Abstract: A method, computer system, and computer program product area provided. A computer transmits a query command to a storage descriptor area of a first disk. The first disk belongs to a dual-site data replication system. The dual-site data replication system provides active-active access to a volume of data stored in an active disk and replicated in a backup disk. The computer receives a response to the query command. The response indicates the active disk and the backup disk for the dual-site data replication system. The computer controls an additional copy of the volume of data at a further remote site based on the active disk.

Abstract: A method, computer system, and computer program product area provided. A computer transmits a query command to a storage descriptor area of a first disk. The first disk belongs to a dual-site data replication system. The dual-site data replication system provides active-active access to a volume of data stored in an active disk and replicated in a backup disk. The computer receives a response to the query command. The response indicates the active disk and the backup disk for the dual-site data replication system. The computer controls an additional copy of the volume of data at a further remote site based on the active disk.

Abstract: A system and method for automatic and dynamic virtual machine (VM) group membership adjustment to identify and maintain VM groupings for maintaining a data consistency and availability at a computer recovery site in response to a disaster event. Based on a hybrid approach of network and storage analytics using cognitive methods, the system automatically groups the VMs based on patterns of data exchanged between the VMs. The system can store the patterns found during the analysis, find the critical elements in those patterns (like VMs playing the key role of DB server), match the patterns and use them in case a detected failure to make the system functional again at the recovery site. The system stores the communications traffic patterns learned during the network analysis and uses analytics to form or change the VM grouping, and can perform the pattern matching to quickly readjust the group.

Abstract: Aspects include prefetching a plurality of high-level information, high-level metadata, low-level metadata, and low-level information including a plurality of components associated with a monitored entity for disaster recovery. A subsequent instance of the high-level information, the high-level metadata, and the low-level metadata is requested. The subsequent instance of the high-level information is fetched based on detecting a change in the high-level metadata. A subsequent instance of one or more of the components of the low-level information corresponding to one or more changes in the low-level metadata is fetched for updating a plurality of disaster recovery data of the monitored entity in a persistent database.

Abstract: A system and method for automatic and dynamic virtual machine (VM) group membership adjustment to identify and maintain VM groupings for maintaining a data consistency and availability at a computer recovery site in response to a disaster event. Based on a hybrid approach of network and storage analytics using cognitive methods, the system automatically groups the VMs based on patterns of data exchanged between the VMs. The system can store the patterns found during the analysis, find the critical elements in those patterns (like VMs playing the key role of DB server), match the patterns and use them in case a detected failure to make the system functional again at the recovery site. The system stores the communications traffic patterns learned during the network analysis and uses analytics to form or change the VM grouping, and can perform the pattern matching to quickly readjust the group.

Abstract: Aspects include prefetching a plurality of high-level information, high-level metadata, low-level metadata, and low-level information including a plurality of components associated with a monitored entity for disaster recovery. A subsequent instance of the high-level information, the high-level metadata, and the low-level metadata is requested. The subsequent instance of the high-level information is fetched based on detecting a change in the high-level metadata. A subsequent instance of one or more of the components of the low-level information corresponding to one or more changes in the low-level metadata is fetched for updating a plurality of disaster recovery data of the monitored entity in a persistent database.