Abstract: Methods and systems for a networked storage system are provided. One method includes receiving a resource identifier identifying a resource of a network storage environment as an input to a processor executable application programming interface (API); and predicting available performance capacity of the resource by using an optimum utilization of the resource, a current utilization and a predicted utilization based on impact of a workload change at the resource, where the optimum utilization is an indicator of resource utilization beyond which throughput gains for a workload is smaller than increase in latency in processing the workload.

Abstract: Methods and systems for a networked storage system are provided. One method includes receiving a resource identifier identifying a resource of a network storage environment as an input to a processor executable application programming interface (API); and predicting available performance capacity of the resource by using an optimum utilization of the resource, a current utilization and a predicted utilization based on impact of a workload change at the resource, where the optimum utilization is an indicator of resource utilization beyond which throughput gains for a workload is smaller than increase in latency in processing the workload.

Abstract: Methods and systems for a networked storage system are provided. One method includes receiving a resource identifier identifying a resource of a network storage environment as an input to a processor executable application programming interface (API); and predicting available performance capacity of the resource by using an optimum utilization of the resource, a current utilization and a predicted utilization based on impact of a workload change at the resource, where the optimum utilization is an indicator of resource utilization beyond which throughput gains for a workload is smaller than increase in latency in processing the workload.

Abstract: Methods and systems for a networked storage system are provided. One method includes receiving a resource identifier identifying a resource of a network storage environment as an input to a processor executable application programming interface (API); and predicting available performance capacity of the resource by using an optimum utilization of the resource, a current utilization and a predicted utilization based on impact of a workload change at the resource, where the optimum utilization is an indicator of resource utilization beyond which throughput gains for a workload is smaller than increase in latency in processing the workload.

Abstract: Methods and systems for a networked storage system are provided. One method includes filtering performance data associated with a resource used in a networked storage environment for reading and writing data at a storage device; and determining available performance capacity of the resource using the filtered performance data. The available performance capacity is based on optimum utilization of the resource and actual utilization of the resource, where utilization of the resource is an indicator of an extent the resource is being used at any given time, the optimum utilization is an indicator of resource utilization beyond which throughput gains for a workload is smaller than increase in latency and latency is an indicator of delay at the resource in processing the workload.

Abstract: Methods and systems for a networked storage system are provided. One method includes receiving a resource identifier identifying a resource of a network storage environment as an input to a processor executable application programming interface (API); and predicting available performance capacity of the resource by using an optimum utilization of the resource, a current utilization and a predicted utilization based on impact of a workload change at the resource, where the optimum utilization is an indicator of resource utilization beyond which throughput gains for a workload is smaller than increase in latency in processing the workload.

Abstract: Methods and systems for a networked storage system are provided. A provisioning engine assigns a plurality of performance parameters in response to a provisioning request for provisioning a workload for storing data in a networked storage environment; identifies a demand for a plurality of resources of the networked storage environment for meeting the provisioning request, transforms historical available performance capacity by filtering any historical performance capacity data related to any transient event; and identifies at least a resource pair that can meet the identified demand based on the transformed historical performance capacity data.

Abstract: Methods and systems for a networked storage system are provided. One method includes receiving a resource identifier identifying a resource of a network storage environment as an input to a processor executable application programming interface (API); and predicting available performance capacity of the resource by using an optimum utilization of the resource, a current utilization and a predicted utilization based on impact of a workload change at the resource, where the optimum utilization is an indicator of resource utilization beyond which throughput gains for a workload is smaller than increase in latency in processing the workload.

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 filtering performance data associated with a resource used in a networked storage environment for reading and writing data at a storage device; and determining available performance capacity of the resource using the filtered performance data. The available performance capacity is based on optimum utilization of the resource and actual utilization of the resource, where utilization of the resource is an indicator of an extent the resource is being used at any given time, the optimum utilization is an indicator of resource utilization beyond which throughput gains for a workload is smaller than increase in latency and latency is an indicator of delay at the resource in processing the workload.

Abstract: Methods and systems for a networked storage system are provided. One method includes filtering performance data associated with a resource used in a networked storage environment for reading and writing data at a storage device; and determining available performance capacity of the resource using the filtered performance data. The available performance capacity is based on optimum utilization of the resource and actual utilization of the resource, where utilization of the resource is an indicator of an extent the resource is being used at any given time, the optimum utilization is an indicator of resource utilization beyond which throughput gains for a workload is smaller than increase in latency and latency is an indicator of delay at the resource in processing the workload.

Abstract: Methods and systems for a networked storage system are provided. A provisioning engine assigns a plurality of performance parameters in response to a provisioning request for provisioning a workload for storing data in a networked storage environment; identifies a demand for a plurality of resources of the networked storage environment for meeting the provisioning request, transforms historical available performance capacity by filtering any historical performance capacity data related to any transient event; and identifies at least a resource pair that can meet the identified demand based on the transformed historical performance capacity data.

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 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 managing resources in a networked storage environment are provided. One method includes generating a relationship between latency and utilization of a resource in a networked storage environment using observation based, current and historical latency and utilization data, where latency is an indicator of delay at the resource for processing any request and utilization of the resource is an indicator of an extent the resource is being used at any given time; and selecting an optimal point for the generated relationship between latency and utilization, where the optimal point is an indicator of resource utilization beyond which throughput gains for a workload is smaller than increase in latency.

Abstract: Methods and systems for presenting a plurality of options to a client for using storage space in a cloud computing environment are provided. Each option is associated with a latency target and/or a throughput target. The latency target provides a delay in processing input/output (I/O) requests and the throughput target provides a number of I/O requests that are processed within a unit of time. An existing volume is assigned to the client when the existing volume meets a guaranteed latency target and/or a guaranteed throughput target for an option selected from the plurality of options, otherwise a new volume is allocated.

Abstract: Methods and systems for a networked storage system are provided. One method includes receiving a resource identifier identifying a resource of a network storage environment as an input to a processor executable application programming interface (API); and predicting available performance capacity of the resource by using an optimum utilization of the resource, a current utilization and a predicted utilization based on impact of a workload change at the resource, where the optimum utilization is an indicator of resource utilization beyond which throughput gains for a workload is smaller than increase in latency in processing the workload.

Abstract: Methods and systems for a networked storage system are provided. One method includes filtering performance data associated with a resource used in a networked storage environment for reading and writing data at a storage device; and determining available performance capacity of the resource using the filtered performance data. The available performance capacity is based on optimum utilization of the resource and actual utilization of the resource, where utilization of the resource is an indicator of an extent the resource is being used at any given time, the optimum utilization is an indicator of resource utilization beyond which throughput gains for a workload is smaller than increase in latency and latency is an indicator of delay at the resource in processing the workload.

Abstract: Methods and systems for managing resources in a networked storage environment are provided. One method includes generating a relationship between latency and utilization of a resource in a networked storage environment using observation based, current and historical latency and utilization data, where latency is an indicator of delay at the resource for processing any request and utilization of the resource is an indicator of an extent the resource is being used at any given time; and selecting an optimal point for the generated relationship between latency and utilization, where the optimal point is an indicator of resource utilization beyond which throughput gains for a workload is smaller than increase in latency.

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.