MuleSoft-Integration-Architect-I Salesforce Certified MuleSoft Platform Integration Architect (Mule-Arch-202) Questions and Answers

In an HTTP/1.1-compliant web service, the class of HTTP response status codes that indicates successful client requests is the 2xx class. These status codes signify that the client's request was successfully received, understood, and accepted by the web service. Common 2xx status codes include:

200 OK: The request was successful.

201 Created: The request was successful and a new resource was created.

202 Accepted: The request has been accepted for processing, but the processing is not yet complete.

Other status code classes like 3xx (redirection), 4xx (client errors), and 5xx (server errors) indicate different types of responses and do not signify successful request processing.

References

IETF RFC 2616: HTTP/1.1 Specification

HTTP Status Code Definitions

Explanation

* Object Store and VM Store is used for sharing data inter or intra mule applications in same setup. Can't be used with external Business Partner

* Also File connector will not be useful as the two companies currently have no shared IT infrastructure. It's specific for local use.

* Correct answer is SFTP connector. The SFTP Connector implements a secure file transport channel so that your Mule application can exchange files with external resources. SFTP uses the SSH security protocol to transfer messages. You can implement the SFTP endpoint as an inbound endpoint with a one-way exchange pattern, or as an outbound endpoint configured for either a one-way or request-response exchange pattern.

* "100% increase in the throughput of the API" might look correct, as the number of requests processed per second might increase, but is it guaranteed to increase by 100%? Using 4 nodes will definitely increase throughput of system. But it is cant be precisely said if there would be 100% increase in throughput as it depends on many other factors. Also it is nowhere mentioned in the description that all nodes have same CPU/memory assigned. The question is about the guaranteed behavior * Increasing number of nodes will have no impact on response time as we are scaling application horizontally and not vertically. Similarly there is no change in JVM heap memory usage. * So Correct answer is 50% reduction in the number of requests being received by each node This is because of the two reasons. 1) API is mentioned as stateless 2) Load Balancer is used

Explanation

* Anypoint Runtime Fabric is a container service that automates the deployment and orchestration of your Mule applications and gateways.

* Runtime Fabric runs on customer-managed infrastructure on AWS, Azure, virtual machines (VMs) or bare-metal servers.

* As none of the Mule applications use Mule domain projects. applications are not required to be rewritten. Also when applications are deployed on RTF, by default ingress is allowed only on 8081.

* Hence port conflicts are not required to be managed by DevOps team

In a typical MuleSoft integration project, the role primarily responsible for building API implementations is the API Developer. The API Developer focuses on writing the code that implements the logic, data transformations, and business processes defined in the API specifications. They use tools like Anypoint Studio to develop and test Mule applications, ensuring that the APIs function as required and integrate seamlessly with other systems and services.

While the API Designer is responsible for defining the API specifications and the Integration Architect for designing the overall integration solution, the API Developer translates these designs into working software. The Operations team typically manages the deployment, monitoring, and maintenance of the APIs in production environments.

References

MuleSoft Documentation on Roles and Responsibilities

Anypoint Platform Development Best Practices

Understanding the Operations:

The Finance operation can only look up one account record at a time.

The Audit operation can only insert one account record at a time.

Parallel For-Each Scope:

Finance Operation: Use a Parallel For-Each scope to process multiple account lookups simultaneously.

This improves performance by allowing concurrent processing of account records, leveraging parallelism.

Async Scope:

Audit Operation: Use an Async scope to handle the insertion of account records independently.

The Async scope ensures that the Audit operation does not block the main processing flow, allowing other processes to continue without waiting for the Audit operation to complete.

Performance Optimization:

Combining Parallel For-Each for the Finance operation and Async scope for the Audit operation maximizes throughput.

This approach ensures efficient use of resources and reduces latency by parallelizing account lookups and asynchronously handling audit inserts.

MuleSoft Documentation on Scopes: Mule Scopes

MuleSoft Best Practices for Performance: Performance Best Practices

Explanation

* If we store Correlation id value in step 1 as Mule event variables/attributes, the values will be cleared after server restart and we want system to be fault tolerant.

* The Correlation ID value in Step 1 should be stored in a persistent object store.

* We don't need to store Correlation ID value in Step 3 to persistent object store. We can store it but as we also need to make application performant. We can avoid this step of accessing persistent object store.

*  Accessing persistent object stores slow down the performance as persistent object stores are by default stored in shared file systems.

*  As the SOAP service is idempotent in nature. In case of any failures , using this Correlation ID saved in first step we can make call to SOAP service and validate the Correlation ID.

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Additional Information:

* Competing Consumers are multiple consumers that are all created to receive messages from a single Point-to-Point Channel. When the channel delivers a message, any of the consumers could potentially receive it. The messaging system's implementation determines which consumer actually receives the message, but in effect the consumers compete with each other to be the receiver. Once a consumer receives a message, it can delegate to the rest of its application to help process the message.

* In case you are unaware about term idempotent re is more info:

Idempotent operations means their result will always same no matter how many times these operations are invoked.

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An Enterprise Architect would use a single enterprise-wide canonical data model (CDM) when designing an integration solution to achieve the following benefits:

Reduced Dependencies: By standardizing on a single data model, it simplifies the integration process between multiple systems that may use different data formats. This eliminates the need for numerous point-to-point transformations.

Consistency and Reusability: A CDM ensures consistent data representation across the enterprise, which promotes data integrity and reusability of integration components.

Simplified Maintenance: Having a single data model reduces the complexity of maintaining and updating integration solutions, as changes need to be made in only one place.

The CDM acts as an abstraction layer that decouples systems, facilitating easier integration and reducing the potential for errors.

References

MuleSoft Documentation on Canonical Data Models

Best Practices for Data Integration with MuleSoft

To track the entire lifecycle of each request across different microservices, the DevOps team should consider adopting tracing. Distributed tracing allows teams to follow a request as it travels through the various microservices, providing visibility into how long each part of the request lifecycle takes and where any bottlenecks or failures occur. Tools like Zipkin, Jaeger, and AWS X-Ray are commonly used for this purpose. Tracing complements metrics and logging by providing detailed insights into the interactions and dependencies between services.

Explanation

Correct answer is Anypoint Runtime Manager

MuleSoft Anypoint Runtime Manager (ARM) provides connectivity to Mule Runtime engines deployed across your organization to provide centralized management, monitoring and analytics reporting. However, most enterprise customers find it necessary for these on-premises runtimes to integrate with their existing non MuleSoft analytics / monitoring systems such as Splunk and ELK to support a single pane of glass view across the infrastructure.

* You can configure the Runtime Manager agent to export data to external analytics tools.

Using either the Runtime Manager cloud console or Anypoint Platform Private Cloud Edition, you can:

--> Send Mule event notifications, including flow executions and exceptions, to Splunk or ELK.

--> Send API Analytics to Splunk or ELK. Sending data to third-party tools is not supported for applications deployed on CloudHub.

You can use the CloudHub custom log appender to integrate with your logging system. Reference: https://docs.mulesoft.com/runtime-manager/ https://docs.mulesoft.com/release-notes/runtime-manager-agent/runtime-manager-agent-release-notes

Additional Info:

It can be achieved in 3 steps:

1) register an agent to a runtime manager,

2) configure a gateway to enable API analytics to be sent to non MuleSoft analytics platform (Splunk for ex.) – as highlighted in the following diagram and

3) setup dashboards.

Explanation

Connected Apps

The Connected Apps feature provides a framework that enables an external application to integrate with Anypoint Platform using APIs through OAuth 2.0 and OpenID Connect. Connected apps help users delegate their access without sharing sensitive credentials or giving full control of their accounts to third parties. Actions taken by connected apps are audited, and users can also revoke access at any time. Note that some products do not currently include client IDs in this release of the Connected Apps feature. The Connected Apps feature enables you to use secure authentication protocols and control an app’s access to user data. Additionally, end users can authorize the app to access their Anypoint Platform data.

Mule Ref Doc : https://docs.mulesoft.com/access-management/connected-apps-overview

In MuleSoft's Anypoint Exchange, a complete API specification in RAML (RESTful API Modeling Language) or OAS (OpenAPI Specification) format is represented as a "REST API". This asset type provides a comprehensive description of the API, including endpoints, methods, request/response structures, and other relevant details. It serves as the blueprint for implementing and consuming the API, ensuring that all stakeholders have a clear understanding of its functionality and design.

Other asset types like connectors, API spec fragments, and SOAP APIs represent different components or partial specifications, but only REST APIs provide the full specification in the mentioned formats.

References

MuleSoft Anypoint Exchange Documentation

API Specification Documentation on RAML and OAS

When using a non-persistent object store in MuleSoft, the state data is stored in memory rather than on disk. This means that if a server crashes, all data stored in the non-persistent object store will be lost because it does not survive a server restart or crash. Non-persistent object stores are typically used for temporary data that does not need to be retained across application restarts. Therefore, in an environment where an API is maintaining its state using a non-persistent object store, a server crash will result in the loss of that state data.

MuleSoft Documentation on Object Store

Anypoint MQ is a cloud-based messaging service provided by MuleSoft, and it cannot be deployed on-premises. If there is a requirement for the messaging broker to be deployed on-premises, Anypoint MQ would not be suitable. Other considerations such as payload format (XML), encryption, and point-to-point messaging are supported by Anypoint MQ, but the deployment environment requirement is a critical constraint.

References

MuleSoft Anypoint MQ Documentation

Cloud vs. On-Premises Messaging Solutions

Set the Anypoint MQ connector operation to publish or consume messages, or to accept (ACK) or not accept (NACK) a message.

Explanation

* XA transaction add tremendous latency so "Reduce Latency" is incorrect option XA transactions define "All or No" commit protocol.

* Each local XA resource manager supports the A.C.I.D properties (Atomicity, Consistency, Isolation, and Durability).

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So correct choice is "Ensure consistency"

To efficiently handle the invocation of vendor applications and retry requests that generate timeout errors, the most performant way is:

Scatter-Gather Scope: Use a Scatter-Gather scope to invoke each vendor application in parallel. This approach allows the API to send requests to both vendors simultaneously, reducing overall processing time.

Until-Successful Scope: Inside each route of the Scatter-Gather scope, use an Until-Successful scope to handle retries. The Until-Successful scope will retry the request in case of timeout errors until the request succeeds or the maximum retry limit is reached.

This combination ensures that the API can handle intermittent network issues efficiently while minimizing redundant transactions and maximizing performance.

References

MuleSoft Documentation on Scatter-Gather Scope

MuleSoft Documentation on Until-Successful Scope and Error Handling

Explanation

Correct behavior is Each request is routed to ONE ARBITRARY CloudHub worker out of ALL three CloudHub workers

Explanation

When an operation in a Mule application fails to connect to an external server, the default behavior is for the operation to fail immediately and return a connectivity error. You can modify this default behavior by configuring a reconnection strategy for the operation. You can configure a reconnection strategy for an operation either by modifying the operation properties or by modifying the configuration of the global element for the operation. The following are the available reconnection strategies and their behaviors: None Is the default behavior, which immediately returns a connectivity error if the attempt to connect is unsuccessful Standard (reconnect) Sets the number of reconnection attempts and the interval at which to execute them before returning a connectivity error Forever (reconnect-forever) Attempts to reconnect continually at a given interval

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.

MuleSoft Documentation on Until Successful Scope: https://docs.mulesoft.com/mule-runtime/4.3/until-successful-scope

ActiveMQ Documentation: https://activemq.apache.org/

SLAs and non-functional requirements to access the backend systems. Only this option actually speaks to design parameters and reqs. * Below two are technical implementations and not the part of design: - Snapshots of the Mule application’s flows, including their error handling - The credentials to access the backend systems and contact details for the administrator of each system * List of consumers is not relevant to the design

To securely handle sensitive properties in a Mule application deployed through a CI/CD pipeline, the properties should be encrypted and stored as global configuration properties. This ensures that sensitive data is not visible in cleartext in Runtime Manager or any other configuration files. The steps are:

Encrypt Sensitive Properties: Use a tool or process to encrypt sensitive property values.

Global Configuration Properties: Store these encrypted values as global configuration properties within the Mule application.

Configuration in Runtime Manager: Ensure that these properties are referenced correctly so that administrators with proper permissions can manage them in Runtime Manager without exposing the sensitive values.

This approach aligns with security best practices and complies with the requirement to hide sensitive properties while allowing administrative control.

References

MuleSoft Documentation on Secure Property Placeholder

Best Practices for Handling Sensitive Data in MuleSoft

To secure all internal APIs within an integration solution by using an API proxy to apply required authentication and authorization policies, the organization should use API Management (APIM). APIM provides a comprehensive platform to manage, secure, and analyze APIs. It allows the IT team to create API proxies, enforce security policies, control access through authentication and authorization mechanisms, and monitor API usage.

Using APIM for this purpose ensures that internal APIs are protected with standardized security policies, facilitating centralized management and governance of API traffic. This approach is specifically designed for managing APIs and their security, making it the most suitable choice among the options provided.

References

MuleSoft Documentation on API Management

Best Practices for API Security and Governance

Explanation

* Semantic Versioning is a 3-component number in the format of X.Y.Z, where :

X stands for a major version.

Y stands for a minor version:

Z stands for a patch.

So, SemVer is of the form Major.Minor.Patch Coming to our question , minor version of the API has been changed which is backward compatible. Hence there is no change required on API client end. If they want to make use of new featured that have been added as a part of minor version change they may need to change code at their end. Hence correct answer is The API client code ONLY needs to be changed if it needs to take advantage of new features.

Explanation

* Shared load balancers don’t allow you to configure custom SSL certificates or proxy rules

* Dedicated Load Balancer are optional but you need to purchase them additionally if needed.

* TLS is a cryptographic protocol that provides communications security for your Mule app. TLS offers many different ways of exchanging keys for authentication, encrypting data, and guaranteeing message integrity.

* The CloudHub Shared Load Balancer terminates TLS connections and uses its own server-side certificate.

* Only a DLB allows the configuration of a custom TLS server certificate

* DLB enables you to define SSL configurations to provide custom certificates and optionally enforce two-way SSL client authentication.

* To use a DLB in your environment, you must first create an Anypoint VPC. Because you can associate multiple environments with the same Anypoint VPC, you can use the same dedicated load balancer for your different environments.

* MuleSoft Reference: https://docs.mulesoft.com/runtime-manager/dedicated-load-balancer-tutorial

Additional Info on SLB Vs DLB:

When migrating from an on-premises cluster to a Runtime Fabric (RTF) cluster, and needing to enable Mule applications to store and share data across application replicas and restarts, the use of Anypoint Object Store V2 is the most suitable option. Here’s why and how to implement it:

Understanding Object Store V2:

Object Store V2 is designed to store and retrieve key-value pairs in a scalable and highly available manner. It is particularly useful for sharing state and data between different instances of applications running on RTF.

Setting Up Anypoint Object Store V2:

First, ensure that your MuleSoft Anypoint Platform account has access to Object Store V2.

Configure your Mule application to use Object Store V2 by defining an object store in your Mule configuration file. This can be done using the objectstore element in your Mule flow.

Configuration Steps:

Add the Object Store connector to your Mule project.

Define the object store configuration in your Mule flow as follows:

xml

Use the object store in your flows to store and retrieve data:

xml

Deploying on RTF:

Deploy your Mule application to the RTF cluster. The RTF will handle scaling and ensure that the Object Store V2 is available to all instances of your application.

Benefits:

Object Store V2 ensures data is shared and persisted across different application replicas and restarts, which meets the requirement of storing and sharing data across application replicas in the RTF cluster.

MuleSoft Documentation on Object Store V2

MuleSoft Documentation on Runtime Fabric

Correct answer is Create WSDL specification using text editor SOAP services are specified using WSDL. A client program connecting to a web service can read the WSDL to determine what functions are available on the server. We can not create WSDL specification in Design Center. We need to use external text editor to create WSDL.

To ensure that data is encrypted both in-transit and at-rest, and to validate incoming requests to the Payment Processing API, the following approach is recommended:

TLS Inbound Policy: Apply a Transport Layer Security (TLS) - Inbound policy in API Manager. This policy ensures that the data is encrypted during transmission and can be decrypted by the API Manager before it reaches the Mule application.

Decryption: With the TLS policy applied, the message payload is decrypted when it is received by the API Manager.

JSON Validation: After decryption, the Mule application can use the JSON Validation module to validate the structure and content of the JSON data. This ensures that the payload conforms to the specified format and contains valid data.

This approach ensures that data is securely transmitted and properly validated upon receipt.

Transport Layer Security (TLS) Policies

JSON Validation Module

Explanation

JMX Management Java Management Extensions (JMX) is a simple and standard way to manage applications, devices, services, and other resources. JMX is dynamic, so you can use it to monitor and manage resources as they are created, installed, and implemented. You can also use JMX to monitor and manage the Java Virtual Machine (JVM). Each resource is instrumented by one or more Managed Beans, or MBeans. All MBeans are registered in an MBean Server. The JMX server agent consists of an MBean Server and a set of services for handling Mbeans. There are several agents provided with Mule for JMX support. The easiest way to configure JMX is to use the default JMX support agent. Log4J Agent The log4j agent exposes the configuration of the Log4J instance used by Mule for JMX management. You enable the Log4J agent using the element. It does not take any additional properties MuleSoft Reference: https://docs.mulesoft.com/mule-runtime/3.9/jmx-management

Explanation

Correct choice is: "The external API reported an error with the HTTP request that was received from the outbound HTTP Request operation of the Mule application"

Understanding HTTP 4XX Client Error Response Codes : A 4XX Error is an error that arises in cases where there is a problem with the user’s request, and not with the server.

Such cases usually arise when a user’s access to a webpage is restricted, the user misspells the URL, or when a webpage is nonexistent or removed from the public’s view.

In short, it is an error that occurs because of a mismatch between what a user is trying to access, and its availability to the user — either because the user does not have the right to access it, or because what the user is trying to access simply does not exist. Some of the examples of 4XX errors are

400 Bad Request The server could not understand the request due to invalid syntax. 401 Unauthorized Although the HTTP standard specifies "unauthorized", semantically this response means "unauthenticated". That is, the client must authenticate itself to get the requested response. 403 Forbidden The client does not have access rights to the content; that is, it is unauthorized, so the server is refusing to give the requested resource. Unlike 401, the client's identity is known to the server. 404 Not Found The server can not find the requested resource. In the browser, this means the URL is not recognized. In an API, this can also mean that the endpoint is valid but the resource itself does not exist. Servers may also send this response instead of 403 to hide the existence of a resource from an unauthorized client. This response code is probably the most famous one due to its frequent occurrence on the web. 405 Method Not Allowed The request method is known by the server but has been disabled and cannot be used. For example, an API may forbid DELETE-ing a resource. The two mandatory methods, GET and HEAD, must never be disabled and should not return this error code. 406 Not Acceptable This response is sent when the web server, after performing server-driven content negotiation, doesn't find any content that conforms to the criteria given by the user agent. The external API reported that the API implementation has moved to a different external endpoint cannot be the correct answer as in this situation 301 Moved Permanently The URL of the requested resource has been changed permanently. The new URL is given in the response. ----------------------------------------------------------------------------------------------------------------------------------------------- In Lay man's term the scenario would be: API CLIENT —> MuleSoft API - HTTP request “Hey, API.. process this” —> External API API CLIENT <– MuleSoft API - http response "I'm sorry Client.. something is wrong with that request" <– (4XX) External API

To design a caching strategy that queries the database only when there is an update to the Employees table, follow these steps:

On Table Row Operation: Configure an On Table Row operation to monitor the Employees table for updates.

Invalidate Cache: When the On Table Row operation detects an update, trigger the invalidate cache operation to clear the cache.

Object Store Caching Strategy: Use an object-store-caching-strategy to store the cached responses.

Default Expiration Interval: Use the default expiration interval for the cache, which ensures that cached data is invalidated based on the detection of changes in the Employees table rather than a fixed time interval.

This strategy ensures that the cache is only invalidated when there are actual changes in the Employees table, thereby minimizing redundant transactions and optimizing database performance.

References

MuleSoft Documentation on Caching Strategies

Best Practices for Database Integration with MuleSoft

Data confidentiality involves protecting information from unauthorized access and disclosure. Encrypting a file containing personally identifiable information (PII) is a prime example of ensuring data confidentiality. Encryption transforms the data into a format that is unreadable without the appropriate decryption key, thereby safeguarding sensitive information such as PII from being accessed by unauthorized parties. This measure is essential for compliance with data protection regulations and maintaining the privacy and security of personal data.

References

MuleSoft Security Best Practices

Data Protection and Encryption Standards Documentation

When a batch job instance running on a runtime fabric environment with two cluster replicas encounters an unexpected failure, the following sequence of events occurs:

Failure Detection: The runtime fabric environment detects the failure of the replica running the batch job.

Replica Replacement: A new replica is provisioned to replace the failed one.

Batch Job State Recovery: MuleSoft’s batch processing mechanism ensures that the state of the batch job is periodically saved (checkpointing). This allows the new replica to resume processing from the last saved state.

Resumption of Processing: The new replica takes over the batch job, continuing from where the previous one left off, thus processing the remaining 99,000 records without starting from scratch or causing duplicate processing.

MuleSoft Documentation on Batch Processing

Runtime Fabric Guide

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The interaction composition pattern used by the integration architect for the order processing API that coordinates stateful interactions with various microservices is called orchestration. Orchestration involves managing and coordinating multiple services to achieve a specific business process or workflow. In this case, the order processing API is responsible for validating, creating, and fulfilling new product orders by coordinating interactions with different microservices.

Orchestration provides a centralized control mechanism where the order processing API acts as the orchestrator, handling the sequence of service calls, managing state, and ensuring that the business process is executed correctly.

References

MuleSoft API-led Connectivity Approach

Patterns for Microservices and API Design

Object Store v2 (OSv2) in MuleSoft allows multiple applications within the same Anypoint Virtual Private Cloud (VPC) to share data. To achieve this, the OSv2 connector must be configured in each application to access the common persistent object store instance. This configuration enables the applications to read from and write to the same object store, facilitating data sharing. Object Store v2 is designed to be persistent and reliable, making it suitable for scenarios where data needs to be retained and shared across multiple applications.

MuleSoft Documentation on Object Store v2

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

Explanation

Correct answer is Workers are randomly distributed across available AZs within that region. This ensure high availability for deployed mule applications Mulesoft documentation reference :

https://docs.mulesoft.com/runtime-manager/cloudhub-hadr

When deploying to Runtime Fabric, there are several tools available within the Anypoint Platform ecosystem that facilitate the deployment process. These include:

AnypointCLI: This command-line interface tool provides comprehensive capabilities for deploying applications to Runtime Fabric. Using AnypointCLI, you can script and automate deployments, which is useful for integrating into CI/CD pipelines.

Anypoint Platform REST APIs: These APIs allow for programmatic deployment and management of applications on Runtime Fabric. They provide flexibility for integrating deployment processes with other systems and tools.

Mule Maven Plugin: This plugin can be used within a Maven project to package and deploy Mule applications to Runtime Fabric as part of a build process.

However, directly uploading a JAR file from the Runtime Manager is not a supported method for deploying to Runtime Fabric.

Anypoint CLI Documentation

Mule Maven Plugin Documentation

Requirement Analysis: The organization wants to standardize dependencies across all new and ongoing MuleSoft projects to minimize the impact of frequent plugin version upgrades and external plugin project dependencies.

Solution: Creating a parent POM (Project Object Model) file with all required dependencies and referencing it in each application's POM.xml file is the best practice.

Implementation Steps:

Create Parent POM:

Define a parent POM.xml file that includes all common dependencies, plugin versions, and configurations.

Example of a parent POM.xml:

pom</artifactId> 1.0.0 pom org.mule.runtime <artifactId>mule-core-extensions-maven-plugin</artifactId> 1.0.0 <!-- Add other dependencies here -->

Reference Parent POM:

In each application's POM.xml file, reference the parent POM.

Example of a child POM.xml referencing the parent POM:

4.0.0 com.example <artifactId>parent-pom</artifactId> 1.0.0 <artifactId>child-application</artifactId> 1.0.0 <!-- Application specific dependencies and configurations -->

Build and Test: Ensure that all applications build successfully with the parent POM and test them to confirm that the common dependencies are correctly applied.

Advantages:

Consistency: Ensures all projects use the same versions of dependencies, reducing the risk of conflicts.

Manageability: Simplifies dependency management by centralizing it in one parent POM file.

Scalability: Makes it easier to update dependencies across multiple projects by changing only the parent POM.

References

MuleSoft Documentation on Managing dependencies with Maven

Apache Maven Documentation on POM Reference

Explanation

* Organization can continue using existing load balancer even if backend application changes are there. So option A is ruled out.

* As Mule runtime is within their datacenter, this model is RTF and not PCE. So option C is ruled out.

Mule runtime deployment model within their datacenter, so each Mule runtime hosts several Mule applications -- This mean PCE or Hybird not RTF - Also mentioned in Question is that - Mule runtime is hosting several Mule Application, so that also rules out RTF and as for hosting multiple Application it will have Domain project which need redesign to make it microservice architecture

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Correct Answer: Required redesign of Mule applications to follow microservice architecture principles

Explanation

Correct answer is Batch-triggered ETL Within a Mule application, batch processing provides a construct for asynchronously processing larger-than-memory data sets that are split into individual records. Batch jobs allow for the description of a reliable process that automatically splits up source data and stores it into persistent queues, which makes it possible to process large data sets while providing reliability. In the event that the application is redeployed or Mule crashes, the job execution is able to resume at the point it stopped.

Explanation

Correct answer is EACH item VM message is processed AT LEAST ONCE by ONE ARBITRARY CloudHub worker. Each of the four CloudHub workers can be expected to process some item VM messages In Cloudhub, each persistent VM queue is listened on by every CloudHub worker - But each message is read and processed at least once by only one CloudHub worker and the duplicate processing is possible - If the CloudHub worker fails , the message can be read by another worker to prevent loss of messages and this can lead to duplicate processing - By default , every CloudHub worker's VM Listener receives different messages from VM Queue Referenece: https://dzone.com/articles/deploying-mulesoft-application-on-1-worker-vs-mult

MuleSoft customers often favor a MuleSoft-hosted Anypoint Platform runtime plane over a customer-hosted runtime for the following reasons:

Reduced time-to-market for the first application (C): Using a MuleSoft-hosted runtime plane accelerates the deployment process because MuleSoft manages the infrastructure, allowing customers to focus on developing and deploying their applications quickly. This leads to faster time-to-market for the initial application and subsequent updates.

Reduced IT operations effort (E): By leveraging a MuleSoft-hosted environment, customers offload the operational responsibilities, such as infrastructure maintenance, updates, and scalability management, to MuleSoft. This reduces the IT operations workload and allows internal teams to focus on more strategic initiatives.

In contrast, other options like reduced application latency and increased application throughput are not directly influenced by whether the runtime plane is MuleSoft-hosted or customer-hosted.

References

MuleSoft Anypoint Platform Documentation

MuleSoft Hosted vs. Customer Hosted Deployment Guides

To meet the requirements of enriching logging with more context and improving throughput while reducing latency, the customer should use an asynchronous logging approach. Here's why option B is correct:

Async Logger: Asynchronous logging helps in improving the performance by decoupling the logging from the main thread of execution. This reduces the latency of message processing since logging operations are offloaded to a separate thread.

Logging Level Greater than INFO: Logging at levels such as WARN, ERROR, or FATAL ensures that only essential logs are written asynchronously, further enhancing performance. Avoiding DEBUG or TRACE levels unless necessary reduces the overhead of logging.

Pattern Layout with [%MDC]: Using the pattern layout with [%MDC] in the log4j2.xml configuration file allows the inclusion of mapped diagnostic context in the logs. MDC is a feature that provides context-specific information, such as transaction IDs or user IDs, which helps in tracing and debugging.

Example configuration in log4j2.xml:

This configuration ensures that the logs are enriched with context information provided by MDC and processed asynchronously to maintain high throughput and low latency.

References

Log4j2 Asynchronous Logging

Mapped Diagnostic Context (MDC) in Log4j2

A Center for Enablement (C4E) provides significant benefits to an enterprise and its lines of business by accelerating self-service capabilities. A C4E is a cross-functional team that promotes the use of best practices, reusable assets, and consistent methodologies across the organization. By enabling lines of business to access and use shared resources, tools, and knowledge independently, a C4E empowers these units to deliver projects faster and more efficiently. This self-service model reduces reliance on central IT for every initiative, fosters innovation, and enhances the overall agility of the organization.

References

MuleSoft Center for Enablement (C4E) Overview

Best Practices for Implementing a C4E on Anypoint Platform

A Center for Enablement (C4E) provides significant benefits by accelerating self-service capabilities for lines of business. Here’s how:

Self-Service Enablement: C4E empowers lines of business to access, use, and create integrations and APIs independently, without relying heavily on central IT teams.

Guidelines and Standards: The C4E establishes best practices, standards, and reusable frameworks, ensuring that lines of business can develop solutions efficiently and consistently.

Faster Time-to-Market: By enabling self-service, lines of business can rapidly develop and deploy solutions to meet their specific needs, resulting in faster time-to-market for new initiatives.

Reduced Bottlenecks: Self-service reduces dependency on central IT, alleviating potential bottlenecks and allowing IT to focus on governance, security, and strategic projects.

The C4E model thus accelerates innovation and responsiveness within the enterprise.

Center for Enablement (C4E)

Benefits of a C4E

Explanation

* Any change in the application will require a restart except when the issue outside the app. For below situations , you would need to redeploy the code after doing necessary changes

-- One of the stored procedures being called by the Mule application has been renamed. In this case, in the Mule application you will have to do changes to accommodate the new stored procedure name.

-- Required redesign of Mule applications to follow microservice architecture principles. As code is changed, deployment is must

-- If the credentials changed and you need to update the connector or the properties.

-- The credentials for accessing the database have been updated and the previous credentials are no longer valid. In this situation you need to restart or redeploy depending on how credentials are configured in Mule application.

* So Correct answer is The database server was unavailable for four hours due to a major outage but is now fully operational again as this is the only external issue to application.

Anypoint Platform offers universal API management and Integration-Platform-as-a-Service (iPaaS) capabilities in a unified platform, meaning that it provides a single control plane to manage both full-lifecycle API management and integration. This allows organizations to easily manage their APIs and integrations, as well as deploy APIs and integrations quickly and efficiently. According to the MuleSoft Certified Integration Architect - Level 1 Course Book, “Anypoint Platform provides a unified platform for managing, deploying, and monitoring both API and integration solutions, allowing organizations to quickly and easily build and manage their APIs and integrations.”

Explanation

Correct answer is It is not possible to store logs for 2 years in CloudHub deployment. External log management system is required. CloudHub has a specific log retention policy, as described in the documentation: the platform stores logs of up to 100 MB per app & per worker or for up to 30 days, whichever limit is hit first. Once this limit has been reached, the oldest log information is deleted in chunks and is irretrievably lost. The recommended approach is to persist your logs to a external logging system of your choice (such as Splunk, for instance) using a log appender. Please note that this solution results in the logs no longer being stored on our platform, so any support cases you lodge will require for you to provide the appropriate logs for review and case resolution

To monitor Mule applications deployed on customer-hosted Mule runtimes from Anypoint Platform, you need to enable monitoring for each application within the Runtime Manager's application settings. This step ensures that the Runtime Manager Agent, which is already part of the Mule runtime, will collect and send monitoring data to Anypoint Monitoring.

The Runtime Manager Agent acts as the intermediary, collecting metrics and operational data from the Mule applications and transmitting this data to Anypoint Monitoring for analysis and visualization. This setup provides real-time insights and allows for effective monitoring and management of Mule applications.

MuleSoft Documentation on Anypoint Monitoring

Explanation

Object Store Connector is a Mule component that allows for simple key-value storage. Although it can serve a wide variety of use cases, it is mainly design for: - Storing synchronization information, such as watermarks. - Storing temporal information such as access tokens. - Storing user information. Additionally, Mule Runtime uses Object Stores to support some of its own components, for example: - The Cache module uses an Object Store to maintain all of the cached data. - The OAuth module (and every OAuth enabled connector) uses Object Stores to store the access and refresh tokens. Object Store data is in the same region as the worker where the app is initially deployed. For example, if you deploy to the Singapore region, the object store persists in the Singapore region. MuleSoft Reference : https://docs.mulesoft.com/object-store-connector/1.1/ Data can be shared between different instances of the Mule application. This is not recommended for Inter Mule app communication. Coming to the question, object store cannot be used to share cached data if it is deployed as separate Mule applications or deployed under separate Business Groups. Hence correct answer is When there is one CloudHub deployment of the API implementation to three workers that must share the cache state.

The MuleSoft-recommended best practice for sharing the connector and configuration information among multiple APIs is to use a Mule domain project. The steps are:

Create a Mule domain project.

Add the Database connector and its configuration to the domain project.

Reference this domain project from each System API that needs to use the Database connector and configuration.

By using a domain project, you centralize the configuration and reuse it across multiple APIs. This approach ensures consistency, reduces duplication, and simplifies maintenance and updates to the connector configuration.

References

MuleSoft Documentation on Domain Projects

Best Practices for Reusable Configuration in MuleSoft

Explanation

Correct answer is using below set of activities Until Successful component ActiveMQ long retry Queue ActiveMQ Dead Letter Queue for manual processing We will see why this is correct answer but before that lets understand few of the concepts which we need to know. Until Successful Scope The Until Successful scope processes messages through its processors until the entire operation succeeds. Until Successful repeatedly retries to process a message that is attempting to complete an activity such as: - Dispatching to outbound endpoints, for example, when calling a remote web service that may have availability issues. - Executing a component method, for example, when executing on a Spring bean that may depend on unreliable resources. - A sub-flow execution, to keep re-executing several actions until they all succeed, - Any other message processor execution, to allow more complex scenarios. How this will help requirement : Using Until Successful Scope we can retry sending the order to backend systems in case of error to avoid manual processing later. Retry values can be configured in Until Successful Scope Apache ActiveMQ It is an open source message broker written in Java together with a full Java Message Service client ActiveMQ has the ability to deliver messages with delays thanks to its scheduler. This functionality is the base for the broker redelivery plug-in. The redelivery plug-in can intercept dead letter processing and reschedule the failing messages for redelivery. Rather than being delivered to a DLQ, a failing message is scheduled to go to the tail of the original queue and redelivered to a message consumer. How this will help requirement : If backend application is down for a longer duration where Until Successful Scope wont work, then we can make use of ActiveMQ long retry Queue. The redelivery plug-in can intercept dead letter processing and reschedule the failing messages for redelivery. Mule Reference: https://docs.mulesoft.com/mule-runtime/4.3/migration-core-until-successful

To automate the API lifecycle in a CI/CD pipeline efficiently, leveraging Anypoint Platform's capabilities is crucial. Anypoint CLI (Command Line Interface) and Anypoint Platform REST APIs provide robust tools for managing various aspects of the API lifecycle, such as publishing, sharing, discovering, registering, applying policies, and deploying APIs. By using these tools with a scripting language like Groovy, you can script and automate these tasks to reduce manual intervention, ensuring consistency and efficiency.

Anypoint CLI allows you to interact with the Anypoint Platform from the command line, enabling automated deployments, management of APIs, and configuration of policies. The Anypoint Platform REST APIs provide comprehensive programmatic access to the platform’s functionalities, allowing for seamless integration into CI/CD pipelines. By combining these with a scripting language, you can create scripts that automate repetitive tasks, streamline processes, and ensure that your API lifecycle management is both efficient and reliable.

MuleSoft Documentation on Anypoint CLI

MuleSoft Documentation on Anypoint Platform REST APIs

The most performant way to handle intermittent network issues with vendor applications and ensure successful transaction reprocessing is to use a combination of the Scatter-Gather scope and the Until-Successful scope. Here’s how it works:

Scatter-Gather Scope: This scope allows you to send requests to multiple endpoints (in this case, the two vendor applications) simultaneously. This ensures that both vendors are queried at the same time, reducing overall processing time.

Until-Successful Scope: This scope is used to implement a retry mechanism. By wrapping each route to the vendor applications with an Until-Successful scope, the flow can automatically retry the request if a timeout error occurs. This scope retries the request until it succeeds or until a specified number of retries is reached.

Implementation Steps:

Configure a Scatter-Gather scope in your Mule application.

Inside each route of the Scatter-Gather scope, place an Until-Successful scope.

Configure the Until-Successful scope with appropriate retry policies, such as retry count and delay between retries.

Inside the Until-Successful scope, configure the HTTP request to the vendor application.

This approach ensures that:

Both vendor applications are queried in parallel.

Each request is retried upon timeout errors, ensuring eventual success without manual intervention.

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

Anypoint Exchange is the Anypoint Platform component that helps integration developers discover and share reusable APIs, connectors, and templates. It acts as a central repository where developers can publish and access various assets, facilitating reuse and collaboration within the organization. By using Anypoint Exchange, developers can reduce duplication of effort, speed up development processes, and ensure consistency across integrations.

Other components like API Manager, Anypoint Studio, and Design Center serve different purposes, such as managing APIs, developing Mule applications, and designing API specifications, but they are not specifically focused on discovering and sharing reusable assets.

References

MuleSoft Documentation on Anypoint Exchange

Best Practices for Asset Reuse on Anypoint Platform

Scatter-Gather sends a request message to multiple targets concurrently. It collects the responses from all routes, and aggregates them into a single message.

Anypoint Runtime Fabric is the appropriate choice for deploying Mule applications in an isolated Mule runtime within Docker containers on an Azure Kubernetes Service (AKS) infrastructure. This solution provides a containerized and orchestrated environment managed from the MuleSoft-hosted control plane. It enhances the availability, scalability, and robustness of Mule applications by allowing fine-grained control over deployments and providing built-in support for high availability and fault tolerance.

Explanation

Correct answer is Depending on the Listener operation configuration, either all messages are consumed by ONLY the primary cluster node or else EACH message is consumed by ANY ONE cluster node

For applications running in clusters, you have to keep in mind the concept of primary node and how the connector will behave. When running in a cluster, the JMS listener default behavior will be to receive messages only in the primary node, no matter what kind of destination you are consuming from. In case of consuming messages from a Queue, you’ll want to change this configuration to receive messages in all the nodes of the cluster, not just the primary.

This can be done with the primaryNodeOnly parameter:

Explanation

As the stakeholders are semitechnical users , preferred option is Create Anypoint Exchange entries with pages elaborating the integration design, including API notebooks (where applicable) to help the stakeholders understand and interact with the Mule applications and APIs at various levels of technical depth

MuleSoft's IT delivery and operating model suggests adopting an approach that decouples core IT projects from the innovation within each line of business. This approach, often referred to as API-led connectivity, allows different lines of business to innovate and deliver projects independently by using reusable APIs that provide access to core systems and data. This decoupling enhances agility, speeds up delivery, and ensures that core IT maintains control over critical systems and data while enabling rapid innovation.

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.

In Anypoint Exchange, policies are the asset type that represents configuration modules extending the functionality of an API and enforcing capabilities such as security. Policies can be applied to APIs to control access, apply throttling, manage security, and other aspects that modify or extend the behavior of APIs.

Rulesets, REST APIs, and connectors serve different purposes within the Anypoint Platform. Rulesets are used for validation or routing decisions. REST APIs define the endpoints and methods for API interactions, and connectors enable connectivity to various systems and services. Only policies are specifically designed to enforce additional capabilities on APIs.

References

MuleSoft Anypoint Platform Documentation on API Policies

Anypoint Exchange Overview

Timeout Attribute:

The timeout attribute in the JMS connector specifies the maximum time allowed for a transaction to be completed. If the transaction does not complete within this specified time, it will be considered a timeout.

Transaction Management:

In the context of an Extended Architecture (XA) transaction, this timeout ensures that if the transaction is not explicitly ended within the defined time, the transaction is rolled back to maintain data consistency.

Implications of Timeout:

If the timeout is exceeded, the JMS message processing is considered unsuccessful, and all operations within the transaction are undone, which helps in avoiding partial updates and maintaining a reliable state.

Explanation

Correct answer is IBM: CICS CRM: SOAP

* Within Anypoint Exchange, MuleSoft offers the IBM CICS connector. Anypoint Connector for IBM CICS Transaction Gateway (IBM CTG Connector) provides integration with back-end CICS apps using the CICS Transaction Gateway.

* Anypoint Connector for Salesforce Marketing Cloud (Marketing Cloud Connector) enables you to connect to the Marketing Cloud API web services (now known as the Marketing Cloud API), which is also known as the Salesforce Marketing Cloud. This connector exposes convenient operations via SOAP for exploiting the capabilities of Salesforce Marketing Cloud.

API Manager is a component of the Anypoint Platform's control plane. The control plane in Anypoint Platform is responsible for managing, securing, and monitoring APIs and integrations. API Manager specifically provides tools for API governance, including policy enforcement, analytics, security, and lifecycle management. It allows organizations to manage APIs centrally, ensuring they adhere to compliance and security standards while providing insights into API usage and performance.

AnTo resolve performance issues with the Master Look Up API, the following methods can be applied:

Implement the HTTP caching policy for all GET endpoints for the Master Look Up API: This caching policy helps reduce the number of database queries by storing frequently accessed data in cache, thus improving response times for subsequent requests.

Upgrade the vCore size from 0.1 vCore to 0.2 vCore: Increasing the vCore size can provide more computational resources, which can improve the processing power and overall performance of the API, particularly under high load conditions.

JMS (Java Message Service): JMS is a robust messaging standard that supports reliable and asynchronous communication. It allows message producers and consumers to exchange messages via a common message broker.

Transactions with Automatic Acknowledgements: Utilizing JMS transactions ensures that messages are processed reliably. The automatic acknowledgement mode means that once the consumer receives the message, it acknowledges the broker automatically, ensuring that no messages are lost.

Performance and Reliability: JMS transactions offer both high performance and reliability. By enabling transactions, each message processing step can be committed or rolled back, ensuring data integrity.

Cross-Cluster Messaging: For a stock trading company dealing with millions of trades, using JMS transactions allows for consistent and reliable message delivery across different clusters in their network. This approach is more suitable compared to non-transactional or VM queues due to the scale and reliability requirements.

Event-Driven APIs: The APIs can leverage the transactional nature of JMS to ensure that messages exchanged between different services are reliable and can recover gracefully from failures.

MuleSoft Documentation on JMS Connector: MuleSoft JMS Connector

JMS 2.0 Specification: Oracle JMS 2.0

https://docs.mulesoft.com/runtime-manager/dedicated-load-balancer-tutorial

Explanation

Correct answer is For Each scope in the parent flow On Error Continue error handler in the child flow. You can extract below set of requirements from the question a) Records should be sent to downstream system in the same order that it was received in the array b) Any validation or communication failures should not prevent further processing of the remaining records First requirement can be met using For Each scope in the parent flow and second requirement can be met using On Error Continue scope in child flow so that error will be suppressed.

To achieve efficient caching and reduce redundant database transactions, the following strategy can be implemented:

On Table Row Listener: Implement an "On Table Row" trigger on the employees' table. This trigger will monitor changes (inserts, updates, deletes) in the employee records.

Invalidate Cache: Upon detecting changes in the employees' table, the trigger will call a flow to invalidate the current cache.

Object Store for Caching: Utilize MuleSoft's object store to cache the employee data. This store can hold the data for quick retrieval.

Set Expiration Interval: Configure the expiration interval for the cached data to ensure it is cleared when necessary. For this scenario, since we are invalidating cache on actual data changes, setting the expiration interval to empty can be suitable.

Return Cached Data: If there are no updates, the cached response is returned, reducing database load.

MuleSoft Documentation on Object Store

Caching Strategies