Question # 1
| In an organization, the InfoSec team is investigating Anypoint Platform related data traffic.
From where does most of the data available to Anypoint Platform for monitoring and
alerting originate?
| | A. From the Mule runtime or the API implementation, depending on the deployment model | | B. From various components of Anypoint Platform, such as the Shared Load Balancer,
VPC, and Mule runtimes | | C. From the Mule runtime or the API Manager, depending on the type of data | | D. From the Mule runtime irrespective of the deployment model |
D. From the Mule runtime irrespective of the deployment model
Explanation
Correct Answer: From the Mule runtime irrespective of the deployment model
*****************************************
>> Monitoring and Alerting metrics are always originated from Mule Runtimes irrespective
of the deployment model.
>> It may seems that some metrics (Runtime Manager) are originated from Mule Runtime
and some are (API Invocations/ API Analytics) from API Manager. However, this is
realistically NOT TRUE. The reason is, API manager is just a management tool for API
instances but all policies upon applying on APIs eventually gets executed on Mule
Runtimes only (Either Embedded or API Proxy).
>> Similarly all API Implementations also run on Mule Runtimes.
So, most of the day required for monitoring and alerts are originated fron Mule Runtimes
only irrespective of whether the deployment model is MuleSoft-hosted or Customer-hosted
or Hybrid.
Question # 2
| A REST API is being designed to implement a Mule application.
What standard interface definition language can be used to define REST APIs? | | A. Web Service Definition Language(WSDL) | | B. OpenAPI Specification (OAS) | | C. YAML | | D. AsyncAPI Specification |
B. OpenAPI Specification (OAS)
Question # 3
| How are an API implementation, API client, and API consumer combined to invoke and process an API? | | A. The API consumer creates an API implementation, which receives API invocations from an API such that they are processed for an API client | | B. The API client creates an API consumer, which receives API invocations from an API such that they are processed for an API implementation | | C. The ApI consumer creates an API client, which sends API invocations to an API such that they are processed by an API implementation | | D. The ApI client creates an API consumer, which sends API invocations to an API such that they are processed by an API implementation |
C. The ApI consumer creates an API client, which sends API invocations to an API such that they are processed by an API implementation
Explanation
Correct Answer: The API consumer creates an API client, which sends API invocations to an API such that they are processed by an API implementation
*****************************************
Terminology:
API Client - It is a piece of code or program the is written to invoke an API
API Consumer - An owner/entity who owns the API Client. API Consumers write API clients.
API - The provider of the API functionality. Typically an API Instance on API Manager where they are managed and operated.
API Implementation - The actual piece of code written by API provider where the functionality of the API is implemented. Typically, these are Mule Applications running on Runtime Manager.
Question # 4
| A retail company is using an Order API to accept new orders. The Order API uses a JMS
queue to submit orders to a backend order management service. The normal load for
orders is being handled using two (2) CloudHub workers, each configured with 0.2 vCore.
The CPU load of each CloudHub worker normally runs well below 70%. However, several
times during the year the Order API gets four times (4x) the average number of orders.
This causes the CloudHub worker CPU load to exceed 90% and the order submission time
to exceed 30 seconds. The cause, however, is NOT the backend order management
service, which still responds fast enough to meet the response SLA for the Order API.
What is the MOST resource-efficient way to configure the Mule application's CloudHub
deployment to help the company cope with this performance challenge?
| | A. Permanently increase the size of each of the two (2) CloudHub workers by at least four
times (4x) to one (1) vCore | | B. Use a vertical CloudHub autoscaling policy that triggers on CPU utilization greater than
70% | | C. Permanently increase the number of CloudHub workers by four times (4x) to eight (8)
CloudHub workers | | D. Use a horizontal CloudHub autoscaling policy that triggers on CPU utilization greater
than 70% |
D. Use a horizontal CloudHub autoscaling policy that triggers on CPU utilization greater
than 70%
Explanation
Correct Answer: Use a horizontal CloudHub autoscaling policy that triggers on CPU
utilization greater than 70%
The scenario in the question is very clearly stating that the usual traffic in the year is pretty
well handled by the existing worker configuration with CPU running well below 70%. The
problem occurs only "sometimes" occasionally when there is spike in the number of orders
coming in.
So, based on above, We neither need to permanently increase the size of each worker nor
need to permanently increase the number of workers. This is unnecessary as other than
those "occasional" times the resources are idle and wasted.
We have two options left now. Either to use horizontal Cloudhub autoscaling policy to
automatically increase the number of workers or to use vertical Cloudhub autoscaling
policy to automatically increase the vCore size of each worker.
Here, we need to take two things into consideration:
1. CPU
2. Order Submission Rate to JMS Queue
>> From CPU perspective, both the options (horizontal and vertical scaling) solves the
issue. Both helps to bring down the usage below 90%.
>> However, If we go with Vertical Scaling, then from Order Submission Rate perspective,
as the application is still being load balanced with two workers only, there may not be much
improvement in the incoming request processing rate and order submission rate to JMS
queue. The throughput would be same as before. Only CPU utilization comes down.
>> But, if we go with Horizontal Scaling, it will spawn new workers and adds extra hand to
increase the throughput as more workers are being load balanced now. This way we can
address both CPU and Order Submission rate.
Hence, Horizontal CloudHub Autoscaling policy is the right and best answer.
Question # 5
| A company wants to move its Mule API implementations into production as quickly as possible. To protect access to all Mule application data and metadata, the company requires that all Mule applications be deployed to the company's customer-hosted infrastructure within the corporate firewall. What combination of runtime plane and control plane options meets these project lifecycle goals? | | A. Manually provisioned customer-hosted runtime plane and customer-hosted control plane | | B. MuleSoft-hosted runtime plane and customer-hosted control plane | | C. Manually provisioned customer-hosted runtime plane and MuleSoft-hosted control plane | | D. iPaaS provisioned customer-hosted runtime plane and MuleSoft-hosted control plane |
A. Manually provisioned customer-hosted runtime plane and customer-hosted control plane
Explanation
Correct Answer: Manually provisioned customer-hosted runtime plane and customer-hosted control plane
*****************************************
There are two key factors that are to be taken into consideration from the scenario given in the question.
Company requires both data and metadata to be resided within the corporate firewall
Company would like to go with customer-hosted infrastructure.
Any deployment model that is to deal with the cloud directly or indirectly (Mulesoft-hosted or Customer's own cloud like Azure, AWS) will have to share atleast the metadata.
Application data can be controlled inside firewall by having Mule Runtimes on customer hosted runtime plane. But if we go with Mulsoft-hosted/ Cloud-based control plane, the control plane required atleast some minimum level of metadata to be sent outside the corporate firewall.
As the customer requirement is pretty clear about the data and metadata both to be within the corporate firewall, even though customer wants to move to production as quickly as possible, unfortunately due to the nature of their security requirements, they have no other option but to go with manually provisioned customer-hosted runtime plane and customer-hosted control plane.
Question # 6
| A company has created a successful enterprise data model (EDM). The company is committed to building an application network by adopting modern APIs as a core enabler of the company's IT operating model. At what API tiers (experience, process, system) should the company require reusing the EDM when designing modern API data models? | | A. At the experience and process tiers | | B. At the experience and system tiers | | C. At the process and system tiers | | D. At the experience, process, and system tiers |
C. At the process and system tiers
Explanation
Correct Answer: At the process and system tiers
*****************************************
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.
Question # 7
| A company wants to move its Mule API implementations into production as quickly as
possible. To protect access to all Mule application data and metadata, the company
requires that all Mule applications be deployed to the company's customer-hosted
infrastructure within the corporate firewall. What combination of runtime plane and control
plane options meets these project lifecycle goals?
| | A. Manually provisioned customer-hosted runtime plane and customer-hosted control plane | | B. MuleSoft-hosted runtime plane and customer-hosted control plane | | C. Manually provisioned customer-hosted runtime plane and MuleSoft-hosted control plane | | D. iPaaS provisioned customer-hosted runtime plane and MuleSoft-hosted control plane |
A. Manually provisioned customer-hosted runtime plane and customer-hosted control plane
Explanation
Correct Answer: Manually provisioned customer-hosted runtime plane and customerhosted control plane
*****************************************
There are two key factors that are to be taken into consideration from the scenario given in
the question.
>> Company requires both data and metadata to be resided within the corporate firewall
>> Company would like to go with customer-hosted infrastructure.
Any deployment model that is to deal with the cloud directly or indirectly (Mulesoft-hosted
or Customer's own cloud like Azure, AWS) will have to share atleast the metadata.
Application data can be controlled inside firewall by having Mule Runtimes on customer
hosted runtime plane. But if we go with Mulsoft-hosted/ Cloud-based control plane, the
control plane required atleast some minimum level of metadata to be sent outside the
corporate firewall.
As the customer requirement is pretty clear about the data and metadata both to be within
the corporate firewall, even though customer wants to move to production as quickly as
possible, unfortunately due to the nature of their security requirements, they have no other
option but to go with manually provisioned customer-hosted runtime plane and customerhosted control plane.
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