Kaseya Assigned Two Patents

Direct-to-cloud backup with local volume failover
Kaseya US LLC, Miami, FL, has been assigned a patent (12353289) developed by Cope; Andrew, Rochester, NY, and Loce; Robert, Webster, NY, for a “direct-to-cloud backup with local volume failover.“

The abstract of the patent published by the U.S. Patent and Trademark Office states: “The disclosure provides methods and systems for direct-to-cloud backup with local volume failover. According to an exemplary embodiment, first and second logical volumes are designated on a protected computing device. The first and second logical volumes may be paired to a cloud storage facility. In response to a received signal, it may be determined if the protected computing device has a communication connection to the cloud storage facility. If the protected computing device does have a communication connection to the cloud storage facility, a first computing device backup of the first logical volume may be sent to the cloud storage facility. If the protected computing device does not have a communication connection to the cloud storage facility, a second computing device backup of the first logical volume may be performed and stored on the second logical volume of the protected computing device.”

The patent application was filed on 2019-11-12 (16/680753).

Autoscreenshot systems and methods for virtual OS states
Kaseya US LLC, Miami, FL, has been assigned a patent (12314137) developed by Mitchell; Collin, Rochester, NY, for “autoscreenshot systems and methods for virtual operating system states“

The abstract of the patent published by the U.S. Patent and Trademark Office states: “Described screenshot verification systems and methods for automatically verifying the integrity of a backup image or other process-of-interest using a screenshot verification system, as well as disaster recovery systems including said systems and performing said methods. In accordance with various aspects of the present disclosure, a virtual machine is booted and screenshots of the boot process are taken, which are used by a trained model, such as a convolutional neural network, to determine a boot state consistency. The systems and methods described deliver over 99% accuracy and do not involve regular expression analysis typical of conventional methods.”

The patent application was filed on 2024-02-09 (18/438150).