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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Deploying API Implementations to CloudHub | 11% | - VPC and private space configuration - Deployment optimization and scaling - CloudHub architecture and capabilities - Worker sizing and resource planning |
| Topic 2: Designing and Sharing APIs | 11% | - Asset sharing and reuse via Anypoint Exchange - API design standards and best practices - API layering: Experience, Process, System APIs - API specification and documentation |
| Topic 3: Applying Integration Patterns | 11% | - Common integration patterns and use cases - Scalability and performance patterns - Error handling and reliability patterns - Event-driven and synchronous integration |
| Topic 4: Monitoring and Analyzing Application Networks | 8% | - Operational visibility and optimization - Monitoring strategies and tools - Logging and alerting configuration - Analytics and insight generation |
| Topic 5: Explaining Application Network Basics | 11% | - Benefits of modern API design - Core concepts of application networks - API-led connectivity principles |
| Topic 6: Establishing Organizational and Platform Foundations | 17% | - Platform strategy and roadmap definition - Governance and organizational structure - Anypoint Platform architecture and components - Center for Enablement (C4E) operating model |
| Topic 7: Architecting and Deploying API Implementations | 11% | - CI/CD and DevOps integration - Runtime architecture and deployment options - Networking and security configuration - High availability and fault tolerance |
| Topic 8: Meeting API Quality Goals | 8% | - Performance and latency requirements - Security and compliance standards - Maintainability and testability - Reliability and availability targets |
| Topic 9: Managing APIs | 12% | - Versioning and deprecation strategies - API lifecycle management - API policies and security enforcement - Rate limiting and throttling |
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NEW QUESTION # 144
What Mule application deployment scenario requires using Anypoint Platform Private Cloud Edition or Anypoint Platform for Pivotal Cloud Foundry?
Answer: B
Explanation:
Correct Answe r: When regulatory requirements mandate on-premises processing of EVERY data item, including meta-data.
*****************************************
We need NOT require to use Anypoint Platform PCE or PCF for the below. So these options are OUT.
>> We can make ALL applications highly available across multiple data centers using CloudHub too.
>> We can use Anypoint VPN and tunneling from CloudHub to connect to ALL backend systems in the application network that are deployed in the organization's intranet.
>> We can use Anypoint VPC and Firewall Rules to make ALL APIs private and NOT exposed to the public cloud.
Only valid reason in the given options that requires to use Anypoint Platform PCE/ PCF is - When regulatory requirements mandate on-premises processing of EVERY data item, including meta-data.
NEW QUESTION # 145
A new upstream API Is being designed to offer an SLA of 500 ms median and 800 ms maximum (99th percentile) response time. The corresponding API implementation needs to sequentially invoke 3 downstream APIs of very similar complexity.
The first of these downstream APIs offers the following SLA for its response time: median: 100 ms, 80th percentile: 500 ms, 95th percentile: 1000 ms.
If possible, how can a timeout be set in the upstream API for the invocation of the first downstream API to meet the new upstream API's desired SLA?
Answer: C
Explanation:
Correct Answe r: Set a timeout of 100ms; that leaves 400ms for other two downstream APIs to complete
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Key details to take from the given scenario:
>> Upstream API's designed SLA is 500ms (median). Lets ignore maximum SLA response times.
>> This API calls 3 downstream APIs sequentially and all these are of similar complexity.
>> The first downstream API is offering median SLA of 100ms, 80th percentile: 500ms; 95th percentile: 1000ms.
Based on the above details:
>> We can rule out the option which is suggesting to set 50ms timeout. Because, if the median SLA itself being offered is 100ms then most of the calls are going to timeout and time gets wasted in retried them and eventually gets exhausted with all retries. Even if some retries gets successful, the remaining time wont leave enough room for 2nd and 3rd downstream APIs to respond within time.
>> The option suggesting to NOT set a timeout as the invocation of this API is mandatory and so we must wait until it responds is silly. As not setting time out would go against the good implementation pattern and moreover if the first API is not responding within its offered median SLA 100ms then most probably it would either respond in 500ms (80th percentile) or 1000ms (95th percentile). In BOTH cases, getting a successful response from 1st downstream API does NO GOOD because already by this time the Upstream API SLA of 500 ms is breached. There is no time left to call 2nd and 3rd downstream APIs.
>> It is NOT true that no timeout is possible to meet the upstream APIs desired SLA.
As 1st downstream API is offering its median SLA of 100ms, it means MOST of the time we would get the responses within that time. So, setting a timeout of 100ms would be ideal for MOST calls as it leaves enough room of 400ms for remaining 2 downstream API calls.
NEW QUESTION # 146
Question 10: Skipped
An API implementation returns three X-RateLimit-* HTTP response headers to a requesting API client. What type of information do these response headers indicate to the API client?
Answer: B
Explanation:
Correct Answe r: The remaining capacity allowed by the API implementation.
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>> Reference: https://docs.mulesoft.com/api-manager/2.x/rate-limiting-and-throttling-sla-based-policies#response-headers
NEW QUESTION # 147
The Line of Business (LoB) of an eCommerce company is requesting a process that sends automated notifications via email every time a new order is processed through the customer's mobile application or through the internal company's web application. In the future, multiple notification channels may be added: for example, text messages and push notifications.
What is the most effective API-led connectivity approach for the scenario described above?
Answer: C
Explanation:
In this scenario, the best approach to satisfy the API-led connectivity principles and support future scalability is:
Experience APIs:
Create separate Experience APIs for the web application and the mobile application. This allows each application to have an optimized interface, supporting different needs and potential differences in request/response structures or security configurations.
Process API:
A single Process API can be used to orchestrate the workflow, including retrieving the email template from a database and preparing the email content. By centralizing this logic in the Process layer, we can ensure it is reusable and easily adaptable for different notification channels in the future.
System API:
A System API specifically designed for sending emails (using the Anypoint Connector for Email) abstracts the email-sending functionality from the business logic. This approach ensures that the email-sending function is reusable and scalable, and it can easily be extended or modified if other notification channels (like SMS or push notifications) are added later.
Why Option A is Correct:
This structure aligns with API-led connectivity principles by separating concerns across Experience, Process, and System layers. It provides flexibility for future notification channels and isolates each layer's responsibility, making it easier to maintain and scale.
of Incorrect Options:
Option B lacks a separate System API for sending emails, which goes against the principle of isolating back-end functionality in System APIs.
Option C similarly lacks a dedicated System API, reducing flexibility and reusability.
Option D suggests creating multiple Process APIs for database retrieval, which adds unnecessary complexity and does not adhere to the single-orchestration principle typically followed in API-led design.
Reference
For further guidance on API-led connectivity and the responsibilities of each API layer, refer to MuleSoft's documentation on API-led architecture and design best practices.
NEW QUESTION # 148
When can CloudHub Object Store v2 be used?
Answer: D
Explanation:
CloudHub Object Store v2 is a managed key-value store provided by MuleSoft to support various use cases where temporary data storage is required. Here's why Option D is correct:
Key Length Support: Object Store v2 allows storage of keys with a length of up to 300 characters, making it suitable for applications needing flexible and descriptive keys.
Limitations on Size:
Object Store v2 is not intended for large payload storage and has a recommended size limit below 10 MB for each value. Payloads exceeding 15 MB may cause performance issues and are better suited to a file storage system or database.
Option B is incorrect because storing payloads above 15 MB exceeds Object Store's optimal usage specifications.
Key-Value Limits: Object Store v2 is designed for moderate, transient storage needs, and does not support unlimited storage. Thus, Option A is incorrect.
Backward Compatibility: Object Store v2 does not support Mule 4 applications running Object Store v1. Option C is incorrect as Object Store v1 and v2 are distinct.
Reference
For more on CloudHub Object Store v2, refer to MuleSoft documentation on Object Store limitations and configuration.
NEW QUESTION # 149
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