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[Hardware] Three Easy-to-Use and Compatible Formats of Dumpleader Salesforce Mule-Arch-201

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【Hardware】 Three Easy-to-Use and Compatible Formats of Dumpleader Salesforce Mule-Arch-201

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Salesforce Certified MuleSoft Platform Architect Sample Questions (Q115-Q120):NEW QUESTION # 115
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
Answer: D
Explanation:
Correct Answe r: 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.

NEW QUESTION # 116
A Rate Limiting policy is applied to an API implementation to protect the back-end system. Recently, there have been surges in demand that cause some API client POST requests to the API implementation to be rejected with policy-related errors, causing delays and complications to the API clients.
How should the API policies that are applied to the API implementation be changed to reduce the frequency of errors returned to API clients, while still protecting the back-end system?
  • A. Remove the Rate Limiting policy and add a Spike Control policy
  • B. Keep the Rate Limiting policy and add 9 Client ID Enforcement policy
  • C. Remove the Rate Limiting policy and add an HTTP Caching policy
  • D. Keep the Rate Limiting policy and add an SLA-based Spike Control policy
Answer: D
Explanation:
When managing high traffic to an API, especially with POST requests, it is crucial to ensure the API's policies both protect the back-end systems and provide a smooth client experience. Here's the approach to reducing errors:
Rate Limiting Policy: This policy enforces a limit on the number of requests within a defined time period. However, rate limiting alone may cause clients to hit limits during demand surges, leading to errors.
Adding an SLA-based Spike Control Policy:
Spike Control is designed to handle sudden increases in traffic by smoothing out bursts of requests, which is particularly useful during high-demand periods.
By configuring SLA-based Spike Control, you can define thresholds for specific client tiers. For instance, premium clients might have higher limits or more flexibility in traffic bursts than standard clients.
Why Option D is Correct:
Keeping the Rate Limiting policy continues to provide baseline protection for the back-end.
Adding the SLA-based Spike Control policy allows for differentiated control, where requests are queued or delayed during bursts rather than outright rejected. This approach significantly reduces error responses to clients while still controlling overall traffic.
of Incorrect Options:
Option A (adding Client ID Enforcement) would not reduce errors related to traffic surges.
Option B (HTTP Caching) is not applicable as caching is generally ineffective for non-idempotent requests like POST.
Option C (only Spike Control without Rate Limiting) may leave the back-end system vulnerable to sustained high traffic levels, reducing protection.
Reference
For more information on configuring Rate Limiting and SLA-based Spike Control policies, refer to MuleSoft documentation on API Policies and Rate Limiting.

NEW QUESTION # 117
An operations team is analyzing the effort needed to set up monitoring of their application network. They are looking at which API invocation metrics can be used to identify and predict trouble without having to write custom scripts or install additional analytics software or tools.
Which type of metrics can satisfy this goal of directly identifying and predicting failures?
  • A. The number and types of API policy violations per day
  • B. The ROI from each APT invocation
  • C. The number and types of past API invocations across the application network
  • D. The effectiveness of the application network based on the level of reuse
Answer: A
Explanation:
To monitor an application network and predict issues without custom scripts, policy violation metrics are critical. They provide insights into potential problems by tracking instances where API usage does not conform to defined policies. Here's why this approach is suitable:
Predictive Monitoring:
Tracking API policy violations (such as rate limits or spike controls being hit) can indicate surges in traffic or misuse, which may lead to throttling or service degradation if not addressed.
By monitoring these violations, teams can proactively adjust limits or optimize API handling to prevent actual failures.
No Custom Scripting Needed:
Policy violation metrics are available within MuleSoft's Anypoint Monitoring, meaning there's no need to implement custom solutions or external tools to gather and interpret this data.
of Incorrect Options:
Option B (effectiveness based on reuse) does not directly predict failures.
Option C (past invocation counts) offers historical usage data but does not inherently identify issues.
Option D (ROI from API invocation) is a business metric and does not provide technical insights for failure prediction.
Reference
For more details on leveraging policy violation metrics for proactive monitoring, refer to MuleSoft documentation on Anypoint Monitoring.

NEW QUESTION # 118
A Mule application exposes an HTTPS endpoint and is deployed to three CloudHub workers that do not use static IP addresses. The Mule application expects a high volume of client requests in short time periods. What is the most cost-effective infrastructure component that should be used to serve the high volume of client requests?
  • A. Runtime Manager autoscaling
  • B. A customer-hosted load balancer
  • C. The CloudHub shared load balancer
  • D. An API proxy
Answer: C
Explanation:
Correct Answe r: The CloudHub shared load balancer
*****************************************
The scenario in this question can be split as below:
>> There are 3 CloudHub workers (So, there are already good number of workers to handle high volume of requests)
>> The workers are not using static IP addresses (So, one CANNOT use customer load-balancing solutions without static IPs)
>> Looking for most cost-effective component to load balance the client requests among the workers.
Based on the above details given in the scenario:
>> Runtime autoscaling is NOT at all cost-effective as it incurs extra cost. Most over, there are already 3 workers running which is a good number.
>> We cannot go for a customer-hosted load balancer as it is also NOT most cost-effective (needs custom load balancer to maintain and licensing) and same time the Mule App is not having Static IP Addresses which limits from going with custom load balancing.
>> An API Proxy is irrelevant there as it has no role to play w.r.t handling high volumes or load balancing.
So, the only right option to go with and fits the purpose of scenario being most cost-effective is - using a CloudHub Shared Load Balancer.

NEW QUESTION # 119
An API client calls one method from an existing API implementation. The API implementation is later updated. What change to the API implementation would require the API client's invocation logic to also be updated?
  • A. When a child method is added to the method called by the API client
  • B. When a new required field is added to the method called by the API client
  • C. When a new method is added to the resource used by the API client
  • D. When the data type of the response is changed for the method called by the API client
Answer: B
Explanation:
Correct Answe r: When a new required field is added to the method called by the API client
*****************************************
>> Generally, the logic on API clients need to be updated when the API contract breaks.
>> When a new method or a child method is added to an API , the API client does not break as it can still continue to use its existing method. So these two options are out.
>> We are left for two more where "datatype of the response if changed" and "a new required field is added".
>> Changing the datatype of the response does break the API contract. However, the question is insisting on the "invocation" logic and not about the response handling logic. The API client can still invoke the API successfully and receive the response but the response will have a different datatype for some field.
>> Adding a new required field will break the API's invocation contract. When adding a new required field, the API contract breaks the RAML or API spec agreement that the API client/API consumer and API provider has between them. So this requires the API client invocation logic to also be updated.

NEW QUESTION # 120
......
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