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MuleSoft-Platform-Architect-I Practice Questions

Question # 1
What is a key performance indicator (KPI) that measures the success of a typical C4E that is immediately apparent in responses from the Anypoint Platform APIs?
A. The number of production outage incidents reported in the last 24 hours
B. The number of API implementations that have a publicly accessible HTTP endpoint and are being managed by Anypoint Platform
C. The fraction of API implementations deployed manually relative to those deployed using a CI/CD tool
D. The number of API specifications in RAML or OAS format published to Anypoint Exchange


D. The number of API specifications in RAML or OAS format published to Anypoint Exchange

Explanation

Correct Answer: The number of API specifications in RAML or OAS format published to Anypoint Exchange

*****************************************

>> The success of C4E always depends on their contribution to the number of reusable assets that they have helped to build and publish to Anypoint Exchange. >> It is NOT due to any factors w.r.t # of outages, Manual vs CI/CD deployments or Publicly accessible HTTP endpoints

>> Anypoint Platform APIs helps us to quickly run and get the number of published RAML/OAS assets to Anypoint Exchange. This clearly depicts how successful a C4E team is based on number of returned assets in the response.

Reference: https://help.mulesoft.com/s/question/0D52T00004mXSTUSA4/how-should-acompany-measure-c4e-success


Question # 2
True or False. We should always make sure that the APIs being designed and developed are self-servable even if it needs more man-day effort and resources.
A. FALSE
B. TRUE


B. TRUE

Explanation

Correct Answer: TRUE

*****************************************

As per MuleSoft proposed IT Operating Model, designing APIs and making sure that they are discoverable and self-servable is VERY VERY IMPORTANT and decides the success of an API and its application network.


Question # 3
What Mule application deployment scenario requires using Anypoint Platform Private Cloud Edition or Anypoint Platform for Pivotal Cloud Foundry?
A. When it Is required to make ALL applications highly available across multiple data centers
B. When it is required that ALL APIs are private and NOT exposed to the public cloud
C. When regulatory requirements mandate on-premises processing of EVERY data item, including meta-data
D. When ALL backend systems in the application network are deployed in the organization's intranet


C. When regulatory requirements mandate on-premises processing of EVERY data item, including meta-data

Explanation

Correct Answer: When regulatory requirements mandate on-premises processing of EVERY data item, including meta-data.

*****************************************

We need NOT require to use Anypoint Platform PCE or PCF for the below. So these options are OUT.

>> We can make ALL applications highly available across multiple data centers using CloudHub too.

>> We can use Anypoint VPN and tunneling from CloudHub to connect to ALL backend systems in the application network that are deployed in the organization's intranet.

>> We can use Anypoint VPC and Firewall Rules to make ALL APIs private and NOT exposed to the public cloud.

Only valid reason in the given options that requires to use Anypoint Platform PCE/ PCF is - When regulatory requirements mandate on-premises processing of EVERY data item, including meta-data.


Question # 4
A Mule application exposes an HTTPS endpoint and is deployed to three CloudHub workers that do not use static IP addresses. The Mule application expects a high volume of client requests in short time periods. What is the most cost-effective infrastructure component that should be used to serve the high volume of client requests?
A. A customer-hosted load balancer
B. The CloudHub shared load balancer
C. An API proxy
D. Runtime Manager autoscaling


B. The CloudHub shared load balancer

Explanation

Correct Answer: The CloudHub shared load balancer

*****************************************

The scenario in this question can be split as below:

There are 3 CloudHub workers (So, there are already good number of workers to handle high volume of requests)

The workers are not using static IP addresses (So, one CANNOT use customer load-balancing solutions without static IPs)

Looking for most cost-effective component to load balance the client requests among the workers.

Based on the above details given in the scenario:

Runtime autoscaling is NOT at all cost-effective as it incurs extra cost. Most over, there are already 3 workers running which is a good number. We cannot go for a customer-hosted load balancer as it is also NOT most cost-effective (needs custom load balancer to maintain and licensing) and same time the Mule App is not having Static IP Addresses which limits from going with custom load balancing.

An API Proxy is irrelevant there as it has no role to play w.r.t handling high volumes or load balancing.

So, the only right option to go with and fits the purpose of scenario being most cost-effective is - using a CloudHub Shared Load Balancer.


Question # 5
An API implementation is updated. When must the RAML definition of the API also be updated?
A. When the API implementation changes the structure of the request or response messages
B. When the API implementation changes from interacting with a legacy backend system deployed on-premises to a modern, cloud-based (SaaS) system
C. When the API implementation is migrated from an older to a newer version of the Mule runtime
D. When the API implementation is optimized to improve its average response time


A. When the API implementation changes the structure of the request or response messages

Explanation

Correct Answer: When the API implementation changes the structure of the request or response messages

*****************************************

>> RAML definition usually needs to be touched only when there are changes in the request/response schemas or in any traits on API.

>> It need not be modified for any internal changes in API implementation like performance tuning, backend system migrations etc..


Question # 6
When designing an upstream API and its implementation, the development team has been advised to NOT set timeouts when invoking a downstream API, because that downstream API has no SLA that can be relied upon. This is the only downstream API dependency of that upstream API. Assume the downstream API runs uninterrupted without crashing. What is the impact of this advice?
A. An SLA for the upstream API CANNOT be provided
B. The invocation of the downstream API will run to completion without timing out
C. Each modern API must be easy to consume, so should avoid complex authentication mechanisms such as SAML or JWT D
D. A toad-dependent timeout of less than 1000 ms will be applied by the Mule runtime in which the downstream API implementation executes
Explanation

Correct Answer: An SLA for the upstream API CANNOT be provided.

*****************************************

>> First thing first, the default HTTP response timeout for HTTP connector is 10000 ms (10 seconds). NOT 500 ms.

>> Mule runtime does NOT apply any such "load-dependent" timeouts. There is no such behavior currently in Mule.

>> As there is default 10000 ms time out for HTTP connector, we CANNOT always guarantee that the invocation of the downstream API will run to completion without timing out due to its unreliable SLA times. If the response time crosses 10 seconds then the request may time out.

The main impact due to this is that a proper SLA for the upstream API CANNOT be provided.

Reference: https://docs.mulesoft.com/http-connector/1.5/

http-documentation#parameters-3


Question # 7
A company requires Mule applications deployed to CloudHub to be isolated between nonQuestion production and production environments. This is so Mule applications deployed to nonproduction environments can only access backend systems running in their customerhosted non-production environment, and so Mule applications deployed to production environments can only access backend systems running in their customer-hosted production environment. How does MuleSoft recommend modifying Mule applications, configuring environments, or changing infrastructure to support this type of perenvironment isolation between Mule applications and backend systems?
A. Modify properties of Mule applications deployed to the production Anypoint Platform environments to prevent access from non-production Mule applications
B. Configure firewall rules in the infrastructure inside each customer-hosted environment so that only IP addresses from the corresponding Anypoint Platform environments are allowed to communicate with corresponding backend systems
C. Create non-production and production environments in different Anypoint Platform business groups
D. Create separate Anypoint VPCs for non-production and production environments, then configure connections to the backend systems in the corresponding customer-hosted environments


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

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.

*****************************************

>> 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.

: https://docs.mulesoft.com/runtime-manager/virtual-private-cloud Bottom of Form

Top of Form

An API has been updated in


Question # 8
What is the most performant out-of-the-box solution in Anypoint Platform to track transaction state in an asynchronously executing long-running process implemented as a Mule application deployed to multiple CloudHub workers?
A. Redis distributed cache
B. java.util.WeakHashMap
C. Persistent Object Store
D. File-based storage


C. Persistent Object Store

Explanation:

Correct Answer: Persistent Object Store

*****************************************

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.


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