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.

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.
References:
* MuleSoft Documentation on Anypoint CLI
* MuleSoft Documentation on Anypoint Platform REST APIs

According to the National Institute of Standards and Technology (NIST), a hybrid cloud is a cloud computing deployment model that describes a composition of two or more distinct cloud infrastructures (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability. Hybrid clouds allow organizations to leverage the advantages of multiple cloud environments, such as combining the scalability and cost-efficiency of public clouds with the security and control of private clouds. This model facilitates flexibility and dynamic scalability, supporting diverse workloads and business needs while ensuring that sensitive data and applications can remain in a controlled private environment.
References
* NIST Definition of Cloud Computing
* Hybrid Cloud Overview and Benefits

High availability is about up-time of your application
A) High availability can be achieved only in CloudHub isn't correct statement. It can be achieved in customer hosted runtime planes as well B) An object store is a facility for storing objects in or across Mule applications. Mule runtime engine (Mule) uses object stores to persist data for eventual retrieval. It can be used for disaster recovery but not for High Availability. Using object store can't guarantee that all instances won't go down at once. So not an appropriate choice.
Reference:
C) High availability can be achieved by below two models for on-premise MuleSoft implementations.
1) Mule Clustering - Where multiple Mule servers are available within the same cluster environment and the routing of requests will be done by the load balancer. A cluster is a set of up to eight servers that act as a single deployment target and high-availability processing unit. Application instances in a cluster are aware of each other, share common information, and synchronize statuses. If one server fails, another server takes over processing applications. A cluster can run multiple applications. ( refer left half of the diagram) In given scenario, it's mentioned that 'data cannot be shared among of different instances'. So this is not a correct choice.
2) Load balanced standalone Mule instances - The high availability can be achieved even without cluster, with the usage of third party load balancer pointing requests to different Mule servers. This approach does not share or synchronize data between Mule runtimes. Also high availability achieved as load balanced algorithms can be implemented using external load balancer. ( refer right half of the diagram)