MuleSoft-Platform-Architect-I Practice Test

Explanation

Correct Answer: Create separate Anypoint VPCs for non-production and production environments, then configure connections to the backend systems in the corresponding customer-hosted environments.

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Creating different Business Groups does NOT make any difference w.r.t accessing the non-prod and prod customer-hosted environments. Still they will be accessing from both Business Groups unless process network restrictions are put in place.

We need to modify or couple the Mule Application Implementations with the environment. In fact, we should never implements application coupled with environments by binding them in the properties. Only basic things like endpoint URL etc should be bundled in properties but not environment level access restrictions.

IP addresses on CloudHub are dynamic until unless a special static addresses are assigned. So it is not possible to setup firewall rules in customer-hosted infrastrcture. More over, even if static IP addresses are assigned, there could be 100s of applications running on cloudhub and setting up rules for all of them would be a hectic task, non-maintainable and definitely got a good practice.

The best practice recommended by Mulesoft (In fact any cloud provider), is to have your Anypoint VPCs seperated for Prod and Non-Prod and perform the VPC peering or VPN tunneling for these Anypoint VPCs to respective Prod and Non-Prod customer-hosted environment networks.

Reference: [: https://docs.mulesoft.com/runtime-manager/virtual-private-cloud, , Bottom of Form, Top of Form, , ]

Explanation

Correct Answer: At the process and system tiers

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Experience Layer APIs are modeled and designed exclusively for the end user's experience. So, the data models of experience layer vary based on the nature and type of such API consumer. For example, Mobile consumers will need light-weight data models to transfer with ease on the wire, where as web-based consumers will need detailed data models to render most of the info on web pages, so on. So, enterprise data models fit for the purpose of canonical models but not of good use for experience APIs.

That is why, EDMs should be used extensively in process and system tiers but NOT in experience tier.

Explanation

Correct Answer: Increase the size of the CloudHub worker(s)

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The key details that we can take out from the given scenario are:

API implementation uses a database bulk insert command to submit all the purchase data to a database

JDBC driver processes the data into a set of several temporary disk files on the CloudHub worker

Sometimes a request fails and the logs show a message indicating an out-of-file-space message

Based on above details:

Both auto-scaling options does NOT help because we cannot set auto-scaling rules based on error messages. Auto-scaling rules are kicked-off based on CPU/Memory usages and not due to some given error or disk space issues.

Increasing the number of CloudHub workers also does NOT help here because the reason for the failure is not due to performance aspects w.r.t CPU or Memory. It is due to disk-space.

Moreover, the API is doing bulk insert to submit the received batch data. Which means, all data is handled by ONE worker only at a time. So, the disk space issue should be tackled on "per worker" basis. Having multiple workers does not help as the batch may still fail on any worker when disk is out of space on that particular worker.

Therefore, the right way to deal this issue and resolve this is to increase the vCore size of the worker so that a new worker with more disk space will be provisioned.

Explanation:

Correct Answer: Persistent Object Store

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Redis distributed cache is performant but NOT out-of-the-box solution in Anypoint Platform

File-storage is neither performant nor out-of-the-box solution in Anypoint Platform

java.util.WeakHashMap needs a completely custom implementation of cache from scratch using Java code and is limited to the JVM where it is running. Which means the state in the cache is not worker aware when running on multiple workers. This type of cache is local to the worker. So, this is neither out-of-the-box nor worker-aware among multiple workers on cloudhub.

https://www.baeldung.com/java-weakhashmap

Persistent Object Store is an out-of-the-box solution provided by Anypoint Platform which is performant as well as worker aware among multiple workers running on CloudHub.

https://docs.mulesoft.com/object-store/

So, Persistent Object Store is the right answer.

Explanation

Correct Answer: When there is one CloudHub deployment of the API implementation to three CloudHub workers that must share the cache state.

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Key details in the scenario:

Use the CloudHub Object Store via the Object Store connector

Considering above details:

CloudHub Object Stores have one-to-one relationship with CloudHub Mule Applications.

We CANNOT use an application's CloudHub Object Store to be shared among multiple Mule applications running in different Regions or Business Groups or Customer-hosted Mule Runtimes by using Object Store connector.

If it is really necessary and very badly needed, then Anypoint Platform supports a way by allowing access to CloudHub Object Store of another application using Object Store REST API. But NOT using Object Store connector.

So, the only scenario where we can use the CloudHub Object Store via the Object Store connector to persist the cache’s state is when there is one CloudHub deployment of the API implementation to multiple CloudHub workers that must share the cache state.