Real Salesforce Certified MuleSoft Integration Architect I Test Questions - MuleSoft-Integration-Architect-I Actual Torrent & Salesforce Certified MuleSoft Integration Architect I Pdf Questions

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Salesforce MuleSoft-Integration-Architect-I Exam Syllabus Topics:

Topic	Details
Topic 1	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.
Topic 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.
Topic 3	Designing Integration Solutions to Meet Security Requirements: This topic emphasizes securing access to the Anypoint Platform and APIs, using Anypoint Security, counteracting security vulnerabilities, and understanding audit logging capabilities.
Topic 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.
Topic 5	Designing Integration Solutions to Meet Performance Requirements: This topic covers meeting performance and capacity goals, using streaming features, and processing large message sequences.
Topic 6	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.
Topic 7	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.

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Salesforce Certified MuleSoft Integration Architect I Sample Questions (Q63-Q68):

NEW QUESTION # 63
Refer to the exhibit.

An organization uses a 2-node Mute runtime cluster to host one stateless API implementation. The API is accessed over HTTPS through a load balancer that uses round-robin for load distribution.
Two additional nodes have been added to the cluster and the load balancer has been configured to recognize the new nodes with no other change to the load balancer.
What average performance change is guaranteed to happen, assuming all cluster nodes are fully operational?

A. 100% increase in the throughput of the API
B. 50% reduction In the JVM heap memory consumed by each node
C. 50% reduction in the response time of the API
D. 50% reduction In the number of requests being received by each node

Answer: D

NEW QUESTION # 64
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 Permanently to inform API clients they should be calling the new API implementation
B. Postpone changes until API consumers acknowledge they are ready to migrate to a new Process API or API version
C. Implement required changes to the Process API implementation so that whenever possible, the Process API's RAML definition remains unchanged
D. Update the RAML definition of the current Process API and notify API client developers by sending them links to the updated RAML definition

Answer: C

Explanation:
* Option B shouldn't be used unless extremely needed, if RAML is changed, client needs to accommodate changes. Question is about minimizing impact on Client. So this is not a valid choice.
* Option C isn't valid as Business can't stop for consumers acknowledgment.
* Option D again needs Client to accommodate changes and isn't viable option.
* Best choice is A where RAML definition isn't changed and underlined functionality is changed without any dependency on client and without impacting client.

NEW QUESTION # 65
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. Do not set a timeout; the Invocation of this API Is mandatory and so we must wait until it responds
B. Set a timeout of 100 ms; that leaves 400 ms for the other two downstream APIs to complete
C. Set a timeout of 50 ms; this times out more invocations of that API but gives additional room for retries
D. 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

Answer: D

Explanation:
Before we answer this question , we need to understand what median (50th percentile) and 80th percentile means. If the 50th percentile (median) of a response time is 500ms that means that 50% of my transactions are either as fast or faster than 500ms.
If the 90th percentile of the same transaction is at 1000ms it means that 90% are as fast or faster and only 10% are slower. Now as per upstream SLA , 99th percentile is 800 ms which means 99% of the incoming requests should have response time less than or equal to 800 ms. But as per one of the backend API , their 95th percentile is 1000 ms which means that backend API will take 1000 ms or less than that for 95% of. requests. As there are three API invocation from upstream API , we can not conclude a timeout that can be set to meet the desired SLA as backend SLA's do not support it.
Let see why other answers are not correct.
1) Do not set a timeout --> This can potentially violate SLA's of upstream API
2) Set a timeout of 100 ms; ---> This will not work as backend API has 100 ms as median meaning only 50% requests will be answered in this time and we will get timeout for 50% of the requests. Important thing to note here is, All APIs need to be executed sequentially, so if you get timeout in first API, there is no use of going to second and third API. As a service provider you wouldn't want to keep 50% of your consumers dissatisfied. So not the best option to go with.
*To quote an example: Let's assume you have built an API to update customer contact details.
- First API is fetching customer number based on login credentials
- Second API is fetching Info in 1 table and returning unique key
- Third API, using unique key provided in second API as primary key, updating remaining details
* Now consider, if API times out in first API and can't fetch customer number, in this case, it's useless to call API 2 and 3 and that is why question mentions specifically that all APIs need to be executed sequentially.
3) Set a timeout of 50 ms --> Again not possible due to the same reason as above Hence correct answer is 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

NEW QUESTION # 66
What aspect of logging is only possible for Mule applications deployed to customer-hosted Mule runtimes, but NOT for Mule applications deployed to CloudHub?

A. To directly reference one shared and customized log4j2.xml file from multiple Mule applications
B. To send Mule application log entries to Splunk
C. To log certain messages to a custom log category
D. To change tog4j2 tog levels in Anypoint Runtime Manager without having to restart the Mule application

Answer: A

Explanation:
* Correct answer is To directly reference one shared and customized log4j2.xml file from multiple Mule applications. Key word to note in the answer is directly.
* By default, CloudHub replaces a Mule application's log4j2.xml file with a CloudHub log4j2.xml file. This specifies the CloudHub appender to write logs to the CloudHub logging service.
* You cannot modify CloudHub log4j2.xml file to add any custom appender. But there is a process in order to achieve this. You need to raise a request on support portal to disable CloudHub provided Mule application log4j2 file.
Graphical user interface, application, Word Description automatically generated

* Once this is done , Mule application's log4j2.xml file is used which you can use to send/export application logs to other log4j2 appenders, such as a custom logging system MuleSoft does not own any responsibility for lost logging data due to misconfiguration of your own log4j appender if it happens by any chance.
Graphical user interface, text, application, email Description automatically generated

* One more difference between customer-hosted Mule runtimes and CloudHub deployed mule instance is that
- CloudHub system log messages cannot be sent to external log management system without installing custom CH logging configuration through support
- where as Customer-hosted runtime can send system and application log to external log management system MuleSoft Reference:
https://docs.mulesoft.com/runtime-manager/viewing-log-data
https://docs.mulesoft.com/runtime-manager/custom-log-appender

NEW QUESTION # 67
Refer to the exhibit.

A Mule application is being designed to be deployed to several CIoudHub workers. The Mule application's integration logic is to replicate changed Accounts from Satesforce to a backend system every 5 minutes.
A watermark will be used to only retrieve those Satesforce Accounts that have been modified since the last time the integration logic ran.
What is the most appropriate way to implement persistence for the watermark in order to support the required data replication integration logic?

A. Persistent Anypoint MQ Queue
B. Persistent VM Queue
C. Persistent Object Store
D. Persistent Cache Scope

Answer: C

Explanation:
* An object store is a facility for storing objects in or across Mule applications. Mule uses object stores to persist data for eventual retrieval.
* Mule provides two types of object stores:
1) In-memory store - stores objects in local Mule runtime memory. Objects are lost on shutdown of the Mule runtime.
2) Persistent store - Mule persists data when an object store is explicitly configured to be persistent.
In a standalone Mule runtime, Mule creates a default persistent store in the file system. If you do not specify an object store, the default persistent object store is used.
MuleSoft Reference: https://docs.mulesoft.com/mule-runtime/3.9/mule-object-stores

NEW QUESTION # 68
......

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Real Salesforce Certified MuleSoft Integration Architect I Test Questions - MuleSoft-Integration-Architect-I Actual Torrent & Salesforce Certified MuleSoft Integration Architect I Pdf Questions

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Salesforce Certified MuleSoft Integration Architect I Sample Questions (Q63-Q68):

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