Abstract: Embodiments of the invention are directed to data replication in an active-active databases having a source site and a target site. Aspects include creating a subscription activation message in a capture address space, the subscription activation message having a timestamp after a latest committed timestamp of the active-active databases and transmitting the subscription activation message to a subscription activation module of the target site of the active-active databases. Based on a determination that one or more tables associated with the subscription activation message are inactive, aspects also include repairing the one or more tables. Based on a determination that all tables associated with the subscription activation message are active, aspects include initiate replication of the capture address space from the source site to the target site with a timestamp of the latest committed timestamp.

Abstract: Aspects include monitoring, by a controller, an operational status of a tracker system that is configured to track and record a current status of a job being executed and to report completion of the job to the controller. The recording includes storing two copies of the current status, where a first copy is stored in a shared memory location accessible by the controller. In response to determining, based on the monitoring, that the tracker system is operational, waiting to receive a job completion message for the job from the tracker system and performing a job completion action based on receiving the job completion message. In response to determining that the tracker system is not operational, obtaining the current status of the job from the shared memory location and performing the job completion action based on the current status indicating that the job has completed.

Abstract: A method and system for predicting a response time for a workload prior to making a hardware upgrade to a computing system. Data related to operation of the system is collected. Then a workload model of a plurality of workloads and CPU utilization for the plurality of workloads and a transaction model for each transaction within a workload of the plurality of workloads are built. Next the process determines that a characteristic of at least one workload in the plurality of workloads will change due to the hardware upgrade. As a result of the change, a new workload model for the changed workload is built based on the changed characteristic, and the response time for the workload based on the new workload model is calculated.

Abstract: A job is received. The job indicates moving one or more data to a pool storage group (PSG). The job includes resource requirements and the resource requirements include a size requirement to store the one or more data and a volume requirement to store the one or more data. A resource availability of the PSG is received. The resource availability of the PSG includes an available space on the PSG and one or more available volume on the PSG. Whether the resource availability of the PSG meets the resource requirements of the job is determined. Whether the PSG has a dynamic pool storage group (DPSG) flag indication on is determined.

Abstract: Disclosed are techniques for migrating the execution of a task from a first host system to a second host system by copying a snapshot of data required for starting the execution of a task from memory of the first host system to memory of a coupling facility, monitoring the execution of the task on the first host system, and, upon detecting failure of the execution of the task on the first host system, initiating execution of the task on the second host system by copying the snapshot of data from the memory of the coupling facility to the memory of the second host system.

Abstract: In various embodiments, a computer-implemented method includes identifying data files in external storage, where the data files correspond to a computer software application (application) on a mobile device. The method may also include sorting the one or more data files into different access levels. The method may also include predicting the sorted one or more data files that will be accessed on the mobile device using a prediction engine. The method may also include locating the predicted one or more data files in the external storage using a migration map. The method may also include determining whether the predicted one or more data files were previously migrated to the external storage from the mobile device. The method may also include migrating the predicted one or more data files from the external storage to the mobile device.

Abstract: Disclosed are techniques for migrating the execution of a task from a first host system to a second host system by copying a snapshot of data required for starting the execution of a task from memory of the first host system to memory of a coupling facility, monitoring the execution of the task on the first host system, and, upon detecting failure of the execution of the task on the first host system, initiating execution of the task on the second host system by copying the snapshot of data from the memory of the coupling facility to the memory of the second host system.

Abstract: In various embodiments, a computer-implemented method includes identifying data files in external storage, where the data files correspond to a computer software application (application) on a mobile device. The method may also include sorting the one or more data files into different access levels. The method may also include predicting the sorted one or more data files that will be accessed on the mobile device using a prediction engine. The method may also include locating the predicted one or more data files in the external storage using a migration map. The method may also include determining whether the predicted one or more data files were previously migrated to the external storage from the mobile device. The method may also include migrating the predicted one or more data files from the external storage to the mobile device.

Abstract: In various embodiments, a computer-implemented method includes identifying data files in external storage, where the data files correspond to a computer software application (application) on a mobile device and where the data files were previously stored on the mobile device. The method may also include sorting the data files into different access levels, where the access levels designate a hierarchy for the data files. The method may also include predicting the sorted data files that will be accessed on the mobile device using a prediction engine. The method may also include locating, in response to the predicting, the predicted data files in the external storage. The method may also include migrating the predicted data files from the external storage to the mobile device, where the migrating is done in order of the access levels.

Abstract: In various embodiments, a computer-implemented method includes identifying computer software applications (applications) on a mobile device. The method may also include generating migration profiles for the applications, where each application corresponds (corresponding application) to a migration profile and where the migration profile includes data files about the corresponding application. The method may also include monitoring storage space of the applications on the mobile device, where the monitoring includes identifying data files of the applications. The method may also include calculating an amount of storage space to determine whether there is a shortage of storage space for the data files. The method may also include, in response to calculating that there is a shortage of storage space, determining when the data files will be migrated. The method may also include, in response to determining when the data files will be migrated, migrating the data files to external storage.

Abstract: In various embodiments, a computer-implemented method includes identifying computer software applications (applications) on a mobile device. The method may also include generating migration profiles for the applications, where each application corresponds (corresponding application) to a migration profile and where the migration profile includes data files about the corresponding application. The method may also include monitoring storage space of the applications on the mobile device, where the monitoring includes identifying data files of the applications. The method may also include calculating an amount of storage space to determine whether there is a shortage of storage space for the data files. The method may also include, in response to calculating that there is a shortage of storage space, determining when the data files will be migrated. The method may also include, in response to determining when the data files will be migrated, migrating the data files to external storage.

Abstract: In various embodiments, a computer-implemented method includes identifying data files in external storage, where the data files correspond to a computer software application (application) on a mobile device and where the data files were previously stored on the mobile device. The method may also include sorting the data files into different access levels, where the access levels designate a hierarchy for the data files. The method may also include predicting the sorted data files that will be accessed on the mobile device using a prediction engine. The method may also include locating, in response to the predicting, the predicted data files in the external storage. The method may also include migrating the predicted data files from the external storage to the mobile device, where the migrating is done in order of the access levels.