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.

An example method of placing a virtual machine (VM) in a cluster of hosts is described. Each of the hosts having a hypervisor managed by a virtualization management server for the cluster, the hosts separated into a plurality of nonuniform memory access (NUMA) domains. The method including: comparing a virtual central processing unit (vCPU) and memory configuration of the VM with physical NUMA topologies of the hosts; selecting a set of the hosts spanning at least one of the NUMA domains, each host in the set of hosts having a physical NUMA topology that maximizes locality for vCPU and memory resources of the VM as specified in the vCPU and memory configuration; and providing the set of hosts to a distributed resource scheduler (DRS) executing in the virtualization management server, the DRS configured to place the VM in a host selected from the set of hosts.

A recording medium stores an application control program for causing a computer to execute processing including: when a specific application included in a applications is executed in response to a processing request from a specific processing request source, referring to a storage unit that stores flow information that indicates a past execution order of the applications for each of the processing request sources of the applications, and calculating an execution probability that each of one or more applications that are likely to be executed after the specific application executed in response to the processing request from the specific processing request source among the applications is executed after the specific application executed in response to the processing request from the specific processing request source; specifying an application to be activated from the one or more applications based on the calculated execution probability; and activating the specified application to be activated.

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 container login method, a container login apparatus, and a storage medium are provided. In an example embodiment, a target container login request from a browser is received; a first connection between a server and the browser is established based on the target container login request; an address of a control node corresponding to a container cluster in which a target container is located is obtained based on an identifier of the container cluster; and a second connection between the server and the target container is established based on the address of the control node and an identifier of the target container, to log in to the target container.

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.

This application describes a virtual machine deployment method and an operation and maintenance management (OMM) virtual machine. The method includes: obtaining, by an OMM virtual machine, a quantity and a specification of service virtual machines created in virtual network function application software to which the OMM virtual machine belongs; and determining, by the OMM virtual machine based on load that needs to be carried by the application software and the quantity and the specification of the service virtual machines, a module to be configured for each service virtual machine. The described implementations avoid or reduce waste of virtual machine resources.

Examples include a method of live migrating a virtual device by creating a virtual device in a virtual machine, creating first and second interfaces for the virtual device, transferring data over the first interface, detecting a disconnection of the virtual device from the virtual machine, switching data transfers for the virtual device from the first interface to the second interface, detecting a reconnection of the virtual device to the virtual machine, and switching data transfers for the virtual device from the second interface to the first interface.

At a first compute instance run on a virtualization host, a local instance scaling manager is launched. The scaling manager determines, based on metrics collected at the host, that a triggering condition for redistributing one or more types of resources of the first compute instance has been met. The scaling manager causes virtualization management components to allocate a subset of the first compute instance's resources to a second compute instance at the host.

One example technique includes receiving a request for accessing a file from a container process. In response to receiving the request, the technique includes querying a mapping table corresponding to the container process to locate an entry corresponding to a file identifier of the requested file. The entry also includes data identifying a file location on the storage device from which the requested file is accessible. The technique further includes retrieving a copy of the requested file according to the file location identified by the data in the located entry in the mapping table and providing the retrieved copy of the requested file to the container process, thereby allowing the container process to access the requested file.