A pipeline task verification method and system is disclosed, and may use one or more processors. The method may comprise providing a data processing pipeline specification, wherein the data processing pipeline specification defines a plurality of data elements of a data processing pipeline. The method may further comprise identifying from the data processing pipeline specification one or more tasks defining a relationship between a first data element and a second data element. The method may further comprise receiving for a given task one or more data processing elements intended to receive the first data element and to produce the second data element. The method may further comprise verifying that the received one or more data processing elements receive the first data element and produce the second data element according to the defined relationship.

Embodiments for predictive scheduling of backups in a data protection system by initiating a first backup job in a series of scheduled consecutive backup jobs, wherein a second backup job is allowed to begin only after the first backup job is finished and not active, detecting whether or not the first backup job is still active when a second job is to start, and if so, estimating an amount of additional time required to finish the first backup job. The second backup job is then rescheduled to start at least at the end of the additional time. The estimated amount of additional time is determined using a throughput to target storage device parameter. This parameter is periodically checked to determine if there is a change to the estimated amount of additional time, and if so, the estimated time is recalculated based on the changed parameter.

Embodiments of an activities-defined software object execution management platform include instantiation of a program based on a program configuration, including customizable scheduling configurations and execution steps of program stages. A current state of the program is received from a state persistence storage. A stage configuration of the current stage is configured. A program execution readiness is determined to identify when to execute the current stage of the program based on an execution configuration and program-specific parameterized values. The current stage is instantiated based on the program execution readiness. An execution status of the stage is determined based on a validation configuration. A previous stage is determined to rollback before the current stage based on the execution status and a rollback configuration. The current state is updated in the persistent storage based on the execution of the state step to form a subsequent state of the program.

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.

Embodiments are disclosed for a method. The method includes determining that a thief thread attempted a work steal from a garbage collection (GC) owner queue. Additionally, the method includes determining that a number of tasks in the GC owner queue meets a predetermined threshold. Further, the method includes determining that the GC owner queue comprises a heavy-weight task. The method also includes moving the heavy-weight task to a top position of the GC owner queue.

An apparatus is configured to collect information related to a first activity and analyze the collected information to determine decision data. The information is stored in a first list of the source processing core for scheduling execution of the activity by a destination processing core to avoid cache misses. The source processing core is configured to transmit information related to the decision data using an interrupt, to a second list associated with a scheduler of the destination processing core, if the destination processing core is currently executing a second activity having a lower priority than the first activity.

In an example embodiment, a new solution is provided for an in-memory database provided in a cloud as a service that enables “job cross running” instead of “parallel job running.” Specifically, job scripts are clustered based on a shared service. A primary job script in the cluster is compiled and executed, but secondary job scripts in the cluster are not compiled until after the execution of the primary job script has begun. A mock library is inserted into each of the secondary job scripts to cause service calls for the shared service in the secondary job scripts to be replaced with mock service calls. The secondary job scripts are then scheduled and executed, and upon completion the primary job script is permitted to delete the shared service.

An apparatus, for an existing schedule indicating time slots during which virtual-machines are to be migrated between physical-machines, acquires change information indicating a change of first time slots during which first virtual-machines are to be migrated, and generates constraint information including a group of constraints regarding the change information and second time slots during which second virtual-machines other than the first virtual-machines are to be migrated. The apparatus generates semi-constraint information items each generated by excluding, from the constraint information, an exclusion target constraint that is selected in turn from among the group of constraints, and generates, for each semi-constraint information item, a rescheduling result by rescheduling migrations of the virtual-machines. The apparatus outputs a first rescheduling result that is one of the generated rescheduling results which reduces a difference between a scheduled migration time indicated by the first rescheduling result and scheduled migration times of the second virtual-machines.

Example implementations relate to method and system for storing and applying updates to a firmware at runtime of a processor-based system. The processor-based system includes a system management (SM) memory, a platform hardware, a main processor, the firmware, and a hotfix-framework. The hotfix-framework includes a hotfix dispatcher module and a service driver module having one or more boot time resources. The firmware and the hotfix-framework are pre-executed in the SM memory. The platform hardware stores a hotfix-firmware including updates to the firmware into a memory of the processor-based system, and generates an interrupt to direct the main processor into an SM mode and get the hotfix-framework notification about the hotfix-firmware. The hotfix dispatcher module loads the hotfix-firmware from the memory into the SM memory, and executes the hotfix-firmware by utilizing the one or more boot time resources to apply the updates to the firmware at runtime of the processor-based system.

A trusted execution environment scheduling method for a device comprising a multicore processor, the processor operable to execute a rich execution environment (REE) and a trusted execution environment (TEE), the method comprising: providing a REE global scheduler in the REE, the REE global scheduler operable to schedule threads for execution in the REE; providing a TEE scheduler in the TEE, the TEE scheduler operable to schedule threads for execution in the TEE, wherein the TEE scheduler determines a number of runnable TEE threads which are either presently, or are awaiting, execution in the TEE and stores the number of runnable TEE threads in a location accessible to threads executing in the REE; providing a plurality of worker threads in the REE, the worker threads being in an activated state or in an deactivated state, wherein when an activated worker thread of the plurality of worker threads is executed according to the schedule of the REE global scheduler the worker thread makes a call to the TEE to cause execution of the TEE on the same core as the worker thread, and wherein the worker thread retrieves the number of runnable TEE threads and compares the retrieved number of runnable TEE threads to the number of currently activated worker threads.