MuleSoft-Integration-Architect-I Exam Dumps - Salesforce MuleSoft Questions and Answers

To discover which API specifications have been created within the organization before starting a new project, a developer can use Anypoint Exchange. Anypoint Exchange is a centralized repository on the Anypoint Platform where developers can find, share, and collaborate on API specifications, connectors, templates, and other reusable assets.

In Anypoint Exchange, developers can browse the currently released API specifications, try them out using the built-in testing tools, and access documentation and other resources. This facilitates the reuse of existing APIs and ensures that the new project aligns with the organization's API strategy.

References

MuleSoft Documentation on Anypoint Exchange

Best Practices for API Reuse and Discovery

Requirement Analysis: The security team requires any external API call to be restricted by an IP include list. This ensures that only specified IP addresses can access the third-party API.

Design Plan: To fulfill this requirement, implementing a proxy for the third-party API is the best approach. This proxy can enforce the IP include list policy.

Implementation Steps:

Create a Proxy API: Set up a new API proxy in Anypoint Platform to act as an intermediary for the third-party API.

Configure IP Include List Policy: Within the Anypoint API Manager, apply the IP whitelist policy to the proxy API. This policy will ensure that only requests from specified IP addresses are allowed to reach the third-party API.

Modify Main API Flow: Update the flow of your main API to call the newly created proxy API instead of directly calling the third-party API.

Testing: Conduct thorough testing to ensure that the proxy API correctly forwards requests to the third-party API only if the requests originate from IPs in the include list.

Advantages:

Security: This method ensures that only approved IPs can access the third-party API, adhering to the security team's requirements.

Manageability: Centralizes the IP restriction management within the API Manager, simplifying maintenance and updates.

References

MuleSoft Documentation on API Proxies

MuleSoft Documentation on IP Whitelist Policy

Explanation

Correct answer is For Each scope in the parent flow On Error Continue error handler in the child flow. You can extract below set of requirements from the question a) Records should be sent to downstream system in the same order that it was received in the array b) Any validation or communication failures should not prevent further processing of the remaining records First requirement can be met using For Each scope in the parent flow and second requirement can be met using On Error Continue scope in child flow so that error will be suppressed.

Explanation

Types of logging:

A) Synchronous: The execution of thread that is processing messages is interrupted to wait for the log message to be fully handled before it can continue.

● The execution of the thread that is processing your message is interrupted to wait for the log message to be fully output before it can continue

● Performance degrades because of synchronous logging

● Used when the log is used as an audit trail or when logging ERROR/CRITICAL messages

● If the logger fails to write to disk, the exception would raise on the same thread that's currently processing the Mule event. If logging is critical for you, then you can rollback the transaction.

B) Asynchronous:

● The logging operation occurs in a separate thread, so the actual processing of your message won’t be delayed to wait for the logging to complete

● Substantial improvement in throughput and latency of message processing

● Mule runtime engine (Mule) 4 uses Log4j 2 asynchronous logging by default

● The disadvantage of asynchronous logging is error handling.

● If the logger fails to write to disk, the thread doing the processing won't be aware of any issues writing to the disk, so you won't be able to rollback anything. Because the actual writing of the log gets differed, there's a chance that log messages might never make it to disk and get lost, if Mule were to crash before the buffers are flushed.

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So Correct answer is: Asynchronous logging can improve Mule event processing throughput while also reducing the processing time for each Mule event

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

Before API developers implement the API specification, it is crucial for the API designer to publish the API specification to Anypoint Exchange and solicit feedback from the API's consumers. This step aligns with MuleSoft's recommended approach to full lifecycle API development, which emphasizes collaboration and feedback to ensure the API meets the needs and expectations of its consumers.

Generating test cases, creating an API portal, and versioning the API specification are important steps in the development lifecycle, but soliciting feedback ensures that any potential issues or improvements are identified early in the process. This collaborative approach helps in building a more effective and consumer-friendly API.

References

MuleSoft API Design Best Practices

Anypoint Platform Documentation on API Development Lifecycle

When leveraging Anypoint MQ Audit Logs, it's important to note that they include logs for operations such as creating, deleting, modifying, and purging queues. These logs are crucial for auditing and monitoring the state and changes made to the message queues within Anypoint MQ. However, they do not include logs for individual message actions like sending, receiving, or browsing messages.

References

MuleSoft Documentation on Anypoint MQ Audit Logs

Anypoint Platform Audit Logging Overview

When a batch job instance running on a runtime fabric environment with two cluster replicas encounters an unexpected failure, the following sequence of events occurs:

Failure Detection: The runtime fabric environment detects the failure of the replica running the batch job.

Replica Replacement: A new replica is provisioned to replace the failed one.

Batch Job State Recovery: MuleSoft’s batch processing mechanism ensures that the state of the batch job is periodically saved (checkpointing). This allows the new replica to resume processing from the last saved state.

Resumption of Processing: The new replica takes over the batch job, continuing from where the previous one left off, thus processing the remaining 99,000 records without starting from scratch or causing duplicate processing.

MuleSoft Documentation on Batch Processing

Runtime Fabric Guide

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JMS (Java Message Service): JMS is a robust messaging standard that supports reliable and asynchronous communication. It allows message producers and consumers to exchange messages via a common message broker.

Transactions with Automatic Acknowledgements: Utilizing JMS transactions ensures that messages are processed reliably. The automatic acknowledgement mode means that once the consumer receives the message, it acknowledges the broker automatically, ensuring that no messages are lost.

Performance and Reliability: JMS transactions offer both high performance and reliability. By enabling transactions, each message processing step can be committed or rolled back, ensuring data integrity.

Cross-Cluster Messaging: For a stock trading company dealing with millions of trades, using JMS transactions allows for consistent and reliable message delivery across different clusters in their network. This approach is more suitable compared to non-transactional or VM queues due to the scale and reliability requirements.

Event-Driven APIs: The APIs can leverage the transactional nature of JMS to ensure that messages exchanged between different services are reliable and can recover gracefully from failures.

MuleSoft Documentation on JMS Connector: MuleSoft JMS Connector

JMS 2.0 Specification: Oracle JMS 2.0

Explanation

High availability is about up-time of your application

A) High availability can be achieved only in CloudHub isn't correct statement. It can be achieved in customer hosted runtime planes as well

B) An object store is a facility for storing objects in or across Mule applications. Mule runtime engine (Mule) uses object stores to persist data for eventual retrieval. It can be used for disaster recovery but not for High Availability. Using object store can't guarantee that all instances won't go down at once. So not an appropriate choice.