Examples relate to a monitoring apparatus, a monitoring device, a monitoring method, and to a corresponding computer program and system. The monitoring apparatus is configured to obtain a first compute kernel to be monitored and to obtain one or more second compute kernels. The monitoring apparatus is configured to provide instructions, using interface circuitry, to control circuitry of a computing device comprising a plurality of execution units, to instruct the control circuitry to execute the first compute kernel using a first slice of the plurality of execution units and to execute the one or more second compute kernels concurrently with the first compute kernel using one or more second slices of the plurality of execution units, and to instruct the control circuitry to provide information on a change of a status of at least one hardware counter associated with the first slice that is caused by the execution of the first compute kernel. The monitoring apparatus is configured to determine information on the execution of the first compute kernel based on the information on the change of the status of the at least one hardware counter.

Examples described herein relate to a method and a system, for example, a workload controller, for accessing purged workloads. An alert indicative of an attempt to access a purged workload of workloads deployed in a workload environment may be received by the workload controller. The purged workload may include one or both of a deactivated workload or an archived workload. The workload controller may detect the attempt to access the purged workload based on port mirrored data traffic. Further, in some examples, the workload controller may activate the purged workload based on the alert.

A data processing system is disclosed that includes one or more processors that can perform producer processes to produce work and consumer processes that can consume work produced by a producer process. The system includes a pool of plural communication resources that may be used for communications between a producer process and a consumer process. The system tracks the usage of communication resources of the pool of communication resources, and allocates a communication resource from the pool of communication resources based on the tracking.

A method and an apparatus for determining a usage level of a memory device to notify a running application to perform memory reduction operations selected based on the memory usage level are described. An application calls APIs (Application Programming Interface) integrated with the application codes in the system to perform memory reduction operations. A memory usage level is determined according to a memory usage status received from the kernel of a system. A running application is associated with application priorities ranking multiple running applications statically or dynamically. Selecting memory reduction operations and notifying a running application are based on application priorities. Alternatively, a running application may determine a mode of operation to directly reduce memory usage in response to a notification for reducing memory usage without using API calls to other software.

Embodiments of the present disclosure may provide dynamic and fair assignment techniques for allocating resources on a demand basis. Assignment control may be separated into at least two components: a local component and a global component. Each component may have an active dialog with each other; the dialog may include two aspects: 1) a demand for computing resources, and 2) a total allowed number of computing resources. The global component may allocate resources from a pool of resources to different local components, and the local components in turn may assign their allocated resources to local competing requests. The allocation may also be throttled or limited at various levels.

A deployment manager includes storage for storing a state repository including a state transitions associated with event descriptions generated by a computing device and a computing device manager. The computing device manager obtains a new event description associated with the computing device, and a workload performed by the computing device; in response to obtaining the new event description: matches the new event description to a state transition of the state transitions; and manages the workload based on a predicted next state associated with the state transition.

Described are examples for monitoring performance metrics of one or more workloads in a cloud-computing environment and reallocating compute resources based on the monitoring. Reallocating compute resources can include migrating workloads among nodes or other resources in the cloud-computing environment, reallocating hardware accelerator resources, adjusting transmit power for virtual radio access network (vRAN) workloads, and/or the like.

Aspects of the disclosure include an electronic device, comprising a processor. The processor is to receive a request to allocate computing resources, the request indicating a content type to use with the computing resources, determine available computing resources, determine a scoring of the computing resources according to the content type, and allocate a portion of the available computing resources according to the request, the content type, and the scoring.

A method for migrating a workload includes: receiving workloads generated from a plurality of applications running in a plurality of server nodes of a rack system; monitoring latency requirements for the workloads and detecting a violation of the latency requirement for a workload; collecting system utilization information of the rack system; calculating rewards for migrating the workload to other server nodes in the rack system; determining a target server node among the plurality of server nodes that maximizes the reward; and performing migration of the workload to the target server node.

Implementations described herein relate to methods, systems, and computer-readable media to provide an alert based on a release of a software application implemented in a distributed computing system. In some implementations, the method includes receiving, at a processor, an indication of the release of the software application, obtaining a first set of metric values for each metric of a list of metrics for a first time period preceding a time of release of the release, obtaining a second set of metric values for each metric of the list of metrics for a second time period following the time of release, comparing the first set of metric values to the second set of metric values to determine a deviation score, generating an alert based on the deviation score, and transmitting the alert via one of a user interface and a communication channel.