A recording medium stores an application control program for causing a computer to execute processing including: when a specific application included in a applications is executed in response to a processing request from a specific processing request source, referring to a storage unit that stores flow information that indicates a past execution order of the applications for each of the processing request sources of the applications, and calculating an execution probability that each of one or more applications that are likely to be executed after the specific application executed in response to the processing request from the specific processing request source among the applications is executed after the specific application executed in response to the processing request from the specific processing request source; specifying an application to be activated from the one or more applications based on the calculated execution probability; and activating the specified application to be activated.

A lock is applied automatically without any user involvement, to each of one or more data objects stored by the data processing system. Each of the one or more locks prevent deletion, by any user, of the one or more data objects within a predetermined time frame. A cloud garbage collector marks the one or more data objects for a) deletion, or b) for lock extension, the garbage collector scheduled to run periodically at a period that is less than the predetermined time frame. The deletion or the lock extension is executed for the one or more data objects, based on marks by the garbage collector. Other embodiments are described and claimed.

Data transformation caching in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, including: identifying, in dependence upon one or more machine learning models to be executed on the GPU servers, one or more transformations to apply to a dataset; generating, in dependence upon the one or more transformations, a transformed dataset; storing, within one or more of the storage systems, the transformed dataset; receiving a plurality of requests to transmit the transformed dataset to one or more of the GPU servers; and responsive to each request, transmitting, from the one or more storage systems to the one or more GPU servers without re-performing the one or more transformations on the dataset, the transformed dataset.

A non-transitory computer-readable storage medium storing a program that causes a computer to execute a process, the process includes acquiring first multiple tasks; dividing each task in the first multiple tasks in accordance with a cache size; classifying second multiple tasks in accordance with a range of data to be referred to at a time of execution of each task in the second multiple tasks that have been obtained by the dividing; and determining an execution order of tasks in a group for each group that has been obtained by the classifying.

To more properly size resources in a destination to which IT resources will be migrated, a system for appraising a resource configuration estimates a source's load model representing a load of first resources in a first computer system which is the source of migration and estimates a destination's load model representing a load of second resources to be built by migrating the first resources to a second computer system based on the source's load model. The system compares performance requirements of the first resources against the destination's load model and finds the destination's load model that is conformable to the performance requirements. When determining design values of the second resources' configuration, the system corrects those design values based on the destination's load model estimated conformable to the performance requirements to decrease design margins of the resource configuration using a design correction value defined to meet a service level requested.

A method for fetching a content from a web server to a client device is disclosed, using tunnel devices serving as intermediate devices. The tunnel device is selected based on an attribute, such as IP Geolocation. A tunnel bank server stores a list of available tunnels that may be used, associated with values of various attribute types. The tunnel devices initiate communication with the tunnel bank server, and stays connected to it, for allowing a communication session initiated by the tunnel bank server. Upon receiving a request from a client to a content and for specific attribute types and values, a tunnel is selected by the tunnel bank server, and is used as a tunnel for retrieving the required content from the web server, using standard protocol such as SOCKS, WebSocket or HTTP Proxy. The client only communicates with a super proxy server that manages the content fetching scheme.

Computer-implemented methods, computer program products, and computer systems are provided. A method includes generating a running result matrix for a plurality of batch jobs, indicating corresponding running results for respective processing actions in batch jobs of the plurality of batch jobs. The method further includes obtaining an internal dependency matrix for the plurality of batch jobs, indicating corresponding dependencies between respective processing actions within a batch job of the plurality of batch jobs. The method further includes calculating a recovery matrix for the plurality of batch jobs based, at least in part, on the running result matrix and the internal dependency matrix, the recovery matrix indicating corresponding recovery actions for respective processing actions in batch jobs of the plurality of batch jobs. The method further includes executing failover management for one or more batch jobs based, at least in part, on the calculated recovery matrix.

A system enabling a hypervisor to assign processor resources for specific tasks to be performed by a virtual machine. An example method may comprise: receiving, by a hypervisor running on a host computer system, a virtual processor (“vCPU”) assignment request from a virtual device driver running on a virtual machine managed by the hypervisor, assigning a vCPU for executing a task associated with the assignment request, and causing the virtual device driver to execute the task using the vCPU.

Operations include halting a runaway query in response to determining that a performance metric of the query exceeds a performance threshold. The runaway query halting system receives a query execution plan associated with a query and divides the received execution plan into one or more components. For each component, the system determines a predicted resource usage associated with executing the component. The system further determines a predicted resource usage associated with the query execution plan based on the predicted resource usage associated with each component. The system executes the query associated with the received query execution plan and compares the predicted resource usage associated with the query to a resource usage threshold. In response to determining that the predicted resource usage of the query execution plan exceeds the resource usage threshold, the system halts execution of the query associated with the query execution plan.

A network device includes a network interface, a host interface and processing circuitry. The network interface is configured to connect to a communication network. The host interface is configured to connect to a host including a processor. The processing circuitry is configured to receive from the processor, via the host interface, a notification specifying an operation for execution by the network device, the operation including (i) multiple tasks that are executable by the network device, and (ii) execution dependencies among the tasks in response to the notification, the processing circuitry is configured to determine a schedule for executing the tasks, the schedule complying with the execution dependencies, and to execute the operation by executing the tasks of the operation is accordance with the schedule.