Netapp, Inc.

Vinod Vasant Pai

Kevin Faulkner

Leon Fairbanks

Siu Wu

Curtis E Hrischuk

Abdul Basit

Phil Larson

Ulhas Pai

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.

Method and system for monitoring and analyzing quality of service in a metro-cluster

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.

Method and system for monitoring and analyzing quality of service in a storage system

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.

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Woburn, MA, United States of America

Vinod Vasant Pai