International Business Machines Corporation

Alon Marx

Amalia Avraham

Ohad Atia

Ran Harel

Yuval A Ben-Horin

Isaac Beckman

Rivka Mayraz Matosevich

Osnat Shasha

Zah Barzik

Shay Berman

Anna Stopel

Olga Shtivelman

Samuel Krikler

Vladislav Drouker

Lior Tamary

Yossi Yamin

Connectivity type detection for a data storage system in accordance with the present description includes, in one aspect of the present description, automated host-target discovery logic which is configured to automatically discover the connectivity type for a connection path between a host and a storage system, and select and initiate target discovery procedures which are appropriate for the discovered connectivity type. As a result, mapping a target volume of the target storage system which is connected to the host, may be facilitated, reducing or eliminating delays which may have otherwise resulted from the change in connectivity type. In this manner, efficiency of the computing system may be improved. Other aspects and advantages may be realized, depending upon the particular application.

Connectivity type detection using a transport protocol and command protocol of the data storage system

Aspects of the present disclosure relate to transmitting prioritized path data to a device based on a set of topology rules and metrics associated with a storage target. A storage target path discovery request is received from the device. In response to the storage target path discovery request, metrics associated with the storage target are collected. Based on the collected metrics, available paths to the storage target are identified. A set of topology rules are then determined. Based on the topology rules and the collected metrics, a subset of available paths are selected. The subset of available paths are then prioritized into prioritized path data. The prioritized path data is then stored and transmitted to the device.

Distributed storage path configuration

Embodiments of the present invention provide methods and systems for calculating capacity allocation in storage systems. Embodiments of the present invention can be used to calculate a capabilities score for all storage systems, resulting in a list of storage systems, prioritized, so that a storage administrator may select automatically or manually, the best system to provision for the requesting application, based on the calculated capabilities score of each storage system.

Provisioning storage allocation using prioritized storage system capabilities

A computer-implemented method according to one embodiment includes receiving, at a storage system, a request to allocate persistent data storage for use by a container within an orchestration system, where the request includes an orchestration system identifier, selecting a storage volume within the storage system for use by the container within the orchestration system, determining a storage identifier for the storage volume within the storage system, and storing, within the storage system, an association between the orchestration system identifier and the storage identifier.

Maintaining container to storage volume relations

Embodiments for managing volume replication and disaster recovery in a containerized storage environment. A mapping is established between a PersistentVolumeClaim (PVC) having a correlated Persistent Volume (PV), and a source storage World Wide Name (WWN) and a target storage WWN. The mapping is replicated as part of a replication operation between the source storage and the target storage thereby maintaining consistency of the PV associated with one or more application containers among the source storage and the target storage.

Container replication and failover orchestration in distributed computing environments

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.

Quality of service (QoS) stored procedures

Methods, computing systems and computer program products implement embodiments of the present invention that include receiving a request including a specified number of logical volumes, and identifying, in a storage system including multiple storage pools having storage space, respective first amounts of the storage space that are available in the multiple storage pools. Based on the specified number of logical volumes and the first amounts of the storage space, a set of volume sizes indicating second amounts of the storage space are defined, and a given volume size indicating a maximum size for the specified number of logical volumes is identified. Upon conveying the maximum size to a user, and receiving, from the user, a specified size less than or equal to the maximum size, the specified number of the volumes having the specified size can be provisioned, wherein each of the volumes is stored in a given storage pool.

Determining maximum volume size

Embodiments for performance management in a computing storage environment. In a storage system having a predetermined number of available quality of service (QoS) values associated with a performance of the storage system, the predetermined number of available QoS values are spread over a range such that a user requested QoS value is matched with one of the available QoS values within an optimal deviation value to a given precision.

Spreading quality of service values over a given range with minimal deviation

Embodiments for volume management in a data storage environment. A storage pool of a plurality of storage pools is selected to provision at least one storage volume by calculating, for each of the plurality of storage pools, a forecast factor representing an expected usage according to an overall size of the at least one storage volume. The selected storage pool is the storage pool of the plurality of storage pools having a smallest forecast factor.

Storage pool selection for provisioning volumes in an over-allocation system

When a volume that was once associated with a consistency group and is to be deleted from the storage system, the to be deleted volume is designated as a ghost volume within the storage system, and the deletion of the ghost volume from the storage system is delayed until there are no snapshots that include a pointer to the ghost volume. The storage system may include a counter that counts the number of instances all volumes within a consistency group are pointed to or that counts the number of instances that only ghost volumes are pointed to. The storage system may reference this count to determine whether to immediately delete or delay the deletion of the volume from the storage system.

Managing a deletion of a volume referenced by a snapshot of a consistency group

A method, including deploying multiple servers as a distributed computing system (DCS) configured to provide a service to clients. At a first time, a given server is configured as an active node in the DCS, the active node configured to and to process requests for the service received from the clients. At the first time, one or more remaining first servers are configured as one or more semi-active nodes in the DCS, each given semi-active node configured to receive, from the clients, requests for the service, and to forward the received requests to the active node for processing. Each of the servers maintains respective counts of the received requests, and at a second time subsequent to the first time, upon identifying a given remaining server having a highest count the given remaining server is reconfigured as the active node, and the given server is reconfigured as a semi-active node.

Dynamic client-based leader election

Various embodiments for multipath management in a storage grid, by a processor device, are provided. In one embodiment, a method comprises continuously monitoring and comparing current data path devices against the current storage structure, and changing routing decision configurations when it is detected there is a more efficient data path.

Adaptive storage-aware multipath management

A method for routing communication paths among computing devices. The method includes a one or more computer processors identifying a computing entity and a data storage entity that transfer data. The method further includes determining a plurality of communication ports that the data storage entity utilizes to transfer data to the computing entity. The method further includes identifying a plurality of computing resources respectively associated with the determined plurality of communication ports that the data storage entity utilizes to transfer the data to the computing entity. The method further includes generating a list of tuples for the data storage entity based, at least in part, on the identified plurality of computing resources and the determined plurality of communication ports.

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Alon Marx