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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/

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

In a microservices application architecture, each service is designed to be an independent deployment artifact. This means that services can be deployed, updated, and scaled independently of one another. This characteristic allows for greater flexibility and agility in managing applications, as individual services can be scaled up or down based on demand without impacting other services. It also enhances fault isolation, as issues in one service do not necessarily affect the entire application.

This is in contrast to monolithic architectures, where all components are packaged and deployed together, often resulting in a single point of failure and difficulties in scaling and updating specific parts of the application.

References

• MuleSoft Documentation on Microservices Architecture
• Principles of Microservices Design

Explanation

* Mule High Availability Clustering provides basic failover capability for Mule. * When the primary Mule Runtime becomes unavailable, for example, because of a fatal JVM or hardware failure or it’s taken offline for maintenance, a backup Mule Runtime immediately becomes the primary node and resumes processing where the failed instance left off. * After a system administrator recovers a failed Mule Runtime server and puts it back online, that server automatically becomes the backup node. In this case, Alice, once up, will become backup ---------------------------------------------------------------------------------------------------------------------------------------------- Reference: So correct choice is : Files are polled form Bob node Bob is now the primary node