Emc IP Holding Company LLC

Netapp, Inc.

Network Appliance, Inc.

Deepa Ramesh

Fani Jenkins

Gobikrishnan Sundharraj

Susan M Coatney

Nitin Madan

Kalaivani Arumugham

Dean Lyle Voiss

Detecting a trend in latency for storage underlying a deduplicated file system includes generating a set of data points by recording when input/output (IO) requests were issued to the storage and recording time required to receive success responses from the storage. Least squares regression is performed on the data points to find a best-fit line through the data points. A slope of the best-fit line is calculated. A determination is made as to whether the slope is positive, a positive slope thereby indicating a trend of increasing latency of the storage. When the slope is determined to be positive, clients accessing the deduplicated file system are throttled.

Using machine learning techniques to flow control clients in a deduplication file system

Embodiments for reducing panic shutdown of components in a pipelined data processing system. Components are monitored for health, processing progress, and dependencies during normal system operation. A directed graph is generated showing non-circular dependencies of components in the pipeline. Deadlock of a particular component may or may not signal a panic condition depending on whether any of its presently downstream and depended on components are operating properly. The continuously monitored knowledge of proper operation of all downstream components is thus used to intelligently apply or defer panic alerts to keep the system operating uninterrupted from panic conditions that might soon or eventually be fixed by continued operation of the system pipeline.

Reducing false positive failure events in a health monitoring system using directional graphs

A method, non-transitory computer readable medium, and device that assists with dynamically determining and readjusting failover targets includes identifying an existing failover target from a plurality of failover targets for backing up an updated object. The identified existing failover target is determined for eligibility for backing up the updated object. One or more new failover targets from the plurality of failover targets are dynamically identified based on a plurality of storage parameters when the identified existing failover target is determined not to be eligible for backing up the updated object. The updated object is backed up in one of the dynamically identified one or more new failover targets.

Methods for dynamically determining and readjusting failover targets and devices thereof

An apparatus and a method that prevent a split-brain problem by preventing a cluster partner from accessing and serving data when the cluster partner is taken over by a storage server, while allowing early release of reservations on the cluster partner's storage devices before control is given back to the cluster partner.

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Cupertino, CA, United States of America

Deepa Ramesh