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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Designing and Sharing APIs | 11% | - API Design Best Practices - Anypoint Exchange for Sharing Assets - API-Led Connectivity Approach |
| Topic 2: Meeting API Quality Goals | 8% | - API Performance Optimization - Unit & Integration Testing - Resilience & Reliability Patterns |
| Topic 3: Understanding the MuleSoft Platform & Application Networks | 11% | - Application Network Fundamentals - MuleSoft Anypoint Platform Core Concepts - C4E (Center for Enablement) Definition |
| Topic 4: Applying Integration Patterns | 11% | - Event-Driven Architecture (EDA) - Batch Processing - Integration Scenarios & Patterns |
| Topic 5: Establishing Organizational and Platform Foundations | 17% | - Platform Foundation Setup - IT Delivery & C4E Operating Model - Governance and Compliance Framework |
| Topic 6: Architecting and Deploying API Implementations | 11% | - Mule Runtime Architecture - Disaster Recovery (DR) Strategies - High Availability (HA) Design |
| Topic 7: Monitoring and Analyzing Application Networks | 8% | - Alerting & Auditing - Analytics & Business Insights - Anypoint Monitoring Tools |
| Topic 8: Managing APIs | 12% | - API Versioning - API Security (Policies, SLAs) - API Lifecycle Management |
| Topic 9: Deploying API Implementations to CloudHub | 11% | - CloudHub Architecture - Deployment Strategies - CloudHub 2.0 & Runtime Fabric |
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NEW QUESTION # 112
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: A
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 # 113
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 # 114
A large company wants to implement IT infrastructure in its own data center, based on the corporate IT policy requirements that data and metadata reside locally.
Which combination of Mule control plane and Mule runtime plane(s) meets the requirements?
Answer: B
Explanation:
Understanding Control and Runtime Planes:
Control Plane: The control plane is responsible for managing, monitoring, and deploying Mule applications. In a Private Cloud Edition (PCE), this control plane is deployed on-premises within the customer's infrastructure, meeting data residency and security requirements.
Runtime Plane: The runtime plane consists of Mule runtimes that execute Mule applications. By hosting these runtimes within the customer's infrastructure, data and metadata can remain local, which complies with corporate policies regarding data residency.
Evaluating the Options:
Option A: Using Anypoint Platform Private Cloud Edition for the control plane and the MuleSoft-hosted runtime plane would not meet the requirement, as the runtime plane is hosted by MuleSoft and would not keep data local.
Option B: The MuleSoft-hosted control plane with Anypoint Runtime Fabric for the runtime plane would still mean that metadata is managed in MuleSoft's cloud, which does not comply with the requirement to keep data and metadata on-premises.
Option C: A MuleSoft-hosted control plane and customer-hosted Mule runtimes also mean that metadata resides in the cloud, not on-premises, failing the residency requirement.
Option D (Correct Answer): Anypoint Platform Private Cloud Edition (PCE) for the control plane and customer-hosted Mule runtimes fulfill both requirements, as both the control plane and runtime plane would be hosted within the customer's data center.
Conclusion:
Option D is the correct answer, as it ensures that both the control plane and runtime plane are hosted on-premises, allowing data and metadata to reside locally per the corporate IT policy.
Refer to MuleSoft's documentation on Private Cloud Edition deployment and on-premise runtime configurations for further details.
NEW QUESTION # 115
A company has created a successful enterprise data model (EDM). The company is committed to building an application network by adopting modern APIs as a core enabler of the company's IT operating model. At what API tiers (experience, process, system) should the company require reusing the EDM when designing modern API data models?
Answer: A
Explanation:
Correct Answe r: At the process and system tiers
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>> Experience Layer APIs are modeled and designed exclusively for the end user's experience. So, the data models of experience layer vary based on the nature and type of such API consumer. For example, Mobile consumers will need light-weight data models to transfer with ease on the wire, where as web-based consumers will need detailed data models to render most of the info on web pages, so on. So, enterprise data models fit for the purpose of canonical models but not of good use for experience APIs.
>> That is why, EDMs should be used extensively in process and system tiers but NOT in experience tier.
NEW QUESTION # 116
An Anypoint Platform organization has been configured with an external identity provider (IdP) for identity management and client management. What credentials or token must be provided to Anypoint CLI to execute commands against the Anypoint Platform APIs?
Answer: C
Explanation:
Correct Answe r: The credentials provided by the IdP for identity management
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Reference:
>> There is no support for OAuth 2.0 tokens from client/identity providers to authenticate via Anypoint CLI. Only possible tokens are "bearer tokens" that too only generated using Anypoint Organization/Environment Client Id and Secret from https://anypoint.mulesoft.com/accounts/login. Not the client credentials of client provider. So, OAuth 2.0 is not possible. More over, the token is mainly for API Manager purposes and not associated with a user. You can NOT use it to call most APIs (for example Cloudhub and etc) as per this Mulesoft Knowledge article.
>> The other option allowed by Anypoint CLI is to use client credentials. It is possible to use client credentials of a client provider but requires setting up Connected Apps in client management but such details are not given in the scenario explained in the question.
>> So only option left is to use user credentials from identify provider
NEW QUESTION # 117
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