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| Section | Weight | Objectives |
|---|---|---|
| Applying Integration Patterns | 11% | - Scalability and performance patterns - Event-driven and synchronous integration - Common integration patterns and use cases - Error handling and reliability patterns |
| Deploying API Implementations to CloudHub | 11% | - CloudHub architecture and capabilities - Worker sizing and resource planning - VPC and private space configuration - Deployment optimization and scaling |
| Architecting and Deploying API Implementations | 11% | - Runtime architecture and deployment options - Networking and security configuration - CI/CD and DevOps integration - High availability and fault tolerance |
| Establishing Organizational and Platform Foundations | 17% | - Anypoint Platform architecture and components - Governance and organizational structure - Center for Enablement (C4E) operating model - Platform strategy and roadmap definition |
| Managing APIs | 12% | - API lifecycle management - API policies and security enforcement - Versioning and deprecation strategies - Rate limiting and throttling |
| Designing and Sharing APIs | 11% | - API design standards and best practices - API layering: Experience, Process, System APIs - Asset sharing and reuse via Anypoint Exchange - API specification and documentation |
| Explaining Application Network Basics | 11% | - API-led connectivity principles - Benefits of modern API design - Core concepts of application networks |
| Meeting API Quality Goals | 8% | - Maintainability and testability - Performance and latency requirements - Reliability and availability targets - Security and compliance standards |
| Monitoring and Analyzing Application Networks | 8% | - Operational visibility and optimization - Monitoring strategies and tools - Logging and alerting configuration - Analytics and insight generation |
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NEW QUESTION # 42
A circuit breaker strategy is planned in order to meet the goal of improved response time and demand on a downstream API.
* Circuit Open: More than 10 errors per minute for three minutes
* Circuit Half-Open: One error per minute
* Circuit Closed: Less than one error per minute for five minutes
Out of several proposals from the engineering team, which option will meet this goal?
Answer: C
Explanation:
Understanding Circuit Breaker Policy:
A circuit breaker is a design pattern used to detect failures and prevent an application from continually trying to execute a failing operation. In this case, it will help improve response time and reduce demand on the downstream API.
The specified configuration includes conditions for opening, half-opening, and closing the circuit based on error rates over time:
Circuit Open: Triggered if there are more than 10 errors per minute for three consecutive minutes.
Circuit Half-Open: The circuit transitions to half-open if there is one error per minute.
Circuit Closed: The circuit closes if the error rate is less than one error per minute for five minutes.
Evaluating the Options:
Option A: Creating a custom policy with template expressions could work, but it would require custom development. Since the Anypoint Platform already has a Circuit Breaker policy available, this would be a less efficient and more complex solution.
Option B: Anypoint Monitoring alerts can be used for monitoring the API, but they do not provide circuit-breaking functionality. Additionally, implementing a retry strategy for the half-open state is not sufficient to achieve the required circuit breaker behavior.
Option C (Correct Answer): Adding the Circuit Breaker policy to the API instance on Anypoint Platform allows you to set up circuit-breaking conditions directly. This approach uses the built-in Circuit Breaker policy, where you can configure parameters such as error thresholds and time intervals to match the requirements. This solution is efficient, reliable, and leverages Anypoint's out-of-the-box capabilities.
Option D: Implementing the strategy within a Mule application with a YAML configuration could be complex and less manageable. Additionally, it does not leverage Anypoint Platform's built-in Circuit Breaker policy, which is more suited to this scenario.
Conclusion:
Option C is the correct choice, as it leverages Anypoint Platform's Circuit Breaker policy. This solution allows for configuring thresholds and time intervals as specified, improving response time and reducing demand on the downstream API while utilizing Anypoint's managed policy feature.
Refer to MuleSoft's documentation on implementing the Circuit Breaker policy in API Manager for detailed configuration guidance.
NEW QUESTION # 43
When could the API data model of a System API reasonably mimic the data model exposed by the corresponding backend system, with minimal improvements over the backend system's data model?
Answer: B
Explanation:
Correct Answe r: When a pragmatic approach with only limited isolation from the backend system is deemed appropriate.
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General guidance w.r.t choosing Data Models:
>> If an Enterprise Data Model is in use then the API data model of System APIs should make use of data types from that Enterprise Data Model and the corresponding API implementation should translate between these data types from the Enterprise Data Model and the native data model of the backend system.
>> If no Enterprise Data Model is in use then each System API should be assigned to a Bounded Context, the API data model of System APIs should make use of data types from the corresponding Bounded Context Data Model and the corresponding API implementation should translate between these data types from the Bounded Context Data Model and the native data model of the backend system. In this scenario, the data types in the Bounded Context Data Model are defined purely in terms of their business characteristics and are typically not related to the native data model of the backend system. In other words, the translation effort may be significant.
>> If no Enterprise Data Model is in use, and the definition of a clean Bounded Context Data Model is considered too much effort, then the API data model of System APIs should make use of data types that approximately mirror those from the backend system, same semantics and naming as backend system, lightly sanitized, expose all fields needed for the given System API's functionality, but not significantly more and making good use of REST conventions.
The latter approach, i.e., exposing in System APIs an API data model that basically mirrors that of the backend system, does not provide satisfactory isolation from backend systems through the System API tier on its own. In particular, it will typically not be possible to "swap out" a backend system without significantly changing all System APIs in front of that backend system and therefore the API implementations of all Process APIs that depend on those System APIs! This is so because it is not desirable to prolong the life of a previous backend system's data model in the form of the API data model of System APIs that now front a new backend system. The API data models of System APIs following this approach must therefore change when the backend system is replaced.
On the other hand:
>> It is a very pragmatic approach that adds comparatively little overhead over accessing the backend system directly
>> Isolates API clients from intricacies of the backend system outside the data model (protocol, authentication, connection pooling, network address, ...)
>> Allows the usual API policies to be applied to System APIs
>> Makes the API data model for interacting with the backend system explicit and visible, by exposing it in the RAML definitions of the System APIs
>> Further isolation from the backend system data model does occur in the API implementations of the Process API tier
NEW QUESTION # 44
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: B
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 # 45
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: C
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 # 46
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?
Answer: D
Explanation:
Correct Answe r: Configure a "Worker not responding" alert in Anypoint Runtime Manager.
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>> All the options eventually helps to generate the alert required when the application stops responding.
>> However, handling exceptions within calling API and then raising alert from API client is inappropriate and silly. There could be many API clients invoking the API implementation and it is not ideal to have this setup consistently in all of them. Not a realistic way to do.
>> Implementing a health check/ heartbeat with in the API and calling from outside to detmine the health sounds OK but needs extra setup for it and same time there are very good chances of generating false alarms when there are any intermittent network issues between external tool calling the health check API on API implementation. The API implementation itself may not have any issues but due to some other factors some false alarms may go out.
>> Creating an alert in API Manager when the API receives no requests within a specified time period would actually generate realistic alerts but even here some false alarms may go out when there are genuinely no requests from API clients.
The best and right way to achieve this requirement is to setup an alert on Runtime Manager with a condition "Worker not responding". This would generate an alert AS SOON AS the workers become unresponsive.
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NEW QUESTION # 47
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