Abstract: Various embodiments are generally directed to techniques for determining whether one node of a HA group is able to take over for another. An apparatus includes a model derivation component to derive a model correlating node usage level to node data propagation latency through and to node resource utilization from a first model of a first node of a storage cluster system and a second model of a second node of the storage cluster system, the first model based on a first usage level of the first node under a first usage type, and the second model based on a second usage level of the second node under a second usage type; and an analysis component to determine whether the first node is able to take over for the second node based on applying to the derived model a total usage level derived from the first and second usage levels.

Abstract: An apparatus for simulating a door light includes a door defining a first opening therethrough, a frame unit engaging the door about the first opening, wherein the frame unit defines a second opening therethrough sized such that an overlay section of the frame unit, defined between the periphery of the first opening and a periphery of the second opening, partially overlays the first opening, and a display monitor received within the first opening and having a front surface engaging the overlay section about the second opening and defining a display screen surrounded by the frame unit with a periphery of the display screen terminating at or spaced-apart from the periphery of the second opening, the monitor further including an integral memory having instructions stored therein executable by an integral processor to control the display screen to display thereon an image or video of a door light.

Abstract: Methods and systems for monitoring quality of service (QOS) data for a plurality of storage volumes from a storage operating system of a storage system are provided. A performance manager collects QOS data for a storage volume from among the plurality of storage volumes and the QOS data includes a response time in which the storage volume responds to an input/output (I/O) request; determines that the collected QOS data is noisy by comparing an average number of I/O requests processed within a time duration for the storage volume with a first threshold value; uses comparable QOS data of another storage volume for generating an expected range for future QOS data; and monitors QOS data for the storage volume for determining whether a current QOS data for the storage volume is within the expected range.

Abstract: Various embodiments are generally directed to techniques for determining whether one node of a HA group is able to take over for another. An apparatus includes a model derivation component to derive a model correlating node usage level to node data propagation latency through and to node resource utilization from a first model of a first node of a storage cluster system and a second model of a second node of the storage cluster system, the first model based on a first usage level of the first node under a first usage type, and the second model based on a second usage level of the second node under a second usage type; and an analysis component to determine whether the first node is able to take over for the second node based on applying to the derived model a total usage level derived from the first and second usage levels.

Abstract: Methods and systems for a networked storage system are provided. One method includes receiving a request for configuring a workload by a processor executing a management application in a networked storage system, the request including a tag with information for identifying a workload type and information defining an expected performance characteristic of the workload; determining by the processor a comparable workload using the tag information; obtaining by the processor current and historical performance data associated with the comparable workload; estimating by the processor performance characteristic of the requested workload using performance data of the comparable workload; identifying by the processor a resource of the networked storage system that meets the estimated performance characteristic; and allocating by the processor the resource to the requested workload.

Abstract: Methods and systems for inter-cluster storage system monitoring and analysis are provided. The method includes monitoring a non-volatile memory delay center for a first storage cluster having a first node and a second node configured to operate as a first high availability pair, where data for a write request to write data to the first node is also written to the second node as well as to a second cluster having a third node and a fourth node, where the third node and the fourth node are also configured to operate as a second high availability pair to store the data for the write request at one or both of the third and fourth node. The non-volatile memory delay center is used to monitor and detect latency due to any delay caused by a non-volatile memory of the first node used as a write cache.

Abstract: The Water Window allows for the viewing of objects that are 1 to 4 feet deep, at the bottom of beaches, lakes and streams, by placing the device on top of the water and giving a clear magnification of objects that are available to be viewed and picked up by children and adults alike and treasured forever.

Abstract: Methods and systems for monitoring quality of service (QOS) data for a plurality of storage volumes are provided. QOS data is collected for the plurality of storage volumes and includes a response time in which each of the plurality of storage volumes respond to an input/output (I/O) request. An expected range for future QOS data based on the collected QOS data is generated. The process then determines a deviation of each potential bully storage volume of a resource used by any victim storage volume, where the deviation of each bully storage volume is based on a number of current I/O requests (IOPS) that are processed by each potential bully storage volume, a forecasted value of TOPS and a predicted upper threshold TOPS value for each potential bully storage volume; and filters the potential bully storage volumes based on an impact of each potential bully storage volume.

Abstract: Methods and systems for monitoring quality of service (QOS) data for a plurality of storage volumes from a storage operating system of a storage system are provided. A performance manager collects the QOS data from the storage operating system and the QOS data includes a response time in which each of the plurality of storage volumes respond to an input/output (I/O) request. An expected range for future QOS data is generated based on the collected QOS data. The QOS data is monitored for each storage volume for determining whether a current QOS data for each storage volume is within the expected range.

Abstract: Methods and systems for monitoring quality of service (QOS) data for a plurality of storage volumes are provided. QOS data is collected for the plurality of storage volumes and includes a response time in which each of the plurality of storage volumes respond to an input/output (I/O) request. The process determines an average of N collected QOS data points at any given time; and iteratively analyzes each QOS data point to detect if a step-up or a step-down function has occurred, where a step-up function represents an unpredictable increase in value of a data point and a step-down function is an unpredictable decrease in value of the data point. A subset of the N QOS data points based on when the step-up function or step-down function occurs is selected for analysis and an expected range for future QOS data based on the subset of the N QOS data points is generated.

Abstract: Methods and systems for monitoring quality of service (QOS) data for a plurality of storage volumes from a storage operating system of a storage system are provided. A performance manager collects QOS data for a storage volume from among the plurality of storage volumes and the QOS data includes a response time in which the storage volume responds to an input/output (I/O) request; determines that the collected QOS data is noisy by comparing an average number of I/O requests processed within a time duration for the storage volume with a first threshold value; uses comparable QOS data of another storage volume for generating an expected range for future QOS data; and monitors QOS data for the storage volume for determining whether a current QOS data for the storage volume is within the expected range.

Abstract: Methods and systems for identifying a victim storage volume from among a plurality of storage volumes based on a comparison of current Quality of Service (QOS) data with a dynamic threshold value that is based on historical QOS collected data for the plurality of storage volumes are provided. A performance manager collects the current and historical QOS data from a storage operating system of the storage system, which includes a response time in which each of the plurality of storage volumes respond to an input/output (I/O) request. The current and historical QOS data for the resources used by the victim storage volume are retrieved and compared with the current QOS data of each resource to an expected range based on the historical QOS data. Another storage volume is identified as a bully when its usage of a resource in contention contributes to creating the victim storage volume.

Abstract: Methods and systems for identifying a victim storage volume from among a plurality of storage volumes based on a comparison of current Quality of Service (QOS) data with a dynamic threshold value that is based on historical QOS collected data for the plurality of storage volumes are provided. A performance manager collects the current and historical QOS data from a storage operating system of the storage system, which includes a response time in which each of the plurality of storage volumes respond to an input/output (I/O) request. The current and historical QOS data for the resources used by the victim storage volume are retrieved and compared with the current QOS data of each resource to an expected range based on the historical QOS data. Another storage volume is identified as a bully when its usage of a resource in contention contributes to creating the victim storage volume.

Abstract: Methods and systems for monitoring quality of service (QOS) data for a plurality of storage volumes are provided. QOS data is collected for the plurality of storage volumes and includes a response time in which each of the plurality of storage volumes respond to an input/output (I/O) request. An expected range for future QOS data based on the collected QOS data is generated. The process then determines a deviation of each potential bully storage volume of a resource used by any victim storage volume, where the deviation of each bully storage volume is based on a number of current I/O requests (IOPS) that are processed by each potential bully storage volume, a forecasted value of TOPS and a predicted upper threshold TOPS value for each potential bully storage volume; and filters the potential bully storage volumes based on an impact of each potential bully storage volume.

Abstract: Methods and systems for monitoring quality of service (QOS) data for a plurality of storage volumes from a storage operating system of a storage system are provided. A performance manager collects the QOS data from the storage operating system and the QOS data includes a response time in which each of the plurality of storage volumes respond to an input/output (I/O) request. An expected range for future QOS data is generated based on the collected QOS data. The QOS data is monitored for each storage volume for determining whether a current QOS data for each storage volume is within the expected range.

Abstract: Methods and systems for inter-cluster storage system monitoring and analysis are provided. The method includes monitoring a non-volatile memory delay center for a first storage cluster having a first node and a second node configured to operate as a first high availability pair, where data for a write request to write data to the first node is also written to the second node as well as to a second cluster having a third node and a fourth node, where the third node and the fourth node are also configured to operate as a second high availability pair to store the data for the write request at one or both of the third and fourth node. The non-volatile memory delay center is used to monitor and detect latency due to any delay caused by a non-volatile memory of the first node used as a write cache.

Abstract: Methods and systems for monitoring quality of service (QOS) data for a plurality of storage volumes are provided. QOS data is collected for the plurality of storage volumes and includes a response time in which each of the plurality of storage volumes respond to an input/output (I/O) request. The process determines an average of N collected QOS data points at any given time; and iteratively analyzes each QOS data point to detect if a step-up or a step-down function has occurred, where a step-up function represents an unpredictable increase in value of a data point and a step-down function is an unpredictable decrease in value of the data point. A subset of the N QOS data points based on when the step-up function or step-down function occurs is selected for analysis and an expected range for future QOS data based on the subset of the N QOS data points is generated.

Abstract: An apparatus for simulating a door light includes a door defining a first opening therethrough, a frame unit engaging the door about the first opening, wherein the frame unit defines a second opening therethrough sized such that an overlay section of the frame unit, defined between the periphery of the first opening and a periphery of the second opening, partially overlays the first opening, and a display monitor received within the first opening and having a front surface engaging the overlay section about the second opening and defining a display screen surrounded by the frame unit with a periphery of the display screen terminating at or spaced-apart from the periphery of the second opening, the monitor further including an integral memory having instructions stored therein executable by an integral processor to control the display screen to display thereon an image or video of a door light.

Abstract: A storage virtualization environment is provided that includes a system for dynamically updating a virtual volume in associated with a host system. The system may include a set of storage devices, each of which includes physical block addresses that store data associated with the virtual volume and a network switch system connecting the host system and the set of storage devices. In one embodiment, the network switch system includes a set of storage processors each maintaining virtual volume objects including at least one of (i) first tier objects reflecting a relationship between the physical block addresses and one or more logical partitions of virtual volume data, and (ii) second tier objects reflecting a logical configuration of the virtual volume. Further, the network switch system uses the virtual volume objects to dynamically update the virtual volume during runtime of the network switch system.

Abstract: An improvement in a networked digital computing system comprises an Information Resource Manager (IRM) operable to communicate with elements of the digital computing system to obtain performance information regarding operation of and resources available in the computing system, and to utilize this information to enable the IRM to adjust the application parameters relating to application execution, thereby to optimize execution of the at least one application program.