MuleSoft MCIA-Level-1 - MuleSoft Certified Integration Architect - Level 1

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

Diagram Description automatically generated

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.

Diagram Description automatically generated

To support the company's goals of unlocking key systems and data, quickly deploying scalable APIs, and connecting to on-premises systems, while also preparing for future migrations, the best runtime deployment option is using Runtime Fabric on self-managed Kubernetes. Here's why:

Scalability: Kubernetes is designed to scale applications easily and efficiently. By deploying Mule runtimes on a self-managed Kubernetes cluster, the company can dynamically scale its APIs based on demand, ensuring performance and reliability.

Flexibility: Running on self-managed Kubernetes allows the company to have control over the infrastructure. They can customize the environment to meet their specific needs, integrate with existing on-premises systems, and support their microservices architecture running in Docker containers.

Future-Proofing: Kubernetes supports hybrid and multi-cloud deployments, making it easier to migrate workloads between different environments as needed. This aligns with the company's goal of being able to migrate their systems as part of their strategic approach.

Efficiency: By leveraging Kubernetes, the company can automate deployment, scaling, and management of containerized applications, reducing the burden on IT and DevOps teams.

References:

MuleSoft Documentation on Runtime Fabric: https://docs.mulesoft.com/runtime-fabric/1.9/

Kubernetes Documentation: https://kubernetes.io/docs/home/

When a RAML definition is updated and a new version is published to Anypoint Exchange, the client applications that consume the API need to be updated to utilize the new operations. Here’s how the Mule application team can achieve this:

Access Anypoint Exchange:

Go to Anypoint Exchange and find the updated RAML definition of the API.

Update the REST Connector:

In the Mule application, locate the existing REST connector that was generated from the previous version of the API.

Update this connector to the latest version by reimporting the RAML definition.

This can be done via the Anypoint Studio by navigating to the Mule Palette, finding the REST connector, and updating it with the new RAML.

Regenerate Client Code (If Necessary):

Sometimes, updating the connector may require regenerating the client code to include new operations.

Ensure that all new methods and endpoints are available in your Mule application after the update.

Test New Operations:

Incorporate and test the new operations in the Mule application to ensure they function correctly with the updated API implementation.

References

MuleSoft Documentation: API Development

Anypoint Studio Documentation: Using Connectors

SOAP API specifications are provided as WSDL. Design center doesn't provide the functionality to create WSDL file. Hence WSDL needs to be created using XML editor

Dealer D1 - AUTO Acknowledgment:

Dealer D1, which has a retry mechanism, can use AUTO acknowledgment. This means that the message is acknowledged automatically once received. The retry mechanism will handle any processing errors and reprocess the message if needed.

Dealer D2 - Manual Acknowledgment:

Dealer D2, which does not have a retry mechanism, must use manual acknowledgment. This approach allows D2 to acknowledge the message only after it has been successfully processed, ensuring no message is lost due to processing errors.

Ensuring Message Delivery:

Using manual acknowledgment for Dealer D2 ensures that the message is not lost and can be reprocessed if an error occurs during processing, which is crucial since it lacks a retry mechanism.

References:

MuleSoft Documentation on JMS Acknowledgment

Best practices for Reliable Messaging

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

A defining characteristic of an Integration-Platform-as-a-Service (iPaaS) is that it is cloud-based. iPaaS provides a cloud-based platform to enable integration of applications and data across various environments. This approach leverages the scalability, flexibility, and accessibility of the cloud to facilitate seamless integrations, reduce on-premises infrastructure requirements, and improve the speed of deployment and maintenance of integration solutions.

References:

What is iPaaS?

Benefits of iPaaS

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

Explanation

V2 Rest API is recommended for on premise applications to access Object Store. It also comes with overhead of encryption and security of using rest api. With Object Store v2, the API call is localized to the same data center as the Runtime Manager app.

But in this case requirement is to access the OS of other mule application and not the same mule application.

You can configure a Mule app to use the Object Store REST API to store and retrieve values from an object store in another Mule app.

However, Object Store v2 is not designed for app-to-app communication.