Methods and apparatus to select virtualization environments are disclosed. An example apparatus includes a logic circuit, a workload analyzer to determine characteristics of a virtualized application, a score generator to compare the characteristics of the virtualized application to a plurality of virtualization environment types to determine scores for each of the plurality of virtualization environment types, the scores based on rules that identify different scores for combinations of characteristics and virtualization environment types, and a workload deployer to deploy the virtualized application using one of the plurality of virtualization environment types based on the scores.

Some examples described herein relate to data restoration. In an example, checkpoints may be defined for converting backup data stored in each of Logical Unit Numbers (LUNs) of a storage system into respective virtual data disk files. Backup data stored in each of the LUNs of the storage system may be converted into respective virtual data disk files at the defined checkpoints. The virtual data disk files with user configuration information of the storage system may be packaged into a Virtual Storage Appliance (VSA), which may include a base operating system (OS) image of the VSA. The VSA may be transferred to an external entity.

Some embodiments of the present invention include a method comprising: accessing units of network storage that encode state data of respective virtual machines, wherein the state data for respective ones of the virtual machines are stored in distinct ones of the network storage units such that the state data for more than one virtual machine are not commingled in any one of the network storage units.

Described in detail herein is a method of copying data of one or more virtual machines being hosted by one or more non-virtual machines. The method includes receiving an indication that specifies how to perform a copy of data of one or more virtual machines hosted by one or more virtual machine hosts. The method may include determining whether the one or more virtual machines are managed by a virtual machine manager that manages or facilitates management of the virtual machines. If so, the virtual machine manager is dynamically queried to automatically determine the virtual machines that it manages or that it facilitates management of. If not, a virtual machine host is dynamically queried to automatically determine the virtual machines that it hosts. The data of each virtual machine is then copied according to the specifications of the received indication.

A disclosed load estimation method includes: collecting run information of a processor being executing a predetermined program; specifying execution status of the processor based on the collected run information; and estimating a load of the predetermined program based on a result of comparison between the execution status of the processor and execution characteristics of the processor. Each of the execution characteristics is stored in association with a load level of the predetermined program.

One example method includes chunking a respective disk of each of a plurality of virtual machines (VM) to create a respective plurality of chunks associated with each of the VMs, creating, based on the chunking process, a cluster comprising one or more of the VMs, creating a VM template whose data and disk structure match respective data and disk structures of each of the VMs in the cluster, and in response to a file operation involving a first one of the VM disks, defragmenting the first VM disk so that a disk structure of the first VM disk is the same as a disk structure of the VM template.

Methods and apparatus are described by which a rich, time-correlated information set is captured during automated testing of an application in a way that allows the application developer to understand the state of the application under test (AUT), the browser interacting with the AUT, and/or the device interacting with the AUT, as it/they changed over time. Mechanisms or features associated with browsers and/or device operating systems are exploited to capture such information, not only for the purpose of better understanding individual test runs, but also to enable the use of analytics over data sets.

A memory controller includes a memory channel controller adapted to receive memory access requests and dispatch associated commands addressable in a system memory address space to a non-volatile storage class memory (SCM) module. The non-volatile error reporting circuit identifies error conditions associated with the non-volatile SCM module and maps the error conditions from a first number of possible error conditions associated with the non-volatile SCM module to a second, smaller number of virtual error types for reporting to an error monitoring module of a host operating system, the mapping based at least on a classification that the error condition will or will not have a deleterious effect on an executable process running on the host operating system.

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.

Systems and methods for determining an access pattern in a computing system. Accesses to a file may contain random accesses and sequential accesses. The file may be divided into multiple regions and the accesses to each region are tracked. The access pattern for each region can then be determined independently of the access patterns of other regions of the file.