Mulesoft MCPA - Level 1 Practice Test Questions, Exam Dumps

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MCPA - Level 1 Mulesoft Practice Test Questions and Exam Dumps

Question No 1:

What API policy would LEAST likely be applied to a Process API?

A. Custom circuit breaker
B. Client ID enforcement
C. Rate limiting
D. JSON threat protection

Answer: B

Explanation:

In API-led connectivity architecture, APIs are categorized into three types: System APIs, Process APIs, and Experience APIs. Each of these APIs serves a different role within the integration layer of an enterprise application network.

System APIs are designed to interact with underlying systems like databases, legacy systems, or third-party services.
Process APIs are used to implement business logic and transformations, coordinating data between system APIs and experience APIs.
Experience APIs are designed to handle the interaction with end users or external applications, presenting data in a consumable format.

Analysis of the API policies:

A. Custom circuit breaker: A circuit breaker is used to prevent failures from propagating through the system, especially when one of the dependencies of the API is down. This policy is typically applied in any API, including Process APIs, to ensure reliability. It can detect if a backend system is failing and stop requests from going to that system, hence improving the overall system's fault tolerance. This policy is applicable and often used for Process APIs.
B. Client ID enforcement: This policy is typically used to enforce security and authentication by ensuring that every request coming into the API is associated with a valid client ID. It is mostly used in Experience APIs because they are the ones interacting with external clients, such as mobile apps or web interfaces. Process APIs generally deal with backend logic and are less likely to interact with external clients directly, so they would least need client ID enforcement.
C. Rate limiting: Rate limiting is applied to manage how many requests an API can handle within a specified period. This is particularly relevant in Experience APIs to prevent abuse from external clients, but it can also be applied to Process APIs to protect them from overloading. This policy ensures that the backend services that the Process API is orchestrating don't become overwhelmed by too many requests.
D. JSON threat protection: This policy is used to prevent malicious attacks like JSON-based injections or denial-of-service (DoS) attacks that target the format of the data being passed in the request (typically in JSON format). This kind of policy is applicable to any API, including Process APIs, to ensure that the data being processed does not pose a security threat.

The policy that would least likely be applied to a Process API is B. Client ID enforcement because Process APIs typically do not directly interact with external clients and focus more on backend business logic and data orchestration. In contrast, Experience APIs are more likely to apply client ID enforcement as they handle the interactions with external clients.

Question No 2:

What is a key performance indicator (KPI) that measures the success of a typical C4E that is immediately apparent in responses from the Anypoint Platform APIs?

A The number of production outage incidents reported in the last 24 hours
B The number of API implementations that have a publicly accessible HTTP endpoint and are being managed by Anypoint Platform
C The fraction of API implementations deployed manually relative to those deployed using a CI/CD tool
D The number of API specifications in RAML or OAS format published to Anypoint Exchange

Correct Answer: C

Explanation:

A C4E (Center for Enablement) is typically responsible for establishing the tools, practices, and methodologies that enable development teams to work more efficiently and effectively. In the context of Anypoint Platform and its API management capabilities, the success of a C4E can be measured through various KPIs that reflect automation, deployment efficiency, and the maturity of development practices within the organization.

In this case, KPI C, which measures the fraction of API implementations deployed manually versus those deployed using CI/CD tools, is a key performance indicator that directly correlates with the success of a C4E. The transition to CI/CD pipelines and automated deployment is a critical indicator of a mature API management process. The more APIs are deployed automatically through CI/CD pipelines, the more successful the C4E is in enabling best practices, streamlining operations, and reducing human error. This is because CI/CD adoption ensures faster, more reliable, and repeatable deployment cycles, which is a cornerstone of modern software development, particularly in API management.

Now, let's look at why the other options are less relevant:

A (The number of production outage incidents reported in the last 24 hours): While outages are a critical metric for overall system health, they do not directly indicate the success of a C4E, particularly since outages can occur for reasons unrelated to the API management processes or the maturity of the C4E.
B (The number of API implementations that have a publicly accessible HTTP endpoint and are being managed by Anypoint Platform): While it is important to manage APIs through Anypoint Platform, this metric does not necessarily reflect success in enabling development teams or automating workflows. This focuses more on the accessibility and management of APIs rather than their deployment process.
D (The number of API specifications in RAML or OAS format published to Anypoint Exchange): This is a good indicator of the adoption of standards and API design practices, but it doesn't directly measure the operational success of a C4E or the impact of automated deployment pipelines.

In summary, C is the best answer because it directly measures the degree of automation in API deployment, which is a key success factor for a C4E focused on scalable, repeatable processes. Hence, the correct answer is C.

Question No 3:

An organization is implementing a Quote of the Day API that caches today's quote. What scenario can use the CloudHub Object Store via the Object Store connector to persist the cache's state?

A. When there are three CloudHub deployments of the API implementation to three separate CloudHub regions that must share the cache state.
B. When there are two CloudHub deployments of the API implementation by two Anypoint Platform business groups to the same CloudHub region that must share the cache state.
C. When there is one deployment of the API implementation to CloudHub and another deployment to a customer-hosted Mule runtime that must share the cache state.
D. When there is one CloudHub deployment of the API implementation to three CloudHub workers that must share the cache state.

Answer: A

Explanation:

In this scenario, the CloudHub Object Store is being used to persist the cache state of a Quote of the Day API. The key point here is that the cache state (in this case, today's quote) must be shared across different CloudHub deployments. The CloudHub Object Store is designed to provide a persistent, shared storage mechanism for cloud-based applications, including the ability to share state across deployments.

Let’s break down each scenario:

A. When there are three CloudHub deployments of the API implementation to three separate CloudHub regions that must share the cache state:

Correct answer. When the deployments are spread across multiple regions, the Object Store is a perfect solution for sharing state between these separate deployments. CloudHub Object Store provides a global, shared cache, meaning that different deployments in different regions can access the same state in the object store.
This allows for a consistent cache across different regions, ensuring that each API deployment can retrieve and persist the quote state, no matter where it is deployed globally.

B. When there are two CloudHub deployments of the API implementation by two Anypoint Platform business groups to the same CloudHub region that must share the cache state:

While the CloudHub Object Store can still be used here, the key aspect of sharing state between different business groups is not a primary reason to use the Object Store. If the deployments are within the same region, CloudHub already provides mechanisms for communication, and this might be simpler to implement without the use of Object Store.
Therefore, this is a possible use case, but it's not as crucial as the multi-region scenario in A.

C. When there is one deployment of the API implementation to CloudHub and another deployment to a customer-hosted Mule runtime that must share the cache state:

This scenario involves a hybrid deployment where one part of the application is running on CloudHub and the other part is on a customer-hosted Mule runtime. While CloudHub Object Store can persist data, it is not directly shared with customer-hosted environments without additional configuration, such as network access or cloud-hosted integration. Typically, this setup would require more complex hybrid integration options like CloudHub VPN or API Gateway for inter-environment communication.
Hence, this scenario would not be ideal for the Object Store alone.

D. When there is one CloudHub deployment of the API implementation to three CloudHub workers that must share the cache state:

This scenario involves a single CloudHub deployment with multiple workers. The workers within a single deployment can share the same Object Store state naturally, without needing to access the cache in the cloud via separate deployments or regions.
Although this scenario can use the Object Store, the need for sharing the cache across multiple workers within the same deployment is less compelling compared to the multi-region scenario in A.

The most compelling use case for the CloudHub Object Store to persist the cache's state and share it across deployments is when the deployments are in multiple CloudHub regions, as described in option A. The Object Store offers a global cache, which is perfect for sharing data across regions. Therefore, A is the correct answer.

Question No 4:

What condition requires using a CloudHub Dedicated Load Balancer?

A. When cross-region load balancing is required between separate deployments of the same Mule application
B. When custom DNS names are required for API implementations deployed to customer-hosted Mule runtimes
C. When API invocations across multiple CloudHub workers must be load balanced
D. When server-side load-balanced TLS mutual authentication is required between API implementations and API clients

Answer: D

Explanation:

A CloudHub Dedicated Load Balancer is a specialized tool designed to address specific requirements for load balancing in MuleSoft's CloudHub environment. It is particularly useful for applications that need high availability, scalability, and secure communication between various services and clients.

Step 1: Understand the Role of the Dedicated Load Balancer

CloudHub's Dedicated Load Balancer is used primarily for situations where enhanced load balancing functionality is needed, especially for traffic routing and security-related requirements. Unlike standard load balancing, which distributes traffic across CloudHub workers, the dedicated version is geared toward specialized, enterprise-level use cases, such as handling TLS mutual authentication and specific routing needs between different Mule applications deployed in separate regions or environments.

Step 2: Review the Options

A. When cross-region load balancing is required between separate deployments of the same Mule application: This option refers to the need to distribute traffic across different regions for the same application. While this may sound relevant, CloudHub provides solutions such as Anypoint Virtual Private Cloud (VPC) or other load balancing strategies that may not require a Dedicated Load Balancer specifically. Cross-region functionality does not always necessitate a dedicated load balancer, but rather different configurations to handle multi-region deployment.
B. When custom DNS names are required for API implementations deployed to customer-hosted Mule runtimes: This scenario describes a need for custom DNS names, which is typically handled through API Gateway configurations and DNS management, not necessarily through a dedicated load balancer.
C. When API invocations across multiple CloudHub workers must be load balanced: This scenario is a common use case for standard CloudHub load balancing, which automatically balances API invocations across multiple workers. The need for a Dedicated Load Balancer would not be required here because CloudHub already provides internal load balancing for its workers.
D. When server-side load-balanced TLS mutual authentication is required between API implementations and API clients: This is the correct use case for a CloudHub Dedicated Load Balancer. When TLS mutual authentication is needed, where both the API client and the API server authenticate each other using certificates, a dedicated load balancer ensures secure, server-side load balancing. This guarantees that the load balancing respects the mutual authentication mechanism and ensures the security of communications.

The correct answer is D because a CloudHub Dedicated Load Balancer is specifically required when server-side load-balanced TLS mutual authentication is necessary between API implementations and API clients. This specialized configuration is crucial for enterprises that require secure and compliant API communication.

Question No 5:

What do the API invocation metrics provided by Anypoint Platform provide?

A. ROI metrics from APIs that can be directly shared with business users
B. Measurements of the effectiveness of the application network based on the level of reuse
C. Data on past API invocations to help identify anomalies and usage patterns across various APIs
D. Proactive identification of likely future policy violations that exceed a given threat threshold

Answer: C

Explanation:

The API invocation metrics provided by Anypoint Platform are designed to help organizations track the usage of APIs and gain valuable insights into how APIs are being used. These metrics offer various types of data to assess API performance, detect anomalies, and understand patterns, which ultimately help improve the management and optimization of APIs. Let's break down the options:

A. ROI metrics from APIs that can be directly shared with business users: While Anypoint Platform does provide metrics to evaluate API performance, ROI (Return on Investment) is generally a broader business metric that goes beyond just invocation counts or usage data. The platform focuses more on technical aspects of API performance rather than business-oriented ROI directly. Therefore, this is not the primary focus of API invocation metrics.
B. Measurements of the effectiveness of the application network based on the level of reuse: API invocation metrics focus more on usage and performance data, rather than measuring the overall effectiveness of the application network. While reuse of APIs might be a factor analyzed in certain reports, it is not the primary focus of invocation metrics, which are more concerned with direct usage statistics and patterns.
C. Data on past API invocations to help identify anomalies and usage patterns across various APIs: This is the correct answer. The primary function of API invocation metrics in Anypoint Platform is to provide data on past invocations (i.e., historical usage). These metrics help identify anomalies (e.g., spikes in traffic or unusual patterns) and usage trends across APIs. This data is essential for debugging, optimizing performance, and making data-driven decisions about API usage.
D. Proactive identification of likely future policy violations that exceed a given threat threshold: While policy violations and security issues are important, API invocation metrics are typically more focused on monitoring usage and performance rather than proactively predicting future policy violations. Security and policy violations might be tracked separately through other security tools or configurations within Anypoint Platform.

In conclusion, the correct answer is C because the API invocation metrics are primarily focused on providing historical data about past API calls to detect anomalies and identify usage patterns, which aids in troubleshooting and improving API performance.

Question No 6:

What is true about the technology architecture of Anypoint VPCs?

A. The private IP address range of an Anypoint VPC is automatically chosen by CloudHub.
B. Traffic between Mule applications deployed to an Anypoint VPC and on-premises systems can stay within a private network.
C. Each CloudHub environment requires a separate Anypoint VPC.
D. VPC peering can be used to link the underlying AWS VPC to an on-premises (non-AWS) private network.

Correct Answer: B

Explanation:

Anypoint VPCs (Virtual Private Clouds) are designed to provide an isolated network environment for Mule applications deployed on CloudHub. They allow for the customization of networking configurations and the management of traffic flow. Let’s break down each option:

Option A: The private IP address range of an Anypoint VPC is automatically chosen by CloudHub.

This statement is incorrect. While CloudHub does manage many aspects of the Anypoint VPC, the private IP address range for an Anypoint VPC is typically defined by the user, not automatically chosen by CloudHub. The user can specify an IP range when setting up the VPC.

Option B: Traffic between Mule applications deployed to an Anypoint VPC and on-premises systems can stay within a private network.

This statement is true. One of the key benefits of using Anypoint VPCs is the ability to create private, secure connections to on-premises systems. Traffic between Mule applications deployed within the VPC and on-premises systems can be kept within the private network using VPN or Direct Connect, ensuring security and privacy.

Option C: Each CloudHub environment requires a separate Anypoint VPC.

This statement is incorrect. CloudHub environments do not require a separate Anypoint VPC for each environment. A single VPC can host multiple environments, depending on how the network and security requirements are designed.

Option D: VPC peering can be used to link the underlying AWS VPC to an on-premises (non-AWS) private network.

This statement is incorrect. While VPC peering can be used to link different VPCs (e.g., between Anypoint VPC and AWS VPCs), it cannot directly link the AWS VPC to a non-AWS (on-premises) network. Instead, to link a non-AWS network to a VPC, you would typically use a VPN connection or Direct Connect, not VPC peering.

The correct answer is B, as it accurately describes how traffic between Mule applications in an Anypoint VPC and on-premises systems can stay within a private network, ensuring security and privacy.

Question No 7:

An API implementation is deployed on a single worker on CloudHub and invoked by external API clients (outside of CloudHub).

How can an alert be set up that is guaranteed to trigger AS SOON AS that API implementation stops responding to API invocations?

A. Implement a heartbeat/health check within the API and invoke it from outside the Anypoint Platform and alert when the heartbeat does not respond.
B. Configure a "worker not responding" alert in Anypoint Runtime Manager.
C. Handle API invocation exceptions within the calling API client and raise an alert from that API client when the API is unavailable.
D. Create an alert for when the API receives no requests within a specified time period.

Answer: B

Explanation:

In this scenario, the goal is to create an alert that triggers immediately when the API implementation stops responding to API invocations. Let's evaluate the options:

A. Implement a heartbeat/health check within the API and invoke it from outside the Anypoint Platform and alert when the heartbeat does not respond: While implementing a heartbeat or health check can be useful for monitoring the API’s status, it would require an external system to frequently check the health status of the API. This method does not guarantee an immediate alert when the API stops responding to actual invocations. Additionally, external health checks may have a delay, and the alert would depend on the frequency of the checks.
B. Configure a "worker not responding" alert in Anypoint Runtime Manager: Anypoint Runtime Manager provides native capabilities for monitoring and alerting on the status of CloudHub workers. By configuring a "worker not responding" alert, you can ensure that an alert is triggered immediately if the worker (or instance) becomes unresponsive. This approach directly monitors the worker itself and is guaranteed to trigger an alert as soon as the worker stops responding to invocations, making it the most appropriate choice.
C. Handle API invocation exceptions within the calling API client and raise an alert from that API client when the API is unavailable: While this approach can detect when the API is unavailable, it relies on the API client (external to the CloudHub infrastructure) to detect issues and raise alerts. This method is dependent on the client’s behavior and would not provide an immediate, centralized alert on CloudHub.
D. Create an alert for when the API receives no requests within a specified time period: This option could trigger an alert if the API isn’t receiving traffic, but it doesn’t directly monitor the responsiveness of the API. The alert would depend on the time period specified and the lack of requests, which may not correlate directly to the API becoming unresponsive (e.g., low traffic periods could trigger the alert even if the API is responsive).

Given these considerations, B, configuring a "worker not responding" alert in Anypoint Runtime Manager, is the best option. It directly monitors the worker’s responsiveness to invocations and guarantees an immediate alert when the API implementation stops responding.

Question No 8:

The implementation of a Process API must change. What is a valid approach that minimizes the impact of this change on API clients?

A. Update the RAML definition of the current Process API and notify API client developers by sending them links to the updated RAML definition.
B. Postpone changes until API consumers acknowledge they are ready to migrate to a new Process API or API version.
C. Implement required changes to the Process API implementation so that, whenever possible, the Process API's RAML definition remains unchanged.
D. Implement the Process API changes in a new API implementation, and have the old API implementation return an HTTP status code 301 - Moved Permanently to inform API clients they should be calling the new API implementation.

Answer: C

Explanation:

When updating an API, especially a Process API, the primary goal is to minimize disruptions to existing clients and ensure backward compatibility as much as possible. There are a few strategies to handle such a change, but the ideal solution ensures that clients can continue using the API without immediate changes on their end.

Let’s break down each option:

A. Update the RAML definition of the current Process API and notify API client developers by sending them links to the updated RAML definition.
This option suggests changing the RAML definition and notifying clients about the updates. However, simply updating the RAML and notifying clients does not address the potential compatibility issues that could arise from changes in the API’s behavior or structure. This option doesn’t necessarily minimize the impact on API clients, as it assumes that clients will need to adapt to the changes.
B. Postpone changes until API consumers acknowledge they are ready to migrate to a new Process API or API version.
While this might sound like a safe approach, it’s generally not optimal. Delaying changes until all consumers acknowledge readiness can create bottlenecks and unnecessary delays in the development cycle. It’s also not scalable for large systems where many clients may rely on the API. API evolution should ideally be managed in such a way that backward compatibility is maintained without needing explicit acknowledgment from all consumers.
C. Implement required changes to the Process API implementation so that, whenever possible, the Process API's RAML definition remains unchanged.
This is the best approach. By making sure that the RAML definition remains unchanged, the API's contract with clients stays the same. This means that clients continue to use the same API interface without needing to update their code or integration. The underlying implementation can change as needed, but as long as the external interface (the contract) remains consistent, clients won’t be impacted. This is a classic approach in API versioning and backward compatibility, where changes are made to the backend but do not break the API contract.
D. Implement the Process API changes in a new API implementation, and have the old API implementation return an HTTP status code 301 - Moved Permanently to inform API clients they should be calling the new API implementation.
While this approach might work in some cases, it has a significant drawback: it forces clients to migrate to the new API version immediately. The 301 status code is typically used for redirecting clients to a new resource, but this doesn’t guarantee a smooth transition. Clients would need to adjust their integration to accommodate the new implementation. This is more disruptive than the previous option, as it forces clients to migrate without necessarily preserving backward compatibility.

The most effective approach is to keep the existing API’s RAML definition unchanged, ensuring that the changes are only reflected in the underlying implementation, where possible. This minimizes the impact on clients and allows them to continue using the API without disruption.

Thus, the correct answer is C.

Question No 9:

A developer is building a client application to invoke an API deployed to the STAGING environment that is governed by a client ID enforcement policy. What is required to successfully invoke the API?

A. The client ID and secret for the Anypoint Platform account owning the API in the STAGING environment
B. The client ID and secret for the Anypoint Platform account's STAGING environment
C. The client ID and secret obtained from Anypoint Exchange for the API instance in the STAGING environment
D. A valid OAuth token obtained from Anypoint Platform and its associated client ID and secret

Answer: D

Explanation:

When invoking an API that is governed by a client ID enforcement policy, the API enforces specific authentication and authorization measures to control access. Typically, this policy requires the client ID and client secret, along with an authentication mechanism like OAuth, to ensure that only authorized clients can access the API.

Option A (The client ID and secret for the Anypoint Platform account owning the API in the STAGING environment) is not the correct answer because it is not common practice to use the platform account's client ID and secret directly to invoke APIs in the staging environment. Typically, client ID enforcement focuses on managing access for applications or clients rather than platform account credentials.
Option B (The client ID and secret for the Anypoint Platform account's STAGING environment) is also incorrect because while this might provide access to certain platform features, it does not specifically satisfy the client ID enforcement policy for invoking an API in the staging environment. It does not address the application's authorization for API access.
Option C (The client ID and secret obtained from Anypoint Exchange for the API instance in the STAGING environment) is not entirely correct. While you might find details related to API definitions in Anypoint Exchange, obtaining a client ID and secret for an API typically requires going through a proper application registration process in Anypoint Platform (rather than directly from Anypoint Exchange).
Option D (A valid OAuth token obtained from Anypoint Platform and its associated client ID and secret) is the correct answer. When using client ID enforcement policies, an application must authenticate itself using an OAuth token. The client ID and secret are used to obtain the OAuth token, which is then used to authenticate API calls. This is the standard approach for securing API access in environments such as STAGING, where the application is authenticated through OAuth before interacting with the API.

Thus, the correct answer is D. A valid OAuth token obtained from Anypoint Platform and its associated client ID and secret.