US 11,989,429 B1
Recommending changes to a storage system
Farhan Abrol, San Francisco, CA (US); Volodymyr Kovalenko, Santa Clara, CA (US); Daniel Wilson, Seattle, WA (US); and Isa Pakatci, Santa Clara, CA (US)
Assigned to PURE STORAGE, INC., Santa Clara, CA (US)
Filed by PURE STORAGE, INC., Mountain View, CA (US)
Filed on Jan. 5, 2021, as Appl. No. 17/141,769.
Application 17/141,769 is a continuation in part of application No. 16/259,012, filed on Jan. 28, 2019, granted, now 10,884,636, issued on Jan. 5, 2021.
Application 16/259,012 is a continuation in part of application No. 15/987,875, filed on May 23, 2018, abandoned.
Claims priority of provisional application 62/674,688, filed on May 22, 2018.
Claims priority of provisional application 62/575,966, filed on Oct. 23, 2017.
Claims priority of provisional application 62/549,399, filed on Aug. 23, 2017.
Claims priority of provisional application 62/518,146, filed on Jun. 12, 2017.
Int. Cl. G06F 3/06 (2006.01)
CPC G06F 3/0629 (2013.01) [G06F 3/0604 (2013.01); G06F 3/067 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method comprising:
generating a plurality of load models that predict corresponding performance loads of a storage system based on characteristics of workloads executing on the storage system, wherein the plurality of load models corresponds to respective configurations of the storage system and wherein the storage system comprises a plurality of storage controllers operatively connected to a plurality of solid state storage devices;
generating predicted characteristics for one or more workloads executed by the storage system using telemetry data associated with the one or more workloads, wherein generating the predicted characteristics comprises performing a time-series analysis of the one or more workloads;
predicting, by a processing device operatively connected to the storage system, the corresponding performance loads on the storage system in dependence upon the plurality of load models and the predicted characteristics of the one or more workloads;
identifying, by the processing device, one or more of the respective configurations that cause one or more metrics of the storage system to remain within an acceptable range for a determined amount of time based on the predictions of the plurality of load models;
selecting, from the one or more of the respective configurations, a particular configuration that improves operation of the storage system;
presenting, on a graphical user interface, a recommendation that includes the particular configuration;
receiving information describing one or more modifications to the storage system;
generating a plurality of subsequent load models of the modified storage system; and
predicting an updated performance load using one or more of the plurality of subsequent load models of the modified storage system.