Pass the MuleSoft MuleSoft Certified Architect MCIA-Level-1 Questions and answers with CertsForce

To hide sensitive data exchanged between API consumers and API implementations while allowing the conversion of tokenized fields back to their original values for other API requests or responses, the best approach is to use tokenization. This involves:

Tokenization Format: Create a tokenization format that will be used to apply a tokenization policy in the API gateway. This format ensures that sensitive fields in message payloads are replaced with tokenized values that maintain a similar format, making them less recognizable as sensitive data.

Tokenization Policy: Apply a tokenization policy in the API gateway that replaces sensitive data with tokenized values.

Detokenization Policy: Apply a corresponding detokenization policy in the API gateway to convert tokenized values back to their original values when required by other APIs.

This method does not require recoding the API implementations and ensures that sensitive data is protected while still being accessible in its original form when necessary.

References

MuleSoft Documentation on Tokenization Policies

API Gateway Security Best Practices

Anypoint MQ is a cloud-based messaging service provided by MuleSoft. It is designed to work within MuleSoft's cloud ecosystem, which can impose certain limitations that might prevent its use in some scenarios:

Message Broker Must Be Hosted On-Premises:

Anypoint MQ is a cloud service and cannot be hosted on-premises. If a company requires its message broker to be hosted within its own data center for security, compliance, or other reasons, Anypoint MQ would not be suitable.

Ability for a Third Party Outside the Company's Network to Consume Events from the Queue:

Anypoint MQ is designed to work primarily within the Anypoint Platform ecosystem. While it does support external consumers, it requires proper security configurations, and there may be limitations or additional steps needed to securely expose queues to third-party systems outside the company's network.

References

MuleSoft Documentation: Anypoint MQ

MuleSoft Anypoint MQ Overview

Explanation

Correct answer is: Add a Mulesoft hosted Anypoint VPC configured and with VPC Peering to the AWS VPC * Connecting to your Anypoint VPC extends your corporate network and allows CloudHub workers to access resources behind your corporate firewall.

* You can connect on-premises data centers through a secured VPN tunnel, or a private AWS VPC through VPC peering, or by using AWS Direct Connect.

MuleSoft Doc Reference : https://docs.mulesoft.com/runtime-manager/virtual-private-cloud

Explanation

CloudHub object store should be in same region where the Mule application is deployed. This will give optimal performance.

Before learning about Cache scope and object store in Mule 4 we understand what is in general Caching is and other related things.

WHAT DOES “CACHING” MEAN?

Caching is the process of storing frequently used data in memory, file system or database which saves processing time and load if it would have to be accessed from original source location every time.

In computing, a cache is a high-speed data storage layer which stores a subset of data, so that future requests for that data are served up faster than is possible by accessing the data’s primary storage location. Caching allows you to efficiently reuse previously retrieved or computed data.

How does Caching work?

The data in a cache is generally stored in fast access hardware such as RAM (Random-access memory) and may also be used in correlation with a software component. A cache’s primary purpose is to increase data retrieval performance by reducing the need to access the underlying slower storage layer.

Caching in MULE 4

In Mule 4 caching can be achieved in mule using cache scope and/or object-store. Cache scope internally uses Object Store to store the data.

What is Object Store

Object Store lets applications store data and states across batch processes, Mule components, and applications, from within an application. If used on cloud hub, the object store is shared between applications deployed on Cluster.

Cache Scope is used in below-mentioned cases:

● Need to store the whole response from the outbound processor

● Data returned from the outbound processor does not change very frequently

● As Cache scope internally handle the cache hit and cache miss scenarios it is more readable

Object Store is used in below-mentioned cases:

● Need to store custom/intermediary data

● To store watermarks

● Sharing the data/stage across applications, schedulers, batch.

If CloudHub object store is in same region where the Mule application is deployed it will aid in fast access of data and give optimal performance.

Mocking REST API Invocations:

To ensure the unit tests do not make actual calls to external REST APIs, which can be unreliable and slow, it is best to mock these invocations. Mocking allows you to simulate the behavior of the external API and provide predefined responses.

Achieving Test Coverage:

By mocking the REST API invocations in your MUnit tests, you can focus on testing the logic within the Mule application itself. This ensures high test coverage and isolates your tests from external dependencies.

Execution of MUnit Tests:

Configure MUnit to return mock responses for the API calls. This enables the MUnit tests to run quickly and consistently, as they are not dependent on the external system's availability or performance.

References:

MuleSoft Documentation on MUnit Testing

Best practices for Mocking in MUnit

Explanation

Correct answer is When a Mule runtime on a given customer-hosted server is experiencing high memory consumption during certain periods Using Anypoint Monitoring, you can configure two different types of alerts: Basic alerts for servers and Mule apps Limit per organization: Up to 50 basic alerts for users who do not have a Titanium subscription to Anypoint Platform You can set up basic alerts to trigger email notifications when a metric you are measuring passes a specified threshold. You can create basic alerts for the following metrics for servers or Mule apps: For on-premises servers and CloudHub apps: * CPU utilization * Memory utilization * Thread count Advanced alerts for graphs in custom dashboards in Anypoint Monitoring. You must have a Titanium subscription to use this feature. Limit per organization: Up to 20 advanced alerts

The File Transfer Protocol (FTP) uses the Transmission Control Protocol (TCP) for reliable communication. TCP is one of the core protocols of the Internet Protocol Suite and provides reliable, ordered, and error-checked delivery of a stream of data between applications running on hosts communicating via an IP network. FTP relies on TCP to ensure that all data packets are delivered accurately and in the correct sequence, which is essential for the reliable transfer of files between a client and server.

References

IETF RFC 959 - File Transfer Protocol (FTP)

TCP/IP Protocol Suite Documentation

Explanation

Before we answer this question , we need to understand what median (50th percentile) and 80th percentile means. If the 50th percentile (median) of a response time is 500ms that means that 50% of my transactions are either as fast or faster than 500ms.

If the 90th percentile of the same transaction is at 1000ms it means that 90% are as fast or faster and only 10% are slower. Now as per upstream SLA , 99th percentile is 800 ms which means 99% of the incoming requests should have response time less than or equal to 800 ms. But as per one of the backend API , their 95th percentile is 1000 ms which means that backend API will take 1000 ms or less than that for 95% of. requests. As there are three API invocation from upstream API , we can not conclude a timeout that can be set to meet the desired SLA as backend SLA's do not support it.

Let see why other answers are not correct.

1) Do not set a timeout --> This can potentially violate SLA's of upstream API

2) Set a timeout of 100 ms; ---> This will not work as backend API has 100 ms as median meaning only 50% requests will be answered in this time and we will get timeout for 50% of the requests. Important thing to note here is, All APIs need to be executed sequentially, so if you get timeout in first API, there is no use of going to second and third API. As a service provider you wouldn't want to keep 50% of your consumers dissatisfied. So not the best option to go with.

*To quote an example: Let's assume you have built an API to update customer contact details.

- First API is fetching customer number based on login credentials

- Second API is fetching Info in 1 table and returning unique key

- Third API, using unique key provided in second API as primary key, updating remaining details

* Now consider, if API times out in first API and can't fetch customer number, in this case, it's useless to call API 2 and 3 and that is why question mentions specifically that all APIs need to be executed sequentially.

3) Set a timeout of 50 ms --> Again not possible due to the same reason as above Hence correct answer is No timeout is possible to meet the upstream API's desired SLA; a different SLA must be negotiated with the first downstream API or invoke an alternative API

To meet the reliability requirements for Mule applications deployed to a Runtime Fabric (RTF) cluster, where data needs to be shared across application replicas and persist through restarts, the best approach is to use Anypoint Object Store v2. This service is designed to provide persistent storage that can be shared among different application instances and across restarts. Steps include:

Configure Object Store v2: Set up Anypoint Object Store v2 in the Mule application to handle data storage needs.

Persistent Data Handling: Ensure that the configuration allows data to be shared and persist, meeting the requirements for reliability and consistency.

This solution leverages MuleSoft's cloud-based storage service optimized for these use cases, ensuring data integrity and availability.

References

MuleSoft Documentation on Object Store v2

Configuring Persistent Data Storage in MuleSoft

A MuleSoft developer can use Anypoint Studio to implement an API as a Mule application, run the application locally, and execute unit tests against the running application. Anypoint Studio is an integrated development environment (IDE) for designing, building, testing, and deploying Mule applications. It provides tools for local development and testing, including MUnit for creating and running unit tests, making it a comprehensive solution for developing MuleSoft applications.

References:

Anypoint Studio Overview

Using MUnit for Unit Testing