Abstract: Embodiments for disaster recovery (DR) configuration management. An orchestration mechanism is used to automate a deployment and/or a configuring of two or more storage clusters for DR by arranging, in one step, a mirroring session between the two or more storage clusters. The two or more storage clusters are existing clusters, and the orchestration mechanism locates each of the existing storage clusters and establishes the mirroring session between the two.

Abstract: Embodiments for volume management in a data storage environment. A network sniffing operation between virtual machines is performed to detect relationships between the virtual machines and thereby identify candidates for subsequent storage volume affiliation operations. The network sniffing operation detects the relationships based on network traffic or alternative similarity attributes of an existing placement of the virtual machines thereby deducing affiliations of storage volumes between the virtual machines such that, during the storage volume affiliation operations, the existing placement of the virtual machines is not modified. The identified candidates to be added to a new or existing storage volume affiliation operation are recommended to a user via a prompt.

Abstract: A mega cluster storage system includes clusters of multiple storage modules. Each module is able to access a portion of the data within the mega cluster and serves as a proxy in order for another storage module to access the remaining portion of the data. A cluster is assigned to a unique cluster volume and all the data within the cluster volume is accessible by all of the modules within the cluster. Each host connection to the mega cluster is associated with a particular cluster volume. A module that receives a host I/O request determines whether the I/O request should be satisfied by a module within its own cluster or be satisfied by a module within a different cluster. The module may forward the I/O request to a module within a different cluster as indicated by a distribution data structure that is allocated and stored within each storage module.

Abstract: A computer-implemented method according to one embodiment includes identifying a host within a container environment, and mapping a volume of a container to the host within the container environment, utilizing small computer system interface (SCSI) second level addressing.

Abstract: Methods, computing systems and computer program products implement embodiments of the present invention that include defining a plurality of failure domains for sets of storage devices in a storage facility, and defining, using the failure domains, one or more limitations for distributing data on the storage devices. Upon identifying a data distribution configuration for a software defined storage system that is compliant with the one or more limitations, the identified data distribution configuration can be presented to a user. The failure domains may include physical failure domains, logical failure domains, or a combination of physical and logical failure domains, and the limitations may include mandatory limitations or a combination of mandatory and non-mandatory limitations.

Abstract: Methods, computing systems and computer program products implement embodiments of the present invention that include detecting a loss of communication with a given storage node among multiple storage nodes in a distributed computing system. Upon detecting the loss of communication, a log including updates to the data stored in the given storage node is recorded and, the recorded updates can be applied to the given storage node upon communication with the given storage node being reestablished. In some embodiments, the distributed storage system may be configured as a software defined storage system where the storage nodes can be implemented as either virtual machines or software containers. In additional embodiments, upon detecting the loss of communication, a redistribution of the mirrored data among remaining storage nodes is initiated upon detecting the loss of communication, and the redistribution is rolled back upon reestablishing the communication.

Abstract: An aggregation volume includes a plurality of sub-volumes. Advanced storage functions or operations are carried out at the aggregation volume granularity and therefore are carried out on all sub-volumes allocated in a single aggregation volume at the same time. Such organization results in a de facto consistency group for all sub-volumes associated with a single aggregation volume. To create a sub-volume the aggregation volume is logically divided into pre-defined size chunks. Each chuck can subsequently be allocated to the sub-volume. When a sub-volume is created it is allocated to a number of chunks according to a requested sub-volume size.

Abstract: Embodiments for disaster recovery (DR) configuration management. An orchestration mechanism is used to automate a deployment and/or a configuring of two or more storage clusters for DR by arranging, in one step, a mirroring session between the two or more storage clusters. The two or more storage clusters are existing clusters, and the orchestration mechanism locates each of the existing storage clusters and establishes the mirroring session between the two.

Abstract: Embodiments for volume management in a data storage environment. A network sniffing operation between virtual machines is performed to detect relationships between the virtual machines and thereby identify candidates for subsequent storage volume affiliation operations. The network sniffing operation detects the relationships based on network traffic or alternative similarity attributes of an existing placement of the virtual machines thereby deducing affiliations of storage volumes between the virtual machines such that, during the storage volume affiliation operations, the existing placement of the virtual machines is not modified. The identified candidates to be added to a new or existing storage volume affiliation operation are recommended to a user via a prompt.

Abstract: Methods, apparatus and computer program products implement embodiments of the present invention that include storing one or more data volumes to a small computer system interface storage device, and receiving a request to map a given data volume to a host computer. One or more attributes of the given data volume are identified, and using the identified one or more attributes, a unique logical unit number (LUN) for the given data volume is generated. The given data volume is mapped to the host computer via the unique LUN. In some embodiments, the generated LUN includes one of the one or more attributes. In additional embodiments, the generated LUN includes a result of a hash function using the one or more attributes. In storage virtualization environments, the data volume may include secondary logical units, and mapping the given data volume to the host may include binding the SLU to the host.

Abstract: Methods, computing systems and computer program products implement embodiments of the present invention that include configuring multiple servers coupled to a network as a software defined storage (SDS) grid. A first given server receives, via the network, an input/output (I/O) request from a host computer, and determines a location of data associated with the I/O request. In some embodiments, each of the servers maintains a local grid data map that store locations for all data managed by the SDS grid. Upon identifying, in its respective local grid data map, that a second given server is configured to process the I/O request, the first given server forwards the I/O request to the second given server for processing, and upon receiving a result of the I/O request from the second given server, the first given server conveys the result of the I/O request to the host computer.

Abstract: Embodiments for disaster recovery (DR) configuration management in a Software-defined Storage (SDS) environment. An orchestration mechanism is used to automate a deployment and/or a configuring of two or more storage clusters for DR by arranging, in one step, a mirroring session between the two or more storage clusters in the SDS environment.

Abstract: Embodiments for performance management in a computing storage environment. At least one of a plurality of performance characteristics associated with a quality of service (QoS) between a storage system and a host is dynamically controlled by uploading code of a QoS logic, from the host to the storage system, for determining and specifying the at least one of the plurality of performance characteristics, thereby reducing overhead of QoS management data required to be stored within or communicated to the storage system.

Abstract: A mega cluster storage system includes clusters of multiple storage modules. Each module is able to access a portion of the data within the mega cluster and serves as a proxy in order for another storage module to access the remaining portion of the data. A cluster is assigned to a unique cluster volume and all the data within the cluster volume is accessible by all of the modules within the cluster. Each host connection to the mega cluster is associated with a particular cluster volume. A module that receives a host I/O request determines whether the I/O request should be satisfied by a module within its own cluster or be satisfied by a module within a different cluster. The module may forward the I/O request to a module within a different cluster as indicated by a distribution data structure that is allocated and stored within each storage module.

Abstract: Embodiments for volume management in a data storage environment. A network sniffing operation between virtual machines is performed to detect relationships between the virtual machines and thereby identify candidates for subsequent storage volume affiliation operations.

Abstract: A mega cluster storage system includes clusters of multiple storage modules. Each module is able to access a portion of the data within the mega cluster and serves as a proxy in order for another storage module to access the remaining portion of the data. A cluster is assigned to a unique cluster volume and all the data within the cluster volume is accessible by all of the modules within the cluster. Each host connection to the mega cluster is associated with a particular cluster volume. A module that receives a host I/O request determines whether the I/O request should be satisfied by a module within its own cluster or be satisfied by a module within a different cluster. The module may forward the I/O request to a module within a different cluster as indicated by a distribution data structure that is allocated and stored within each storage module.

Abstract: Methods, computing systems and computer program products implement embodiments of the present invention that include configuring multiple servers coupled to a network as a software defined storage (SDS) grid. A first given server receives, via the network, an input/output (I/O) request from a host computer, and determines a location of data associated with the I/O request. In some embodiments, each of the servers maintains a local grid data map that store locations for all data managed by the SDS grid. Upon identifying, in its respective local grid data map, that a second given server is configured to process the I/O request, the first given server forwards the I/O request to the second given server for processing, and upon receiving a result of the I/O request from the second given server, the first given server conveys the result of the I/O request to the host computer.

Abstract: Embodiments for network management in a Software-defined Storage (SDS) environment. Remote mirroring connectivity and data transfer is optimized in the SDS environment by establishing each of a plurality of nodes in a local storage array and a remote storage array as a gateway node. Data residing on a local gateway node is transferred directly to a remote gateway node owning the data, thereby avoiding interconnect data hops and improving datacenter network utilization.

Abstract: Methods, computing systems and computer program products implement embodiments of the present invention that include assigning multiple storage resources to a reserve pool, and defining one or more storage policy parameters that include allocation policies and deallocation policy parameters. A software defined storage (SDS) controller is initialized by allocating, from the reserve pool, one or more of the storage resources to the SDS controller, and a current state of the SDS controller is monitored. In a first embodiment, upon detecting that the state of the SDS controller meets a given allocation policy parameter, an additional storage resource from the reserve pool is allocated from the reserve pool to the SDS controller. In a second embodiment, upon detecting that the state of the SDS controller meets a given deallocation policy parameter, a given the SDS controller is deallocated from the SDS controller and released back to the storage pool.

Abstract: Methods, computing systems and computer program products implement embodiments of the present invention that include initializing, by a hypervisor executing on a processor, first and second virtual machines. A first software application configured to provide a service is executed on the first virtual machine, and a logical data connection is established between the first and the second virtual machines. Examples of the logical connection include physical and virtual serial connections, and physical and virtual data networking connections. A second software application configured to enable remote monitoring of the first software application via the logical data connection is executed on the second virtual machine. In some embodiments, the second software application can remotely monitor the first software application via an interface such as a command line interface, a graphical user interface and an application programming interface.