Abstract: Methods and systems for a networked storage system are provided. One method includes categorizing by a processor performance data associated with a resource used in a networked storage environment for reading and writing data at a storage device based on a workload mix, where the workload mix is determined by a service time in which the resource processes the workload mix, a parameter indicating variability of the service time and a utilization bin index value indicating resource utilization at a given time; and determining by the processor available performance capacity of the resource using the categorized performance data, where the available performance capacity is based on optimum utilization of the resource and utilization of the resource.

Abstract: Techniques for grouping data portions are disclosed. Each group includes data portions determined to exhibit similar behavior. The techniques may include determining whether an affinity measurement with respect to two groups exceeds an affinity threshold; merging the two groups into a single group responsive to the affinity measurement exceeding the affinity threshold; modeling movement of at least one data portion of the single group between two storage tiers at a particular time of day using predicted workload metrics; and performing the data movement of the at least one data portion between the two storage tiers. Predicted workload metrics may be determined by revising first modeled workload metrics using a bias value, where bias values are associated with different times of day, and the bias value is selected based on the particular time of day that the predicted workload metrics are modeling.

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 network storage environment are provided. One method includes retrieving stored performance data associated with a resource used in the networked storage environment, where the stored performance data includes latency data, utilization data and a service time; filtering the stored performance data by removing any observations that are beyond a certain value of the service time; grouping the filtered stored performance into utilization bins and identifying a representative of each utilization bin; generating by the processor a hybrid latency versus utilization curve comprising a first portion that is based on the representative of each utilization bin and a second portion generated using a model based technique and determining by the processor available performance capacity of the resource using the hybrid latency versus utilization curve; where the available performance capacity is based on optimum utilization of the resource and actual utilization of the resource.

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 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 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 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 using a queuing model for a resource that processes a plurality of requests at a networked storage environment for predicting a relationship between latency and utilization of the resource. The queueing model uses inter-arrival time and service time to determine latency, where inter-arrival time is a duration that tracks when requests arrive at the resource and the service time tracks a duration for servicing the requests by the resource. The method further includes identifying optimum utilization of the resource using the predicted relationship between latency and utilization, where the optimum utilization is an indicator of resource utilization beyond which throughput gains for a workload is smaller than increase in latency; and determining available performance capacity for the resource using the optimum utilization and actual utilization of the resource.