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MuleSoft-Integration-Architect-I Übungstest: Salesforce Certified MuleSoft Integration Architect I & MuleSoft-Integration-Architect-I Braindumps Prüfung
Übrigens, Sie können die vollständige Version der It-Pruefung MuleSoft-Integration-Architect-I Prüfungsfragen aus dem Cloud-Speicher herunterladen: https://drive.google.com/open?id=1yfT5I8zZXBbBR3oVCycQrp__UD8BhVwx
Die echten und originalen Prüfungsfragen und Antworten zu MuleSoft-Integration-Architect-I(Salesforce Certified MuleSoft Integration Architect I)bei It-Pruefung wurden verfasst von unseren Salesforce-Experten mit den Informationen von MuleSoft-Integration-Architect-I(Salesforce Certified MuleSoft Integration Architect I)aus dem Testcenter wie PROMETRIC oder VUE.
Salesforce MuleSoft-Integration-Architect-I Prüfungsplan:
Thema
Einzelheiten
Thema 1
- Designing Integration Solutions to Meet Persistence Requirements: It addresses the usage of VM queues and connectors, object stores and services, and stateful components configured with object stores.
Thema 2
- Applying DevOps Practices and Operating Integration Solutions: Its sub-topics are related to designing CI
- CD pipelines with MuleSoft plugins, automating interactions with Anypoint Platform, designing logging configurations, and identifying Anypoint Monitoring features.
Thema 3
- Designing Integration Solutions to Meet Reliability Requirements: It includes selecting alternatives to traditional transactions, recognizing the purpose of various scopes and strategies, differentiating disaster recovery and high availability, and using local and XA transactions.
Thema 4
- Designing Architecture Using Integration Paradigms: This topic focuses on creating high-level integration architectures using various paradigms. It includes API-led connectivity, web APIs and HTTP, event-driven APIs, and message brokers, and designing Mule application using messaging patterns and technologies.
Thema 5
- Designing and Developing Mule Applications: It includes selecting application properties, using fundamental features, designing with core routers, understanding the Salesforce Connector, and leveraging core connectors.
Thema 6
- Initiating Integration Solutions on Anypoint Platform: Summarizing MuleSoft Catalyst and Catalyst Knowledge Hub, differentiating between functional and non-functional requirements, selecting features for designing and managing APIs, and choosing deployment options are its sub-topics.
Thema 7
- Designing for the Runtime Plane Technology Architecture: It includes analyzing Mule runtime clusters, designing solutions for CloudHub, choosing Mule runtime domains, leveraging Mule 4 class loader isolation, and understanding the reactive event processing model.
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MuleSoft-Integration-Architect-I Simulationsfragen & MuleSoft-Integration-Architect-I Prüfung
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Salesforce Certified MuleSoft Integration Architect I MuleSoft-Integration-Architect-I Prüfungsfragen mit Lösungen (Q24-Q29):
24. Frage
A Mule application is being designed To receive nightly a CSV file containing millions of records from an external vendor over SFTP, The records from the file need to be validated, transformed. And then written to a database. Records can be inserted into the database in any order.
In this use case, what combination of Mule components provides the most effective and performant way to write these records to the database?
- A. Use a DataWeave map operation and an Async scope to insert records one by one into the database.
- B. Use a Parallel for Each scope to Insert records one by one into the database
- C. Use a Batch job scope to bulk insert records into the database.
- D. Use a Scatter-Gather to bulk insert records into the database
Antwort: C
Begründung:
Correct answer is Use a Batch job scope to bulk insert records into the database
* Batch Job is most efficient way to manage millions of records.
A few points to note here are as follows :
Reliability: If you want reliabilty while processing the records, i.e should the processing survive a runtime crash or other unhappy scenarios, and when restarted process all the remaining records, if yes then go for batch as it uses persistent queues.
Error Handling: In Parallel for each an error in a particular route will stop processing the remaining records in that route and in such case you'd need to handle it using on error continue, batch process does not stop during such error instead you can have a step for failures and have a dedicated handling in it.
Memory footprint: Since question said that there are millions of records to process, parallel for each will aggregate all the processed records at the end and can possibly cause Out Of Memory.
Batch job instead provides a BatchResult in the on complete phase where you can get the count of failures and success. For huge file processing if order is not a concern definitely go ahead with Batch Job
25. Frage
Refer to the exhibit.
One of the backend systems invoked by an API implementation enforces rate limits on the number of requests a particular client can make. Both the backend system and the API implementation are deployed to several non-production environments in addition to production.
Rate limiting of the backend system applies to all non-production environments. The production environment, however, does NOT have any rate limiting.
What is the most effective approach to conduct performance tests of the API implementation in a staging (non- production) environment?
- A. Use MUnit to simulate standard responses from the backend system then conduct performance tests to identify other bottlenecks in the system
- B. Include logic within the API implementation that bypasses invocations of the backend system in a performance test situation. Instead invoking local stubs that replicate typical backend system responses then conduct performance tests using this API Implementation
- C. Create a mocking service that replicates the backend system's production performance characteristics.
Then configure the API implementation to use the mocking service and conduct the performance tests - D. Conduct scaled-down performance tests in the staging environment against the rate limited backend system then upscale performance results to full production scale
Antwort: C
Begründung:
Correct answer is Create a mocking service that replicates the backend system's production performance characteristics. Then configure the API implementation to use the mocking service and conduct the performance tests
* MUnit is for only Unit and integration testing for APIs and Mule apps. Not for performance Testing, even if it has the ability to Mock the backend.
* Bypassing the backend invocation defeats the whole purpose of performance testing. Hence it is not a valid answer.
* Scaled down performance tests cant be relied upon as performance of API's is not linear against load.
26. Frage
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 invocation of the fallback API provides the best resilience?
- A. 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 received from Order API
- B. 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
- C. Redirect client requests through an HTTP 303 temporary redirect status code to the fallback API whenever the Order API is unavailable
- D. Search Anypoint Exchange for a suitable existing fallback API and them implement invocations to their fallback API in addition to the Order API
Antwort: C
Begründung:
* Resilience testing is a type of software testing that observes how applications act under stress. It's meant to ensure the product's ability to perform in chaotic conditions without a loss of core functions or data; it ensures a quick recovery after unforeseen, uncontrollable events.
* In case an API invocation fails - even after a certain number of retries - it might be adequate to invoke a different API as a fallback. A fallback API, by definition, will never be ideal for the purpose of the API client, otherwise it would be the primary API.
* Here are some examples for fallback APIs:
- An old, deprecated version of the same API.
- An alternative endpoint of the same API and version (e.g. API in another CloudHub region).
- An API doing more than required, and therefore not as performant as the primary API.
- An API doing less than required and therefore forcing the API Client to offer a degraded service, which is still better than no service at all.
* API clients implemented as Mule applications offer the 'Until Successful Scope and Exception' strategies at their disposal, which together allow configuring fallback actions such as a fallback API invocation.
* All HTTP response status codes within the 3xx category are considered redirection messages. These codes indicate to the user agent (i.e. your web browser) that an additional action is required in order to complete the request and access the desired resource Hence correct answer is Redirect client requests through an HTTP 303 temporary redirect status code to the fallback API whenever the Order API is unavailable
27. Frage
A team has completed the build and test activities for a Mule application that implements a System API for its application network.
Which Anypoint Platform component should the team now use to both deploy and monitor the System AP implementation?
- A. Design Center
- B. Anypoint Exchange
- C. API Manager
- D. Runtime Manager
Antwort: D
Begründung:
After completing the build and test activities for a Mule application that implements a System API, the team should use Runtime Manager to both deploy and monitor the System API implementation. Runtime Manager is a component of Anypoint Platform that provides capabilities for deploying, managing, and monitoring Mule applications and APIs. It allows teams to manage applications and APIs across various environments, ensuring they operate correctly and efficiently.
References:
* Anypoint Runtime Manager
* Deploying and Managing Applications with Runtime Manager
28. Frage
What operation can be performed through a JMX agent enabled in a Mule application?
- A. Replay an unsuccessful message
- B. Deploy a Mule application
- C. Set a particular tog4J2 log level to TRACE
- D. View object store entries
Antwort: D
Begründung:
JMX Management Java Management Extensions (JMX) is a simple and standard way to manage applications, devices, services, and other resources. JMX is dynamic, so you can use it to monitor and manage resources as they are created, installed, and implemented. You can also use JMX to monitor and manage the Java Virtual Machine (JVM). Each resource is instrumented by one or more Managed Beans, or MBeans. All MBeans are registered in an MBean Server. The JMX server agent consists of an MBean Server and a set of services for handling Mbeans. There are several agents provided with Mule for JMX support. The easiest way to configure JMX is to use the default JMX support agent. Log4J Agent The log4j agent exposes the configuration of the Log4J instance used by Mule for JMX management. You enable the Log4J agent using the <jmx-log4j> element. It does not take any additional properties MuleSoft Reference: https://docs.mulesoft.com/mule-runtime/3.9/jmx-management
29. Frage
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