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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Designing and Sharing APIs | 11% | - API specification and documentation - API layering: Experience, Process, System APIs - API design standards and best practices - Asset sharing and reuse via Anypoint Exchange |
| Topic 2: Explaining Application Network Basics | 11% | - Benefits of modern API design - Core concepts of application networks - API-led connectivity principles |
| Topic 3: Establishing Organizational and Platform Foundations | 17% | - Center for Enablement (C4E) operating model - Platform strategy and roadmap definition - Governance and organizational structure - Anypoint Platform architecture and components |
| Topic 4: Deploying API Implementations to CloudHub | 11% | - Worker sizing and resource planning - CloudHub architecture and capabilities - VPC and private space configuration - Deployment optimization and scaling |
| Topic 5: Applying Integration Patterns | 11% | - Error handling and reliability patterns - Common integration patterns and use cases - Event-driven and synchronous integration - Scalability and performance patterns |
| Topic 6: Meeting API Quality Goals | 8% | - Security and compliance standards - Reliability and availability targets - Performance and latency requirements - Maintainability and testability |
| Topic 7: Managing APIs | 12% | - API lifecycle management - Rate limiting and throttling - API policies and security enforcement - Versioning and deprecation strategies |
| Topic 8: Architecting and Deploying API Implementations | 11% | - Networking and security configuration - High availability and fault tolerance - CI/CD and DevOps integration - Runtime architecture and deployment options |
| Topic 9: Monitoring and Analyzing Application Networks | 8% | - Operational visibility and optimization - Logging and alerting configuration - Monitoring strategies and tools - Analytics and insight generation |
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NEW QUESTION # 61
An Order API must be designed that contains significant amounts of integration logic and involves the invocation of the Product API.
The power relationship between Order API and Product API is one of "Customer/Supplier", because the Product API is used heavily throughout the organization and is developed by a dedicated development team located in the office of the CTO.
What strategy should be used to deal with the API data model of the Product API within the Order API?
Answer: A
Explanation:
Correct Answe r: Convince the development team of the product API to adopt the API data model of the Order API such that integration logic of the Order API can work with one consistent internal data model
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Key details to note from the given scenario:
>> Power relationship between Order API and Product API is customer/supplier So, as per below rules of "Power Relationships", the caller (in this case Order API) would request for features to the called (Product API team) and the Product API team would need to accomodate those requests.
NEW QUESTION # 62
Version 3.0.1 of a REST API implementation represents time values in PST time using ISO 8601 hh:mm:ss format. The API implementation needs to be changed to instead represent time values in CEST time using ISO 8601 hh:mm:ss format. When following the semver.org semantic versioning specification, what version should be assigned to the updated API implementation?
Answer: D
Explanation:
Correct Answe r: 4.0.0
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As per semver.org semantic versioning specification:
Given a version number MAJOR.MINOR.PATCH, increment the:
- MAJOR version when you make incompatible API changes.
- MINOR version when you add functionality in a backwards compatible manner.
- PATCH version when you make backwards compatible bug fixes.
As per the scenario given in the question, the API implementation is completely changing its behavior. Although the format of the time is still being maintained as hh:mm:ss and there is no change in schema w.r.t format, the API will start functioning different after this change as the times are going to come completely different.
Example: Before the change, say, time is going as 09:00:00 representing the PST. Now on, after the change, the same time will go as 18:00:00 as Central European Summer Time is 9 hours ahead of Pacific Time.
>> This may lead to some uncertain behavior on API clients depending on how they are handling the times in the API response. All the API clients need to be informed that the API functionality is going to change and will return in CEST format. So, this considered as a MAJOR change and the version of API for this new change would be 4.0.0
NEW QUESTION # 63
Refer to the exhibit.
Three business processes need to be implemented, and the implementations need to communicate with several different SaaS applications.
These processes are owned by separate (siloed) LOBs and are mainly independent of each other, but do share a few business entities. Each LOB has one development team and their own budget In this organizational context, what is the most effective approach to choose the API data models for the APIs that will implement these business processes with minimal redundancy of the data models?
A) Build several Bounded Context Data Models that align with coherent parts of the business processes and the definitions of associated business entities
B) Build distinct data models for each API to follow established micro-services and Agile API-centric practices C) Build all API data models using XML schema to drive consistency and reuse across the organization D) Build one centralized Canonical Data Model (Enterprise Data Model) that unifies all the data types from all three business processes, ensuring the data model is consistent and non-redundant
Answer: D
Explanation:
Correct Answe r: Build several Bounded Context Data Models that align with coherent parts of the business processes and the definitions of associated business entities.
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>> The options w.r.t building API data models using XML schema/ Agile API-centric practices are irrelevant to the scenario given in the question. So these two are INVALID.
>> Building EDM (Enterprise Data Model) is not feasible or right fit for this scenario as the teams and LOBs work in silo and they all have different initiatives, budget etc.. Building EDM needs intensive coordination among all the team which evidently seems not possible in this scenario.
So, the right fit for this scenario is to build several Bounded Context Data Models that align with coherent parts of the business processes and the definitions of associated business entities.
NEW QUESTION # 64
A system API is deployed to a primary environment as well as to a disaster recovery (DR) environment, with different DNS names in each environment. A process API is a client to the system API and is being rate limited by the system API, with different limits in each of the environments. The system API's DR environment provides only 20% of the rate limiting offered by the primary environment. What is the best API fault-tolerant invocation strategy to reduce overall errors in the process API, given these conditions and constraints?
Answer: B
Explanation:
Correct Answe r: Invoke the system API deployed to the primary environment; add timeout and retry logic to the process API to avoid intermittent failures; if it still fails, invoke the system API deployed to the DR environment
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There is one important consideration to be noted in the question which is - System API in DR environment provides only 20% of the rate limiting offered by the primary environment. So, comparitively, very less calls will be allowed into the DR environment API opposed to its primary environment. With this in mind, lets analyse what is the right and best fault-tolerant invocation strategy.
1. Invoking both the system APIs in parallel is definitely NOT a feasible approach because of the 20% limitation we have on DR environment. Calling in parallel every time would easily and quickly exhaust the rate limits on DR environment and may not give chance to genuine intermittent error scenarios to let in during the time of need.
2. Another option given is suggesting to add timeout and retry logic to process API while invoking primary environment's system API. This is good so far. However, when all retries failed, the option is suggesting to invoke the copy of process API on DR environment which is not right or recommended. Only system API is the one to be considered for fallback and not the whole process API. Process APIs usually have lot of heavy orchestration calling many other APIs which we do not want to repeat again by calling DR's process API. So this option is NOT right.
3. One more option given is suggesting to add the retry (no timeout) logic to process API to directly retry on DR environment's system API instead of retrying the primary environment system API first. This is not at all a proper fallback. A proper fallback should occur only after all retries are performed and exhausted on Primary environment first. But here, the option is suggesting to directly retry fallback API on first failure itself without trying main API. So, this option is NOT right too.
This leaves us one option which is right and best fit.
- Invoke the system API deployed to the primary environment
- Add Timeout and Retry logic on it in process API
- If it fails even after all retries, then invoke the system API deployed to the DR environment.
NEW QUESTION # 65
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: B
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 # 66
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