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| Section | Weight | Objectives |
|---|---|---|
| Architecting and Deploying API Implementations | 11% | - Networking and security configuration - Runtime architecture and deployment options - High availability and fault tolerance - CI/CD and DevOps integration |
| Applying Integration Patterns | 11% | - Error handling and reliability patterns - Scalability and performance patterns - Event-driven and synchronous integration - Common integration patterns and use cases |
| Explaining Application Network Basics | 11% | - Benefits of modern API design - Core concepts of application networks - API-led connectivity principles |
| Designing and Sharing APIs | 11% | - Asset sharing and reuse via Anypoint Exchange - API specification and documentation - API layering: Experience, Process, System APIs - API design standards and best practices |
| Establishing Organizational and Platform Foundations | 17% | - Governance and organizational structure - Anypoint Platform architecture and components - Center for Enablement (C4E) operating model - Platform strategy and roadmap definition |
| Deploying API Implementations to CloudHub | 11% | - Deployment optimization and scaling - CloudHub architecture and capabilities - VPC and private space configuration - Worker sizing and resource planning |
| Meeting API Quality Goals | 8% | - Performance and latency requirements - Reliability and availability targets - Security and compliance standards - Maintainability and testability |
| Managing APIs | 12% | - API policies and security enforcement - API lifecycle management - Versioning and deprecation strategies - Rate limiting and throttling |
| Monitoring and Analyzing Application Networks | 8% | - Logging and alerting configuration - Analytics and insight generation - Monitoring strategies and tools - Operational visibility and optimization |
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NEW QUESTION # 102
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: C
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 # 103
4A developer for a transportation organization is implementing exactly one processing functionality in a Reservation Mule application to process and store passenger records. This Reservation application will be deployed to multiple CloudHub workers/replicas. It is possible that several external systems could send duplicate passenger records to the Reservation application.
An appropriate storage mechanism must be selected to help the Reservation application process each passenger record exactly once as much as possible. The selected storage mechanism must be shared by all the CloudHub workers/replicas in order to synchronize the state information to assist attempting exactly once processing of each passenger record by the deployed Reservation Mule application.
Which type of simple storage mechanism in Anypoint Platform allows the Reservation Mule application to update and share data between the CloudHub workers/replicas exactly once, with minimal development effort?
Answer: C
Explanation:
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.
NEW QUESTION # 104
What is true about automating interactions with Anypoint Platform using tools such as Anypoint Platform REST APIs, Anypoint CU, or the Mule Maven plugin?
Answer: B
Explanation:
Correct Answe r: By default, the Anypoint CLI and Mule Maven plugin are NOT included in the Mule runtime, so are NOT available to be used by deployed Mule applications
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>> We CANNOT apply API policies to the Anypoint Platform APIs like we can do on our custom written API instances. So, option suggesting this is FALSE.
>> Anypoint Platform APIs can be used for automating interactions with both CloudHub and customer-hosted Mule runtimes. Not JUST the CloudHub. So, option opposing this is FALSE.
>> Mule Maven plugin is NOT mandatory for deployment to customer-hosted Mule runtimes. It just helps your CI/CD to have smoother automation. But not a compulsory requirement to deploy. So, option opposing this is FALSE.
>> We DO NOT have any such special roles and permissions on the platform to separately control access for some users to have Anypoint CLI and others to have Anypoint Platform APIs. With proper general roles/permissions (API Owner, Cloudhub Admin etc..), one can use any of the options (Anypoint CLI or Platform APIs). So, option suggesting this is FALSE.
Only TRUE statement given in the choices is that - Anypoint CLI and Mule Maven plugin are NOT included in the Mule runtime, so are NOT available to be used by deployed Mule applications.
Maven is part of Studio or you can use other Maven installation for development.
CLI is convenience only. It is one of many ways how to install app to the runtime.
These are definitely NOT part of anything except your process of deployment or automation.
NEW QUESTION # 105
A REST API is being designed to implement a Mule application.
What standard interface definition language can be used to define REST APIs?
Answer: D
NEW QUESTION # 106
A System API is designed to retrieve data from a backend system that has scalability challenges. What API policy can best safeguard the backend system?
Answer: C
Explanation:
Correct Answe r: SLA-based rate limiting
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>> Client Id enforement policy is a "Compliance" related NFR and does not help in maintaining the "Quality of Service (QoS)". It CANNOT and NOT meant for protecting the backend systems from scalability challenges.
>> IP Whitelisting and OAuth 2.0 token enforcement are "Security" related NFRs and again does not help in maintaining the "Quality of Service (QoS)". They CANNOT and are NOT meant for protecting the backend systems from scalability challenges.
Rate Limiting, Rate Limiting-SLA, Throttling, Spike Control are the policies that are "Quality of Service (QOS)" related NFRs and are meant to help in protecting the backend systems from getting overloaded.
https://dzone.com/articles/how-to-secure-apis
NEW QUESTION # 107
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