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 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:
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.
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. 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. 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 assigning by a processor executable management module a service level objective (SLO) for a workload, where the SLO is allotted a plurality of performance parameters for tracking performance of the workload for storing data in a networked storage environment; tracking historical performance of the workload to determine a duration when SLO allotment defined by the plurality of performance parameters is being under-utilized; adjusting automatically the SLO allotment for the workload during the duration when the SLO allotment is under-utilized; and re-allocating automatically the available performance capacity of a resource used by the workload to another workload whose assigned SLO is not being under-utilized.
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.