Pure Storage, Inc.

Patrick D Lee

Ronald S Karr

Andrew Kutner

Andrew Miller

David Huskisson

John Colgrove

Sergey Zhuravlev

Vinay Perneti

Brian Carpenter

Cynthia Dote

Ethan L Miller

Taher Vohra

Jean-Luc Degrenand

Self-tuning clusters for resilient microservices, including: receiving, by a services orchestrator within a cloud-computing environment and from a plurality of cloud computing instances, respective latency measurements corresponding to respective control plane operations directed to a shared resource of the plurality of cloud computing instances; determining, based on a current timeout value and on the respective latency measurements from the plurality of cloud computing instances, an updated timeout value for the shared resource; and providing, to each of the plurality of cloud computing instances, the updated timeout value for the shared resource.

Orchestrating self-tuning for cloud storage

A method includes a data protection system determining, based on a first security threat detection process, that a storage system is possibly being targeted by a security threat; performing, based on the determining that the storage system is possibly being targeted by the security threat, a first remedial action with respect to the storage system, the first remedial action comprising generating a snapshot of data stored by the storage system; confirming, based on a second security threat detection process, whether the storage system is possibly being targeted by the security threat; and performing, based on the confirming whether the storage system is possibly being targeted by the security threat, a second remedial action with respect to the storage system, the second remedial action comprising specifying a retention duration with respect to the snapshot.

Ransomware detection using multiple security threat detection processes

An illustrative method includes determining that a total amount of read traffic and write traffic processed by a storage system during a time period exceeds a threshold; determining a first compressibility metric associated with the write traffic; determining a second compressibility metric associated with the read traffic; determining, based on a comparison of the first compressibility metric with the second compressibility metric, that the write traffic is less compressible than the read traffic; determining, based on the total amount of read traffic and write traffic exceeding the threshold and on the write traffic being less compressible than the read traffic, that the storage system is possibly being targeted by a security threat; and modifying, in response to the determining that the storage system is possibly being targeted by the security threat, a data protection parameter set for one or more recovery datasets generated by the storage system.

Ransomware-based data protection parameter modification

A method may include detecting, by a computing device based on a problem signature, that a system has experienced a problem that is associated with the problem signature, wherein the problem signature comprises a specification of a pattern of events indicative of the particular problem experienced by at least one other system; determining that the particular problem violates an operational policy of the system; and deploying, without user intervention, one or more corrective measures that modify the system to resolve the problem.

Problem signature-based corrective measure deployment

Self-tuning clusters for resilient microservices

An illustrative method includes a data protection system directing a storage system to generate recovery datasets over time in accordance with a data protection parameter set, the recovery datasets usable to restore data maintained by the storage system to a state corresponding to a selectable point in time, determining that the storage system is possibly being targeted by a security threat, and modifying, in response to the determining that the storage system is possibly being targeted by the security threat, the data protection parameter set for one or more of the recovery datasets.

Recovery dataset management for security threat monitoring

An illustrative method includes a data protection system determining a first compressibility metric associated with write traffic processed by a storage system, the first compressibility metric indicating an amount of storage space saved if the write traffic is compressed; determining a second compressibility metric associated with read traffic processed by a storage system, the second compressibility metric indicating an amount of storage space saved if the read traffic is compressed; determining, based on a comparison of the first compressibility metric with the second compressibility metric, that the write traffic is less compressible than the read traffic; determining, based on the write traffic being less compressible than the read traffic, that the storage system is possibly being targeted by a security threat; and performing, based on the determining that the storage system is possibly being targeted by the security threat, a remedial action with respect to the storage system.

Compressibility metric-based detection of a ransomware threat to a storage system

An illustrative method includes a data protection system detecting, for a storage system, a potential data corruption in the storage system, analyzing, in response to the detecting of the potential data corruption, one or more metrics of the storage system, and determining, based on the analyzing of the one or more metrics of the storage system, a corruption-free recovery point for potential use to recover from the potential data corruption.

Recovery point determination for data restoration in a storage system

An illustrative method includes a data protection system performing, for a storage system, a first security threat detection process, determining, based on the performing of the first security threat detection process, that the storage system is possibly being targeted by a security threat, and performing a second security threat detection process, the second security threat detection process providing higher confidence threat detection than the first security threat detection process.

Multi-layer security threat detection for a storage system

An illustrative method includes detecting, by a cloud based storage system services provider based on a problem signature, that a storage system has experienced a problem that is associated with the problem signature; and deploying, without user intervention, one or more corrective measures that modify the storage system to resolve the problem.

Cloud-based providing of one or more corrective measures for a storage system

An illustrative method includes a data protection system determining that a total amount of read traffic and write traffic processed by a storage system during a time period exceeds a threshold, the read traffic representing data read from the storage system during the time period and the write traffic representing data written to the storage system during the time period, determining that the write traffic is less compressible than the read traffic, and determining, based on the total amount of read traffic and write traffic exceeding the threshold and on the write traffic being less compressible than the read traffic, that the storage system is possibly being targeted by a security threat.

Traffic-based detection of a security threat to a storage system

Proactively providing corrective measures for storage arrays includes: receiving data from a storage array, the data including one or more events; detecting, in dependence upon a problem signature, one or more events from the data indicative of a particular problem, where the problem signature comprises a specification of a pattern of events indicative of the particular problem experienced by at least one other storage array; determining whether the particular problem violates an operational policy of the storage array, the operational policy specifying at least one requirement for an operational metric of the storage array; and if the particular problem violates the operational policy of the storage array, deploying automatically without user intervention one or more corrective measures to prevent the storage array from experiencing the particular problem.

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Los Altos, CA, United States of America

Patrick D Lee