A company wants its users to log in to Anypoint Platform using the company's own internal user credentials. To achieve this, the company needs to integrate an external identity provider (IdP) with the company's Anypoint Platform master organization, but SAML 2.0 CANNOT be used. Besides SAML 2.0, what single-sign-on standard can the company use to integrate the IdP with their Anypoint Platform master organization?
A. SAML 1.0
B. OAuth 2.0
C. Basic Authentication
D. OpenID Connect
Explanation
As the Anypoint Platform organization administrator, you can configure identity management in Anypoint Platform to set up users for single sign-on (SSO).
Configure identity management using one of the following single sign-on standards:
1) OpenID Connect: End user identity verification by an authorization server including SSO
2) SAML 2.0: Web-based authorization including cross-domain SSO
A platform architect includes both an API gateway and a service mesh in the architect of a distributed application for communication management. Which type of communication management does a service mesh typically perform in this architecture?
A. Between application services and the firewall
B. Between the application and external API clients
C. Between services within the application
D. Between the application and external API implementations.
Explanation:
In a distributed application architecture, a service mesh typically manages communication between services within the application. A service mesh provides a dedicated infrastructure layer that handles service-to-service communication, including service discovery, load balancing, failure recovery, metrics, and monitoring. This allows developers to offload these operational concerns from individual services, ensuring consistent and reliable inter-service communication.
References:
Understanding Service Mesh
Service Mesh for Microservices
According to MuleSoft's API development best practices, which type of API development approach starts with writing and approving an API contract?
A. Implement-first
B. Catalyst
C. Agile
D. Design-first
Explanation:
MuleSoft's API development best practices emphasize a design-first approach, which starts with writing and approving an API contract before any implementation begins. This approach ensures that the API's interface is agreed upon and understood by all stakeholders before the backend is built. It involves creating an API specification using tools like RAML or OpenAPI, which serves as a blueprint for development. This method promotes better planning, communication, and alignment between different teams and stakeholders, leading to more efficient and predictable API development processes.
References:
API Design Best Practices
MuleSoft's Approach to API Development
An organization is evaluating using the CloudHub shared Load Balancer (SLB) vs creating a CloudHub dedicated load balancer (DLB). They are evaluating how this choice affects the various types of certificates used by CloudHub deplpoyed Mule applications, including MuleSoft-provided, customer-provided, or Mule application-provided certificates. What type of restrictions exist on the types of certificates that can be exposed by the CloudHub Shared Load Balancer (SLB) to external web clients over the public internet?
A. Only MuleSoft-provided certificates are exposed.
B. Only customer-provided wildcard certificates are exposed.
C. Only customer-provided self-signed certificates are exposed.
D. Only underlying Mule application certificates are exposed (pass-through)
Explanation:
https://docs.mulesoft.com/runtime-manager/dedicated-load-balancer-tutorial
An organization plans to migrate all its Mule applications to Runtime Fabric (RTF). Currently, all Mule applications have been deployed to CloudHub using automated CI/CD scripts. What steps should be taken to properly migrate the applications from CloudHub to RTF, while keeping the same automated CI/CD deployment strategy?
A. A runtimefabric dependency should be added as a mule-plugin to the pom.xml file in all the Mule applications.
B. runtimeFabric command-line parameter should be added to the CI/CD deployment scripts.
C. A runtimefFabricDeployment profile should be added to Mule configuration properties YAML files in all the Mule applications. CI/CD scripts must be modified to use the new configuration properties.
D. runtimefabricDeployment profile should be added to the pom.xml file in all the Mule applications. CI/CD scripts must be modified to use the new RTF profile.
E. - The pom.xml and Mule configuration YAML files can remain unchanged in each Mule application. A --runtimeFabric command-line parameter should be added to the CI/CD deployment scripts
Explanation:
To migrate Mule applications from CloudHub to Runtime Fabric (RTF) while maintaining the same automated CI/CD deployment strategy, follow these steps:
Add runtimefabricDeployment Profile: Add a runtimefabricDeployment profile to the pom.xml file in all Mule applications. This profile will include the necessary configurations specific to RTF deployments.
Modify CI/CD Scripts: Update the CI/CD deployment scripts to use the new runtimefabricDeployment profile. This modification ensures that the deployment process will correctly reference the RTF-specific configurations when deploying applications.
Keep Configuration Files Unchanged: There is no need to change the pom.xml and Mule configuration YAML files other than adding the runtimefabricDeployment profile. This maintains consistency and reduces the risk of errors during the migration.
This approach ensures a smooth transition to RTF while leveraging existing CI/CD scripts with minimal changes, maintaining the automated deployment strategy.
References
MuleSoft Documentation on Runtime Fabric Deployment
Best Practices for CI/CD with MuleSoft
An organization is using Mulesoft cloudhub and develops API's in the latest version. As a part of requirements for one of the API's, third party API needs to be called. The security team has made it clear that calling any external API needs to have include listing As an integration architect please suggest the best way to accomplish the design plan to support these requirements?
A. Implement includelist IP on the cloudhub VPC firewall to allow the traffic
B. Implement the validation of includelisted IP operation
C. Implement the Any point filter processor to implement the include list IP
D. Implement a proxy for the third party API and enforce the IPinclude list policy and call this proxy from the flow of the API
Explanation:
Requirement Analysis: The security team requires any external API call to be restricted by an IP include list. This ensures that only specified IP addresses can access the third-party API.
Design Plan: To fulfill this requirement, implementing a proxy for the third-party API is the best approach. This proxy can enforce the IP include list policy.
Implementation Steps:
Advantages:
References
MuleSoft Documentation on API Proxies
MuleSoft Documentation on IP Whitelist Policy
What is required before an API implemented using the components of Anypoint Platform can be managed and governed (by applying API policies) on Anypoint Platform?
A. 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
B. The API implementation source code must be committed to a source control management system (such as GitHub)
C. A RAML definition of the API must be created in API designer so it can then be published to Anypoint Exchange
D. The API must be shared with the potential developers through an API portal so API consumers can interact with the API
Explanation
Context of the question is about managing and governing mule applications deployed on Anypoint platform.
Anypoint API Manager (API Manager) is a component of Anypoint Platform that enables you to manage, govern, and secure APIs. It leverages the runtime capabilities of API Gateway and Anypoint Service Mesh, both of which enforce policies, collect and track analytics data, manage proxies, provide encryption and authentication, and manage applications.
Mule Ref Doc : https://docs.mulesoft.com/api-manager/2.x/getting-started-proxy
Reference: [Reference: https://docs.mulesoft.com/api-manager/2.x/api-auto-discovery-new-concept, ]
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.
What Anypoint Platform service is most idiomatic (used for its intended purpose) for publishing these Mule events to all external consumers while addressing the desired reliability goals?
A. CloudHub VM queues
B. Anypoint MQ
C. Anypoint Exchange
D. CloudHub Shared Load Balancer
Explanation:
Set the Anypoint MQ connector operation to publish or consume messages, or to accept (ACK) or not accept (NACK) a message.
Reference: [Reference: https://docs.mulesoft.com/mq/, , , ]
A mule application is required to periodically process large data set from a back-end database to Salesforce CRM using batch job scope configured properly process the higher rate of records. The application is deployed to two cloudhub workers with no persistence queues enabled. What is the consequence if the worker crashes during records processing?
A. Remaining records will be processed by a new replacement worker
B. Remaining records be processed by second worker
C. Remaining records will be left and processed
D. All the records will be processed from scratch by the second worker leading to duplicate processing
Explanation:
When a Mule application uses batch job scope to process large datasets and is deployed on multiple CloudHub workers without persistence queues enabled, the following scenario occurs if a worker crashes:
Batch Job Scope: Batch jobs are designed to handle large datasets by splitting the work into records and processing them in parallel.
Non-Persistent Queues: When persistence is not enabled, the state of the batch processing is not stored persistently. This means that if a worker crashes, the state of the in-progress batch job is lost.
Worker Crash Consequence:
This behavior can cause issues such as duplicate data in Salesforce CRM and inefficiencies in processing.
References
MuleSoft Batch Processing
MuleSoft CloudHub Workers
A company is designing an integration Mule application to process orders by submitting them to a back-end system for offline processing. Each order will be received by the Mule application through an HTTP5 POST and must be acknowledged immediately.
Once acknowledged the order will be submitted to a back-end system. Orders that cannot be successfully submitted due to the rejections from the back-end system will need to be processed manually (outside the banking system).
The mule application will be deployed to a customer hosted runtime and will be able to use an existing ActiveMQ broker if needed. The ActiveMQ broker is located inside the organization's firewall. The back-end system has a track record of unreliability due to both minor network connectivity issues and longer outages.
Which combination of Mule application components and ActiveMQ queues are required to ensure automatic submission of orders to the back-end system while supporting but minimizing manual order processing?
A. One or more On Error scopes to assist calling the back-end system An Untill successful scope containing VM components for long retries A persistent dead-letter VM queue configure in Cloud hub
B. An Until Successful scope to call the back-end system One or more ActiveMQ long-retry queues One or more ActiveMQ dead-letter queues for manual processing
C. One or more on-Error scopes to assist calling the back-end system one or more ActiveMQ long-retry queues A persistent dead-letter Object store configuration in the CloudHub object store service
D. A batch job scope to call the back in system An Untill successful scope containing Object Store components for long retries. A dead-letter object store configured in the Mule application
Explanation:
To design an integration Mule application that processes orders and ensures reliability even with an unreliable back-end system, the following components and ActiveMQ queues should be used:
Until Successful Scope: This scope ensures that the Mule application will continue trying to submit the order to the back-end system until it succeeds or reaches a specified retry limit. This helps in handling transient network issues or minor outages of the back-end system.
ActiveMQ Long-Retry Queues: By placing the orders in long-retry queues, the application can manage retries over an extended period. This is particularly useful when the back-end system experiences longer outages. The ActiveMQ broker, located within the organization’s firewall, can reliably handle these queues.
ActiveMQ Dead-Letter Queues: Orders that cannot be successfully submitted after all retry attempts should be moved to dead-letter queues. This allows for manual processing of these orders. The dead-letter queue ensures that no orders are lost and provides a clear mechanism for handling failed submissions.
Implementation Steps:
HTTP Listener: Set up an HTTP listener to receive incoming orders.
Immediate Acknowledgment: Immediately acknowledge the receipt of the order to the client.
Until Successful Scope: Use the Until Successful scope to attempt submitting the order to the back-end system. Configure retry intervals and limits.
Long-Retry Queues: Configure ActiveMQ long-retry queues to manage retries.
Dead-Letter Queues: Set up ActiveMQ dead-letter queues for orders that fail after maximum retry attempts, allowing for manual intervention.
This approach ensures that the system can handle temporary and prolonged back-end outages while minimizing manual processing.
References:
MuleSoft Documentation on Until Successful Scope: https://docs.mulesoft.com/mule-runtime/4.3/until-successful-scope
ActiveMQ Documentation: https://activemq.apache.org/
How should the developer update the logging configuration in order to enable this package specific debugging?
A. In Anypoint Monitoring, define a logging search query with class property set to org.apache.cxf and level set to DEBUG
B. In the Mule application's log4j2.xml file, add an AsyncLogger element with name property set to org.apache.cxf and level set to DEBUG, then redeploy the Mule application in the CloudHub production environment
C. In the Mule application's log4j2.xmI file, change the root logger's level property to DEBUG, then redeploy the Mule application to the CloudHub production environment
D. In Anypoint Runtime Manager, in the Deployed Application Properties tab for the Mule application, add a line item with DEBUG level for package org.apache.cxf and apply the changes
Explanation:
To enable package-specific debugging for the org.apache.cxf package, you need to update the logging configuration in the Mule application's log4j2.xml file. The steps are as follows:
Open the log4j2.xml file in your Mule application.
Add an AsyncLogger element with the name property set to org.apache.cxf and the level set to DEBUG. This configuration specifies that only the logs from the org.apache.cxf package should be logged at the DEBUG level.
Save the changes to the log4j2.xml file.
Redeploy the updated Mule application to the CloudHub production environment to apply the new logging configuration.
This approach ensures that only the specified package's logging level is changed to DEBUG, minimizing the potential performance impact on the application.
References
MuleSoft Documentation on Configuring Logging
Log4j2 Configuration Guide
A leading eCommerce giant will use MuleSoft APIs on Runtime Fabric (RTF) to process customer orders. Some customer-sensitive information, such as credit card information, is required in request payloads or is included in response payloads in some of the APIs. Other API requests and responses are not authorized to access some of this customer-sensitive information but have been implemented to validate and transform based on the structure and format of this customer-sensitive information (such as account IDs, phone numbers, and postal codes).
What approach configures an API gateway to hide sensitive data exchanged between API consumers and API implementations, but can convert tokenized fields back to their original value for other API requests or responses, without having to recode the API implementations?
Later, the project team requires all API specifications to be augmented with an additional non-functional requirement (NFR) to protect the backend services from a high rate of requests, according to defined service-level
agreements (SLAs). The NFR's SLAs are based on a new tiered subscription level "Gold", "Silver", or "Platinum" that must be tied to a new parameter that is being added to the Accounts object in their enterprise data model.
Following MuleSoft's recommended best practices, how should the project team now convey the necessary non-functional requirement to stakeholders?
A. Create and deploy API proxies in API Manager for the NFR, change the baseurl in each API specification to the corresponding API proxy implementation endpoint, and publish each modified API specification to Exchange
B. Update each API specification with comments about the NFR's SLAs and publish each modified API specification to Exchange
C. Update each API specification with a shared RAML fragment required to implement the NFR and publish the RAML fragment and each modified API specification to Exchange
D. Create a shared RAML fragment required to implement the NFR, list each API implementation endpoint in the RAML fragment, and publish the RAML fragment to Exchange
Explanation:
To convey the necessary non-functional requirement (NFR) related to protecting backend services from a high rate of requests according to SLAs, the following steps should be taken:
Create a Shared RAML Fragment: Develop a RAML fragment that defines the NFR, including the SLAs for different subscription levels ("Gold", "Silver", "Platinum"). This fragment should include the details on rate limiting and throttling based on the new parameter added to the Accounts object.
Update API Specifications: Integrate the shared RAML fragment into each API specification. This ensures that the NFR is consistently applied across all relevant APIs.
Publish to Exchange: Publish the updated API specifications and the shared RAML fragment to Anypoint Exchange. This makes the NFR visible and accessible to all stakeholders and developers, ensuring compliance and implementation consistency.
This approach ensures that the NFR is clearly communicated and applied uniformly across all API implementations.
References
MuleSoft Documentation on RAML and API Specifications
Best Practices for API Design and Documentation
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