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Updated Certification MuleSoft-Integration-Architect-I Torrent | Easy To Study and Pass Exam at first attempt & High-quality Salesforce Salesforce Certified MuleSoft Integration Architect I

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

Topic
Details

Topic 1

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 2

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 3

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

Topic 4

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 5

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.

Topic 6

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 7

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 8

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.

Salesforce Certified MuleSoft Integration Architect I Sample Questions (Q167-Q172):

NEW QUESTION # 167
When the mule application using VM is deployed to a customer-hosted cluster or multiple cloudhub workers, how are messages consumed by the Mule engine?

A. the primary only in order to avoid duplicate processing
B. in non-deterministic way
C. in a deterministic way
D. by starting an XA transaction for each new message

Answer: B

Explanation:
When a Mule application using VM (Virtual Machine) queues is deployed to a customer-hosted cluster or multiple CloudHub workers, the messages are consumed by the Mule engine in a non-deterministic way. Here' s an in-depth explanation:
* VM Queues Overview:
* VM queues in Mule applications are used for intra-application communication, allowing different flows within the same application to exchange messages.
* Deployment in Clusters or Multiple Workers:
* Customer-Hosted Cluster: In a customer-hosted cluster, multiple Mule runtime instances work together to process messages. Each instance can pick up messages from the VM queue.
* CloudHub Workers: When deployed on CloudHub, multiple worker instances can run the same Mule application, and each worker can access the VM queue.
* Non-Deterministic Message Consumption:
* Load Distribution: Messages are distributed among the available nodes or workers based on their availability. This means any node or worker that is ready to process a message can pick it up from the queue.
* No Guaranteed Order: Because any available node or worker can consume messages, the order in which messages are processed is not guaranteed, making the consumption non-deterministic.
* Parallel Processing: This approach allows for parallel processing of messages, which improves the scalability and throughput of the application.
* Advantages:
* Scalability: By allowing multiple nodes or workers to process messages, the system can handle increased load more effectively.
* Fault Tolerance: If one node or worker fails, other nodes/workers can continue processing messages from the VM queue, providing higher availability.
* Considerations:
* Idempotency: Ensure that the processing logic is idempotent, meaning that processing the same message more than once does not produce different outcomes. This is crucial in a non- deterministic consumption environment to avoid issues with data consistency.
* Transaction Management: Proper transaction management should be in place to handle scenarios where a message might need to be reprocessed due to errors.
References:
* MuleSoft Documentation on VM Connector
* MuleSoft Documentation on High Availability Clustering
* MuleSoft Documentation on Deploying to CloudHub

NEW QUESTION # 168
One of the backend systems involved by the API implementation enforces rate limits on the number of request a particle client can make.
Both the back-end system and API implementation are deployed to several non-production environments including the staging environment and to a particular production environment. Rate limiting of the back-end system applies to all non-production environments.
The production environment however does not have any rate limiting.
What is the cost-effective approach to conduct performance test of the API implementation in the non-production staging environment?

A. Including logic within the API implementation that bypasses in locations of the back-end system in the staging environment and invoke a Mocking service that replicates typical back-end system responses Then conduct performance test using this API implementation
B. Conduct scaled-down performance tests in the staging environment against rate-limiting back-end system. Then upscale performance results to full production scale
C. Use MUnit to simulate standard responses from the back-end system.
Then conduct performance test to identify other bottlenecks in the system
D. Create a Mocking service that replicates the back-end system's
production performance characteristics
Then configure the API implementation to use the mocking
service and conduct the performance test

Answer: D

NEW QUESTION # 169
Which Exchange asset type represents configuration modules that extend the functionality of an API and enforce capabilities such as security?

A. Connectors
B. RESTAPIs
C. Policies
D. Rulesets

Answer: C

Explanation:
In Anypoint Exchange, policies are the asset type that represents configuration modules extending the functionality of an API and enforcing capabilities such as security. Policies can be applied to APIs to control access, apply throttling, manage security, and other aspects that modify or extend the behavior of APIs.
Rulesets, REST APIs, and connectors serve different purposes within the Anypoint Platform. Rulesets are used for validation or routing decisions. REST APIs define the endpoints and methods for API interactions, and connectors enable connectivity to various systems and services. Only policies are specifically designed to enforce additional capabilities on APIs.
References
* MuleSoft Anypoint Platform Documentation on API Policies
* Anypoint Exchange Overview

NEW QUESTION # 170
A Mule application is being designed to do the following:
Step 1: Read a SalesOrder message from a JMS queue, where each SalesOrder consists of a header and a list of SalesOrderLineltems.
Step 2: Insert the SalesOrder header and each SalesOrderLineltem into different tables in an RDBMS.
Step 3: Insert the SalesOrder header and the sum of the prices of all its SalesOrderLineltems into a table In a different RDBMS.
No SalesOrder message can be lost and the consistency of all SalesOrder-related information in both RDBMSs must be ensured at all times.
What design choice (including choice of transactions) and order of steps addresses these requirements?

A. 1) Read and acknowledge the JMS message (NOT in an XA transaction)
2) In a NEW XA transaction, perform BOTH DB inserts
B. 1) Read the JMS message in an XA transaction
2) In the SAME XA transaction, perform BOTH DB inserts but do NOT acknowledge the JMS message
C. 1) Read the JMS message (NOT in an XA transaction)
2) Perform EACH DB insert in a SEPARATE DB transaction
3) Acknowledge the JMS message
D. 1) Read the JMS message (NOT in an XA transaction)
2) Perform BOTH DB inserts in ONE DB transaction
3) Acknowledge the JMS message

Answer: D

Explanation:
* Option A says "Perform EACH DB insert in a SEPARATE DB transaction". In this case if first DB insert is successful and second one fails then first insert won't be rolled back causing inconsistency. This option is ruled out.
* Option D says Perform BOTH DB inserts in ONE DB transaction.
Rule of thumb is when one or more DB connections are required we must use XA transaction as local transactions support only one resource. So this option is also ruled out.
* Option B acknowledges the before DB processing, so message is removed from the queue. In case of system failure at later point, message can't be retrieved.
* Option C is Valid: Though it says "do not ack JMS message", message will be auto acknowledged at the end of transaction. Here is how we can ensure all components are part of XA transaction: https://docs.mulesoft.com/jms-connector/1.7/jms-transactions Additional Information about transactions:
* XA Transactions - You can use an XA transaction to group together a series of operations from multiple transactional resources, such as JMS, VM or JDBC resources, into a single, very reliable, global transaction.
* The XA (eXtended Architecture) standard is an X/Open group standard which specifies the interface between a global transaction manager and local transactional resource managers.
The XA protocol defines a 2-phase commit protocol which can be used to more reliably coordinate and sequence a series of "all or nothing" operations across multiple servers, even servers of different types
* Use JMS ack if
- Acknowledgment should occur eventually, perhaps asynchronously
- The performance of the message receipt is paramount
- The message processing is idempotent
- For the choreography portion of the SAGA pattern
* Use JMS transactions
- For all other times in the integration you want to perform an atomic unit of work
- When the unit of work comprises more than the receipt of a single message
- To simply and unify the programming model (begin/commit/rollback)

NEW QUESTION # 171
Additional nodes are being added to an existing customer-hosted Mule runtime cluster to improve performance. Mule applications deployed to this cluster are invoked by API clients through a load balancer.
What is also required to carry out this change?

A. API implementations using an object store must be adjusted to recognize the new nodes and persist to them
B. A new load balancer must be provisioned to allow traffic to the new nodes in a round-robin fashion
C. External monitoring tools or log aggregators must be configured to recognize the new nodes
D. New firewall rules must be configured to accommodate communication between API clients and the new nodes

Answer: C

Explanation:
* Clustering is a group of servers or mule runtime which acts as a single unit.
* Mulesoft Enterprise Edition supports scalable clustering to provide high availability for the Mulesoft application.
* In simple terms, virtual servers composed of multiple nodes and they communicate and share information through a distributed shared memory grid.
* By default, Mulesoft ensures the High availability of applications if clustering implemented.
* Let's consider the scenario one of the nodes in cluster crashed or goes down and under maintenance. In such cases, Mulesoft will ensure that requests are processed by other nodes in the cluster. Mulesoft clustering also ensures that the request is load balanced between all the nodes in a cluster.
* Clustering is only supported by on-premise Mule runtime and it is not supported in Cloudhub.
Correct answer is External monitoring tools or log aggregators must be configured to recognize the new nodes
* Rest of the options are automatically taken care of when a new node is added in cluster.

NEW QUESTION # 172
......

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