MCIA-Level-1-Maintenance MuleSoft Certified Integration Architect

MuleSoft Certified Integration Architect - Level 1 MAINTENANCE

Last Update 19 hours ago Total Questions : 116

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Question # 4

A Mule application is built to support a local transaction for a series of operations on a single database. The Mule application has a Scatter-Gather that participates in the local transaction.

What is the behavior of the Scatter-Gather when running within this local transaction?

Execution of each route within the Scatter-Gather occurs sequentially

Any error that occurs inside the Scatter-Gather will result in a rollback of all the database operations

Execution of all routes within the Scatter-Gather occurs in parallel

Any error that occurs inside the Scatter-Gather will result in a rollback of all the database operations

Execution of each route within the Scatter-Gather occurs sequentially

Any error that occurs inside the Scatter-Gather will NOT result in a rollback of any of the database operations

Execution of each route within the Scatter-Gather occurs in parallel

Any error that occurs inside the Scatter-Gather will NOT result in a rollback of any of the database operations

Question # 5

The ABC company has an Anypoint Runtime Fabric on VMs/Bare Metal (RTF-VM) appliance installed on its own customer-hosted AWS infrastructure.

Mule applications are deployed to this RTF-VM appliance. As part of the company standards, the Mule application logs must be forwarded to an external log management tool (LMT).

Given the company's current setup and requirements, what is the most idiomatic (used for its intended purpose) way to send Mule application logs to the external LMT?

In RTF-VM, install and configure the external LTM's log-forwarding agent

In RTF-VM, edit the pod configuration to automatically install and configure an Anypoint Monitoring agent

In each Mule application, configure custom Log4j settings

In RTF-VM. configure the out-of-the-box external log forwarder

Question # 6

Insurance organization is planning to deploy Mule application in MuleSoft Hosted runtime plane. As a part of requirement , application should be scalable . highly available. It also has regulatory requirement which demands logs to be retained for at least 2 years. As an Integration Architect what step you will recommend in order to achieve this?

It is not possible to store logs for 2 years in CloudHub deployment. External log management system is required.

When deploying an application to CloudHub , logs retention period should be selected as 2 years

When deploying an application to CloudHub, worker size should be sufficient to store 2 years data

Logging strategy should be configured accordingly in log4j file deployed with the application.

Question # 7

A leading bank implementing new mule API.

The purpose of API to fetch the customer account balances from the backend application and display them on the online platform the online banking platform. The online banking platform will send an array of accounts to Mule API get the account balances.

As a part of the processing the Mule API needs to insert the data into the database for auditing purposes and this process should not have any performance related implications on the account balance retrieval flow

How should this requirement be implemented to achieve better throughput?

Implement the Async scope fetch the data from the backend application and to insert records in the Audit database

Implement a for each scope to fetch the data from the back-end application and to insert records into the Audit database

Implement a try-catch scope to fetch the data from the back-end application and use the Async scope to insert records into the Audit database

Implement parallel for each scope to fetch the data from the backend application and use Async scope to insert the records into the Audit database

Question # 8

A company is designing an integration Mule application to process orders by submitting them to a back-end system for offline processing. Each order will be received by the Mule application through an HTTP5 POST and must be acknowledged immediately.

Once acknowledged the order will be submitted to a back-end system. Orders that cannot be successfully submitted due to the rejections from the back-end system will need to be processed manually (outside the banking system).

The mule application will be deployed to a customer hosted runtime and will be able to use an existing ActiveMQ broker if needed. The ActiveMQ broker is located inside the organization's firewall. The back-end system has a track record of unreliability due to both minor network connectivity issues and longer outages.

Which combination of Mule application components and ActiveMQ queues are required to ensure automatic submission of orders to the back-end system while supporting but minimizing manual order processing?

One or more On Error scopes to assist calling the back-end system An Untill successful scope containing VM components for long retries A persistent dead-letter VM queue configure in Cloud hub

An Until Successful scope to call the back-end system One or more ActiveMQ long-retry queues One or more ActiveMQ dead-letter queues for manual processing

One or more on-Error scopes to assist calling the back-end system one or more ActiveMQ long-retry queues A persistent dead-letter Object store configuration in the CloudHub object store service

A batch job scope to call the back in system An Untill successful scope containing Object Store components for long retries. A dead-letter object store configured in the Mule application

Question # 9

An organization has several APIs that accept JSON data over HTTP POST. The APIs are all publicly available and are associated with several mobile applications and web applications. The organization does NOT want to use any authentication or compliance policies for these APIs, but at the same time, is worried that some bad actor could send payloads that could somehow compromise the applications or servers running the API implementations. What out-of-the-box Anypoint Platform policy can address exposure to this threat?

Apply a Header injection and removal policy that detects the malicious data before it is used

Apply an IP blacklist policy to all APIs; the blacklist will Include all bad actors

Shut out bad actors by using HTTPS mutual authentication for all API invocations

Apply a JSON threat protection policy to all APIs to detect potential threat vectors

Question # 10

A new upstream API Is being designed to offer an SLA of 500 ms median and 800 ms maximum (99th percentile) response time. The corresponding API implementation needs to sequentially invoke 3 downstream APIs of very similar complexity. The first of these downstream APIs offers the following SLA for its response time: median: 100 ms, 80th percentile: 500 ms, 95th percentile: 1000 ms. If possible, how can a timeout be set in the upstream API for the invocation of the first downstream API to meet the new upstream API's desired SLA?

Set a timeout of 100 ms; that leaves 400 ms for the other two downstream APIs to complete

Do not set a timeout; the Invocation of this API Is mandatory and so we must wait until it responds

Set a timeout of 50 ms; this times out more invocations of that API but gives additional room for retries

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

Answer:

Explanation:

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

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