MCIA Practice Exam
docx
keyboard_arrow_up
School
Xavier University *
*We aren’t endorsed by this school
Course
12
Subject
Computer Science
Date
May 14, 2024
Type
docx
Pages
55
Uploaded by ElderRain13987
1)
Question:
An organization is sizing an Anypoint Virtual Private Cloud (VPC) to extend its
internal network to CloudHub 1.0. For this sizing calculation, the organization
assumes three production-type environments will each support up to 150 Mule
application deployments. Each Mule application deployment is expected to be
configured with two CloudHub 1.0 workers and will use the zero-downtime feature in
CloudHub 1.0. This is expected to result in, at most, several Mule application
deployments per hour.
What is the minimum number of IP addresses that should be configured for this VPC
resulting in the smallest usable range of private IP addresses to support the
deployment and zero- downtime of these 150 Mule applications (not accounting for
any future Mule applications)?
A)
10.0.0.0/24 (256 IPs)
B) 10.0.0.0/23 (512 IPs)
C) 10.0.0.0/22 (1024 IPs)
D) 10.0.0.0/21 (2048 IPs)
Answer:
To determine the minimum number of IP addresses required for the Anypoint Virtual
Private Cloud (VPC) based on the provided information, let's analyse the
requirements:
1. **
Number of Mule application deployments:
** 3 environments * 150
deployments/environment = 450 deployments.
2. **
Number of workers per deployment:
** 2 CloudHub workers per deployment.
Now, considering the zero-downtime feature, several Mule application deployments
can occur per hour, but the exact number is not specified. To ensure sufficient IP
addresses for scaling and potential simultaneous deployments, we can make a
reasonable assumption about the maximum number of concurrent deployments.
Let's assume a maximum of 10 simultaneous deployments (this is just a hypothetical
number, and you may need to adjust it based on your specific requirements).
So, the total number of IP addresses required = 450 deployments * 2
workers/deployment + 10 simultaneous deployments
[
= 450 times 2 + 10 = 910
]
Now, let's choose the smallest usable range of private IP addresses that covers at least
910 addresses:
The options provided are:
A) 10.0.0.0/24 (256 IPs)
B) 10.0.0.0/23 (512 IPs)
C) 10.0.0.0/22 (1024 IPs)
D) 10.0.0.0/21 (2048 IPs)
Since 910 addresses fall between 512 and 1024, the correct answer would be:
**C) 10.0.0.0/22 (1024 IPs) **
This subnet provides enough addresses to accommodate the calculated minimum
number of IP addresses needed for the given scenario.
2)
Question
:
A Mule application is deployed to a single CloudHub 1.0 worker, and the public URL
appears in Runtime Manager as the App URL. Requests are sent by external web
clients over the public internet to the Mule application's App URL. Each of these
requests is routed to the HTTPS Listener event source of the running Mule
application. Later, the DevOps team edits some properties of this running Mule
application in Runtime Manager. Immediately after the new property values are
applied in Runtime Manager, how is the current Mule application deployment
affected, and how will future web client requests to the Mule application be handled?
A) CloudHub 1.0 will redeploy the Mule application to the old CloudHub 1.0 worker.
New web client requests are routed to the old CloudHub 1.0 worker both before and
after the Mule application is redeployed.
B) CloudHub 1.0 will redeploy the Mule application to a new CloudHub 1.0 worker.
New web client requests are routed to the old CloudHub 1.0 worker until the new
CloudHub 1.0 worker is available.
C) CloudHub 1.0 will redeploy the Mule application to the old CloudHub 1.0 worker.
New web client requests will return an error until the Mule application is redeployed
to the old CloudHub 1.0 worker.
D) CloudHub 1.0 will redeploy the Mule application to a new CloudHub 1.0 worker.
New web client requests will return an error until the new CloudHub 1.0 worker is
available.
Answer
: In CloudHub, when you edit properties of a running Mule application in Runtime
Manager, the changes are applied without redeploying the application. This is known
as dynamic configuration updates. The application remains running, and new
configurations take effect immediately.
Therefore, in the scenario described:
**
How is the current Mule application deployment affected immediately after
the new property values are applied?
**
**
Answer: D)
CloudHub 1.0 will redeploy the Mule application to a new CloudHub
1.0 worker. New web client requests will return an error until the new CloudHub 1.0
worker is available. **
This statement is not accurate for dynamic configuration updates. Dynamic updates
do not involve redeployment to a new worker, and existing requests are not
interrupted.
**
How will future web client requests to the Mule application be handled?
**
**Answer: B) CloudHub 1.0 will redeploy the Mule application to a new CloudHub
1.0 worker. New web client requests are routed to the old CloudHub 1.0 worker until
the new CloudHub 1.0 worker is available. **
When dynamic configuration updates are applied, the Mule application is not
redeployed to a new worker immediately. However, if you later decide to explicitly
redeploy the application, the new deployment may go to a different worker. Until that
new worker is fully available, existing requests will continue to be served by the old
worker.
So, the correct answer is a combination of options D and B:
**D) CloudHub 1.0 will redeploy the Mule application to a new CloudHub 1.0
worker. New web client requests are routed to the old CloudHub 1.0 worker until the
new CloudHub 1.0 worker is available. **
3)
Question
:
An airline's passenger reservations centre is designing an integration solution that
combines invocations of three different System APIs (bookFlight, bookHotel, and
bookCar) in a business transaction. Each System API makes calls to a single database.
The entire business transaction must be rolled back when at least one of the APIs fails.
What is the most direct way to integrate these APIs in near real-time that provides the
best balance of consistency, performance, and reliability?
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
A) Implement an extended Architecture (XA) transaction manager in a Mule
application using a Saga pattern. Connect each API implementation with the Mule
application using XA transactions. Apply various compensating actions depending on
where a failure occurs.
B) Implement local transactions within each API implementation Configure each API
implementation to also participate in the same extended Architecture (XA)
transaction. Implement caching in each API implementation to improve performance.
C) Implement extended Architecture (XA) transactions between the API
implementations. Coordinate between the API implementations using a Saga pattern
Implement caching in each API implementation to improve performance.
D) Implement local transactions in each API implementation. Coordinate between the
API implementations using a Saga pattern. Apply various compensating actions
depending on where a failure occurs.
Answer
: The most direct way to integrate the System APIs in near real-time with the best balance of consistency, performance, and reliability, considering the requirement for the entire business transaction to be rolled back when at least one API fails, is by using a Saga pattern.
**
Option D is the most suitable choice:
**
D) **
Implement local transactions in each API implementation. Coordinate between the API implementations using a Saga pattern. Apply various compensating actions depending on where a failure occurs.
**
Explanation:
**
Local Transactions:
** Each API implementation should use local transactions to ensure consistency within its own database operations. Local transactions are generally more performant than distributed transactions.
**
Saga Pattern:
** The Saga pattern is designed for long-lived transactions where a sequence of local transactions is coordinated to achieve a global outcome. If any step in the saga fails, compensating transactions are executed to undo the effects of the preceding steps. This aligns well with the requirement of rolling back the entire business transaction if at least one API fails.
**
Compensating Actions:
** Using compensating actions ensures that if a failure occurs at any point in the saga, appropriate actions can be taken to revert the changes made by the preceding steps.
While options A and C mention the use of XA transactions, they might introduce more
complexity and potentially impact performance. The Saga pattern, as described in option D, is a more practical and straightforward approach for managing distributed transactions with compensating actions.
4)
Question:
An organization plans to leverage the Anypoint Security policies for Edge to enforce
security policies on nodes deployed to its Anypoint Runtime Fabric.
Which two considerations must be kept in mind to configure and use the security
policies? (Choose two.)
A)
Runtime Fabric with inbound traffic must be configured.
B)
HTTP limits policies are designed to protect the network nodes against malicious
clients such as DoS applications trying to flood the network to prevent legitimate
traffic to APIs.
C)
Runtime Fabric with outbound traffic must be configured.
D)
Web application firewall policies allow configuring an explicit list of IP addresses
that can access deployed endpoints.
E) Anypoint Security for Edge entitlement must be configured for the Anypoint
Platform account.
Answer
: The correct considerations to keep in mind when configuring and using Anypoint
Security policies for Edge on nodes deployed to Anypoint Runtime Fabric are:
B) **
HTTP limits policies are designed to protect the network nodes against
malicious clients such as DoS applications trying to flood the network to prevent
legitimate traffic to APIs.
**
Explanation: HTTP limits policies help protect against various types of attacks,
including Denial of Service (DoS) attacks, by limiting the rate and size of incoming
requests.
E) **
Anypoint Security for Edge entitlement must be configured for the
Anypoint Platform account.
**
Explanation: Anypoint Security for Edge is a feature that requires proper entitlement
and configuration for the Anypoint Platform account. This entitlement ensures that the
security policies are available and can be applied to the deployed nodes.
The other options (A, C, D) are not specifically related to Anypoint Security policies
for Edge. However, configuring inbound and outbound traffic (consideration A and C)
is generally important for network configurations, but they are not specific to
Anypoint Security policies. Similarly, the explicit list of IP addresses for access
control (consideration D) is not a direct consideration for Anypoint Security policies.
5)
Question:
An API is being implemented using the components of Anypoint Platform. The API
implementation must be managed and governed (by applying API policies) on
Anypoint Platform. What must be done before the API implementation can be
governed by Anypoint Platform? A) The OAS definitions in the Design Centre project of the API and the API
implementation's corresponding Mule project in Anypoint Studio must be
synchronized.
B) A RAML definition of the API must be created in API Designer so the API can
then be published to Anypoint Exchange.
C) The API must be published to the organization's public portal so potential
developers and API consumers both inside and outside of the organization can interact
with the API.
D) The API must be published to Anypoint Exchange, and a corresponding API
Instance ID must be obtained from API Manager to be used in the API
implementation.
Answer
: The correct answer is:
D) **
The API must be published to Anypoint Exchange, and a corresponding
API Instance ID must be obtained from API Manager to be used in the API
implementation.
**
Explanation:
**
Publishing to Anypoint Exchange:
** Anypoint Exchange is the repository where
APIs, templates, connectors, and other reusable assets are stored and shared. Before
an API can be governed by Anypoint Platform, it needs to be published to Anypoint
Exchange.
**
API Instance ID from API Manager:
** After publishing the API to Anypoint
Exchange, it must be subscribed to and managed by API Manager. When the API is
managed, it gets a unique API Instance ID assigned by API Manager. This API
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
Instance ID is used in the API implementation to associate the implementation with
the managed API on Anypoint Platform.
Options A, B, and C do not directly address the steps required for governance on
Anypoint Platform:
**
Option A (Synchronizing OAS definitions):
** While synchronization between
the Design Centre project and the Mule project is important for consistency, it is not a
prerequisite for governance. The API Instance ID from API Manager is what
establishes the connection between the API implementation and the governed API.
**
Option B (Creating RAML definition in API Designer):
** Creating a RAML
definition in API Designer is a step in designing the API, but it doesn't directly enable
governance. The API must still be published to Anypoint Exchange and managed by
API Manager.
**
Option C (Publishing to the organization's public portal):
** While publishing
to a public portal is a step in making the API discoverable, it is not a prerequisite for
governance. The key step is publishing to Anypoint Exchange and obtaining the API
Instance ID from API Manager.
6)
Question
:
An internet company is building a new search engine that indexes sites on the internet
and ranks them according to various signals. The management team wants various
features added to the site. There is a team of software developers eager to start on the
functional requirements received from the management team.
Which two traditional architectural requirements should the integration architect
ensure are in place to support the new search engine? (Choose two.)
A) New features can be added to the system with ease.
B) Relevant search results are returned for a query.
C) Search results are returned in the language chosen by the user.
D) Search result listings link to the correct website.
E) The system can handle increased load as more people utilize the engine.
Answer
:
The two traditional architectural requirements that the integration architect should
ensure are in place to support the new search engine are:
A) **
New features can be added to the system with ease.
**
Explanation: This requirement emphasizes the need for a modular and extensible
architecture. The system should be designed in a way that allows new features to be
added without significant rework. This can be achieved through a modular and
scalable architecture.
E) **
The system can handle increased load as more people utilize the engine
. **
Explanation: This requirement addresses the scalability and performance aspects of
the system. As the user base grows, the system should be able to handle increased
load efficiently without degradation in performance. Scalability considerations
involve horizontal scaling, load balancing, and other measures to ensure the system's
capacity can be expanded as needed.
While the other options (B, C, D) are important functional requirements for a search
engine, they are more related to the behaviour and functionality of the search engine
rather than the architectural considerations. The architectural requirements (A and E)
focus on the system's design and ability to evolve and scale.
7)
Question
:
An organization has a mission-critical application that processes some of its valuable
real-time transactions. The application needs to be highly available, and the
organization does not have any cost constraints. But it expects minimal downtime.
Which high-availability option supports the organization's requirements?
A) Active-Active
B) Hot Standby - Active-Passive
C) Warm Standby
D) Cold Standby
Answer
:
For a mission-critical application that requires high availability with minimal
downtime and where cost constraints are not a primary concern, the option that best
supports these requirements is:
A) **
Active-Active
**
Explanation:
**
Active-Active:
** In an Active-Active configuration, multiple instances of the
application are actively processing transactions simultaneously. Each instance is
capable of handling the full load, and there is load balancing to distribute traffic
across all instances. This setup provides high availability by allowing continued
operation even if one instance experiences issues. It minimizes downtime as the other
instances can take over seamlessly.
**
Hot Standby - Active-Passive:
** In a Hot Standby - Active-Passive setup, there is
a primary active instance handling transaction, and a standby (passive) instance ready
to take over if the primary fails. While this provides high availability, the passive
instance is not actively processing transactions until a failover occurs.
**
Warm Standby:
** In a Warm Standby configuration, a standby instance is ready
to take over, but it may take some time to fully start and become operational. This
introduces a longer downtime during failover compared to Active-Active.
**
Cold Standby:
** In a Cold Standby setup, the standby instance is not actively
running. It needs to be started and initialized when a failover is required, leading to
longer downtime compared to Warm Standby and Active-Active.
Active-Active is typically the most preferred option for organizations with minimal
downtime expectations and no significant cost constraints because it allows for
continuous processing of transactions even in the event of failures.
8)
Question
:
A Mule application is deployed to an existing Runtime Fabric (RTF) cluster and must
access the data saved in the Object Store V2 by a CloudHub application.
Which steps should be followed to achieve the requirement and enable the shared
Object Store access across these two applications?
A) Obtain the Client ID and Client Secret from the Business Group
Obtain the access token from the /object-store/token endpoint.
Invoke the Object Store API from the application deployed in RTF including the
Bearer token.
B) Obtain the Access Token from the /oauth2/token endpoint
Invoke the Access Management API to approve the read access.
Invoke the Object Store API from the application in CloudHub including the Bearer
token.
C) Obtain the Access Token from the CloudHub App Object Store
Obtain the Client ID and Client Secret from the /object-store/client credentials
endpoint.
Invoke the Object Store API including the Bearer token.
D) Obtain the Client ID and Client Secret from the CloudHub App Object Store
Obtain the access token from the /oauth2/token endpoint
Invoke from the application deployed in RTF the Object Store API including the
Bearer token.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
Answer
: The correct steps to achieve the requirement and enable shared Object Store access
across two applications (one deployed in CloudHub and the other in Runtime Fabric)
are:
D) **
Obtain the Client ID and Client Secret from the CloudHub App Object
Store. Obtain the access token from the /oauth2/token endpoint. Invoke from the
application deployed in RTF the Object Store API including the Bearer token.
**
Explanation:
1. **
Obtain the Client ID and Client Secret from the CloudHub App Object
Store:
** This involves retrieving the necessary credentials to authenticate and obtain
an access token.
2. **
Obtain the access token from the /oauth2/token endpoint:
** Authenticate
using the obtained Client ID and Client Secret to get an access token.
3. **
Invoke from the application deployed in RTF the Object Store API
including the Bearer token:
** Use the obtained access token (Bearer token) to
make requests to the Object Store API.
This approach ensures that the Runtime Fabric application can access the data saved
in the Object Store V2 by a CloudHub application.
Options A, B, and C include incorrect sequences or reference endpoints and entities
that are not directly related to the Object Store V2 in the context of Mule applications
and Runtime Fabric.
9)
NEED TO SET
10)
Question
:
An organization is automating the deployment of several Mule applications to a single
customer-hosted Mule runtime. There is also a corporate regulatory requirement to
have all payload data and usage data reside in the organization's network. The
automation will be invoked from one of the organization's internal systems and should
not involve connecting to Runtime Manager in Anypoint Platform. Which Anypoint
Platform component(s) and REST API(s) are required to configure the automated
deployment of the Mule applications?
A) The Anypoint Monitoring REST API (without any agents) to deploy Mule
applications to the Mule runtime using Anypoint Monitoring
B) A Runtime Manager agent installed in the Mule runtime
The Runtime Manager agent REST API to deploy the Mule applications.
C) The Runtime Manager REST API (without any agents) to deploy the Mule
applications directly to the Mule runtime
D) An Anypoint Monitoring agent installed in the Mule runtime
The Anypoint Monitoring REST API to deploy the Mule applications.
Answer
:
The correct option for configuring the automated deployment of Mule applications to
a customer-hosted Mule runtime without connecting to Runtime Manager is:
C) **
The Runtime Manager REST API (without any agents) to deploy the Mule
applications directly to the Mule runtime.
**
Explanation:
The Runtime Manager REST API allows you to programmatically manage and deploy
Mule applications. This API can be used to deploy applications directly to the Mule
runtime without relying on a Runtime Manager agent.
Options A and D mention the Anypoint Monitoring REST API, which is typically
used for monitoring and managing application metrics. It is not the primary API for
deploying Mule applications.
Option B mentions the Runtime Manager agent REST API but using the Runtime
Manager REST API directly (without agents) is a valid approach and aligns with the
requirement of not connecting to Runtime Manager in Anypoint Platform.
Therefore, the correct choice for automating the deployment without connecting to
Runtime Manager is to use the Runtime Manager REST API directly (Option C).
11)
NEED TO SET
12)
Question
:
Answer
:
With the provided configuration for the repeatable in-memory stream:
- **
Initial Buffer Size:
** 512 KB
- **
Buffer Size Increment:
** 512 KB
- **
Max Buffer Size:
** 512 KB
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
The connector will use an in-memory buffer to process the payload. When the
payload size exceeds the initial buffer size, the buffer will dynamically grow in
increments specified by the buffer size increment. However, the maximum size of the
buffer is capped at the max buffer size.
Given that the output payload size is 1,000 KB, and the max buffer size is configured
to be 512 KB, the behaviour is:
**B) The Mule runtime stops with a java.lang.OutOfMemoryError
.**
Explanation:
- The initial buffer size of 512 KB is not sufficient to accommodate the entire payload
(1,000 KB).
- The buffer size increment is not used because the buffer cannot grow beyond the
max buffer size.
- As a result, the Mule runtime will attempt to allocate memory beyond the allowed
maximum, leading to a java.lang.OutOfMemoryError
.
To avoid this issue, you may consider increasing the max buffer size to accommodate
larger payloads or use a different streaming strategy based on your specific
requirements.
13)
Question
:
An organization uses a set of customer-hosted Mule runtimes that are managed using
the MuleSoft-hosted control plane. What is a condition that can be alerted on from
Anypoint Runtime Manager without any custom components or custom coding?
A)
When an SSL certificate used by one of the deployed Mule applications is about
to expire.
B)
When a Mule runtime license installed on a Mule runtime is about to expire.
C)
When a Mule runtime's customer-hosted server is about to run out of disk space
D) When a Mule runtime on a given customer-hosted server is experiencing high
memory consumption during certain periods
Answer
:
As of my last knowledge update in January 2022, the available features in Anypoint
Runtime Manager may have evolved. However, based on the information available up
to that point, the condition that can be alerted on from Anypoint Runtime Manager
without any custom components or custom coding is:
A) **
When an SSL certificate used by one of the deployed Mule applications is
about to expire.
**
Explanation:
- Anypoint Runtime Manager typically provides monitoring and management
capabilities for Mule runtimes, and SSL certificates are part of the configuration for
secure communication.
- SSL certificate expiration is a critical event that can impact the security and proper
functioning of an application. Anypoint Runtime Manager often includes features for
monitoring SSL certificate expiration and generating alerts when certificates are about
to expire.
While certain monitoring features may evolve, it's advisable to refer to the latest
Anypoint Runtime Manager documentation or the Anypoint Platform interface to
confirm the available monitoring and alerting capabilities.
14)
NEED TO SET
15)
Question
:
In an organization, there are multiple backend systems that contain customer-related
data. There are multiple client systems that request the customer data from only one or
more backend systems. How can the integration between the source and target
systems be designed to maximize efficiency?
A) Create a single Experience API with one endpoint for all consumers.
Receive the request and transform it into a Common Data Model.
Have a single Process API that will route it to a single System API. The System API is
designed to have multiple connections to multiple end systems.
B) Create multiple Experience APIs exposed to the different end users. Have separate
Process APIs to route the request to the different System APIs and send back the
response.
C) Create a single Experience API and expose multiple endpoints.
Have separate Process APIs to route the request to the different System APIs and send
back the response.
D) Create a single Experience API with one endpoint for all consumers.
Receive the request, transform it into a Common Data Model, and then send it to the
Process API.
Have a single Process API that will route it to different System APIs using content-
based routing.
Answer
:
The most suitable approach for maximizing efficiency in the integration between
multiple backend systems and multiple client systems is:
B) **
Create multiple Experience APIs exposed to the different end users. Have
separate Process APIs to route the request to the different System APIs and send
back the response.
**
Explanation:
**
Multiple Experience APIs:
** This approach recognizes the different needs of
various client systems and provides dedicated Experience APIs for each end user. This
allows for tailored experiences based on the requirements of different clients.
**
Separate Process APIs:
** By having separate Process APIs, you can design
specific routing logic for each client or group of clients. This enables a more modular
and maintainable architecture, as changes in one Process API do not affect others.
**
Routing to Different System APIs:
** The use of separate Process APIs to route
requests to different System APIs allows for flexibility in connecting to the
appropriate backend systems based on the client's needs. This approach supports a
more scalable and adaptable integration architecture.
While option A involves a single System API with multiple connections to multiple
end systems, it might not be as efficient if different clients have significantly different
requirements. Option B provides a more modular and scalable approach to meet the
specific needs of various client systems.
16)
Question:
A developer is developing an MUnit test suite for a Mule application. This application
must access third-party vendor SOAP services. In the CI/CD pipeline, access to third-
party vendor services is restricted. Without MUnits, a successful run and coverage
report score is less than the threshold, and builds will fail.
Which solution can be implemented to execute MUnits successfully?
A) In MUnits, mock a SOAP service invocation and provide a mock response for
those calls
B) For the CI/CD pipeline, add a skip clause in the flow for invoking SOAP services
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
C) In the CI/CD pipeline, create and deploy mock SOAP services
D) In MUnits, invoke a dummy SOAP service to send a mock response for those calls
Answer
: The solution that can be implemented to execute MUnits successfully in a CI/CD
pipeline, where access to third-party vendor services is restricted, is:
A) **
In MUnits, mock a SOAP service invocation and provide a mock response
for those calls.
**
Explanation:
- **
Mocking SOAP Service Invocation:
** MUnit provides capabilities for mocking
external services, including SOAP services. You can mock the SOAP service
invocation within your MUnit tests and provide predefined mock responses. This
allows you to simulate the behaviour of the third-party vendor services without
actually making real calls.
- **
CI/CD Pipeline Consideration:
** When running the tests in the CI/CD
pipeline, you won't need access to the actual third-party vendor services. Instead, the
MUnit tests will use the mocked responses, enabling a successful run even in
environments where external service access is restricted.
Options B, C, and D don't directly address the specific need of testing SOAP service
invocations with restricted access to third-party vendor services.
Option B (adding a skip clause) might result in incomplete test coverage and doesn't
allow for the comprehensive testing of SOAP service integrations.
Option C (creating and deploying mock SOAP services) introduces additional
complexity and may not be necessary for unit testing within the MUnit framework.
Option D (invoking a dummy SOAP service) might be feasible but using MUnit's
built-in mocking capabilities (Option A) is a more direct and focused approach for
unit testing SOAP service interactions.
17)
Question
:
What are two considerations when designing Mule APIs and integrations that leverage
an enterprise-wide common data model (CDM)? (Choose two.)
A) Changes made to the data model do not impact the implementations of the APIs.
B) The CDM typically does not model experience-level APIs.
C) The CDM models multiple definitions of a given data type based on separate
domains.
D) All data types required by the APIs are not typically defined by the CDM.
E) The CDM typically does not model process-level APIs.
Answer
: The two considerations when designing Mule APIs and integrations that leverage an
enterprise-wide common data model (CDM) are:
A) **
Changes made to the data model do not impact the implementations of the
APIs.
**
Explanation: One of the key benefits of using a common data model is to decouple
the data model from the API implementations. This ensures that changes to the data
model do not have a direct impact on the implementations of the APIs. API
implementations can be updated independently of changes to the underlying data
model.
B) **
The CDM typically does not model experience-level APIs.
**
Explanation: The common data model is primarily focused on defining the structure
and semantics of data shared across the enterprise. It may not necessarily capture the
specific needs and structures required for experience-level APIs, which are more
tailored to the user interface and interaction patterns.
Options C, D, and E are not typical considerations for leveraging a common data
model:
C) **
The CDM models multiple definitions of a given data type based on
separate domains.
**
Explanation: A well-designed common data model should provide a single, shared
definition for each data type, ensuring consistency across different domains.
D) **
All data types required by the APIs are not typically defined by the CDM.
**
Explanation: Ideally, the common data model should cover the majority, if not all,
of the data types required by APIs to promote consistency and reusability.
E) **
The CDM typically does not model process-level APIs.
**
Explanation: The common data model focuses on data structures and semantics,
while process-level APIs are concerned with the orchestration and execution of
business processes. Process-level APIs are not typically modelled in a common data
model.
18)
Question
:
A manufacturing organization has implemented a continuous integration (CI) lifecycle
that promotes Mule applications through code, build, and test stages. To standardize
the organization's Cl journey, a new dependency control approach is being designed to
store artifacts that include information such as dependencies, versioning, and build
promotions.
To implement these process improvements, the organization requires developers to
maintain all dependencies related to Mule application code in a shared location.
Which system should the organization use in a shared location to standardize all
dependencies related to Mule application code?
A) A binary artifact repository
B) A MuleSoft-managed repository at repository.mulesoft.org
C) The Anypoint Object Store service at cloudhub.io
D) API Community Manager
Answer
:
The system that the organization should use in a shared location to standardize all
dependencies related to Mule application code is:
A) **
A binary artifact repository.
**
Explanation:
**
Binary Artifact Repository:
** A binary artifact repository is designed to store
and manage binary artifacts, including dependencies, libraries, and other artifacts
needed for software development. It is a common practice in CI/CD workflows to use
a binary artifact repository to store and manage dependencies centrally. Popular
examples include JFrog Artifactory, Nexus Repository, and others.
**
MuleSoft-managed repository at repository.mulesoft.org:
** This is a repository
managed by MuleSoft for distributing MuleSoft-related artifacts. While it may
contain MuleSoft-specific dependencies, it's not intended to be a general-purpose
binary artifact repository for all dependencies related to Mule application code.
**
Anypoint Object Store service at cloudhub.io:
** Anypoint Object Store is
primarily used for storing and retrieving data within Mule applications. It is not
designed for managing general dependencies and artifacts related to the build and
development process.
**
API Community Manager:
** API Community Manager is a platform for
managing APIs and engaging with API consumers. It is not designed for artifact
storage and dependency management for Mule application code.
Therefore, for dependency control and standardization of dependencies related to
Mule application code, the organization should use a binary artifact repository
(Option A).
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
19)
Question:
An organization plans to use the Salesforce Connector as an intermediate layer for
applications that need access to Salesforce events such as adding, changing, or
deleting objects, topics, documents, and channels. What are two features to keep in
mind when using the Salesforce Connector for this integration? (Choose two.)
A) GraphQL
B) Streaming API
C) Chatter API
D) gRPC
E) REST API
Answer:
When using the Salesforce Connector for integration with Salesforce events, two
features to keep in mind are:
B) **Streaming API: **
- Explanation: Streaming API is a feature that allows applications to receive
notifications for changes in Salesforce data in real-time. It provides a push mechanism
to receive updates about changes, such as adding, changing, or deleting objects,
topics, documents, and channels.
C) **Chatter API: **
- Explanation: Chatter API is used to integrate with Salesforce Chatter, the social
collaboration platform within Salesforce. It allows access to Chatter feeds, comments,
and other collaboration-related functionalities. For applications that need access to
Salesforce events, including topics and channels, Chatter API can be relevant.
Options A, D, and E are not directly related to Salesforce events and integration:
A) **GraphQL: **
- Explanation: While GraphQL is a query language and runtime for APIs, it is not
specific to Salesforce and is not a feature of the Salesforce Connector for handling
events.
D) **gRPC: **
- Explanation: gRPC is a high-performance open-source framework for building
remote procedure call (RPC) APIs. It is not specific to Salesforce and is not a feature
of the Salesforce Connector for handling Salesforce events.
E) **REST API: **
- Explanation: REST API is a common way to interact with Salesforce, but it is not
specific to handling events. Streaming API and Chatter API are more relevant features
for real-time event notification and collaboration in the Salesforce context.
20)
What limits whether a particular Anypoint Platform user can discover an asset in Anypoint Exchange?
A) Accessibility of the asset in the API Manager
B) The teams to which the user belongs
C) The type of the asset in Anypoint Exchange
D) The existence of a public Anypoint Exchange portal to which the asset has been published
Answer: The factor that limits whether a particular Anypoint Platform user can discover an asset in Anypoint Exchange is:
A) **Accessibility of the asset in the API Manager.**
Explanation:
- **Accessibility in API Manager:** Anypoint Exchange integrates with Anypoint API Manager, and the visibility of assets in Anypoint Exchange is often controlled by the access and visibility settings configured in API Manager. Users need the necessary
permissions to access and discover assets.
Options B, C, and D are not the primary factors that limit a user's ability to discover an asset:
B) **The teams to which the user belongs:**
- While team membership can influence access to certain assets, the primary control often lies with the API Manager's access settings.
C) **The type of the asset in Anypoint Exchange:**
- The asset type may affect how it is presented, but it doesn't necessarily limit a user's ability to discover it. Access permissions are usually controlled at the API Manager level.
D) **The existence of a public Anypoint Exchange portal to which the asset has been published:**
- Publishing to a public portal affects the visibility of the asset to external users, but it doesn't limit whether a specific Anypoint Platform user can discover the asset. Access permissions are managed through API Manager.
21)
An organization has previously provisioned its own AWS virtual private cloud (VPC) that contains several AWS instances. The organization now needs to use CloudHub 1.0 to host a Mule application that will implement a REST API. Once deployed to CloudHub 1.0, this Mule application must be able to communicate securely with the customer-provisioned AWS VPC resources within the same region, without being intercept able on the public internet. Which Anypoint Platform features should be used to meet these network communication requirements between CloudHub 1.0 and the existing customer-provisioned AWS VPC?
A) Add default API Allowlist policies to API Manager that automatically secure traffic from the range of IP addresses located in the customer-provisioned AWS VPC to access the Mule application B) Configure a MuleSoft-hosted (CloudHub 1.0) Dedicated Load Balancer with mapping rules that allow secure traffic from the range of IP addresses located in the customer-provisioned AWS VPC to access the Mule application C) Configure an external identity provider (IdP) in Anypoint Platform with certificates from an AWS Transit Gateway for the customer-hosted AWS VPC, where the certificates allow the range of IP addresses located in the customer-provisioned AWS VPC
D) Add a MuleSoft-hosted (CloudHub 1.0) Anypoint VPC configured with VPC peering to the range of IP addresses located in the customer-provisioned AWS VPC
Answer:
The Anypoint Platform features that should be used to meet the network communication requirements between CloudHub 1.0 and the existing customer-
provisioned AWS VPC are:
D) **Add a MuleSoft-hosted (CloudHub 1.0) Anypoint VPC configured with VPC peering to the range of IP addresses located in the customer-provisioned AWS VPC.**
Explanation:
- **Anypoint VPC with VPC Peering:** Anypoint VPC allows you to create a secure and private network connection between your CloudHub instances and other systems. By configuring VPC peering, you can establish a direct network connection between the MuleSoft-hosted Anypoint VPC and the customer-provisioned AWS VPC, enabling secure communication.
Option A is not the correct choice because API Allowlist policies are typically related to securing APIs and might not be directly related to the network communication between CloudHub and the AWS VPC.
Option B is not the best fit because configuring a Dedicated Load Balancer with mapping rules is more related to load balancing and routing traffic within CloudHub, but it doesn't address the secure communication requirement with the customer-
provisioned AWS VPC.
Option C mentions configuring an external identity provider (IdP) with certificates from an AWS Transit Gateway, but this is more related to identity and access management, and it might not be the most straightforward solution for secure network
communication.
Therefore, the most appropriate option for secure network communication is to configure an Anypoint VPC with VPC peering (Option D).
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
22)
An organization is implementing a Quote of the Day API that caches today's quote.
Which scenario can use the CloudHub Object Store v2 via the Object Store Connector
to persist the cache's state?
A) When there is one deployment of the API implementation to CloudHub and another deployment to a customer-hosted Mule runtime, where both deployments must share the cache state
B) When there are two CloudHub deployments of the API implementation that must share the cache state, where each API implementation is deployed from a different Anypoint Platform business group to the same CloudHub region
C) When there is one CloudHub deployment of the API implementation to three CloudHub workers/replicas, where all three CloudHub workers/replicas must share the cache state
D) When there are two CloudHub deployments of the API implementation that must share the cache state, where the API implementations are deployed to two different CloudHub VPNs within the same business group
Answer:
The scenario that can use the CloudHub Object Store v2 via the Object Store Connector to persist the cache's state is:
C) **When there is one CloudHub deployment of the API implementation to three CloudHub workers/replicas, where all three CloudHub workers/replicas must share the cache state.**
Explanation:
- In this scenario, when there is a single CloudHub deployment with three CloudHub workers or replicas, using the CloudHub Object Store v2 is appropriate for persisting and sharing the cache state among the workers.
- The CloudHub Object Store v2 is designed for scenarios where data needs to be shared or persisted across multiple instances of the same application deployed to CloudHub. It provides a distributed storage solution for maintaining state information.
Options A, B, and D are not the best fits for the CloudHub Object Store v2:
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
A) In this scenario, the deployments are to different runtimes (CloudHub and customer-hosted Mule runtime), and sharing the cache state between them might not be straightforward using the CloudHub Object Store v2.
B) While both deployments are on CloudHub, they are from different Anypoint Platform business groups, which might have separate instances of the Object Store.
D) Deployments to different CloudHub VPNs within the same business group may have isolated instances of the Object Store.
Therefore, the most suitable scenario for using the CloudHub Object Store v2 is when
there is a single CloudHub deployment with multiple workers or replicas that need to share the cache state (Option C).
23)
NEED TO SET
24)
An organization has deployed both Mule and non-Mule API implementations to integrate its customer and order management systems. All the APIs are available to REST clients on the public internet.
The organization wants to monitor these APIs by running health checks, for example, to determine if an API can properly accept and process requests. The organization does not have subscriptions to any external monitoring tools and also does not want to
extend its IT footprint. Which Anypoint Platform feature monitors the availability of both the Mule and the non-Mule API implementations?
A) API Functional Monitoring
B) Anypoint Visualizer
C) Runtime Manager
D) API Manager
Answer: The Anypoint Platform feature that monitors the availability of both Mule and non-
Mule API implementations and can run health checks is:
C) **Runtime Manager**
Explanation:
- **Runtime Manager:** Runtime Manager is a feature of Anypoint Platform that provides monitoring and management capabilities for Mule runtimes, including both Mule APIs and non-Mule API implementations. It allows you to monitor the health, performance, and availability of your applications in real-time. Health checks and
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
alerts can be configured to determine if an API can properly accept and process requests.
- **API Functional Monitoring:** While API Functional Monitoring (Option A) is designed for monitoring the functional aspects of APIs, it may not cover non-Mule API implementations.
- **Anypoint Visualizer:** Anypoint Visualizer (Option B) is a tool for visualizing and understanding the dependencies between APIs and systems but does not provide health monitoring capabilities.
- **API Manager:** API Manager (Option D) focuses more on API governance, security, and control rather than real-time health monitoring.
Therefore, for monitoring the availability of both Mule and non-Mule API implementations, Runtime Manager (Option C) is the appropriate Anypoint Platform feature.
25)
Additional nodes are being added to an existing customer-hosted Mule runtime cluster
to improve performance. Mule applications deployed to this cluster are invoked by API clients through a load balancer. What is also required to carry out this change?
A) A new load balancer entry must be configured to allow traffic to the new nodes
B) API implementations using an object store must be adjusted to recognize and persist to the new nodes
C) External monitoring tools or log aggregators must be configured to recognize the new nodes
D) New firewall rules must be configured to accommodate communication between API clients and the new nodes
Answer:
The additional nodes being added to an existing customer-hosted Mule runtime cluster
to improve performance, especially when Mule applications are invoked through a load balancer, require the following:
A) **A new load balancer entry must be configured to allow traffic to the new nodes.**
Explanation:
- When new nodes are added to a Mule runtime cluster to enhance performance, the load balancer needs to be aware of these new nodes to distribute traffic effectively.
- Configuring a new load balancer entry ensures that incoming API client requests are appropriately routed to the new nodes in the cluster.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
Options B, C, and D are not directly related to load balancing for the purpose of routing traffic to the new nodes:
B) Adjusting API implementations using an object store (Option B) might be necessary for certain scenarios, but it's not a direct requirement when adding nodes to a cluster for load balancing.
C) Configuring external monitoring tools or log aggregators (Option C) may be beneficial for monitoring purposes, but it's not a direct requirement for the load balancer to recognize the new nodes.
D) Configuring new firewall rules (Option D) might be needed in some cases, but it doesn't directly address the load balancing configuration.
Therefore, to carry out the change of adding new nodes to a Mule runtime cluster, configuring a new load balancer entry (Option A) is crucial for effective traffic distribution.
26)
A company is designing a Mule application named Inventory that uses a persistent Object Store. The Inventory Mule application is deployed to CloudHub and is configured to use Object Store v2. Another Mule application named Cleanup is being developed to delete values from the Inventory Mule application's persistent Object Store. The Cleanup Mule application will also be deployed to CloudHub. What is the most direct way for the Cleanup Mule application to delete values from the Inventory Mule application's persistent Object Store with the least latency?
A) Use a VM connector configured to directly access the persistent queue of the Inventory Mule application's persistent Object Store
B) Use an Object Store connector configured to access the Inventory Mule application's persistent Object Store
C) Use the Object Store v2 REST API configured to access the Inventory Mule application's persistent Object Store
D) Use an Anypoint MQ connector configured to directly access the Inventory Mule application's persistent Object Store
Answer:
The most direct way for the Cleanup Mule application to delete values from the Inventory Mule application's persistent Object Store with the least latency is:
C) **Use the Object Store v2 REST API configured to access the Inventory Mule application's persistent Object Store.**
Explanation:
- **Object Store v2 REST API:** Object Store v2 provides a REST API that allows direct access to the persistent Object Store from external applications. Using this
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
REST API, the Cleanup Mule application can make direct calls to delete values from the Inventory Mule application's persistent Object Store.
- **Least Latency:** Directly using the Object Store v2 REST API is typically the most efficient way to interact with the Object Store when you need to perform operations from another Mule application. This avoids unnecessary overhead associated with using connectors or other intermediaries.
Options A, B, and D involve using specific connectors or configurations that may not be as direct or efficient as using the Object Store v2 REST API:
A) Using a VM connector (Option A) is not the standard way to interact with an Object Store, and it may introduce additional complexities.
B) While an Object Store connector (Option B) can be used, using the Object Store v2
REST API is typically more direct and efficient in this scenario.
D) An Anypoint MQ connector (Option D) is not designed for direct interaction with an Object Store, and using the Object Store v2 REST API is more appropriate.
Therefore, Option C is the most direct and efficient way to delete values from the Inventory Mule application's persistent Object Store with the least latency.
27)
An automation engineer must write scripts to automate the steps of the API lifecycle, including
steps to create, publish, deploy, and manage APIs and their implementations in Anypoint Platform.
Which Anypoint Platform feature can be most easily used to automate the execution of all these actions in scripts without needing to directly invoke the Anypoint Platform
REST APIs?
A) Mule Maven plugin
B) Anypoint CLI
C) Custom-developed Postman scripts
D) GitHub actions
Answer:
The Anypoint Platform feature that can be most easily used to automate the execution of API lifecycle actions in scripts without needing to directly invoke the Anypoint Platform REST APIs is:
B) **Anypoint CLI (Command Line Interface).**
Explanation:
- **Anypoint CLI:** Anypoint CLI is a command-line interface provided by MuleSoft to interact with various Anypoint Platform features. It allows automation of
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
tasks related to the API lifecycle, including creating, publishing, deploying, and managing APIs and their implementations.
- **Mule Maven Plugin:** While the Mule Maven plugin (Option A) is useful for automating the deployment of Mule applications, it is more focused on the deployment aspect rather than the broader API lifecycle.
- **Custom-developed Postman scripts:** Postman scripts (Option C) are more commonly used for testing APIs and may not cover the full range of API lifecycle actions.
- **GitHub Actions:** GitHub Actions (Option D) can be used for automation, but they are typically used for CI/CD workflows and may not be as tailored for the full range of Anypoint Platform API lifecycle actions.
Therefore, Anypoint CLI (Option B) is the most suitable choice for automating API lifecycle actions in scripts without directly invoking the Anypoint Platform REST APIs.
28)
NEED TO SET
29)
NEED TO SET
30)
A company uses CloudHub for API application deployment so that experience APIs and/or API proxies are publicly exposed using custom mTLS. The company's InfoSec team requires
isolated, restricted access that is limited internally to system APIs deployed to CloudHub and the company's data center.
What are the minimum infrastructure, component, connection, and software requirements to meet the company's goal and the InfoSec team's requirements?
A) Virtual Private Cloud
Two Dedicated Load Balancers for access to public APIs and internal APIs using IP Allowlist rules
Two-way custom TLS
VPN IPSec tunneling to connect the VPC to the company's on-premises data center
B) Virtual Private Cloud
One Shared Load Balancer and One Dedicated Load Balancer for access to public APIs and internal APIs, respectively, using IP Allowlist rules Two-way custom TLS
VPN IPSec tunneling to connect the VPC to the company's on-premises data center
C) Virtual Private Cloud
One Shared Load Balancer and One Dedicated Load Balancer for access to public APIs and internal APIs, respectively, using IP Allowlist rules
One-way custom TLS
VPN IPSec tunneling to connect the VPC to the company's on-premises data center
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
D) Virtual Private Cloud
Two Shared Load Balancers for access to public APIs and internal APIs using IP Allowlist rules
Two-way custom TLS
VPN IPSec tunneling to connect the VPC to the company's on-premises data center
Answer:
To meet the company's goal of publicly exposing experience APIs and/or API proxies using custom mTLS, while also providing isolated, restricted access internally to system APIs deployed to CloudHub and the company's data center, the most suitable option is:
B) **Virtual Private Cloud, One Shared Load Balancer, One Dedicated Load Balancer, Two-way custom TLS, VPN IPSec tunneling to connect the VPC to the company's on-premises data center.**
Explanation:
- **Virtual Private Cloud (VPC):** A VPC provides network isolation and segmentation. It helps in creating a private network environment for the deployment.
- **One Shared Load Balancer and One Dedicated Load Balancer:** Using a Shared Load Balancer for public APIs and a Dedicated Load Balancer for internal APIs helps manage traffic and access control separately for different types of APIs.
- **IP Allowlist Rules:** Applying IP Allowlist rules on the load balancers allows controlling and restricting access based on specified IP addresses.
- **Two-way custom TLS:** Two-way custom TLS (mutual TLS) provides secure communication between clients and APIs, ensuring that both parties authenticate each other.
- **VPN IPSec Tunneling:** Establishing a VPN IPSec tunnel between the VPC and the company's on-premises data center ensures a secure and private connection between CloudHub and the internal network.
Options A, C, and D have variations in the configurations that may not align with the specified requirements:
- **Option A:** Two Dedicated Load Balancers might lead to unnecessary complexity, and the absence of a Shared Load Balancer for public APIs may not be optimal.
- **Option C:** One-way custom TLS may not provide mutual authentication, which might be required for more robust security.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
- **Option D:** Two Shared Load Balancers for public and internal APIs might not align with the goal of isolating access through different load balancers.
Therefore, Option B is the most suitable choice for meeting the company's goal and the InfoSec team's requirements.
31)
What are two valid considerations when implementing a reliability pattern? (Choose two.)
A) It requires using an XA transaction to bridge message sources when multiple managed resources need to be enlisted within the same transaction
B) It has performance implications
C) It provides high performance
D) It is not possible to have multiple message sources within the same transaction while implementing reliability pattern
E) It does not support VM queues in an HA cluster
Answer:
Two valid considerations when implementing a reliability pattern are:
B) **It has performance implications.**
- Reliability patterns, especially those involving things like message retries, acknowledgments, and guaranteed message delivery, can introduce additional processing overhead and potential latency. The impact on system performance is an important consideration.
D) **It is not possible to have multiple message sources within the same transaction while implementing reliability pattern.**
- In certain scenarios, having multiple message sources within the same transaction while implementing a reliability pattern might be complex or not supported, depending on the specific implementation or messaging infrastructure being used.
Options A, C, and E are not accurate:
A) **It requires using an XA transaction to bridge message sources when multiple managed resources need to be enlisted within the same transaction.**
- Reliability patterns may not always require the use of XA transactions, and the necessity depends on the specific requirements and components involved.
C) **It provides high performance.**
- The performance of reliability patterns can vary based on the specific implementation, requirements, and technologies used. It is not accurate to generalize reliability patterns as always providing high performance.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
E) **It does not support VM queues in an HA cluster.**
- Reliability patterns are typically independent of the messaging system being used, and support for VM queues in an HA cluster depends on the capabilities of the specific messaging infrastructure.
Therefore, options B and D are valid considerations when implementing a reliability pattern.
32)
An organization plans to leverage the MuleSoft open-source Serialization API to serialize or de-serialize objects into a byte array. Which two considerations must be kept in mind while using the Serialization API? (Choose
two.)
A) The API does not provide any flexibility to specify which classloader to use
B) The API does not support configuring a Custom Serializer
C) The API is not thread-safe
D) The API allows an InputStream as an input source
E) The API passes an OutputStream when serializing and streaming
Answer:
Two considerations to keep in mind while using the MuleSoft open-source Serialization API are:
C) **The API is not thread-safe.**
- This means that caution should be taken when using the Serialization API in a multi-threaded environment to avoid potential race conditions or unexpected behavior.
E) **The API passes an OutputStream when serializing and streaming.**
- When serializing and streaming, the API uses an OutputStream to write the serialized data. Understanding this behavior is important when working with the Serialization API.
Options A, B, and D are not accurate:
A) **The API does not provide any flexibility to specify which classloader to use.**
- This statement is not accurate. The Serialization API may provide ways to specify or control which classloader to use, depending on the specific implementation or version.
B) **The API does not support configuring a Custom Serializer.**
- This statement is not accurate. The Serialization API may support configuring custom serializers, and the support may vary based on the specific implementation or version.
D) **The API allows an InputStream as an input source.**
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
- This statement is not accurate based on the common usage of serialization APIs. Serialization APIs typically deal with output streams when serializing data, and input streams when deserializing data.
Therefore, options C and E are valid considerations when using the MuleSoft open-
source Serialization API.
33)
A developer at an insurance company has developed a Mule application that has two modules as dependencies for two different operations. These two modules use the same library Joda- Time to return a DateTimeFormatter class. One of the module uses Joda-Time version 2.9.5 and the other one uses Joda-Time version 2.1.1. The DateTimeFormatter class lives in the same package in both versions, but the different implementations of each version make the classes incompatible.
First Module
public DateTimeFormatter getCreate TimestampDateTimeFormatter() {
}
// Here DateTimeFormatter is from joda-time 2.9.5
return DateTimeFormat.forPattern("yyyyMMdd");
Second Module
}
public DateTimeFormatter getUpdate TimestampDateTimeFormatter() {
// Here DateTimeFormatter is from joda-time 2.1.1
return DateTimeFormat.forPattern("yyyyMMddHH24mm");
Given the details of these two modules, what will happen when the Mule application is deployed?
A) It will load both module versions and, when each individual operation is executed, it will not run into any errors
B) The deployment will fail because the two modules try to return the same class
C) It will only load the latest version of Joda-Time; older versions of Joda-Time applications will throw a ClassLoaderException error
D) It will only load one of the versions; the module that needs the unloaded version of
the package will behave differently and be prone to errors such as
ClassCastException or NoSuchMethodException
Answer:
The situation described suggests the possibility of class conflicts due to different versions of the Joda-Time library being used by the two modules. In Java, when different versions of a library are present in the classpath, it can lead to classloading issues and runtime errors.
Given the scenario:
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
D) **It will only load one of the versions; the module that needs the unloaded version
of the package will behave differently and be prone to errors such as ClassCastException or NoSuchMethodException.**
Explanation:
- When the Mule application is deployed, the classloader will typically load one version of the Joda-Time library. The version loaded is often influenced by the classloading order and the specifics of the classloading mechanism used by the runtime environment.
- If the classloader loads the older version (2.1.1) first, the first module expecting version 2.9.5 will not find the expected methods or behaviors, leading to potential errors such as NoSuchMethodException or ClassCastException.
- If the classloader loads the newer version (2.9.5) first, the second module expecting version 2.1.1 will not find the expected methods or behaviors, again leading to potential errors.
In either case, there's a risk of behavior inconsistencies and runtime errors due to the mismatch in the Joda-Time library versions used by the two modules.
Option A is not likely because classloading issues typically result in problems, and it's
not common for different versions of a library to coexist harmoniously in the same application.
Options B and C do not accurately capture the likely scenario of classloading issues and runtime errors that can occur when different versions of a library are present.
Therefore, option D is the most plausible outcome given the situation described.
34)
Which statement is true about the network connections when a Mule application uses a JMS
connector to interact with a JMS provider (message broker)?
A) For the Mule application to receive JMS messages, the JMS provider initiates a network connection to the Mule application's JMS connector and then the JMS provider pushes messages along this connection
B) The Advanced Message Queuing Protocol (AMQP) can be used by the JMS connector to portably establish connections to various types of JMS providers
C) To complete sending a JMS message, the JMS connector must establish a network connection with the JMS message recipient
D) The JMS connector supports both sending and receiving JMS messages over the protocol determined by the JMS provider
Answer:
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
The correct statement about the network connections when a Mule application uses a JMS connector to interact with a JMS provider (message broker) is:
D) **The JMS connector supports both sending and receiving JMS messages over the
protocol determined by the JMS provider.**
Explanation:
- The JMS (Java Message Service) connector in MuleSoft is designed to facilitate communication with JMS providers, which are message brokers.
- The JMS connector supports both sending (producing) and receiving (consuming) JMS messages.
- The specific protocol used for communication, such as TCP, can be determined by the configuration of the JMS provider. The JMS connector itself doesn't dictate the underlying transport protocol; it adapts to the protocol specified by the JMS provider.
Option A is not accurate because in JMS, it is the consumer (Mule application) that typically initiates the connection to the JMS provider to pull messages.
Option B is not accurate because AMQP (Advanced Message Queuing Protocol) is a different messaging protocol and is not directly related to JMS.
Option C is not accurate because sending a JMS message involves the Mule application establishing a connection with the JMS provider (message broker), not necessarily the recipient.
Therefore, option D is the correct and true statement in the context of a Mule application using a JMS connector to interact with a JMS provider.
35)
A software company is creating a Mule application that will be deployed to CloudHub. The Mule application has a property named dbpassword that stores a database user's password. The organization's security standards indicate that the dbPassword property must be hidden from every Anypoint Platform user after the value is set in the Runtime Manager Properties tab. Which configuration in the Mule application helps hide the dbPassword property value in Runtime Manager? A) Add the dbpassword property to the secureProperties section of the pom.xml file B) Store the encrypted db Password value in a secure properties placeholder file C) Use secure::dbPassword as the property placeholder name and store the cleartext (unencrypted) value in a secure properties placeholder file D) Add the dbPassword property to the secureProperties section of the mule- artifact.json file
Answer:
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
The configuration in the Mule application that helps hide the `dbPassword` property value in Runtime Manager is:
B) **Store the encrypted `dbPassword` value in a secure properties placeholder file.**
Explanation:
- Storing sensitive information such as passwords in clear text is a security risk. To address this, you can use encrypted values for sensitive properties.
- The recommended approach is to store the encrypted `dbPassword` value in a secure
properties placeholder file. MuleSoft provides a way to encrypt sensitive properties, and the encrypted values can be stored in a separate file, typically referred to as a secure properties file.
Option A is not accurate because adding the property to the `secureProperties` section of the `pom.xml` file is not a common practice for securing sensitive information, and
it is not the standard approach recommended by MuleSoft.
Option C is not accurate because using `secure::dbPassword` as the property placeholder name suggests using the built-in secure property placeholder feature in MuleSoft, but it doesn't automatically encrypt the value. You would still need to encrypt the value and store the encrypted version in a secure properties file.
Option D is not accurate because adding the property to the `secureProperties` section
of the `mule-artifact.json` file is not a standard approach for securing properties in CloudHub. The `mule-artifact.json` file is more about configuring the deployment characteristics of the Mule application.
Therefore, option B is the most appropriate and secure approach for hiding the `dbPassword` property value in Runtime Manager.
36)
A Mule application is deployed to a cluster of two customer-hosted Mule runtimes. Currently, the node named Alex is the primary node and the node named Lee is the secondary node. The Mule application has a flow that polls a directory on a file system for new files. The primary node Alex fails for an hour and then is restarted. After the Alex node completely restarts, from which node are the files polled, and which node is now the primary node for the cluster? A) Files are polled from the Lee node Alex is now the primary node B) Files are polled from the Alex node Lee is now the primary node C) Files are polled from the Lee node Lee is now the primary node D) Files are polled from the Alex node Alex is now the primary node
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
Answer:
In a Mule runtime cluster, the behaviour after a primary node failure depends on the clustering configuration and how the cluster handles failover. In a default configuration, when the primary node fails, another node takes over as the primary node.
The correct answer depends on the specific failover and clustering configuration, but based on typical failover behaviour, the answer would be:
A) **Files are polled from the Lee node, and Alex is now the primary node.**
Explanation:
- When the primary node (Alex) fails, the secondary node (Lee) takes over and becomes the primary node.
- After the primary node (Alex) is restarted, it doesn't automatically resume its role as the primary node. Failover mechanisms typically do not revert to the original primary node immediately to avoid potential instability.
- Files are polled from the Lee node because it has taken over the primary role during the failure of Alex.
The specifics of failover behaviour can be influenced by the clustering configuration, and if custom failover logic is implemented, the behaviour might differ. However, based on standard failover behaviour, option A is the most likely scenario.
37)
An organization is designing an integration solution to replicate financial transaction data from a legacy system into a data warehouse (DWH). The DWH must contain a daily snapshot of financial transactions, to be delivered as a CSV file. Daily transaction volume exceeds tens of millions of records, with significant spikes in volume during popular shopping periods. What is the most appropriate integration style for an integration solution that meets the organization's current requirements? A) Splitter-Aggregator Integration Pattern B) Microservice architecture C) Event-driven architecture D) Batch-triggered data integration
Answer:
For an integration solution that needs to replicate financial transaction data from a legacy system into a data warehouse, with a requirement for a daily snapshot in the form of a CSV file, and considering the potentially high transaction volume, the most appropriate integration style is:
D) **Batch-triggered data integration.**
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
Explanation:
1. **Batch Processing:**
- Given the large volume of daily financial transactions, a batch processing approach is suitable. Batch processing allows the system to handle data in chunks, processing them in a scheduled, efficient manner.
- Daily snapshots can be created by aggregating and processing transactions in batches.
2. **CSV File Output:**
- Batch processing can easily handle the creation of CSV files, which is a common requirement for data warehousing scenarios.
3. **Efficient Handling of Spikes:**
- Batch processing is well-suited for handling spikes in volume. It allows the system
to manage large amounts of data in a controlled manner, preventing overload during peak periods.
4. **Scheduled Execution:**
- Daily snapshots imply a scheduled or periodic execution, which aligns with the nature of batch processing.
Option A (Splitter-Aggregator Integration Pattern) might be suitable for scenarios where data needs to be split, processed in parallel, and then aggregated, but it might not be the most efficient for large-scale batch processing.
Option B (Microservice architecture) and Option C (Event-driven architecture) might be more suitable for scenarios with different characteristics, such as real-time processing or distributed, decoupled systems. However, for a daily batch processing requirement with potential spikes in volume, a batch-triggered data integration approach is more appropriate.
38)
In a Mule application, a flow contains two JMS Consume operations that are used to connect to a JMS broker and consume messages from two JMS destinations. The Mule application then joins the two consumed JMS messages together. The JMS broker does not implement high availability and periodically experiences scheduled outages of up to 10 minutes for routine maintenance. How should the Mule flow be built so it can recover from the expected outages? A) Configure a reconnection strategy for the JMS connector B) Configure a transaction for the JMS connector C) Enclose the two JMS operations in an Until Successful scope
D) Enclose the two JMS operations in a Try scope with an On Error Continue error handler
Answer:
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
To build a Mule flow that can recover from expected outages in a scenario where a JMS broker periodically experiences scheduled outages, the most appropriate approach would be:
C) **Enclose the two JMS operations in an Until Successful scope.**
Explanation:
- **Until Successful Scope:**
- The Until Successful scope in MuleSoft allows you to repeatedly execute a sequence of message processors until a specified condition is met.
- In the context of JMS operations, this means that the JMS consume operations will be retried until they are successful or until a maximum number of retries is reached.
- **Handling Outages:**
- When the JMS broker experiences scheduled outages, the Until Successful scope will keep retrying the JMS consume operations until the broker is available again.
- This helps in handling temporary outages without causing the entire flow to fail.
- **Configuration Options:**
- Within the Until Successful scope, you can configure parameters such as the maximum number of retries, retry interval, and the condition for success.
Options A and B are not directly addressing the periodic outages in the JMS broker:
- Option A (Configure a reconnection strategy for the JMS connector) is a good practice for handling transient failures but may not be sufficient for longer outages.
- Option B (Configure a transaction for the JMS connector) is more related to ensuring transactional consistency but does not directly address the scenario of periodic outages.
Option D (Enclose the two JMS operations in a Try scope with an On Error Continue error handler) is an option but may require additional configuration for handling retries.
Therefore, option C is the most appropriate choice for handling expected outages and ensuring the flow's resilience to temporary disruptions in the JMS broker's availability.
39)
An MUnit case is written for a Main Flow that consists of a Listener, a set payload, a set variable, a Transform message, and a logger and error handler. The case is passed but with a coverage of 80 percent. What could be the reason for not covering the remaining 20 percent, and how can coverage be achieved? A) The error handler; use Mock when in MUnit test suite
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
B) The Listener; send a dummy payload in MUnit test suite C) The error handler; use error handler in MUnit test suite D) The Listener; use Mock when in MUnit test suite
Answer:
The reason for not achieving 100% coverage in the MUnit test suite could be related to the error handler not being triggered during the test. To achieve full coverage, you should simulate an error condition that causes the error handler to be invoked.
Therefore, the correct answer is:
C) **The error handler; use error handler in MUnit test suite.**
Explanation:
- In MUnit, to achieve full coverage, you need to ensure that all parts of your flow are exercised during the test. In this case, the error handler is not being triggered in the existing test scenario.
- To cover the error handler, you should design your test case to intentionally cause an
error condition that would trigger the error handler. This can be done by sending a message that results in an error, such as sending invalid input or configuring the test to simulate a failure scenario.
- Using the MUnit `error-handler` element in your test configuration allows you to test how your flow handles errors and whether the error handler is invoked appropriately.
Here's a general example of how you might structure your MUnit test case to cover the error handler:
```xml
<munit:test name="YourTestCase">
<!-- Set up the test configuration -->
<munit:config name="mule-configuration" doc:name="Mule Configuration" />
<!-- Trigger an error condition -->
<munit:input expectedOutput="...">
<set-payload value="#['your test data']" />
</munit:input>
<!-- Validate the behavior of the error handler -->
<munit:assertions>
<!-- Add assertions related to the error handler's behavior -->
</munit:assertions>
</munit:test>
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
```
By intentionally causing an error and validating the behaviour within the error handler, you can achieve full coverage for your MUnit test suite.
40)
An organization's release engineer wants to override secure properties in a CloudHub production environment. Properties can be updated in the Properties tab in Runtime Manager, but the password is not being hidden even after the application is restarted or redeployed. What could be the reason? A) The secureProperties key in the mule-artifact.json file does not list properties B) Properties do not exist in the prod properties file C) In a secure-prod.yaml file properties are not marked secure D) Properties need to be prefixed with a secure keyword when entered in the Properties tab
Answer:
The reason for the password not being hidden in the Properties tab in Runtime Manager, even after restarting or redeploying the application, could be related to how the secure properties are configured.
The correct option is:
C) **In a secure-prod.yaml file properties are not marked secure.**
Explanation:
- MuleSoft uses a file named `secure.properties` to store encrypted property values. This file is usually located in the `src/main/resources` directory.
- In your Mule application, you may have a file named `secure.properties` or a variant
like `secure-prod.yaml` (as mentioned in the option).
- The properties in this file should be marked as secure for them to be treated as sensitive information and hidden in the Properties tab in Runtime Manager.
- For example, in a `secure.properties` file, properties can be defined as follows:
```properties
db.password=ENC(encrypted_value)
```
- If you are using a YAML file (like `secure-prod.yaml`), the syntax would be different, but the idea is the same:
```yaml
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
db:
password: ENC(encrypted_value)
```
- Make sure that the properties are marked as secure using the `ENC` prefix, and the corresponding encrypted values are present.
Option A is not a typical reason for this behavior, and options B and D do not directly address the issue of marking properties as secure. The focus should be on ensuring that the secure properties file is correctly configured with the encrypted values and the
`ENC` prefix.
41)
A Mule application is designed to periodically synchronize 1 million records from a source system to a SaaS target system using a Batch Job scope. The current application design includes using the default Batch Job scope to process records while
managing high throughput requirements. However, what actually happens is the application takes too long to process records even with the application deployed to a customer-hosted cluster of two Mule runtime 4.3 instances. What must occur to achieve the required high throughput, considering the Mule runtimes' CPU and memory requirements are met with no expected contentions from other applications running under the same cluster? A) Change the application design and increase the Batch Job scope concurrency and the records block size
B) Modify the cluster Mule runtimes UBER thread pool strategy with a high concurrency in the conf/scheduler-pools.conf files C) Modify the cluster Mule runtimes concurrency by changing the memory allocation in the conf/wrapper.conf files D) Scale the cluster Mule runtimes horizontally by adding a third instance needed to support high rate of records processing
Answer:
To achieve the required high throughput, considering the Mule runtimes' CPU and memory requirements are met, and there are no expected contentions from other applications running under the same cluster, the most suitable action would be:
A) **Change the application design and increase the Batch Job scope concurrency and the records block size.**
Explanation:
- The Batch Job scope in Mule allows for processing records in parallel to achieve higher throughput.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
- By increasing the Batch Job scope concurrency, you enable the processing of multiple records simultaneously. This can significantly improve the application's ability to handle a large volume of records.
- Adjusting the records block size can also impact performance. A larger block size can lead to more efficient processing, especially when dealing with large datasets.
- Scaling horizontally by adding more runtime instances (Option D) is a viable strategy, but it might involve additional infrastructure costs. Before resorting to scaling, optimizing the application design is recommended.
Options B and C seem less relevant to the issue at hand. Modifying thread pool strategies or changing runtime concurrency through configuration files might not directly address the need for high throughput in the context of Batch processing. The focus should be on optimizing the Batch Job scope within the application.
42)
A client system sends marketing-related data to a legacy system within the company data center. The Center for Enablement team has identified that this marketing data has no reuse by any other system. How should the APIs be designed most efficiently using API-led connectivity? A) Create a Process API, route the request to the System API, and insert the data in the legacy system
B) Create a System API, call the System API from the client application, and insert the data into the legacy system C) Create an Experience API to take the data from the client, forward the message to a
Process API in the Common Data Model, and invoke a System API to insert the data into the legacy system
D) Create an Experience API, route the data to the System API, and insert the data in the legacy system
Answer:
The most efficient way to design the APIs using API-led connectivity, considering that
the marketing data has no reuse by any other system, is:
**B) Create a System API, call the System API from the client application, and insert the data into the legacy system.**
Explanation:
- In API-led connectivity, a System API is designed to encapsulate the internal systems and provide a clear interface for external consumers.
- Since the marketing data has no reuse by any other system, creating a dedicated System API to handle the interaction with the legacy system is a straightforward and efficient approach.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
- The client application directly calls the System API, which then handles the integration with the legacy system. This simplifies the architecture and avoids unnecessary layers, making it a more efficient design.
Option B aligns with the principles of API-led connectivity, focusing on creating purpose-specific APIs for different layers of the architecture.
43)
An organization will deploy Mule applications to CloudHub. Business requirements mandate that all application logs be stored only in an external Splunk consolidated logging service and not in CloudHub. In order to most easily store Mule application logs only in Splunk, how must Mule application logging be configured in Runtime Manager, and where should the log4j2 Splunk appender be defined? A) Disable CloudHub logging in Runtime Manager. Define the Splunk appender in one global log4j2.xml file that is uploaded once to Runtime Manager to support all Mule application deployments.
B) Keep the default logging configuration in Runtime Manager. Define the Splunk appender in the Logging section of Runtime Manager in each application so that it overwrites the default logging configuration.
C) Disable CloudHub logging in Runtime Manager. Submit a ticket to MuleSoft Support with Splunk appender information so that CloudHub can automatically forward logs to the specified Splunk appender.
D) Disable CloudHub logging in Runtime Manager. Define the Splunk appender in each Mule application's log4j2.xml file.
Answer:
To configure Mule application logging to store logs only in an external Splunk consolidated logging service and not in CloudHub, you should:
**D) Disable CloudHub logging in Runtime Manager. Define the Splunk appender in each Mule application's log4j2.xml file.**
Explanation:
- By disabling CloudHub logging in Runtime Manager, you ensure that CloudHub does not handle the logging for your Mule applications.
- Define the Splunk appender in each Mule application's log4j2.xml file. This allows you to customize the logging configuration for each Mule application individually, including specifying the Splunk appender.
This approach provides the flexibility to configure logging for each Mule application according to its specific requirements, and it ensures that logs are sent to the external Splunk service as desired.
44)
NEED TO SET
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
45)
An organization is trying to invoke REST APIs as part of its integration with external systems, which requires OAuth 2.0 tokens for authorization. How should authorization tokens be acquired in a Mule application?
A) Use HTTP Connector's Authentication Feature B) Write custom Java code for handling authorization tokens C) Implement Scheduler-based flow for retrieving/saving OAuth 2.0 tokens in Object Store D) Configure OAuth 2.0 in Client Management in Anypoint Platform
Answer:
D) Configure OAuth 2.0 in Client Management in Anypoint Platform
Explanation:
To acquire OAuth 2.0 tokens in a Mule application, it's recommended to configure OAuth 2.0 in Client Management in Anypoint Platform. Anypoint Platform provides a
comprehensive way to manage client credentials, configure OAuth 2.0 flows, and obtain authorization tokens. This approach abstracts the complexities of OAuth 2.0 and provides a more streamlined and secure way to handle authorization in Mule applications.
The other options:
- A) Using HTTP Connector's Authentication Feature: The HTTP Connector's authentication feature is generally used for basic authentication, not for handling OAuth 2.0 tokens.
- B) Writing custom Java code for handling authorization tokens: While it's technically possible to write custom code, leveraging the built-in OAuth 2.0 support in Anypoint Platform is a more standard and manageable approach.
- C) Implementing Scheduler-based flow for retrieving/saving OAuth 2.0 tokens in Object Store: This approach might work, but it could introduce complexities and potential issues in terms of token lifecycle management. Using Anypoint Platform's built-in capabilities is generally more straightforward and recommended.
46)
A Mule application receives a JSON request, and it uses the validation module extensively to perform certain validations like isNotEmpty, isEmail, and isNotElapsed. It throws an error if any of these validations fails. A new requirement is
added that says a validation error should be thrown only if all above individual validations fail, and then an aggregation of individual errors should be returned. Which MuleSoft component supports this new requirement? A) Use VALIDATION:ALL scope wrapper enclosing all individual validations B) Add try-catch with on-error-continue wrapper over each individual validation
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
C) Use VALIDATION:ANY scope wrapper enclosing all individual validations D) Add try-catch with on-error-propagate wrapper over each individual validation
Answer:
C) Use VALIDATION:ANY scope wrapper enclosing all individual validations
Explanation:
The `VALIDATION:ANY` scope wrapper in MuleSoft is designed to perform multiple validations and return success if at least one of the validations passes. This aligns with the new requirement, where you want to throw a validation error only if all individual validations fail and then aggregate the errors.
So, by using `VALIDATION:ANY` with individual validation components inside it, you can achieve the desired behavior. If any of the individual validations succeed, the overall validation will be considered successful.
The other options:
- A) Use VALIDATION:ALL scope wrapper enclosing all individual validations: This
would require all validations to pass for the overall validation to be successful, which is not aligned with the new requirement.
- B) Add try-catch with on-error-continue wrapper over each individual validation: This approach could handle errors but might not be as clean and structured as using the `VALIDATION:ANY` scope for this specific scenario.
- D) Add try-catch with on-error-propagate wrapper over each individual validation: This would propagate the error immediately, and aggregating errors might become more complex. The `VALIDATION:ANY` scope is better suited for this purpose.
47)
An organization is designing a Mule application to support an all-or-nothing transaction between several database operations and some other connectors so that all operations automatically roll back if there is a problem with any of the connectors. Besides the database connector, what other Anypoint connector can be used in the Mule application to participate in the all-or-nothing transaction? A) Object Store B) JMS C) Anypoint MQ D) SFTP
Answer:
A) Object Store
Explanation:
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
In MuleSoft, the Object Store connector can be used to participate in an all-or-nothing
transaction along with the database connector. The Object Store allows you to store and retrieve data during the flow execution, and it participates in the same transaction context as other connectors when using the all-or-nothing pattern.
So, if you want to ensure that all operations, including database operations and interactions with the Object Store, are part of a single transaction that either commits all changes or rolls back all changes in case of an error, you can include both the database connector and the Object Store connector in your Mule application.
The other connectors mentioned:
- B) JMS (Java Message Service): JMS can be used for messaging, but it doesn't inherently participate in the same transaction as database operations and Object Store operations.
- C) Anypoint MQ: Similar to JMS, Anypoint MQ is a messaging service and operates
independently of the transaction context of other connectors.
- D) SFTP (Secure File Transfer Protocol): SFTP is typically used for file transfer operations and is not designed to participate in the same transaction context as database operations and Object Store operations.
48)
An organization has used a Centre for Enablement (C4E) to help teach its various business groups best practices for building a large and mature application network. What is a key performance indicator (KPI) to measure the success of the C4E in teaching the organization's various business groups how to build an application network? A) The number of each business group's APIs that connect with C4E-documented APIs B) The number of each C4E-managed business group's Anypoint Platform user requests to the CloudHub Shared Load Balancer service C) The number of end user or consumer requests per day to C4E-deployed API instances D) The number of C4E-documented code snippets used by Mule apps deployed by the
C4E to each environment in each network region
Answer:
A) The number of each business group's APIs that connect with C4E-documented APIs
Explanation:
The key performance indicator (KPI) to measure the success of the Center for Enablement (C4E) in teaching the organization's various business groups how to build
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
an application network is best represented by the extent to which each business group's APIs connect with C4E-documented APIs. This metric indicates the adoption and integration of best practices and standards promoted by the C4E.
Options B, C, and D may provide useful metrics in certain contexts, but they don't directly capture the collaborative and standardized nature of API development encouraged by the C4E. The number of APIs connecting with C4E-documented APIs reflects the influence and acceptance of the C4E's guidance in building a cohesive and
interoperable application network across different business groups.
49)
An external web Ul application currently accepts occasional HTTP requests from client web browsers to change (insert, update, or delete) inventory pricing information
in an inventory system's database. Each inventory pricing change must be transformed
and then synchronized with multiple customer experience systems in near real-time (in under 10 seconds). New customer experience systems are expected to be added in the future. The database is used heavily and limits the number of SELECT queries that can be made to the database to 10 requests per hour per user. How can inventory pricing changes synchronize with the various customer experience systems in near real-time using an integration mechanism that is scalable, decoupled, reusable, and maintainable? A) Write a Mule application with a Database On Table Row event source configured for the inventory pricing database, with the watermark attribute set to an appropriate database column. In the same flow, use a Scatter-Gather to call each customer experience system's REST API with transformed inventory pricing records. B) Add a trigger to the inventory-pricing database table so that for each change to the inventory pricing database, a stored procedure is called that makes a REST call to a Mule application. Write the Mule application to publish each Mule event as a message
to an Anypoint MQ exchange. Write other Mule applications to subscribe to the Anypoint MQ exchange, transform each received message, and then update the Mule application's C) Write a Mule application with a Database On Table Row event source configured for the inventory pricing database, with the ID attribute set to an appropriate database column. In the same flow, use a Batch Job scope to publish transformed inventory pricing records to an Anypoint MQ queue. Write other Mule applications to subscribe to the Anypoint MQ queue, transform each received message, and then update the Mule application's corresponding customer experience system(s). D) Replace the external web UI application with a Mule application to accept HTTP requests from client web browsers. In the same Mule application, use a Batch Job scope to test if the database request will succeed, aggregate pricing changes within a short time window, and then update both the inventory pricing database and each customer experience system using a Parallel For Each scope.
Answer:
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
C) Write a Mule application with a Database On Table Row event source configured for the inventory pricing database, with the ID attribute set to an appropriate database column. In the same flow, use a Batch Job scope to publish transformed inventory pricing records to an Anypoint MQ queue. Write other Mule applications to subscribe to the Anypoint MQ queue, transform each received message, and then update the Mule application's corresponding customer experience system(s).
Explanation:
Option C involves using the Database On Table Row event source in MuleSoft to listen for changes in the inventory pricing database. The event source is configured with an appropriate database column (ID) to trigger the flow when a row is updated. The flow then uses a Batch Job scope to publish the transformed inventory pricing records to an Anypoint MQ queue.
Subsequently, other Mule applications are designed to subscribe to the Anypoint MQ queue. They can receive the messages, transform them as needed, and then update the corresponding customer experience systems. This approach is scalable, decoupled, reusable, and maintainable, meeting the specified requirements.
Option A involves using Scatter-Gather, which may not be the best choice for this scenario, and option B introduces a stored procedure, which might not align with the scalable and maintainable criteria. Option D suggests replacing the external web UI application, which might not be a feasible or efficient solution.
50)
A Mule application is being designed to receive a CSV file nightly that contains millions of records from an external vendor over SFTP. The records from the file must
be transformed and then written to a database. Records can be inserted into the database in any order. In this use case, which combination of Mule components provides the most effective way to write these records to the database? A) Use a Batch Job scope to bulk-insert records into the database B) Use a Scatter-Gather router to bulk-insert records into the database C) Use a Parallel For Each scope to insert records in-parallel into the database D) Use the DataWeave map function and an Async scope to insert records in- parallel into the database
Answer:
A) Use a Batch Job scope to bulk-insert records into the database
Explanation:
In this use case, where millions of records need to be processed and inserted into the database nightly, the most effective way is to use a Batch Job scope. The Batch Job scope allows you to process records in bulk, providing optimizations for large datasets.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
The Batch Job scope can efficiently handle the transformation and insertion of records
into the database. It is designed for bulk processing scenarios and supports parallel processing, which can significantly improve performance when dealing with a large number of records.
Options B, C, and D are not as suitable for this specific use case:
- Scatter-Gather (Option B) is more suitable for parallel processing of independent tasks rather than bulk processing of records.
- Parallel For Each (Option C) might introduce complexities in maintaining the order of records during parallel processing, and it may not be as optimized for large-scale bulk inserts.
- Using DataWeave map function and Async scope (Option D) might introduce complexities in managing the asynchronous processing of records and may not provide the same level of optimization as the Batch Job scope for bulk inserts.
51)
A manufacturing company has an HTTPS-enabled Mule application named Orders API that receives requests from another Mule application named Process Orders. The communication between these two Mule applications must be secured by TLS mutual authentication (two-way TLS). At a minimum, what must be stored in each truststore and keystore of these two Mule applications to properly support two-way TLS between the two Mule applications while properly protecting each Mule application's keys? A) Orders API keystore: The Orders API private key Process Orders truststore: The Orders API public key Process Orders keystore: The Process Orders private key B) Orders API truststore: The Process Orders private key Orders API keystore: The Orders API private key and public key Process Orders truststore: The Orders API private key Process Orders keystore: The Process Orders private key and public key C) Orders API truststore: The Process Orders public key Orders API keystore: The Orders API private key Process Orders truststore: The Orders API public key D) Orders API truststore: The Process Orders public key Orders API keystore: The Orders API private key and public key Process Orders truststore: The Orders API public key Process Orders keystore: The Process Orders private key and public key
Answer: C) Orders API truststore: The Process Orders public key
Orders API keystore: The Orders API private key
Process Orders truststore: The Orders API public key
Explanation:
In a two-way TLS (mutual authentication) setup, both parties (Orders API and Process
Orders) need to verify each other's identity. Each party has its own keystore
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
containing its private key and public key, and a truststore containing the public key of the other party.
For the Orders API:
- Orders API keystore: Contains the private key (used for authentication) and the public key (shared with the Process Orders for verification).
- Orders API truststore: Contains the public key of the Process Orders, used to verify the authenticity of the Process Orders.
For the Process Orders:
- Process Orders keystore: Contains the private key (used for authentication) and the public key (shared with the Orders API for verification).
- Process Orders truststore: Contains the public key of the Orders API, used to verify the authenticity of the Orders API.
This ensures that each party has its own private key for authentication and the other party's public key for verification, establishing a secure two-way TLS communication.
52)
A Mule Process API is being designed to provide product usage details. The Mule application must join together the responses from an Inventory API and a Product Sales History API with the least latency. How should each API request be called in the
Mule application to minimize overall latency? A) Call each API request in a separate Mule flow B) Call each API request in a Batch Step within a Batch Job C) In a separate route of a Scatter-Gather D) In a separate lookup call from a DataWeave reduce function
Answer: C) In a separate route of a Scatter-Gather
Explanation:
The Scatter-Gather router is designed to send a message to multiple routes concurrently and gather the responses. This allows parallel processing of API requests, reducing overall latency.
In this scenario, you have two API requests (from the Inventory API and Product Sales History API), and you want to minimize latency. Using a Scatter-Gather with separate routes for each API request allows both requests to be executed concurrently, and their responses are gathered, reducing the overall time it takes to retrieve data from both APIs.
Option C is the most suitable for minimizing latency in this case.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
53)
A Mule application is running on a customer-hosted Mule runtime in an organization's
network. The Mule application acts as a producer of asynchronous Mule events. Each Mule event must be broadcast to all interested external consumers outside the Mule application. The Mule events should be published in a way that is guaranteed in normal situations and also minimizes duplicate delivery in less-frequent failure scenarios. The organizational firewall is configured to only allow outbound traffic on ports 80 and 443. Some external event consumers are within the organizational network, while others are located outside the firewall. Which Anypoint Platform service facilitates publishing these Mule events to all external consumers while addressing the desired reliability goals?
A) CloudHub VM queues B) Anypoint MQ C) CloudHub Shared Load Balancer D) Anypoint Exchange
Answer:
B) Anypoint MQ
Explanation:
Anypoint MQ is a cloud-based message queue service provided by MuleSoft. It supports reliable asynchronous communication between applications, and it can be used to decouple producers and consumers of messages. Anypoint MQ ensures message delivery guarantees, including at-least-once delivery and in-order message processing.
In this scenario, where you need to broadcast Mule events to external consumers outside the Mule application and guarantee reliable delivery with minimized duplicate
delivery, Anypoint MQ is a suitable choice. It allows you to publish messages to a topic or queue, and external consumers can subscribe to receive those messages.
CloudHub VM queues (Option A) are specific to CloudHub, and they may not be accessible for external consumers outside the organizational network. Anypoint Exchange (Option D) is a collaboration platform but not specifically designed for event broadcasting. The CloudHub Shared Load Balancer (Option C) is used for routing traffic to different instances of an application running on CloudHub and doesn't directly address the requirement of broadcasting Mule events to external consumers.
54)
An organization uses MuleSoft extensively and has about 2,000 employees. Many of them work on MuleSoft APIs. The organization has approximately 500 APIs in production. The organization's leadership strictly discourages direct API modification (for example, stop/start/delete in production); however, there have been a few instances where modifications in production occurred. Now leadership wants to know
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
every instance when this occurred in the past year and include timestamps and user IDs. What is the easiest way to retrieve this information? A) Submit a support ticket to the MuleSoft product team to create a custom report B) Use MuleSoft audit logs; however, the audit logs only store data for six months C) Invoke the Runtime Manager Platform API for each production API and check access_history one-by-one D) Invoke Audit Log Query Platform API and using a combination of filters such as timeframe and action Type to extract a user list
Answer:
D) Invoke Audit Log Query Platform API and using a combination of filters such as timeframe and action type to extract a user list
Explanation:
The easiest way to retrieve information about API modifications in production, including timestamps and user IDs, is to use the MuleSoft Audit Log Query Platform API. The Audit Log provides a record of operations performed in Anypoint Platform, including changes to API configurations and runtime actions.
By invoking the Audit Log Query Platform API, you can filter the logs based on criteria such as timeframe and action type. In this case, you can filter for actions related to API modifications in the past year. The combination of filters will allow you
to extract a user list along with timestamps and details of the modifications.
This approach provides a programmatic way to retrieve the required information without manual checking or submitting a support ticket. It leverages the capabilities of the Audit Log to track and report on user activities in Anypoint Platform.
55)
NEED TO SET
56)
An organization is automating its deployment process to increase the reliability of its builds and general development process by automating the running of tests during its builds. Which tool is responsible for automating its test execution? A) Mule Maven plugin B) Anypoint CLI C) MUnit Maven plugin D) Munit
Answer:
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
C) MUnit Maven plugin
Explanation:
The MUnit Maven plugin is responsible for automating the execution of MUnit tests. MUnit is a testing framework for Mule applications, and the MUnit Maven plugin allows you to integrate MUnit tests into your Maven build process. By using the MUnit Maven plugin, you can automate the execution of tests during builds, ensuring that tests are run automatically as part of your continuous integration and deployment pipeline.
57)
A large enterprise is building APIs to connect to their 300 systems of records across all of their departments. These systems have a variety of data formats to exchange with the APIs, and the Solution Architect plans to use the application/dw format for data transformations. What are two facts that the Integration Architect must be aware of when using the application/dw format for transformations? (Choose two.) A) The application/dw configuration property must be set to "onlyData=true" when reading or writing data in the application/dw format B) The application/dw format is the only native format that never runs into an Out Of Memory Error C) The application/dw format can impact performance and is not recommended in a production environment D) The application/dw format stores input data from an entire file in-memory if the file is 10MB or less E) The application/dw format improves performance and is recommended for all production environments
Answer:
C) The application/dw format can impact performance and is not recommended in a production environment
D) The application/dw format stores input data from an entire file in-memory if the file is 10MB or less
Explanation:
A and B are incorrect because there is no "onlyData" property associated with the application/dw format, and the statement that the application/dw format is the only native format that never runs into an Out Of Memory Error is not accurate.
C is correct because the application/dw format can impact performance, especially when dealing with large datasets, and it's generally not recommended for use in a production environment where performance is crucial.
D is correct because, by default, the application/dw format stores input data from an entire file in-memory if the file is 10MB or less. This behavior can lead to increased memory usage for large files.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
E is incorrect because the application/dw format's impact on performance may make it unsuitable for all production environments. The choice of format depends on various factors, including the specific use case and performance requirements.
58)
A company is tracking the number of patient COVID-19 tests given across a region, and the number of records handled by the system is in the millions. Test results must be accessible to doctors in offices, hospitals, and urgent-care facilities within three seconds of the request, particularly for patients at high risk. Given this information, which test supports the system for the risk assessment? A) Unit test B) Performance test C) Integration test D) User acceptance test
Answer:
B) Performance test
Explanation:
A performance test is designed to evaluate the system's performance, scalability, and responsiveness under different conditions, including heavy loads. In this case, the requirement is to ensure that test results are accessible within three seconds of the request, particularly for high-risk patients. A performance test can help assess whether
the system can handle the required load and respond within the specified time frame.
Unit tests are focused on individual components or functions and may not address the broader system's performance characteristics.
Integration tests check interactions between different components or systems but may not specifically focus on performance metrics.
User acceptance tests are typically designed to ensure that the system meets user requirements and expectations but may not specifically address performance criteria.
59)
An organization has defined a common object model in Java to mediate the communication between different Mule applications in a consistent way. A Mule application is being built to use this common object model to process responses from a SOAP API and a REST API and then write the processed results to an order management system. The developers want Anypoint Studio to utilize these common objects to assist in creating mappings for various transformation steps in the Mule application. What is the most straightforward way to utilize these common objects to map between the inbound and outbound systems in the Mule application? A) Use JAXB (XML) and Jackson (JSON) data bindings B) Use Idempotent Message Validator components
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
C) Use the Transform Message component D) Use the Java module
Answer:
D) Use the Java module
Explanation:
The most straightforward way to utilize common Java objects to map between the inbound and outbound systems in a Mule application is to use the Java module. The Java module in Anypoint Studio allows you to leverage Java code directly within your
Mule application. You can write custom Java transformers or processors that work with your common Java objects and perform the necessary mapping.
Option A mentions JAXB (XML) and Jackson (JSON) data bindings, which are related to data serialization and deserialization. While they are useful for handling XML and JSON formats, they may not directly address the use of common Java objects for mapping transformations.
Options B and C are not specifically designed for utilizing common Java objects for mapping transformations in the way described in the question. The Transform Message component is more generic and can work with various data formats, but it may not directly integrate with a predefined common object model. The Idempotent Message Validator is used for ensuring idempotence in processing, not for mapping between different objects.
60)
An external REST client periodically sends an array of records in a single POST request to a Mule application's API endpoint. The Mule application must validate each
record of the request against a JSON schema before sending it to a downstream system in the same order that it was received in the array. Record processing will take place inside a router or scope that calls a child flow. The child flow has its own error handling defined. Any validation or communication failures should not prevent further processing of the remaining records. Which router or scope should be used in the parent flow, and which type of error handler should be used in the child flow in order to meet these requirements? A) Choice router in the parent flow On Error Continue error handler in the child flow B) Parallel For Each scope in the parent flow On Error Propagate error handler in the child flow C) Until Successful router in the parent flow On Error Propagate error handler in the child flow D) For Each scope in the parent flow On Error Continue error handler in the child flow
Answer:
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
C) Until Successful router in the parent flow
On Error Propagate error handler in the child flow
Explanation:
To meet the requirements outlined in the question, you should use the "Until Successful" router in the parent flow and an "On Error Propagate" error handler in the
child flow.
1. **Until Successful Router (Parent Flow):**
- The "Until Successful" router allows you to repeatedly execute a set of message processors until the processing is successful. It retries the processing until either a successful response is received or a specified number of retries is exhausted.
- Configure the "Until Successful" router to repeat the processing for each record in the array. If a record fails validation or communication, the router will retry processing that record.
2. **On Error Propagate Error Handler (Child Flow):**
- Configure the child flow with an "On Error Propagate" error handler.
- The "On Error Propagate" error handler allows the flow to continue processing the remaining records even if an error occurs within the child flow. It propagates the error
to the parent flow but does not cause the entire parent flow to fail.
This setup ensures that the parent flow continues processing the array of records until all records are successfully processed or the maximum retry attempts are reached. If a record fails validation or communication, it doesn't prevent the processing of subsequent records. The error is propagated to the parent flow, but the flow continues with the next record.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
Related Documents
Recommended textbooks for you
Operations Research : Applications and Algorithms
Computer Science
ISBN:9780534380588
Author:Wayne L. Winston
Publisher:Brooks Cole
Systems Architecture
Computer Science
ISBN:9781305080195
Author:Stephen D. Burd
Publisher:Cengage Learning
Principles of Information Security (MindTap Cours...
Computer Science
ISBN:9781337102063
Author:Michael E. Whitman, Herbert J. Mattord
Publisher:Cengage Learning
Principles of Information Systems (MindTap Course...
Computer Science
ISBN:9781305971776
Author:Ralph Stair, George Reynolds
Publisher:Cengage Learning
Fundamentals of Information Systems
Computer Science
ISBN:9781305082168
Author:Ralph Stair, George Reynolds
Publisher:Cengage Learning
Recommended textbooks for you
- Operations Research : Applications and AlgorithmsComputer ScienceISBN:9780534380588Author:Wayne L. WinstonPublisher:Brooks ColeSystems ArchitectureComputer ScienceISBN:9781305080195Author:Stephen D. BurdPublisher:Cengage LearningPrinciples of Information Security (MindTap Cours...Computer ScienceISBN:9781337102063Author:Michael E. Whitman, Herbert J. MattordPublisher:Cengage Learning
- Principles of Information Systems (MindTap Course...Computer ScienceISBN:9781305971776Author:Ralph Stair, George ReynoldsPublisher:Cengage LearningFundamentals of Information SystemsComputer ScienceISBN:9781305082168Author:Ralph Stair, George ReynoldsPublisher:Cengage Learning
Operations Research : Applications and Algorithms
Computer Science
ISBN:9780534380588
Author:Wayne L. Winston
Publisher:Brooks Cole
Systems Architecture
Computer Science
ISBN:9781305080195
Author:Stephen D. Burd
Publisher:Cengage Learning
Principles of Information Security (MindTap Cours...
Computer Science
ISBN:9781337102063
Author:Michael E. Whitman, Herbert J. Mattord
Publisher:Cengage Learning
Principles of Information Systems (MindTap Course...
Computer Science
ISBN:9781305971776
Author:Ralph Stair, George Reynolds
Publisher:Cengage Learning
Fundamentals of Information Systems
Computer Science
ISBN:9781305082168
Author:Ralph Stair, George Reynolds
Publisher:Cengage Learning