NOT necessary that all APIs managed by Anypoint Platform must be protected by SAML 2.0 policies because we are using an external Identity Provider for Client Management
>> Not TRUE that the application network must include System APIs that interact with the Identity Provider because we are using an external Identity Provider for Client Management Only TRUE statement in the given options is - "To invoke OAuth 2.0-protected APIs managed by Anypoint Platform, API clients must submit access tokens issued by that same Identity Provider" References:
https://docs.mulesoft.com/api-manager/2.x/external-oauth-2.0-token-validation-policy
https://blogs.mulesoft.com/dev/api-dev/api-security-ways-to-authenticate-and-authorize/
質問 # 44
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 a pragmatic approach with only limited isolation from the backend system is deemed appropriate
- D. When the System API can be assigned to a bounded context with a corresponding data model
正解：C
解説：
Correct answer: 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 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
質問 # 45
What CANNOT be effectively enforced using an API policy in Anypoint Platform?
- A. Logging HTTP requests and responses
- B. Guarding against Denial of Service attacks
- C. Backend system overloading
- D. Maintaining tamper-proof credentials between APIs
正解：A
質問 # 46
The responses to some HTTP requests can be cached depending on the HTTP verb used in the request.
According to the HTTP specification, for what HTTP verbs is this safe to do?
- A. PUT, POST, DELETE
- B. GET, HEAD, POST
- C. GET, OPTIONS, HEAD
- D. GET, PUT, OPTIONS
正解：C
解説：
Explanation/Reference: http://restcookbook.com/HTTP%20Methods/idempotency/
質問 # 47
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
正解：D
解説：
Correct answer: When the API implementation changes the structure of the request or response messages
*****************************************
>> 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..
質問 # 48
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. File-based storage
- D. Persistent Object Store
正解：D
解説：
Persistent Object Store
*****************************************
>> 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.
質問 # 49
Refer to the exhibit.
An organization uses one specific CloudHub (AWS) region for all CloudHub deployments.
How are CloudHub workers assigned to availability zones (AZs) when the organization's Mule applications are deployed to CloudHub in that region?
- A. AZs are selected as part of the Mule application's deployment configuration
- B. Workers belonging to a given environment are assigned to the same AZ within that region
- C. An AZ is randomly selected for a Mule application, and all the Mule application's CloudHub workers are assigned to that one AZ
- D. Workers are randomly distributed across available AZs within that region
正解：D
質問 # 50
......
合格させるMCPA-Level-1試験にはリアル問題解答：https://www.passtest.jp/MuleSoft/MCPA-Level-1-shiken.html