Pure Storage, Inc.

Kshithij Iyer

Luis Pablo Pabón

Naveen Revanna

Paul Theunis

Aditya Dani

Piyush Nimbalkar

Prabir Paul

Lakshmi Narasimhan Sundararajan

Abhay Chavan

Neelesh Thakur

Vijayan Satyamoorthy Srinivasa

Mohammed Umair Mufti

Ram Suradkar

Chun-Yi Su

Ladislav Prskavec

Priyanshu Pandey

Jan Vrtiska

Systems, apparatuses, and methods of multi-cluster database deployment are disclosed. An illustrative method includes receiving, by a controller, a request to deploy a database to multiple clusters; determining, by the controller and based on the request, a set of clusters to which to deploy the database, wherein the determining is based on the set of clusters including a first cluster and a second cluster having a relationship established using a storage system implemented on the first cluster and the second cluster; and deploying, by the controller, the database to the set of clusters, wherein the deploying the database to the set of clusters comprises directing the storage system implemented on the first cluster and the second cluster to replicate data of the database between the first cluster and the second cluster.

Multi-cluster database deployment

An example method for detecting and remediating anomalies in a container system by a storage system comprises detecting, by a container storage management system, a change in resources utilized on a volume of the container system by an application of the container system; determining, by the container storage management system and in response to the detecting, whether the change in resources utilized is anomalous for the application; and performing, by the container storage management system and based on the determining, an action associated with the application.

Detecting and remediating anomalies of a container system by a distributed storage system

An illustrative method includes accessing, by a controller operating within a global control plane, a recovery policy that specifies parameters for generating recovery data associated with one or more resources of a first cluster comprising a first one or more containers, wherein the first cluster comprises a first local control plane separate from the global control plane; determining, by the controller and based on the recovery policy, a second cluster comprising a second one or more containers, wherein the second cluster comprises a second local control plane separate from the global control plane; and generating, by the controller and with respect to the second cluster, the recovery data associated with the one or more resources of the first cluster.

Data recovery using recovery policies

An example method for monitoring volume dependencies for security threats comprises: detecting a request to perform an operation with respect to a volume included in a plurality of volumes included in a storage system; determining, based on a dependency mapping that specifies dependencies between the plurality of volumes, that performance of the operation would affect a dependency between the volume and one or more other volumes included in the plurality of volumes; and determining, based on the determining that the performance of the operation would affect the dependency between the volume and the one or more other volumes, that the request is possibly associated with a security threat against data stored by the storage system.

Volume dependencies in a storage system

An example method for analyzing logs for root causes of errors in a cloud environment comprises: detecting an error in a component deployed within a cloud environment; providing, based on the detecting the error, log data associated with the component to a root cause analysis machine learning model; determining, based on an output of the machine learning model, a corrective measure configured to address the error; and performing a remedial action associated with the corrective measure.

Analyzing logs for root causes of errors in a cloud environment

An example method for adjusting IO profiles in a distributed storage system comprises: determining, by a storage system that provides a volume as persistent storage for a container application running in a container system, a characteristic of the container application; and adjusting, by the storage system and based on the characteristic of the container application, an input/output (IO) profile of the volume.

IO profiles in a distributed storage system

An example method for prioritizing deployment of nodes in a cluster comprises: determining, at a first time and by a first node of a plurality of nodes in a cluster of a distributed storage system, that a second node having a higher priority than the first node is in a startup phase of the second node; determining, at a second time subsequent to the first time and by the first node, that the second node has completed the startup phase of the second node; and initiating, based on the determining that the second node has completed the startup phase and by the first node, a startup phase of the first node.

Prioritized deployment of nodes in a distributed storage system

An example method for dynamic determination of locks for prioritized deployment in a distributed storage system comprises providing, by a storage management system, N locks to a cluster of a distributed storage system, the cluster including a plurality of nodes and the N locks allowing N nodes of the plurality of nodes to each initiate a startup phase during a first time window, wherein N is a number greater than zero; tracking, by the storage management system, application programming interface (API) calls made by the N nodes to a platform of the cluster during the first time window; and providing, by the storage management system based on the tracking, M locks to the cluster, the M locks allowing M nodes of the plurality of nodes to each initiate a startup phase during a second time window subsequent to the first time window, wherein M is a number greater than zero.

Dynamic determination of locks for a prioritized deployment of nodes in a distributed storage system

An illustrative method of container recovery using layer prioritization includes identifying a set of immutable layers of container images included in a dataset used by a container system to run containerized applications on a first cluster; copying the set of immutable layers of container images to a second cluster in preparation for a recovery event; receiving, after the set of immutable layers of container images are copied to the second cluster, a recovery request to recover the containerized applications; and copying, in response to the recovery request, a set of mutable layers included in the dataset to the second cluster, the second cluster configured to use the copied set of immutable layers and the copied set of mutable layers to recover the containerized applications on the second cluster.

Growing community of inventors

Gujarat, India

Kshithij Iyer