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Salesforce MuleSoft-Integration-Architect-I Exam Syllabus Topics:

TopicDetails
Topic 1
  • Designing Integration Solutions to Meet Performance Requirements: This topic covers meeting performance and capacity goals, using streaming features, and processing large message sequences.
Topic 2
  • Initiating Integration Solutions on Anypoint Platform: Summarizing MuleSoft Catalyst and Catalyst Knowledge Hub, differentiating between functional and non-functional requirements, selecting features for designing and managing APIs, and choosing deployment options are its sub-topics.
Topic 3
  • Designing and Developing Mule Applications: It includes selecting application properties, using fundamental features, designing with core routers, understanding the Salesforce Connector, and leveraging core connectors.
Topic 4
  • Applying DevOps Practices and Operating Integration Solutions: Its sub-topics are related to designing CI
  • CD pipelines with MuleSoft plugins, automating interactions with Anypoint Platform, designing logging configurations, and identifying Anypoint Monitoring features.
Topic 5
  • Designing Integration Solutions to Meet Persistence Requirements: It addresses the usage of VM queues and connectors, object stores and services, and stateful components configured with object stores.
Topic 6
  • Designing Integration Solutions to Meet Security Requirements: This topic emphasizes securing access to the Anypoint Platform and APIs, using Anypoint Security, counteracting security vulnerabilities, and understanding audit logging capabilities.
Topic 7
  • Designing Integration Solutions to Meet Reliability Requirements: It includes selecting alternatives to traditional transactions, recognizing the purpose of various scopes and strategies, differentiating disaster recovery and high availability, and using local and XA transactions.

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Salesforce Certified MuleSoft Integration Architect I Sample Questions (Q134-Q139):

NEW QUESTION # 134
Refer to the exhibit.

A Mule application is deployed to a cluster of two customer-hosted Mute runtimes. The Mute application has a flow that polls a database and another flow with an HTTP Listener.
HTTP clients send HTTP requests directly to individual cluster nodes.
What happens to database polling and HTTP request handling in the time after the primary (master) node of the cluster has railed, but before that node is restarted?

Answer: C

Explanation:
Correct answer is Database polling continues Only HTTP requests sent to the remaining node continue to be accepted. Explanation : Architecture descripted in the question could be described as follows.When node 1 is down , DB polling will still continue via node 2 . Also requests which are coming directly to node 2 will also be accepted and processed in BAU fashion. Only thing that wont work is when requests are sent to Node 1 HTTP connector. The flaw with this architecture is HTTP clients are sending HTTP requests directly to individual cluster nodes. By default, clustering Mule runtime engines ensures high system availability. If a Mule runtime engine node becomes unavailable due to failure or planned downtime, another node in the cluster can assume the workload and continue to process existing events and messages Diagram Description automatically generated


NEW QUESTION # 135
Refer to the exhibit.
A customer is running Mule applications on Runtime Fabric for Self-Managed Kubernetes (RTF-BYOKS) in a multi-cloud environment.
Based on this configuration, how do Agents and Runtime Manager
communicate, and what Is exchanged between them?

Answer: C

Explanation:
In the context of Mule applications running on Runtime Fabric for Self-Managed Kubernetes (RTF-BYOKS) in a multi-cloud environment, understanding the thread pools used for communication between Agents and Runtime Manager is crucial:
* Shared NIO Selector Pool: This pool is responsible for handling non-blocking IO operations, such as network communication. It ensures efficient handling of IO operations by using a small number of threads to manage multiple IO tasks simultaneously.
* CPU_LITE: This thread pool is used for lightweight CPU operations. It is designed to handle tasks that do not require significant computational resources, ensuring that lightweight operations are processed efficiently without overwhelming the system.
The combination of the Shared NIO Selector Pool and CPU_LITE thread pool ensures efficient and reliable communication between Agents and Runtime Manager in the RTF environment.
MuleSoft Threading and Thread Pools
Runtime Fabric Architecture


NEW QUESTION # 136
A company is using Mulesoft to develop API's and deploy them to Cloudhub and on premises targets.
Recently it has decided to enable Runtime Fabric deployment option as well and infrastructure is set up for this option.
What can be used to deploy Runtime Fabric?

Answer: B

Explanation:
When deploying to Runtime Fabric, there are several tools available within the Anypoint Platform ecosystem that facilitate the deployment process. These include:
* AnypointCLI: This command-line interface tool provides comprehensive capabilities for deploying applications to Runtime Fabric. Using AnypointCLI, you can script and automate deployments, which is useful for integrating into CI/CD pipelines.
* Anypoint Platform REST APIs: These APIs allow for programmatic deployment and management of applications on Runtime Fabric. They provide flexibility for integrating deployment processes with other systems and tools.
* Mule Maven Plugin: This plugin can be used within a Maven project to package and deploy Mule applications to Runtime Fabric as part of a build process.
However, directly uploading a JAR file from the Runtime Manager is not a supported method for deploying to Runtime Fabric.
Anypoint CLI Documentation
Mule Maven Plugin Documentation


NEW QUESTION # 137
An organization is choosing between API-led connectivity and other integration approaches.
According to MuleSoft, which business benefits is associated with an API-led connectivity approach using Anypoint Platform?

Answer: A

Explanation:
According to MuleSoft, a significant business benefit associated with an API-led connectivity approach using Anypoint Platform is increased developer productivity through self-service of API assets. API-led connectivity promotes the creation of reusable APIs that can be easily discovered and consumed by developers across the organization. This self-service model reduces dependencies, accelerates development, and fosters innovation by enabling teams to quickly build and integrate applications using existing APIs without waiting for central IT to provide access.
References:
* API-led Connectivity: The Key to Unlocking IT Agility
* Benefits of API-led Connectivity


NEW QUESTION # 138
As a part of design , Mule application is required call the Google Maps API to perform a distance computation. The application is deployed to cloudhub.
At the minimum what should be configured in the TLS context of the HTTP request configuration to meet these requirements?

Answer: B


NEW QUESTION # 139
......

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