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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Deploying API Implementations to CloudHub | 11% | - CloudHub 2.0 & Runtime Fabric - CloudHub Architecture - Deployment Strategies |
| Topic 2: Monitoring and Analyzing Application Networks | 8% | - Alerting & Auditing - Anypoint Monitoring Tools - Analytics & Business Insights |
| Topic 3: Designing and Sharing APIs | 11% | - API Design Best Practices - Anypoint Exchange for Sharing Assets - API-Led Connectivity Approach |
| Topic 4: Meeting API Quality Goals | 8% | - API Performance Optimization - Resilience & Reliability Patterns - Unit & Integration Testing |
| Topic 5: Establishing Organizational and Platform Foundations | 17% | - IT Delivery & C4E Operating Model - Platform Foundation Setup - Governance and Compliance Framework |
| Topic 6: Managing APIs | 12% | - API Versioning - API Security (Policies, SLAs) - API Lifecycle Management |
| Topic 7: Applying Integration Patterns | 11% | - Integration Scenarios & Patterns - Batch Processing - Event-Driven Architecture (EDA) |
| Topic 8: Architecting and Deploying API Implementations | 11% | - Mule Runtime Architecture - High Availability (HA) Design - Disaster Recovery (DR) Strategies |
| Topic 9: Understanding the MuleSoft Platform & Application Networks | 11% | - Application Network Fundamentals - C4E (Center for Enablement) Definition - MuleSoft Anypoint Platform Core Concepts |
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NEW QUESTION # 91
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: A
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 # 92
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: C
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 # 93
A company uses a hybrid Anypoint Platform deployment model that combines the EU control plane with customer-hosted Mule runtimes. After successfully testing a Mule API implementation in the Staging environment, the Mule API implementation is set with environment-specific properties and must be promoted to the Production environment. What is a way that MuleSoft recommends to configure the Mule API implementation and automate its promotion to the Production environment?
Answer: D
NEW QUESTION # 94
A Mule application exposes an HTTPS endpoint and is deployed to three CloudHub workers that do not use static IP addresses. The Mule application expects a high volume of client requests in short time periods. What is the most cost-effective infrastructure component that should be used to serve the high volume of client requests?
Answer: B
Explanation:
Correct Answe r: The CloudHub shared load balancer
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The scenario in this question can be split as below:
>> There are 3 CloudHub workers (So, there are already good number of workers to handle high volume of requests)
>> The workers are not using static IP addresses (So, one CANNOT use customer load-balancing solutions without static IPs)
>> Looking for most cost-effective component to load balance the client requests among the workers.
Based on the above details given in the scenario:
>> Runtime autoscaling is NOT at all cost-effective as it incurs extra cost. Most over, there are already 3 workers running which is a good number.
>> We cannot go for a customer-hosted load balancer as it is also NOT most cost-effective (needs custom load balancer to maintain and licensing) and same time the Mule App is not having Static IP Addresses which limits from going with custom load balancing.
>> An API Proxy is irrelevant there as it has no role to play w.r.t handling high volumes or load balancing.
So, the only right option to go with and fits the purpose of scenario being most cost-effective is - using a CloudHub Shared Load Balancer.
NEW QUESTION # 95
Once an API Implementation is ready and the API is registered on API Manager, who should request the access to the API on Anypoint Exchange?
Answer: C
Explanation:
Correct Answe r: API Consumer
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>> API clients are piece of code or programs that use the client credentials of API consumer but does not directly interact with Anypoint Exchange to get the access
>> API consumer is the one who should get registered and request access to API and then API client needs to use those client credentials to hit the APIs So, API consumer is the one who needs to request access on the API from Anypoint Exchange
NEW QUESTION # 96
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