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

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: From the Mule runtime irrespective of the deployment model

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>> Monitoring and Alerting metrics are always originated from Mule Runtimes irrespective of the deployment model.

>> It may seems that some metrics (Runtime Manager) are originated from Mule Runtime and some are (API Invocations/ API Analytics) from API Manager. However, this is realistically NOT TRUE. The reason is, API manager is just a management tool for API instances but all policies upon applying on APIs eventually gets executed on Mule Runtimes only (Either Embedded or API Proxy).

>> Similarly all API Implementations also run on Mule Runtimes.

So, most of the day required for monitoring and alerts are originated fron Mule Runtimes only irrespective of whether the deployment model is MuleSoft-hosted or Customer-hosted or Hybrid.

Explanation

Correct Answer: Implement required changes to the Process API implementation so that, whenever possible, the Process API’s RAML definition remains unchanged.

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Key requirement in the question is:

>> Approach that minimizes the impact of this change on API clients

Based on above:

>> Updating the RAML definition would possibly impact the API clients if the changes require any thing mandatory from client side. So, one should try to avoid doing that until really necessary.

>> Implementing the changes as a completely different API and then redirectly the clients with 3xx status code is really upsetting design and heavily impacts the API clients.

>> Organisations and IT cannot simply postpone the changes required until all API consumers acknowledge they are ready to migrate to a new Process API or API version. This is unrealistic and not possible.

The best way to handle the changes always is to implement required changes to the API implementations so that, whenever possible, the API’s RAML definition remains unchanged.