Embodiments described herein provide for an election procedure, in a high availability (“HA”) environment, for a backup controller to assume operations performed by a master controller in the event that the master controller becomes unreachable. The master controller may be associated with (e.g., provisioned on) the same set of hardware as one or more worker nodes, and may control operation of the one or more worker nodes. The election procedure may be performed based on performance metrics, location, or efficiency metrics associated with candidate backup controllers (e.g., cloud-based backup controllers), including performance of communications between particular backup controllers and the one or more worker nodes.

Data recovery systems and methods utilize object-based storage for providing a data protection and recovery methodology with low recovery point objectives, and for enabling both full recovery and point-in-time based recovery. Data generated at a protected site (e.g., via one or more virtual machines) is intercepted during write procedures to primary storage. The intercepted data is replicated via a replication log, provided as data objects, and transmitted to an object based storage system. During recovery, data objects may be retrieved through point-in-time based recovery directly by the systems of the protected site, and/or data objects may be provided via full recovery, for example, within a runtime environment of a recovery site, with minimal data loss and operation interruption by rehydrating data objects within the runtime environment via low-latency data transfer and rehydration systems.

A virtual machine that includes a plurality of processes executes on a computer processor. A record-replay file, trace annotations, and an application program interface request are received into the computer processor. The trace annotations and application program interface request are translated into record-replay commands. The record-replay commands capture data from the record-replay file, and the captured data can be accessed via a programmatic interface.

A method for containerized workload scheduling can include determining a network state for a first hypervisor in a virtual computing cluster (VCC). The method can further include determining a network state for a second hypervisor. Containerized workload scheduling can further include deploying a container to run a containerized workload on a virtual computing instance (VCI) deployed on the first hypervisor or the second hypervisor based, at least in part, on the determined network state for the first hypervisor and the second hypervisor.

An apparatus comprises an interrupt distributor to distribute virtual interrupts to one or more physical processors, each virtual interrupt to be handled by one of a plurality of virtual processors mappable to said one or more physical processors; and control circuitry to maintain virtual processor interrupt tracking information corresponding to a given virtual processor. The virtual processor interrupt tracking information includes a pending interrupt record tracking which types of virtual interrupts are pending for the given virtual processor, and separate from the pending interrupt record, a pending interrupt status indication indicating a pending interrupt status for the given virtual processor. The pending interrupt status indicates whether the number of pending virtual interrupts for the given virtual processor is zero.

Techniques are provided for enforcing policies at a sub-logical unit number (LUN) granularity, such as at a virtual disk or virtual machine granularity. A block range of a virtual disk of a virtual machine stored within a LUN is identified. A quality of service policy object is assigned to the block range to create a quality of service workload object. A target block range targeted by an operation is identified. A quality of service policy of the quality of service policy object is enforced upon the operation using the quality of service workload object based upon the target block range being within the block range of the virtual disk.

Apparatus and method for managing pipeline depth of a data processing device. For example, one embodiment of an apparatus comprises: an interface to receive a plurality of work requests from a plurality of clients; and a plurality of engines to perform the plurality of work requests; wherein the work requests are to be dispatched to the plurality of engines from a plurality of work queues, the work queues to store a work descriptor per work request, each work descriptor to include information needed to perform a corresponding work request, wherein the plurality of work queues include a first work queue to store work descriptors associated with first latency characteristics and a second work queue to store work descriptors associated with second latency characteristics; engine configuration circuitry to configure a first engine to have a first pipeline depth based on the first latency characteristics and to configure a second engine to have a second pipeline depth based on the second latency characteristics.

The present disclosure is related to Virtual Desktop Infrastructure (VDI) that discloses a method and system for performing dynamic patch management in VDI platform. A patch managing system retrieves operational data and vulnerability remediation data related to IT services and infrastructures of the VDI platform from first and second data sources. Thereafter, the patch managing system detects gap in patching level based on operational data, vulnerability remediation data and corresponding industrial standard, and rolls out patches based on detected gap in patching level. Further, a patch prediction score that facilitates in identifying a probability of rolling back the patches rolled out for patching IT services and infrastructures of VDI platform is determined based on prediction parameters. A plan is generated based on the patch prediction score and executed to optimally patch the patches to IT services and infrastructures of the VDI platform, based on patching rules.

A guest operating system executing on a virtual machine hosted by a host operating system may forward information about the state of the guest operating system to the host operating system for analysis regarding security threats. The host operating system may also forward information about the state of the host operating system to the guest operating system for analysis regarding security threats. One or both of the guest operating system and the host operating system may also forward the information about their state(s) to a remote server for analysis regarding security threats to the machine running the host operating system and hosting the virtual machine running the guest operating system. Security threats may be identified based on a detection of abnormal behavior. Abnormal behavior may be detected using machine-learning models. The machine-learning models may be trained/refined over time based on collected state information.

A method for fetching a content from a web server to a client device is disclosed, using tunnel devices serving as intermediate devices. The tunnel device is selected based on an attribute, such as IP Geolocation. A tunnel bank server stores a list of available tunnels that may be used, associated with values of various attribute types. The tunnel devices initiate communication with the tunnel bank server, and stays connected to it, for allowing a communication session initiated by the tunnel bank server. Upon receiving a request from a client to a content and for specific attribute types and values, a tunnel is selected by the tunnel bank server, and is used as a tunnel for retrieving the required content from the web server, using standard protocol such as SOCKS, WebSocket or HTTP Proxy. The client only communicates with a super proxy server that manages the content fetching scheme.