Some embodiments provide a hierarchical data service (HDS) that manages many resource clusters that are in a resource cluster hierarchy. In some embodiments, each resource cluster has its own cluster manager, and the cluster managers are in a cluster manager hierarchy that mimics the hierarchy of the resource clusters. In some embodiments, both the resource cluster hierarchy and the cluster manager hierarchy are tree structures, e.g., a directed acyclic graph (DAG) structure that has one root node with multiple other nodes in a hierarchy, with each other node having only one parent node and one or more possible child nodes.

A load balancing method and a related device is provided. The method includes: determining topology information of each of a plurality of smallest management units pods in a load balancing cluster to which a first node belongs, where the plurality of pods are distributed on at least two nodes; determining a weight of each of the plurality of pods based on the topology information of each pod; and selecting a target pod from the plurality of pods based on the weight of each pod, where the target pod is configured to process a currently to-be-processed task in the first node. In embodiments of this application, network overheads can be reduced when a task request is allocated.

Systems and methods for inter-cluster deployment of compute services using federated operator components are generally described. In some examples, a first request to deploy a compute service may be received by a federated operator component. In various examples, the federated operator component may send a second request to provision a first compute resource for the compute service to a first cluster of compute nodes. In various examples, the first cluster of compute nodes may be associated with a first hierarchical level of a computing network. In some examples, the federated operator component may send a third request to provision a second compute resource for the compute service to a second cluster of compute nodes. The second cluster of compute nodes may be associated with a second hierarchical level of the computing network that is different from the first hierarchical level.

A virtual-machine cold migration method, an electronic device and a storage medium, which relate to the field of artificial intelligence, such as cloud computing, distributed storage, or the like. The method may include: selecting a node as a target physical machine from nodes of a cluster where a to-be-migrated virtual machine is located, the target physical machine and a source physical machine where the virtual machine is located being different nodes; and migrating, by means of point-to-point data transmission, system disk data and data disk data in the virtual machine from the source physical machine to the target physical machine to obtain a migrated virtual machine, and deleting the virtual machine on the source physical machine.

Methods, computer readable media, and systems service a queue, comprising a plurality of jobs, by identifying nodes satisfying a hardware requirement for at least a subset of jobs in the queue. Each job indicates when it was submitted to the queue and one or more node resource requirements. A current availability score for each node class in a plurality of node classes is determined and nodes of a first node class in the plurality of node classes are reserved when a demand score for the class satisfies the current availability score for the first node class by a first threshold amount. Reserved nodes are permitted to draw jobs from the queue in accordance with satisfaction by such nodes of the node resource requirements of the jobs but are terminated, without completing the jobs, when the current availability score for their node class exceeds a second threshold amount.

The present disclosure relates to computer-implemented methods, software, and systems for an automatic recovery job execution through a scheduling framework in a cloud environment. One or more recovery jobs are scheduled to be performed periodically for one or more registered service components included in a service instance running on a cluster node of a cloud platform. Each recovery job is associated with a corresponding service component of the service instance. A health check operation is invoked at a service component based on executing a recovery job at the scheduling framework corresponding to the service component. In response to determining that the service component needs a recovery measure based on a result from the health check operation, a recovery operation is invoked as part of executing a set of scheduled routines of the recovery job. Implemented logic for the recovery operation is stored and executed at the service component.

Thread group dispatch in a clustered graphics architecture is described. An example of an apparatus includes of compute front end (CFE) clusters to receive dispatched thread groups, the CFE clusters including at least a first CFE cluster and a second CFE cluster; processing resources coupled with the CFE clusters to execute threads within thread groups; and cache clusters to cache data including thread groups, wherein the apparatus is to receive thread groups for dispatch, and to dispatch the thread groups to the CFE clusters according to a dispatch operation, the dispatch operation including dispatching multiple thread groups to each of multiple CFEs in the first CFE cluster and multiple thread groups to each of multiple CFEs in the second CFE cluster.

Apparatuses, systems, and techniques to perform a K-nearest-neighbor query. In at least one embodiment, a set of bounding boxes corresponding to a set of primitives is generated that allows the query to be solved using light transport simulation acceleration features of a GPU.

Systems and methods for managing containerized clusters from virtualization management systems. An example method may include identifying one or more cluster entities of a containerized computing cluster, where the containerized computing cluster comprises a plurality of virtual machines running on one or more host computer systems, generating one or more virtualization management entities in the virtualization management system, wherein each virtualization management entity represents a respective cluster entity, receiving a request to perform an operation on a specified virtualization management entity in the virtualization management system, identifying a cluster entity represented by the virtualization management entity, translating, responsive to the request, the request to one or more commands to be performed on the identified cluster entity of the containerized computing cluster, and sending the one or more commands to the containerized computing cluster.

A disclosed method for developing and testing a hyper-converged infrastructure (HCI) platform creates a snapshot pool with one or more virtual resource snapshots that include one or more virtual node snapshots, one or more virtual cluster snapshots, or both. The snapshot pool may be maintained with a desired quantity of the virtual resource snapshots by adjusting the composition of the snapshot pool in response to snapshot events, including an event that alters either a composition of the snapshot pool or a configuration of the HCI platform. The desired quantity of virtual resource snapshots may be determined in accordance with one or more snapshot thresholds. The snapshot thresholds may include a snapshot pertaining to a quantity of virtual node snapshots in the snapshot pool and/or a snapshot pertaining to a quantity of virtual cluster snapshots. Specifically, the threshold may include a cluster maximum and minimum and a node maximum and minimum.