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

Topic
Details

Topic 1

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 2

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 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

Designing for the Runtime Plane Technology Architecture: It includes analyzing Mule runtime clusters, designing solutions for CloudHub, choosing Mule runtime domains, leveraging Mule 4 class loader isolation, and understanding the reactive event processing model.

Topic 5

Designing Architecture Using Integration Paradigms: This topic focuses on creating high-level integration architectures using various paradigms. It includes API-led connectivity, web APIs and HTTP, event-driven APIs, and message brokers, and designing Mule application using messaging patterns and technologies.

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 Performance Requirements: This topic covers meeting performance and capacity goals, using streaming features, and processing large message sequences.

Topic 8

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 9

Designing Automated Tests for Mule Applications: This topic covers unit test suites, and scenarios for integration and performance testing.

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Salesforce Certified MuleSoft Integration Architect I Sample Questions (Q252-Q257):

NEW QUESTION # 252
A stock trading company handles millions of trades a day and requires excellent performance and reliability within its stock trading system. The company operates a number of event-driven APIs Implemented as Mule applications that are hosted on various customer-hosted Mule clusters and needs to enable message exchanges between the APIs within their internal network using shared message queues.
What is an effective way to meet the cross-cluster messaging requirements of its event-driven APIs?

A. Non-transactional JMS operations with a reliability pattern and manual acknowledgements
B. JMS transactions with automatic acknowledgements
C. extended Architecture (XA) transactions and XA connected components with manual acknowledgements
D. Persistent VM queues with automatic acknowledgements

Answer: A

NEW QUESTION # 253
A leading e-commerce giant will use Mulesoft API's on runtime fabric (RTF) to process customer orders.
Some customer's sensitive information such as credit card information is also there as a part of a API payload.
What approach minimizes the risk of matching sensitive data to the original and can convert back to the original value whenever and wherever required?

A. Apply masking to hide the sensitive information and then use API
B. create a tokenization format and apply a tokenization policy to the API Gateway
C. Used both masking and tokenization
D. manager to detokenize the masking format to return the original value
E. Apply a field level encryption policy in the API Gateway

Answer: B

Explanation:
To minimize the risk of exposing sensitive data such as credit card information while still allowing it to be converted back to its original value when necessary, tokenization is the most effective approach. Tokenization replaces sensitive data with a non-sensitive equivalent, called a token, which has no exploitable value. This method ensures that the original sensitive data is stored securely and only accessible through a secure tokenization system.
In this scenario, applying a tokenization policy at the API Gateway ensures that sensitive information is replaced with tokens before the data leaves the trusted boundary. This minimizes the risk of matching sensitive data to the original. When the original data is needed, the tokenization system can detokenize the token back to its original value securely.
References:
* MuleSoft Documentation on Tokenization

NEW QUESTION # 254
What metrics about API invocations are available for visualization in custom charts using Anypoint Analytics?

A. Request size, number of requests, JDBC Select operation response time
B. Request size, number of requests, response size, response time
C. Request size, number of requests, JDBC Select operation result set size
D. Request size, request HTTP verbs, response time

Answer: B

Explanation:
Correct answer is Request size, number of requests, response size, response time Analytics API Analytics can provide insight into how your APIs are being used and how they are performing. From API Manager, you can access the Analytics dashboard, create a custom dashboard, create and manage charts, and create reports. From API Manager, you can get following types of analytics: - API viewing analytics - API events analytics - Charted metrics in API Manager It can be accessed using: http://anypoint.mulesoft.com/analytics API Analytics provides a summary in chart form of requests, top apps, and latency for a particular duration.
The custom dashboard in Anypoint Analytics contains a set of charts for a single API or for all APIs Each chart displays various API characteristics
- Requests size: Line chart representing size of requests in KBs
- Requests : Line chart representing number of requests over a period
- Response size : Line chart representing size of response in KBs
- Response time :Line chart representing response time in ms
* To check this, You can go to API Manager > Analytics > Custom Dashboard > Edit Dashboard > Create Chart > Metric

Reference:
Additional Information:
The default dashboard contains a set of charts
- Requests by date: Line chart representing number of requests
- Requests by location: Map chart showing the number of requests for each country of origin
- Requests by application: Bar chart showing the number of requests from each of the top five registered applications
- Requests by platform: Ring chart showing the number of requests broken down by platform

NEW QUESTION # 255
An organization plans to migrate its deployment environment from an onpremises cluster to a Runtime Fabric (RTF) cluster. The on-premises Mule applications are currently configured with persistent object stores.
There is a requirement to enable Mule applications deployed to the RTF cluster to store and share data across application replicas and through restarts of the entire RTF cluster, How can these reliability requirements be met?

A. Replace persistent object stores with persistent VM queues in each Mule application deployment
B. Configure the Persistence Gateway in the RTF installation
C. Configure Anypoint Object Store v2 to share data between replicas in the RTF cluster
D. Install the Object Store pod on one of the cluster nodes

Answer: A

NEW QUESTION # 256
In which order are the API Client, API Implementation, and API interface components called in a typical REST request?

A. API Client > API implementation > API Interface
B. API Implementation > API Interface > API Client
C. API interface > API Client > API Implementation
D. API Client > API Interface > API implementation

Answer: A

NEW QUESTION # 257
......

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