MuleSoft-Platform-Architect-I Exam Dumps : Salesforce Certified MuleSoft Platform Architect (Mule-Arch-201)

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.

Explanation 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.

ReferencesFor more information on configuring Rate Limiting and SLA-based Spike Control policies, refer to MuleSoft documentation on API Policies and Rate Limiting​​.

In MuleSoft CloudHub, autoscaling is essential to managing application load efficiently. CloudHub supports horizontal scaling based on CPU usage, which is well-suited to applications experiencing variable demand and needing responsive resource allocation.

Autoscaling on CloudHub:

Horizontal scaling increases the number of workers in response to CPU usage thresholds, allowing the application to handle higher loads dynamically. This approach improves performance without downtime or manual intervention.

Why Option C is Correct:

Setting up autoscaling based on CPU usage aligns with MuleSoft’s best practices for scalable and responsive applications on CloudHub, particularly in an environment with fluctuating load patterns.

Option C correctly leverages CloudHub’s autoscaling features based on resource metrics, which are part of CloudHub’s managed scaling solutions.

Explanation of Incorrect Options:

Option A (based on HTTP request thresholds) and Option B (separate policies for CPU and memory) do not represent CloudHub’s recommended scaling practices.

Option D suggests vertical scaling based on response time, which is not how CloudHub handles autoscaling.

ReferencesFor more on CloudHub’s autoscaling configuration, refer to MuleSoft documentation on CloudHub autoscaling policies​.

Explanation

Correct Answer: Create API Notebooks and Include them in the relevant Anypoint exchange entries

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>> API Notebooks are the one on Anypoint Platform that enable us to provide code-centric API documentation

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