Guilherme Denapoli Ferreira

20220247766, Aug 4, 2022

Jan 29, 2021

17/162808

- Palo Alto CA, US
Sumeet Bharatbhai Varma - Sunnyvale CA, US
Guilherme Vale Ferreira Menezes - San Jose CA, US
Stephen Chu - San Francisco CA, US
Mohit Gupta - Palo Alto CA, US

H04L 29/06
G06F 9/455
G06N 20/00
G06K 9/62
G06F 16/953

Techniques for implementing a scalable automated training framework for anomaly and ransomware detection are disclosed. In some embodiments, a computer system performs operations comprising: instantiating a plurality of virtual machines, each one of the virtual machines being loaded with a corresponding file system; simulating user actions and ransomware on the virtual machines, the simulating of user actions and ransomware on the virtual machines causing changes to the corresponding file systems of the virtual machines; for each one of the plurality of virtual machines, generating a corresponding metadata file based on one or more corresponding snapshots of the virtual machine, the one or more corresponding snapshots indicating the changes to the corresponding file system of the virtual machine; and training a ransomware detection model using a machine learning algorithm and training data, the training data being based on the corresponding metadata files of the virtual machines.

20190250991, Aug 15, 2019

Feb 14, 2018

15/897084

- Palo Alto CA, US
Guilherme Vale Ferreira Menezes - San Jose CA, US

G06F 11/14
G06F 17/30
G06F 3/06
G06F 11/07

In one approach, filesets to be backed up are divided into partitions and snapshots are pulled for each partition. In one architecture, a data management and storage (DMS) cluster includes a plurality of peer DMS nodes and a distributed data store implemented across the peer DMS nodes. One of the peer DMS nodes receives fileset metadata for the fileset and defines a plurality of partitions for the fileset based on the fileset metadata. The peer DMS nodes operate autonomously to execute jobs to pull snapshots for each of the partitions and to store the snapshots of the partitions in the distributed data store.

20190179711, Jun 13, 2019

Dec 11, 2017

15/837998

- Palo Alto CA, US
Biswaroop Palit - Redwood City CA, US
Guilherme Vale Ferreira Menezes - Santa Clara CA, US

RUBRIK, INC. - Palo Alto CA

G06F 11/14

Methods and systems for efficiently capturing snapshots of a computing application or environment over time and transferring the snapshots to an integrated data management and storage system are described. A snapshot agent may detect that one or more electronic files associated with the computing application or environment are greater than a threshold file size and in response perform an incremental backup optimization in which the snapshot agent may identify files that have been touched since a previous snapshot by accessing file system metadata (e.g., last modified timestamps) or utilizing a tracking agent to detect potential file changes that have occurred since the previous snapshot was captured. The snapshot agent may then generate fingerprints for data blocks of the touched files, which may reduce the total number of fingerprints needing to be generated to identify the changed data blocks corresponding with a current snapshot to be transferred.

20190050296, Feb 14, 2019

Aug 8, 2017

15/672159

- Palo Alto CA, US
Guilherme Vale Ferreira Menezes - Santa Clara CA, US

RUBRIK, INC. - Palo Alto CA

G06F 11/14
G06F 9/455
G06F 17/30
G06F 11/20

Methods and systems for automatically upgrading or synchronizing a remote data management agent running on a remote host machine (e.g., a hardware server) to a particular version that is in-sync with a corresponding version used by a cluster of data storage nodes controlling the remote data management agent are described. The remote agent may be initially installed on the remote host and subsequent updates to the remote agent may be performed using the remote agent itself without requiring intervention by the remote host. The remote agent may comprise a backup agent and a bootstrap agent that are each exposed in different network ports or associated with different port numbers or networking addresses. The backup agent may perform data backup related tasks for backing up files stored on the remote host and the bootstrap agent may perform upgrade related tasks for upgrading the backup agent.