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

Correct answer is VM VM support Transactional Type. When an exception occur, The transaction rolls back to its original state for reprocessing. This feature is not supported by other connectors.
Here is additional information about Transaction management:

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)