Abstract: Task management techniques, in a storage system, involve: dividing a task to be processed into a plurality of child tasks, so that a processing time required by each of the plurality of child tasks is same, the number of the plurality of child tasks being a first number; dividing a progress to be reported and being associated with the processing of the task into a plurality of child progresses, the number of the plurality of the child progresses being a second number, the second number being less than the first number, and each of the plurality of child progresses having a same value; and associating, based on the first and the second number, and according to a predetermined mapping between the plurality of child progresses and the plurality of child tasks, each of the plurality of child progresses with a respective child task of the plurality of child tasks.

Abstract: A system, computer readable medium and a method that may include performing multiple iterations of: determining, by each active initiator of the multiple initiators, a number of pending access requests generated by the active initiator, wherein each access request is a request to access a shared resource out of the shared resources; determining, by each active initiator, a priority level to be assigned to all pending access requests generated by the active initiator, wherein the determining is based on the number of pending access requests generated by the active initiator, a number of active initiators out of the multiple initiators, and a number of access requests serviceable by the shared resource; for each active initiator, informing an arbitration hardware of a network on chip about the priority level to be assigned to all pending access requests generated by the active initiator; and managing access to the shared resources, by the arbitration hardware, based on the priority level to be assigned to all p

Abstract: An example operation may include one or more of connecting, by a load leveler, to a blockchain network comprising a plurality of nodes and configured to store a common work item, computing, by the load leveler, loads across the plurality of the nodes that need to execute the common work item upon completion of current tasks, determining, by the load leveler, a network load impact based on execution of a common blockchain consensus checking process on the network nodes, executing, by the load leveler, a work assessment process based on the loads computed across the plurality of the nodes and on the determined network load impact of the blockchain network, and assigning, by the load leveler, new tasks to the nodes based on results of the execution of the work assessment process.

Abstract: A method to implement a cloud application includes receiving a blueprint of the cloud application, wherein the blueprint specifies virtual machines and a network connecting the virtual machines and being isolated from traffic external to the virtual machines. The method further includes automatically selecting a cloud profile specifying a cloud provider and a network isolation strategy and deploying the blueprint with the cloud provider by causing the cloud provider to create the virtual machines, create the network with the network isolation strategy, and attach the virtual machines to the network.

Abstract: The present disclosure discloses a method and apparatus for loading a kernel module. A specific embodiment of the method comprises: detecting an instruction for loading a to-be-loaded kernel module into a target kernel; determining, in response to detecting the instruction, whether identifier information is included in the to-be-loaded kernel module, the identifier information being used to represent loading the to-be-loaded kernel module into the target kernel; and loading, in response to determining the identifier information being included in the to-be-loaded kernel module, the to-be-loaded kernel module into the target kernel. This embodiment improves the applicability of the to-be-loaded kernel module.

Abstract: In server/client architectures, the server application and client applications are often developed in different languages and execute in different environments specialized for the different contexts of each application (e.g., low-level, performant, platform-specialized, and stateless instructions on the server, and high-level, flexible, platform-agnostic, and stateful languages on the client) and are often executed on different devices. Convergence of these environments (e.g., server-side JavaScript using Node.js) enables the provision of a server that services client applications executing on the same device. The local server may monitor local events occurring on the device, and may execute one or more server scripts associated with particular local events on behalf of local clients subscribing to the local event (e.g., via a subscription model).

Abstract: Embodiments are described for dynamically allocating and reallocating system resources between production work tasks and administrative tasks using policies. A resource monitor continuously monitors all resources in a computing system, and whether the resources are used for production work or administrative tasks. A policy can define resources needed to execute an administrative task and conditions which can be used to determine whether or not the administrative command is allocated the resources, even at the expense of a negative impact to production work.

Abstract: An analysis and visualization depicts how an application is leveraging computer processor cores in time. The analysis and visualization enables a developer to readily identify the degree of concurrency exploited by an application at runtime. Information regarding processes or threads running on the processor cores over time is received, analyzed, and presented to indicate portions of processor cores that are used by the application, idle, or used by other processes in the system. The analysis and visualization can help a developer understand contention for processor resources, confirm the degree of concurrency, or identify serial regions of execution that might provide opportunities for exploiting parallelism.

Abstract: Methods and systems for executing code referenced from a microservice registry are disclosed. For example, a microservice registry is stored in a memory. The microservice registry includes references to a plurality of microservices including a first microservice. An isolated guest executing on one or more processors receives a request to execute an executable code and determines that the executable code is unavailable in the first isolated guest. The isolated guest determines that, based on the microservice registry, the first microservice executes the executable code. The isolated guest forwards the first request to the first microservice and receives a result of the request from the first microservice.

Abstract: A memory reclamation method and apparatus, where the method includes determining a target process from a background process list when current available memory of a system is less than a memory threshold, where the background process list includes a process of one or more applications, the target process is a process among the process of the one or more applications meeting a condition that an absolute value of a difference between memory occupied by the process and a memory pressure value is less than a preset threshold, and the memory pressure value is a difference between the memory threshold and the current available memory of the system, and sending a processing instruction to a system kernel to trigger the system kernel to reclaim the memory occupied by the target process.

Abstract: The technology disclosed herein relates to method, system, and computer program product (computer-readable storage device) embodiments for managing resource allocation in a stream processing framework. An embodiment operates by configuring an allocation of a task sequence and machine resources to a container, partitioning a data stream into a plurality of batches arranged for parallel processing by the container via the machine resources allocated to the container, and running the task sequence, running at least one batch of the plurality of batches. Some embodiments may also include changing the allocation responsive to a determination of an increase in data volume, and may further include changing the allocation to a previous state of the allocation, responsive to a determination of a decrease in data volume. Additionally, time-based throughput of the data stream may be monitored for a given worker node configured to run a batch of the plurality of batches.

Abstract: The technology disclosed herein relates to method, system, and computer program product (computer-readable storage device) embodiments for managing resource allocation in a stream processing framework. An embodiment operates by configuring an allocation of a task sequence and machine resources to a container, and by running the task sequence, wherein the task sequence is configured to be run continuously as a plurality of units of work corresponding to the task sequence. Some embodiments further include changing the allocation responsive to a determination of an increase in data volume. A query may be taken from the task sequence and processed. Responsive to the query, a real-time result may be returned. Query processing may involve continuously applying a rule to the data stream, in real time or near real time. The rule may be set via a query language. Additionally, the data stream may be partitioned into batches for parallel processing.

Abstract: A number of cells of a control plane of a virtualized computing service are set up, including a first cell with one or more request processing nodes, a local instance of a data store, and metadata indicating a set of virtualization hosts. A request processer transmits a request for a virtual machine to the first cell. A request processor of the cell initiates a workflow to launch the virtual machine using a virtualization host; the workflow includes storing a record of the request in the local instance of the data store.

Abstract: A parallel processing apparatus includes: a memory; and a processor coupled to the memory, the processor is configured to: acquire a first time and a second time; divide a plurality of nodes into a plurality of groups; generate a plurality of schedule candidates each which assigns time zones corresponding to a length of time used to perform a maintenance operation at one or more nodes included in the plurality of groups in a time period from the first time to the second time to the plurality of groups such that no overlap occurs among the plurality of groups; evaluate the plurality of schedule candidates based on one or more process execution schedules of the one or more nodes in the time period; and output one schedule candidate of the plurality of schedule candidates based on a result of the evaluation.

Abstract: An embodiment of the invention may include a method, computer program product and system for multi-threaded programming. An embodiment may include creating a plurality of threads. Each of the plurality of threads implements a same functionality. An embodiment may include determining a first operation implementing the functionality using a first group of resources. An embodiment may include determining at least one second operation implementing the functionality using at least one second group of resources. An embodiment may include enabling each thread of the plurality of threads to call the first operation or the at least one second operation.

Abstract: Composite virtual machine templates may be used in the deployment of virtual machines into virtualized computing environments. A composite virtual machine template may define a plurality of deployment attributes for use in a virtual machine deployment, and at least some of these deployment attributes may be determined through references to other virtual machine templates and included in the composite virtual machine template.

Abstract: A device that includes a parsing engine and an execution engine. The parsing engine is configured to identify micro operations corresponding with operations that are common among at least two jobs from a set of jobs and to store the identified micro operations in memory. The execution engine is configured to receive a job from the set of jobs, to identity micro operations and dependencies within the job, and to execute the identified micro operations for the job in accordance with the identified dependencies.

Abstract: Provided is a microkernel architecture control system of an industrial server and an industrial server, which relate to the technical field of industrial servers. According to the microkernel architecture control system, scheduling configuration information is customized on the basis of an architecture including a plurality of microkernels and a virtual machine monitor prior to startup of a system, each microkernel including industrial control middleware and a real-time operating system.

Abstract: Methods and systems for evaluating compatibility of a cloud of computers to perform one or more workload tasks. One or more computing solution aspects are determined that corresponding to one or more sets of workload factors, where the workload factors characterize one or more workloads, to characterize one or more computing solutions. The workload factors are compared to the computing solution aspects in a rule-based system to exclude computing solutions that cannot satisfy the workload factors. A computing solution is selected that has aspects that accommodate all of the workload factors to find a solution that accommodates the one or more individual workloads.

Abstract: 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.