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.

The present disclosure relates to a method performed by a process control node (210) configured to allocate resources shared by a plurality of tenant applications, wherein each tenant application comprises a selection of non real-time processes and real-time processes, the method comprising receiving a first resource request, from a tenant application, indicative of resources requested to be allocated, by the process control node, for one or more real-time processes of the tenant application, evaluating a scheduling test to determine if the set of processing resources can be allocated from the shared resources by determining if resources requested by the first resource request can be allocated, and if it is determined that the requested resources can be allocated from the shared resources, the method further comprises performing the steps starting the one or more real-time processes of the tenant application within a resource partition of the tenant application, calculating updated resource quotas and priorities for non real-time processes comprised by the tenant application, transmitting a first resource response to the tenant application.

A system for managing access to a shared resource includes a plurality of nodes is described. The system may determine a quota for each of a plurality of nodes in view of one or more factors associated with a respective node and set a local counter stored in a memory of each of the nodes to the value of the relevant quota. In response to a request to access a resource made by an end device, the system may serve the request with a first node in the nodes, wherein the local counter stored in the memory of the first node is more than zero, and decrement the local counter stored in the memory of the first node by one after serving the request. Synchronization data is sent from each of the nodes, including the value of the local counter stored in the memory of the relevant node.

The disclosure relates to systems, methods and computer-readable media for dynamically provisioning resources within a compute environment. The method aspect of the disclosure comprises A method of dynamically provisioning resources within a compute environment, the method comprises analyzing a queue of jobs to determine an availability of compute resources for each job, determining an availability of a scheduler of the compute environment to satisfy all service level agreements (SLAs) and target service levels within a current configuration of the compute resources, determining possible resource provisioning changes to improve SLA fulfillment, determining a cost of provisioning; and if provisioning changes improve overall SLA delivery, then re-provisioning at least one compute resource.

A system and methods are provided for improving power efficiency of a data center, including: acquiring training data including power caps, utilization rates, and a measure of Service Level Agreement (SLA) compliance of one or more computer servers of the data center; creating a model for determining power caps according to measured utilization rates of the one or more computer servers, wherein the determined power caps, when applied to the one or more computer servers, reduce power consumption and meet the measure of SLA compliance; and applying the model, according to subsequent data received during a second operating period, to determine a power cap to apply to the one or more computer servers, wherein the subsequent data includes a subsequent utilization rate of the one or more computer servers.

Provided are an electronic system of a real-time operating system, an operating method thereof, and an operating method for a memory device. The operating method comprising obtaining a call graph by performing static code analysis on at least one thread that corresponds to a task, obtaining a stack usage of the thread and a call probability for each node by performing runtime profiling of the call graph, allocating a threshold value of a stack size for a first memory area by taking into account the call graph, the call probability for each node, and the stack usage, expanding and storing a stack from the first memory area to a second memory area according to a comparison result between the threshold value and a stack usage of the first memory area and returning the stack to the first memory when execution is completed in the second memory area, wherein the electronic system comprises a memory device configured to include the first memory area and the second memory area.

Systems and methods described herein support a usage calculation process in a cloud infrastructure environment. The usage calculation process can be used to determine whether a requested transaction that targets a compartment within a tree-structure of compartments violates any compartment quota or limit within parent compartments within the tree-structure.

Systems, computer-implemented methods, and computer program products to facilitate using multiple quota trees in resource scheduling are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components comprise an evaluation component that executes admissibility of a job request based on a scope property of one or more quota trees that apply to the job request.

A credit regulation and monitoring module receives a command for an application that is to be executed. In response to the command, credit amount for execution of the command is calculated. Further, an outstanding credit amount is determined based on an outstanding credit table and the other commands being executed. It is determined whether the credit amount and the outstanding credit are below a threshold value. If so, the command is executed and an outstanding credit table is updated to reduce the amount of credit available according to the credit amount allocated to the command.

Examples include techniques to enable quality of service (QoS) control for an accelerator device. Circuitry at an accelerator device implements QoS control responsive to receipt of a submission descriptor for a work request to execute a workload for an application hosted by a compute device coupled with the accelerator device. An example QoS control includes accepting the submission descriptor to a work queue at the accelerator device based on a work size of submission descriptor submissions of the application to the work queue over a unit of time not exceeding a submission rate threshold. The work queue is associated with an operational unit at the accelerator device to execute the workload based on information included in the submission descriptor. The work queue to be shared with at least one other application hosted by the compute device.