Abstract: The present disclosure relates to a method for automatically scaling a multi-container-based computational session on a cluster. The method includes: receiving, by a node controller, event information and statistical information about a container from a container engine; forwarding, by the node controller, the sensed event information and statistical information to a cluster controller; determining, by the cluster controller, whether to add or delete the container for a specific session based on the received event information and statistical information; forwarding, by the cluster controller, a container addition or deletion command to the node controller of the specific session according to a determination result; and determining, by the cluster controller, whether to add or delete the node by determining whether it is impossible to add the container only with an existing node or when it is necessary to delete the container.

Abstract: This application provides a virtualized device, and an interrupt processing method running on the virtualized device. The method includes: performing, by a processor, the following operations in a guest mode: receiving, by the processor, an interrupt request from hardware; determining, by the processor, a processing entity of the received interrupt request based on a correspondence between the interrupt request and the processing entity; and when the processing entity of the received interrupt request includes the virtual processor currently running on the processor, determining, by the processor based on a correspondence between the interrupt request and an interrupt service routine, the interrupt service routine corresponding to the received interrupt request, and invoking the interrupt service routine to process the interrupt request.

Abstract: A set of virtual machines is deployed on a hypervisor. At each virtual machine, one or more local scans is performed to generate a set of computing resource consumption data. In response to receiving a set of hypervisor resource consumption data, a stability factor is generated. Based on the set of resource consumption data, the set of hypervisor resource consumption data, and the stability factor, a determination is made that a default consumption metric exceeds a threshold. In response to the determination, a custom consumption metric is generated, based on at least the set of computing resource consumption data. A user is notified of the custom consumption metric.

Abstract: Data protection operations including replication operations are disclosed. Virtual machines, applications, and/or application data are replicated according to at least one strategy. The replication strategy can improve performance of the recovery operation.

Abstract: Techniques are provided for managing quality of service (QoS) policies in a virtual storage environment. A data storage system receives a request from a host system to connect to a target virtual volume in a storage array of the data storage system, and determines a protocol endpoint which has an assigned QoS policy which corresponds to a QoS policy of the target virtual volume. The data storage system binds the target virtual volume to the protocol endpoint which is determined to have an assigned QoS policy which corresponds to the QoS policy of the target virtual volume, and sends a unique identifier of the protocol endpoint, which is bound to the target virtual volume, to the host system. The data storage system utilizes the protocol endpoint, which is bound to the target virtual volume, to handle data access requests received from the host system for accessing the target virtual volume.

Abstract: A virtual machine management method and apparatus, a device, and a readable storage medium. The virtual machine management method is applied to a private cloud, and comprises: acquiring a SELinux label, the SELinux label comprising five elements: User, Role, Type, Sensitivity, and Category (S101); setting elements other than Category in the SELinux label as default values (S102); assigning different values to Category according to a preset Category variable combination so as to obtain multiple non-duplicate label groups (S103); and configuring each label group to a virtual machine in the private cloud, so that virtual machines configured with the same label group communicate with each other, and virtual machines configured with different label groups are isolated from each other (S104).

Abstract: When containers run in a guest operating system of a virtual machine running on the host computer system, the containers communicate with each other via ports of each container and a network. The ports of each container stay constant, but the virtual machine in which they run may change its IP address on the network when it is power-cycled. To avoid losing connection to the ports of the containers, a record table that associates static identifiers, such as MAC addresses, of the virtual machine with the container ports is maintained. The static identifiers of the virtual machines do not change and provide a way of identifying the virtual machine on which the virtual container was running before it was powered off. When the virtual machine is powered on, the linkage between the container port and the network can be re-established using the record table.

Abstract: Systems and techniques are described for virtual machine communication and migration. A described technique includes operating server systems that are configured to run virtual machines and providing a virtual network for Internet Protocol (IP) based communications to the virtual machines. The virtual machines can be assigned network addresses, such as IP addresses, on the virtual network. Providing the virtual network can include using separate IP tunnels to effect delivery of IP packets on the virtual network to the virtual machines, respectively. The technique includes migrating a virtual machine running on a first server system to a second server system. The migrated virtual machine can maintain its assigned IP address. The technique includes updating a tunnel endpoint destination associated with the assigned IP address of the migrated virtual machine. The updated tunnel endpoint destination can be based on a network address associated with the second server system.

Abstract: Systems, methods, and other embodiments associated with performing maintenance of a hardware node and relocating (live migrating) virtual machine (VM) instances in a multi-tenant, hyper scale, public Cloud service are described. In one embodiment, the method includes finding a suitable hardware node for hosting one or more VM instances from a hardware node selected for maintenance, preparing it for hosting VMs, and moving (live migrating) all virtual machines from the hardware node to the hosting hardware node.

Abstract: A client device includes resource caches, and a processor coupled to the resource caches. The processor receives resources from different resource feeds, and caches user interfaces (UI) of the resources from the different resource feeds, with at least one resource feed having a resource cache separate from the resource cache of the other resource feeds. Statuses of the resource feeds are determined, with at least one status indicating availability of the at least one resource feed having the separate resource cache. UI elements from the separate resource cache are retrieved for display in response to the at least one resource feed associated with the separate resource cache not being available.

Abstract: According to a disclosed embodiment, data analysis is secured with a microservice architecture and data anonymization in a multitenant application. Tenant data is received by a first microservice in a multitenant application. The tenant data is isolated from other tenant data in the first microservice and stored separately from other tenant data in a tenant database. The tenant data is anonymized in the first microservice and thereafter provided to a second microservice. The second microservice stores the anonymized tenant data in an analytics database. The second microservice, upon request, analyzes anonymized tenant data from a plurality of tenants from the analytics database and provides an analytics result to the first microservice.

Abstract: Various aspects are disclosed for graphics processing unit (GPU)-remoting latency aware migration. In some aspects, a host executes a GPU-remoting client that includes a GPU workload. GPU-remoting latencies are identified for hosts of a cluster. A destination host is identified based on having a lower GPU-remoting latency than the host currently executing the GPU-remoting client. The GPU-remoting client is migrated from its current host to the destination host.

Abstract: Facilitating running a multi-process application using a set of unikernels includes receiving an indication of a request to fork a first process running in a first unikernel virtual machine. It further includes, in response to receiving the indication of the request to fork the process running in the first unikernel virtual machine, deploying a second unikernel virtual machine to run a second process that is a child of the first process. Unikernel scaling includes determining that a unikernel virtual machine to be deployed is associated with at least a portion of a kernel image that is already cached. It further includes, in response to determining that the unikernel virtual machine to be deployed is associated with the at least portion of the kernel image that is already cached, mapping the unikernel virtual machine to the at least portion of the kernel image that is already cached.

Abstract: Examples described herein relate to a manageability controller for controlling a display of a screen video. The manageability controller may receive screen video data from a hypervisor running on a host operating system (OS) that is executable by a main processing resource separate from the manageability processing resource. The screen video data may include a host OS screen video data corresponding to the host OS, a virtual machine (VM) screen video data corresponding to a VM running on the hypervisor, or both. Further, the manageability controller may store the host OS screen video data or the VM screen video data in a physical video memory based on a screen selection input.

Abstract: Disclosed are various embodiments for centralized and dynamically generated service configurations for data center and other region builds. A computing environment may be configured to receive requests to deploy a new computing stack or service from different geographical regions at a central service. For the individual ones of the requests, the computing environment may identify computing resources of the computing environment required to deploy the new computing stack or service, determine an order of creation of the computing resources, and create at least one virtual process that automatically allocates the computing resources for the new computing stack based on a predetermined order of creation.

Abstract: Routing log-based information between production servers and logging servers is disclosed. A log entry for a logging server is generated at a production server. A shard identifier is computed for a shard associated with the logging server based on application of a hashing algorithm to properties associated with the production server. The hashing algorithm and properties are selected to prevent or minimize the likelihood of computing of the same shard identifier by another production server for the same shard associated with the logging server. The log entry is transmitted to the shard associated with the logging server. A determination is made that the logging server has malfunctioned by detecting that the log entry transmitted to the shard is absent. In response, another shard identifier is computed for another shard of another logging server and a subsequent log entry from the production server is transmitted to the another shard of the another logging over. No load balancers are used by the routing system.

Abstract: The present disclosure discloses a data processing method and related products, in which the data processing method includes: generating, by a general-purpose processor, a binary instruction according to device information of an AI processor, and generating an AI learning task according to the binary instruction; transmitting, by the general-purpose processor, the AI learning task to the cloud AI processor for running; receiving, by the general-purpose processor, a running result corresponding to the AI learning task; and determining, by the general-purpose processor, an offline running file according to the running result, where the offline running file is generated according to the device information of the AI processor and the binary instruction when the running result satisfies a preset requirement. By implementing the present disclosure, the debugging between the AI algorithm model and the AI processor can be achieved in advance.

Abstract: A method of marshalling existing software applications to automatically execute a task in a cloud environment includes generating actions that together execute the task; passing the actions to code generation services, where each of the code generation services is associated with a corresponding software application. Each of the code generation services is configured to select a subset of the actions that can be executed by the corresponding software application, and to generate second actions to be executed by the corresponding software application that implement the subset of the actions. The method also includes providing a job definition for the task including each of the second actions for each of the software applications.

Abstract: In response to a request to remove a PCI device from a virtual machine (VM), a processing device may transmit, to a guest operating system (OS) of a VM, an indication that a peripheral component interconnect (PCI) device connected to the VM has been disconnected such that the PCI device appears disconnected to a PCI port driver of the guest OS and simultaneously communicates with a device driver of the guest OS. The processing device may transmit a device removal request to the device driver. The removal request may be transmitted to the device driver without the delay associated with the “push button” approach to device removal since the guest OS already believes the PCI device has been disconnected from the VM. A graceful removal of the device driver may be performed and the PCI device may be disconnected from the VM.

Abstract: A computer implemented method includes: accessing from a configuration management database, by a virtualization manager, configuration data for a first computing node of a computing system; generating, by the virtualization manager, a set of attribute/value pairs for the first computing node using the configuration data; and managing, by the virtualization manager, a first container on the first computing node using the set of attribute/value pairs for the first computing node.