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| Section | Weight | Objectives |
|---|---|---|
| Managing APIs | 12% | - API Versioning - API Security (Policies, SLAs) - API Lifecycle Management |
| Meeting API Quality Goals | 8% | - Resilience & Reliability Patterns - Unit & Integration Testing - API Performance Optimization |
| Monitoring and Analyzing Application Networks | 8% | - Analytics & Business Insights - Alerting & Auditing - Anypoint Monitoring Tools |
| Applying Integration Patterns | 11% | - Event-Driven Architecture (EDA) - Integration Scenarios & Patterns - Batch Processing |
| Understanding the MuleSoft Platform & Application Networks | 11% | - Application Network Fundamentals - C4E (Center for Enablement) Definition - MuleSoft Anypoint Platform Core Concepts |
| Deploying API Implementations to CloudHub | 11% | - CloudHub 2.0 & Runtime Fabric - Deployment Strategies - CloudHub Architecture |
| Establishing Organizational and Platform Foundations | 17% | - Governance and Compliance Framework - Platform Foundation Setup - IT Delivery & C4E Operating Model |
| Architecting and Deploying API Implementations | 11% | - Disaster Recovery (DR) Strategies - Mule Runtime Architecture - High Availability (HA) Design |
| Designing and Sharing APIs | 11% | - Anypoint Exchange for Sharing Assets - API-Led Connectivity Approach - API Design Best Practices |
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NEW QUESTION # 21
In an organization, the InfoSec team is investigating Anypoint Platform related data traffic.
From where does most of the data available to Anypoint Platform for monitoring and alerting originate?
Answer: D
Explanation:
Correct Answe r: From the Mule runtime irrespective of the deployment model
*****************************************
>> 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.
NEW QUESTION # 22
An organization has built an application network following the API-led connectivity approach recommended by MuleSoft. To protect the application network against attacks from malicious external API clients, the organization plans to apply JSON Threat Protection policies.
To which API-led connectivity layer should the JSON Threat Protection policies most commonly be applied?
Answer: D
Explanation:
Understanding JSON Threat Protection Policies:
JSON Threat Protection policies are used to protect APIs from attacks that exploit JSON payloads, such as oversized payloads, deeply nested objects, and excessive array elements. This helps prevent Denial of Service (DoS) attacks and other malicious payload-related threats.
These policies are typically applied to safeguard APIs that are directly exposed to external clients, where the risk of receiving malicious payloads is highest.
API-led Connectivity Layers:
Experience Layer: This layer is designed to expose APIs to end-users or external API clients, often acting as the interface that interacts with users or applications.
Process Layer: This layer is used for orchestration and aggregation of data from various System APIs, typically operating within a trusted environment and not directly exposed to external clients.
System Layer: This layer provides access to backend systems and databases, often within the organization's secure environment and not directly accessible to external clients.
Evaluating the Options:
Option A (All layers): While JSON Threat Protection can technically be applied to all layers, it is most commonly applied at the Experience layer, where APIs are exposed to external traffic and are more vulnerable to attacks.
Option B (System layer): The System layer is generally not exposed to external clients directly, so JSON Threat Protection is less critical here.
Option C (Process layer): Similar to the System layer, the Process layer is typically internal and not exposed directly to external clients, so JSON Threat Protection is less commonly applied.
Option D (Correct Answer): The Experience layer is the correct answer because it is the layer that directly interacts with external clients, making it the primary target for malicious payloads. Applying JSON Threat Protection here effectively protects the application network from external threats.
Conclusion:
Option D is the correct answer, as the Experience layer is the most common layer for applying JSON Threat Protection policies to protect against external attacks.
For further reference, consult MuleSoft's documentation on API security policies and best practices for securing APIs at the Experience layer.
NEW QUESTION # 23
An API with multiple API implementations (Mule applications) is deployed to both CloudHub and customer-hosted Mule runtimes. All the deployments are managed by the MuleSoft-hosted control plane. An alert needs to be triggered whenever an API implementation stops responding to API requests, even if no API clients have called the API implementation for some time.
What is the most effective out-of-the-box solution to create these alerts to monitor the API implementations?
Answer: B
Explanation:
In scenarios where multiple API implementations are deployed across different environments (CloudHub and customer-hosted runtimes), Anypoint Functional Monitoring is the most effective tool to monitor API availability and trigger alerts when an API implementation becomes unresponsive. Here's how it works:
Using Anypoint Functional Monitoring:
Functional Monitoring allows you to create monitors that periodically invoke specific endpoints on the API implementations, simulating a client request. This helps ensure that the API is responsive, even if no actual client requests are being made.
If an API implementation does not respond as expected, Functional Monitoring can generate alerts, notifying administrators of potential issues.
Why Option A is Correct:
By setting up Functional Monitoring to automatically invoke the API endpoints at regular intervals, you ensure continuous monitoring and alerting capabilities, which are especially useful for APIs that may experience periods of low or no traffic. This approach provides a proactive solution, allowing you to identify and address issues before actual users are impacted.
of Incorrect Options:
Option B suggests modifying client applications to trigger alerts, which is not a best practice as it shifts monitoring responsibility to clients, reducing control and consistency.
Option C involves handling exceptions within client applications, which does not address situations where no clients are making requests.
Option D proposes a Worker Not Responding alert in Runtime Manager, which is limited to worker-specific alerts and may not reliably monitor the API's actual responsiveness to requests.
Reference
For further information, refer to MuleSoft documentation on Anypoint Functional Monitoring setup and usage for API availability monitoring.
NEW QUESTION # 24
An online store's marketing team has noticed an increase in customers leaving online baskets without checking out. They suspect a technology issue is at the root cause of the baskets being left behind. They approach the Center for Enablement to ask for help identifying the issue. Multiple APIs from across all the layers of their application network are involved in the shopping application.
Which feature of the Anypoint Platform can be used to view metrics from all involved APIs at the same time?
Answer: D
Explanation:
Understanding the Need for Cross-API Monitoring:
The Center for Enablement (C4E) needs to investigate potential technical issues across multiple APIs in the application network that may be causing customers to abandon their carts.
This requires a solution that allows viewing metrics across several APIs in real-time to identify any performance issues or bottlenecks.
Evaluating Anypoint Platform Features:
Built-in Dashboards: Anypoint Platform provides built-in dashboards in Anypoint Monitoring, allowing teams to view metrics from multiple APIs in a single interface. This feature is designed to monitor API performance, latency, errors, and throughput, and is ideal for tracking performance across all layers of the application network.
Custom Dashboards: While custom dashboards allow for more tailored views, the built-in dashboards already aggregate metrics for multiple APIs, making it unnecessary to build a custom solution for this scenario.
Functional Monitoring: This feature is used to set up tests to monitor specific API functionality and uptime but is not suited for tracking metrics across multiple APIs in real-time.
API Manager: API Manager primarily focuses on managing API policies, contracts, and access control rather than providing detailed, real-time metrics across the entire application network.
Conclusion:
Option B (Built-in dashboards) is the best choice because it provides a comprehensive view of metrics from all APIs involved, enabling the C4E team to quickly identify any issues that may be contributing to abandoned shopping carts.
Refer to MuleSoft's documentation on Anypoint Monitoring and built-in dashboards for more details on configuring and using these dashboards effectively.
NEW QUESTION # 25
A company uses a hybrid Anypoint Platform deployment model that combines the EU control plane with customer-hosted Mule runtimes. After successfully testing a Mule API implementation in the Staging environment, the Mule API implementation is set with environment-specific properties and must be promoted to the Production environment. What is a way that MuleSoft recommends to configure the Mule API implementation and automate its promotion to the Production environment?
Answer: C
Explanation:
Correct Answe r: Bundle properties files for each environment into the Mule API implementation's deployable archive, then promote the Mule API implementation to the Production environment using Anypoint CLI or the Anypoint Platform REST APIs
*****************************************
>> Anypoint Exchange is for asset discovery and documentation. It has got no provision to modify the properties of Mule API implementations at all.
>> API Manager is for managing API instances, their contracts, policies and SLAs. It has also got no provision to modify the properties of API implementations.
>> API policies are to address Non-functional requirements of APIs and has again got no provision to modify the properties of API implementations.
So, the right way and recommended way to do this as part of development practice is to bundle properties files for each environment into the Mule API implementation and just point and refer to respective file per environment.
NEW QUESTION # 26
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