MuleSoft MCPA-Level-1 - MuleSoft Certified Platform Architect - Level 1

Explanation

Correct Answer: The number of API specifications in RAML or OAS format published to Anypoint Exchange

*****************************************

>> The success of C4E always depends on their contribution to the number of reusable assets that they have helped to build and publish to Anypoint Exchange.

>> It is NOT due to any factors w.r.t # of outages, Manual vs CI/CD deployments or Publicly accessible HTTP endpoints

>> Anypoint Platform APIs helps us to quickly run and get the number of published RAML/OAS assets to Anypoint Exchange. This clearly depicts how successful a C4E team is based on number of returned assets in the response.

Explanation

Correct Answer: Guarding against Denial of Service attacks

*****************************************

>> Backend system overloading can be handled by enforcing "Spike Control Policy"

>> Logging HTTP requests and responses can be done by enforcing "Message Logging Policy"

>> Credentials can be tamper-proofed using "Security" and "Compliance" Policies

However, unfortunately, there is no proper way currently on Anypoint Platform to guard against DOS attacks.

Explanation

Correct Answer: The credentials provided by the IdP for identity management

*****************************************

Explanation

Correct Answer: Create reusable assets, Make them discoverable so that LOB teams can self-serve and browse the APIs, Get active feedback and usage metrics.

*****************************************

Diagram, arrow Description automatically generated

Scenario Analysis:

The eCommerce company’s Product Details feature requires low response time and consistent data for a feature where data rarely changes (only once or twice a year).

The database response time is slow due to high volume, so querying the database directly on each request would lead to poor performance and higher response times.

Optimal Solution Requirements:

Low Response Time: Data retrieval should be fast and not depend on database performance.

Fault Tolerance and Data Consistency: Cached or stored data should be consistent and resilient in case of database unavailability, as the product details data changes infrequently.

Evaluating the Options:

Option A: Using a Cache scope would temporarily store the product details in memory, which could improve performance but might not be suitable for infrequent updates (only twice a year), as cache expiration policies typically require shorter durations.

Option B: Storing product details in Anypoint MQ and then retrieving it through a subscriber is not suitable for this use case. Anypoint MQ is better for messaging rather than as a data storage mechanism.

Option C (Correct Answer): Using an object store to store and retrieve product details is ideal. Object stores in MuleSoft are designed for persistent storage of key-value pairs, which allows storing data retrieved from the database initially. This provides quick, consistent access without querying the database on every request, aligning with requirements for low response time, fault tolerance, and data consistency.

Option D: Selecting data directly from the database for each request would not meet the performance requirement due to known slow response times from the database.

Conclusion:

Option C is the best answer, as using an object store allows caching the infrequently updated product details. This approach reduces the dependency on the database, significantly improving response time and ensuring consistent data.

Refer to MuleSoft documentation on Object Store v2 and best practices for data caching to implement this solution effectively.

Explanation

Correct Answer: A Non-Mule application

*****************************************

>> All type of Mule applications (Mule 3/ Mule 4/ with APIkit/ with Custom Java Code etc) running on Mule Runtimes support the Embedded Policy Enforcement on them.

>> The only option that cannot have or does not support embedded policy enforcement and must have API Proxy is for Non-Mule Applications.

So, Non-Mule application is the right answer.

Monitoring On-Premise Mule Applications:

For Mule applications deployed on an on-premises cluster, monitoring detailed performance metrics requires communication with the MuleSoft-hosted control plane. The control plane, when used with on-premises runtimes, relies on Anypoint Monitoring and requires a Monitoring Agent to gather and send detailed performance metrics.

Setting Up Monitoring:

To enable detailed metrics, the Monitoring Agent must be installed on each node in the cluster where Mule applications are deployed. This agent collects data on memory usage, CPU load, response times, and other metrics, and sends it to the control plane for aggregation and visualization.

Evaluating the Options:

Option A: Updating settings in the control plane alone does not enable detailed monitoring; the agent must be installed on each node to capture detailed metrics.

Option B (Correct Answer): Installing the Monitoring Agent on each node ensures that each runtime node in the cluster can send its metrics to the control plane, enabling detailed monitoring.

Option C: Installing the agent on a separate server would not be effective, as each node in the cluster needs to independently report its metrics to ensure full visibility.

Option D: The on-prem runtime does not automatically send detailed metrics to the control plane without the Monitoring Agent installed.

Conclusion:

Option B is the correct answer, as installing the Monitoring Agent on each node is essential for detailed performance monitoring of on-prem applications in a cluster.

Refer to MuleSoft’s documentation on configuring Anypoint Monitoring for on-premises deployments and using the Monitoring Agent.

Explanation

Correct Answer: Ask the Marketing Department to interact with a mocking implementation of the API using the automatically generated API Console.

*****************************************

As per MuleSoft's IT Operating Model:

>> API consumers need NOT wait until the full API implementation is ready.

>> NO technical test-suites needs to be shared with end users to interact with APIs.

>> Anypoint Platform offers a mocking capability on all the published API specifications to Anypoint Exchange which also will be rich in documentation covering all details of API functionalities and working nature.

>> No needs of arranging days of workshops with end users for feedback.

API consumers can use Anypoint Exchange features on the platform and interact with the API using its mocking feature. The feedback can be shared quickly on the same to incorporate any changes.

Processing Requirements and Storage Mechanism:

The Reservation Mule application will be deployed to multiple CloudHub workers/replicas, meaning that each worker must share state information to handle records exactly once. This requires a shared storage mechanism where state can be stored and accessed by multiple instances to avoid duplicate processing of the same records.

A Persistent Object Store in Anypoint Platform can be used to store records in a way that is accessible across multiple workers, providing a reliable mechanism for "exactly once" processing.

Evaluating the Options:

Option A (Correct Answer): A Persistent Object Store is designed to retain data across different application instances and can be shared by all workers on CloudHub. It helps achieve idempotency by ensuring that a record is processed exactly once.

Option B: Runtime Fabric Object Store is used for applications deployed in Anypoint Runtime Fabric, not CloudHub. This option would not be compatible with the CloudHub deployment.

Option C: A Non-persistent Object Store does not retain data across application restarts or different instances, making it unsuitable for the requirement of synchronized storage for exactly-once processing.

Option D: An In-memory Mule Object Store is local to each worker and is not shared across instances, so it does not meet the requirement for a shared storage mechanism accessible to all CloudHub workers.

Conclusion:

Option A is the correct answer, as a Persistent Object Store allows data sharing across multiple CloudHub workers, enabling them to synchronize and achieve "exactly once" processing of passenger records with minimal development effort.

Refer to MuleSoft’s documentation on Object Store configurations and usage for best practices on handling state across distributed instances.

When an API implementation is deployed on CloudHub without configuring automatic restarts in case of worker non-responsiveness, MuleSoft’s monitoring and alerting behavior is as follows:

API Invocation Alerts:

If no clients are invoking the API, there will be no invocation alerts triggered, as alerts related to invocations depend on actual client requests.

Implementation-Level Alerts:

Even without invocation, CloudHub can still monitor the state of the API implementation. If the worker becomes unresponsive, an alert related to the API implementation's health or availability could still be raised.

Why Option C is Correct:

This option correctly identifies that no invocation-related alerts would be triggered in the absence of client requests, while implementation-level alerts could still be generated based on the worker's state.

ReferencesFor additional information, check MuleSoft documentation on CloudHub monitoring and alert configurations to understand worker status alerts versus invocation alerts​.