Reliable Salesforce MuleSoft-Platform-Architect-I Real Test & Valid Test MuleSoft-Platform-Architect-I Experience

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

Topic	Details
Topic 1	Establishing Organizational and Platform Foundations: Advising on a Center for Enablement (C4E) and identifying KPIs, describing MuleSoft Catalyst's structure, comparing Identity and Client Management options, and identifying data residency types are essential sub-topics.
Topic 2	Governing Web APIs on Anypoint Platform: This topic includes sub-topics related to managing API instances and environments, selecting API policies, enforcing API policies, securing APIs, and understanding OAuth 2.0 relationships.
Topic 3	Designing APIs Using System, Process, and Experience Layers: Identifying suitable APIs for business processes, assigning them according to functional focus, and recommending data model approaches are its sub-topics.
Topic 4	Monitoring and Analyzing Application Networks: It discusses Anypoint Platform components for data generation, collected metrics, and key alerts. This topic also includes specifying alerts to define Mule applications.
Topic 5	Deploying API Implementations to CloudHub: Understanding Object Store usage, selecting worker sizes, predicting app reliability and performance, and comparing load balancers. Avoiding single points of failure in deployments is also its sub-topic.
Topic 6	Designing and Sharing APIs: Identifying dependencies between API components, creating and publishing reusable API assets, mapping API data models between Bounded Contexts, and recognizing idempotent HTTP methods.
Topic 7	Architecting and Deploying API Implementations: It covers important aspects like using auto-discovery, identifying VPC requirements, comparing hosting options and understanding testing methods. The topic also involves automated building, testing, and deploying in a DevOps setting.
Topic 8	Explaining Application Network Basics: This topic includes sub-topics related to identifying and differentiating between technologies for API-led connectivity, describing the role and characteristics of web APIs, assigning APIs to tiers, and understanding Anypoint Platform components.

Salesforce Certified MuleSoft Platform Architect I Sample Questions (Q149-Q154):

NEW QUESTION # 149
Version 3.0.1 of a REST API implementation represents time values in PST time using ISO 8601 hh:mm:ss format. The API implementation needs to be changed to instead represent time values in CEST time using ISO 8601 hh:mm:ss format. When following the semver.org semantic versioning specification, what version should be assigned to the updated API implementation?

A. 3.1.0
B. 3.0.1
C. 3.0.2
D. 4.0.0

Answer: D

Explanation:
Correct Answer : 4.0.0
*****************************************
As per semver.org semantic versioning specification:
Given a version number MAJOR.MINOR.PATCH, increment the:
- MAJOR version when you make incompatible API changes.
- MINOR version when you add functionality in a backwards compatible manner.
- PATCH version when you make backwards compatible bug fixes.
As per the scenario given in the question, the API implementation is completely changing its behavior. Although the format of the time is still being maintained as hh:mm:ss and there is no change in schema w.r.t format, the API will start functioning different after this change as the times are going to come completely different.
Example: Before the change, say, time is going as 09:00:00 representing the PST. Now on, after the change, the same time will go as 18:00:00 as Central European Summer Time is 9 hours ahead of Pacific Time.
>> This may lead to some uncertain behavior on API clients depending on how they are handling the times in the API response. All the API clients need to be informed that the API functionality is going to change and will return in CEST format. So, this considered as a MAJOR change and the version of API for this new change would be 4.0.0

NEW QUESTION # 150
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. Permanently increase the number of CloudHub workers by four times (4x) to eight (8) CloudHub workers
B. Permanently increase the size of each of the two (2) CloudHub workers by at least four times (4x) to one (1) vCore
C. Use a vertical CloudHub autoscaling policy that triggers on CPU utilization greater than 70%
D. Use a horizontal CloudHub autoscaling policy that triggers on CPU utilization greater than 70%

Answer: D

Explanation:
Correct Answer : Use a horizontal CloudHub autoscaling policy that triggers on CPU utilization greater than 70%
*****************************************
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 # 151
A retail company with thousands of stores has an API to receive data about purchases and insert it into a single database. Each individual store sends a batch of purchase data to the API about every 30 minutes. The API implementation uses a database bulk insert command to submit all the purchase data to a database using a custom JDBC driver provided by a data analytics solution provider. The API implementation is deployed to a single CloudHub worker. The JDBC driver processes the data into a set of several temporary disk files on the CloudHub worker, and then the data is sent to an analytics engine using a proprietary protocol. This process usually takes less than a few minutes. Sometimes a request fails. In this case, the logs show a message from the JDBC driver indicating an out-of-file-space message. When the request is resubmitted, it is successful. What is the best way to try to resolve this throughput issue?

A. Increase the number of CloudHub workers
B. Increase the size of the CloudHub worker(s)
C. se a CloudHub autoscaling policy to add CloudHub workers
D. Use a CloudHub autoscaling policy to increase the size of the CloudHub worker

Answer: A

Explanation:
Correct Answer : Increase the size of the CloudHub worker(s)
*****************************************
The key details that we can take out from the given scenario are:
>> API implementation uses a database bulk insert command to submit all the purchase data to a database
>> JDBC driver processes the data into a set of several temporary disk files on the CloudHub worker
>> Sometimes a request fails and the logs show a message indicating an out-of-file-space message Based on above details:
>> Both auto-scaling options does NOT help because we cannot set auto-scaling rules based on error messages. Auto-scaling rules are kicked-off based on CPU/Memory usages and not due to some given error or disk space issues.
>> Increasing the number of CloudHub workers also does NOT help here because the reason for the failure is not due to performance aspects w.r.t CPU or Memory. It is due to disk-space.
>> Moreover, the API is doing bulk insert to submit the received batch data. Which means, all data is handled by ONE worker only at a time. So, the disk space issue should be tackled on "per worker" basis. Having multiple workers does not help as the batch may still fail on any worker when disk is out of space on that particular worker.
Therefore, the right way to deal this issue and resolve this is to increase the vCore size of the worker so that a new worker with more disk space will be provisioned.

NEW QUESTION # 152
How are an API implementation, API client, and API consumer combined to invoke and process an API?

A. The API consumer creates an API implementation, which receives API invocations from an API such that they are processed for an API client
B. The ApI consumer creates an API client, which sends API invocations to an API such that they are processed by an API implementation
C. The API client creates an API consumer, which receives API invocations from an API such that they are processed for an API implementation
D. The ApI client creates an API consumer, which sends API invocations to an API such that they are processed by an API implementation

Answer: B

Explanation:
Correct Answer : The API consumer creates an API client, which sends API invocations to an API such that they are processed by an API implementation
*****************************************
Terminology:
>> API Client - It is a piece of code or program the is written to invoke an API
>> API Consumer - An owner/entity who owns the API Client. API Consumers write API clients.
>> API - The provider of the API functionality. Typically an API Instance on API Manager where they are managed and operated.
>> API Implementation - The actual piece of code written by API provider where the functionality of the API is implemented. Typically, these are Mule Applications running on Runtime Manager.

NEW QUESTION # 153
Refer to the exhibit.
What is a valid API in the sense of API-led connectivity and application networks?
A) Java RMI over TCP
B) Java RMI over TCP

C) CORBA over HOP
D) XML over UDP

A. Option B
B. Option D
C. Option A
D. Option C

Answer: B

Explanation:
Correct Answe r: XML over HTTP
*****************************************
>> API-led connectivity and Application Networks urge to have the APIs on HTTP based protocols for building most effective APIs and networks on top of them.
>> The HTTP based APIs allow the platform to apply various varities of policies to address many NFRs
>> The HTTP based APIs also allow to implement many standard and effective implementation patterns that adhere to HTTP based w3c rules.

Bottom of Form
Top of Form

NEW QUESTION # 154
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Reliable Salesforce MuleSoft-Platform-Architect-I Real Test & Valid Test MuleSoft-Platform-Architect-I Experience

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

Salesforce Certified MuleSoft Platform Architect I Sample Questions (Q149-Q154):

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