Abstract: A non-disruptive cross-protocol live data migration process, such as from a legacy SAN storage network to a modern NVMe-oF storage network, includes maintaining a bitmap to track the transferred blocks at migration time, and utilizing the bitmap for intelligent I/O routing decisions that take into account characteristics of SSD-type NVM storage, such as endurance characteristics associated with solid state type memory. Furthermore, protocol command translations and multipath layer capabilities such as I/O queuing are advantaged at migration time to hide the underlying complexities related to a cross-protocol mass data migration, to enable a non-disruptive data migration process intended to avoid application downtime.

Abstract: A non-disruptive cross-protocol live data migration process, such as from a legacy SAN storage network to a modern NVMe-oF storage network, includes maintaining a bitmap to track the transferred blocks at migration time, and utilizing the bitmap for intelligent I/O routing decisions that take into account characteristics of SSD-type NVM storage, such as endurance characteristics associated with solid state type memory. Furthermore, protocol command translations and multipath layer capabilities such as I/O queuing are advantaged at migration time to hide the underlying complexities related to a cross-protocol mass data migration, to enable a non-disruptive data migration process intended to avoid application downtime.

Abstract: Technology is disclosed for determining high availability readiness of a distributed computing system (“system”). A confidence measure (CM) can be computed for a particular controller in the system to determine whether a takeover by the particular controller from a first controller would be successful. The CM can be a percentage value. A CM of 0% indicates that a takeover would be a failure, which results in loss of access to data managed by the first controller. A CM of 100% indicates a successful takeover with no performance impact on the system. A CM between 0% and 100% indicates a successful takeover but with a performance impact. The CM can be computed based on events occurring in the system, e.g., veto and non-veto events. The CM is computed as a function of various weights and/or indices associated with the veto events and/or non-veto events.

Abstract: Technology is disclosed for determining high availability readiness of a distributed computing system (“system”). A confidence measure (CM) can be computed for a particular controller in the system to determine whether a takeover by the particular controller from a first controller would be successful. The CM can be a percentage value. A CM of 0% indicates that a takeover would be a failure, which results in loss of access to data managed by the first controller. A CM of 100% indicates a successful takeover with no performance impact on the system. A CM between 0% and 100% indicates a successful takeover but with a performance impact. The CM can be computed based on events occurring in the system, e.g., veto and non-veto events. The CM is computed as a function of various weights and/or indices associated with the veto events and/or non-veto events.

Abstract: Technology is disclosed for determining high availability readiness of a distributed computing system (“system”). A confidence measure (CM) can be computed for a particular controller in the system to determine whether a takeover by the particular controller from a first controller would be successful. The CM can be a percentage value. A CM of 0% indicates that a takeover would be a failure, which results in loss of access to data managed by the first controller. A CM of 100% indicates a successful takeover with no performance impact on the system. A CM between 0% and 100% indicates a successful takeover but with a performance impact. The CM can be computed based on events occurring in the system, e.g., veto and non-veto events. The CM is computed as a function of various weights and/or indices associated with the veto events and/or non-veto events.

Abstract: Technology is disclosed for determining high availability readiness of a distributed computing system (“system”). A confidence measure (CM) can be computed for a particular controller in the system to determine whether a takeover by the particular controller from a first controller would be successful. The CM can be a percentage value. A CM of 0% indicates that a takeover would be a failure, which results in loss of access to data managed by the first controller. A CM of 100% indicates a successful takeover with no performance impact on the system. A CM between 0% and 100% indicates a successful takeover but with a performance impact. The CM can be computed based on events occurring in the system, e.g., veto and non-veto events. The CM is computed as a function of various weights and/or indices associated with the veto events and/or non-veto events.