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| Section | Weight | Objectives |
|---|---|---|
| Meeting API Quality Goals | 8% | - Security and compliance standards - Performance and latency requirements - Reliability and availability targets - Maintainability and testability |
| Applying Integration Patterns | 11% | - Error handling and reliability patterns - Scalability and performance patterns - Common integration patterns and use cases - Event-driven and synchronous integration |
| Explaining Application Network Basics | 11% | - API-led connectivity principles - Benefits of modern API design - Core concepts of application networks |
| Managing APIs | 12% | - API policies and security enforcement - Rate limiting and throttling - API lifecycle management - Versioning and deprecation strategies |
| Architecting and Deploying API Implementations | 11% | - Runtime architecture and deployment options - High availability and fault tolerance - Networking and security configuration - CI/CD and DevOps integration |
| Establishing Organizational and Platform Foundations | 17% | - Center for Enablement (C4E) operating model - Anypoint Platform architecture and components - Governance and organizational structure - Platform strategy and roadmap definition |
| Designing and Sharing APIs | 11% | - Asset sharing and reuse via Anypoint Exchange - API design standards and best practices - API specification and documentation - API layering: Experience, Process, System APIs |
| Monitoring and Analyzing Application Networks | 8% | - Operational visibility and optimization - Logging and alerting configuration - Analytics and insight generation - Monitoring strategies and tools |
| Deploying API Implementations to CloudHub | 11% | - Worker sizing and resource planning - Deployment optimization and scaling - CloudHub architecture and capabilities - VPC and private space configuration |
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NEW QUESTION # 127
A client has several applications running on the Salesforce service cloud. The business requirement for integration is to get daily data changes from Account and Case Objects. Data needs to be moved to the client's private cloud AWS DynamoDB instance as a single JSON and the business foresees only wanting five attributes from the Account object, which has 219 attributes (some custom) and eight attributes from the Case Object.
What design should be used to support the API/ Application data model?
Answer: B
Explanation:
Understanding the Requirements:
The business needs to transfer daily data changes from the Salesforce Account and Case objects to AWS DynamoDB in a single JSON format.
Only a subset of attributes (5 from Account and 8 from Case) is required, so it is not necessary to include all 219 attributes of the Account object.
Design Approach:
A System API (SAPI) should be created for each Salesforce object (Account and Case), exposing only the required fields (5 attributes for Account and 8 for Case).
A Process API (PAPI) can be used to aggregate and transform the data from these SAPIs, combining the 13 selected attributes from Account and Case into a single JSON structure for DynamoDB.
Evaluating the Options:
Option A: Mimicking all attributes in the SAPI is inefficient and unnecessary, as only 13 attributes are required.
Option B: Replicating all attributes in DynamoDB is excessive and would result in higher storage and processing costs, which is unnecessary given the requirement for only a subset of attributes.
Option C: Implementing an Enterprise Data Model could be useful in broader data management but is not required here, as the focus is on a lightweight integration.
Option D (Correct Answer): Creating separate entities in SAPI for Account and Case with only the required attributes and using the PAPI to aggregate them into a single JSON is the most efficient and meets the requirements effectively.
Conclusion:
Option D is the best choice as it provides a lightweight, efficient design that meets the requirements by transferring only the necessary attributes and minimizing resource use.
Refer to MuleSoft's best practices for API-led connectivity and data modeling to structure SAPIs and PAPIs efficiently.
NEW QUESTION # 128
An organization wants to make sure only known partners can invoke the organization's APIs. To achieve this security goal, the organization wants to enforce a Client ID Enforcement policy in API Manager so that only registered partner applications can invoke the organization's APIs. In what type of API implementation does MuleSoft recommend adding an API proxy to enforce the Client ID Enforcement policy, rather than embedding the policy directly in the application's JVM?
Answer: A
Explanation:
Correct Answe r: 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.
NEW QUESTION # 129
Refer to the exhibit.
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?
Answer: C
Explanation:
Correct Answe r: The client ID and secret obtained from Anypoint Exchange for the API instance in the STAGING environment
*****************************************
>> We CANNOT use the client ID and secret of Anypoint Platform account or any individual environments for accessing the APIs
>> As the type of policy that is enforced on the API in question is "Client ID Enforcment Policy", OAuth token based access won't work.
Right way to access the API is to use the client ID and secret obtained from Anypoint Exchange for the API instance in a particular environment we want to work on.
Reference:
Managing API instance Contracts on API Manager
https://docs.mulesoft.com/api-manager/1.x/request-access-to-api-task
https://docs.mulesoft.com/exchange/to-request-access
https://docs.mulesoft.com/api-manager/2.x/policy-mule3-client-id-based-policies
NEW QUESTION # 130
An API client calls one method from an existing API implementation. The API implementation is later updated. What change to the API implementation would require the API client's invocation logic to also be updated?
Answer: C
Explanation:
Correct Answe r: When a new required field is added to the method called by the API client
*****************************************
>> Generally, the logic on API clients need to be updated when the API contract breaks.
>> When a new method or a child method is added to an API , the API client does not break as it can still continue to use its existing method. So these two options are out.
>> We are left for two more where "datatype of the response if changed" and "a new required field is added".
>> Changing the datatype of the response does break the API contract. However, the question is insisting on the "invocation" logic and not about the response handling logic. The API client can still invoke the API successfully and receive the response but the response will have a different datatype for some field.
>> Adding a new required field will break the API's invocation contract. When adding a new required field, the API contract breaks the RAML or API spec agreement that the API client/API consumer and API provider has between them. So this requires the API client invocation logic to also be updated.
NEW QUESTION # 131
A customer has an ELA contract with MuleSoft. An API deployed to CloudHub is consistently experiencing performance issues. Based on the root cause analysis, it is determined that autoscaling needs to be applied.
How can this be achieved?
Answer: B
Explanation:
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.
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.
Reference
For more on CloudHub's autoscaling configuration, refer to MuleSoft documentation on CloudHub autoscaling policies.
NEW QUESTION # 132
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