Abstract: A method for intelligently distributing messages across multiple devices and associated chat applications is disclosed. In one embodiment, such a method includes registering multiple devices and associated chat applications to receive intelligent distribution of messages. The method monitors, using an agent, a message copied from a first device of the multiple devices to a clipboard. The method automatically analyzes content of the message to determine which other devices and associated chat applications of the plurality are eligible to receive the message. The message is then distributed to other devices and associated chat applications that are deemed eligible to receive the message. In certain embodiments, the message originates from a first chat application of a first type and the message is distributed to a second chat application of a second type that is different from the first type. A corresponding system and computer program product are also disclosed.

Abstract: Computer-implemented methods for performing shutdown of a computing system using custom shutdown intervals are provided. Aspects include receiving, by the computing system, a command to shutdown the computing system and issuing a first command to shutdown a first subsystem of the computing system. Aspects also include determining, after a first interval since issuing the first command, that the first subsystem has not shutdown and issuing a second command to shutdown the first subsystem of the computing system, wherein the first interval is obtained from a trained machine learning model.

Abstract: Shutdown intervals between nodes of a dependency tree are determined. The dependency tree represents a system to be shut down and the nodes represent system components of the system. The determining the shutdown intervals includes calculating, for a pair of nodes of the dependency tree, a shutdown interval. The calculating is based on a relationship between the pair of nodes. The calculating is repeated for a plurality of pairs of nodes to obtain a plurality of shutdown intervals. The plurality of shutdown intervals is used in a shutdown of the system components. At least one system component represented by at least one node on a higher node level of the dependency tree is to be shut down prior to at least one other system component represented by at least one other node on a lower node level of the dependency tree.

Abstract: A method, computer system, and a computer program product are provided for managing an accelerated shutdown of a networked system having a having a plurality of nodes. The system to be shutdown is analyzed and a priority order is determined for the nodes. An interval period is also determined between each node according to the priority order. A leaf node set is constructed according to different shutdown types required for each node and a dependency tree is constructed by analyzing the leaf node sets. Each node is then shutdown according to the tree and the interval period determined. The dependency tree and the interval period is iteratively modified during the node shutdown until all nodes and ultimately the system shutdown has been completed.

Abstract: A system and/or method that can reduce impact of network latency can be provided. Information associated with a user device participating in an online meeting can be determined, for user devices connecting to the online meeting. Based on the information, the user devices can be grouped. For each of the user devices in a group, network quality associated with network connection between a user device in the group and a server managing the online meeting can be evaluated. Based on the network quality, at least one user device in the group can be designated to operate as a sharer device to at least one other user device in the group. The sharer device can be caused to stream data directly from the server during the online meeting. That one other user device can be caused to connect with and stream data from the sharer device.

Abstract: Container data sharing is provided. A second container of a cluster of containers is started to process a service request in response to detecting a failure of a first container processing the service request. The service request and data generated by the first container that failed stored on a physical external memory device is accessed. The service request and the data generated by the first container that failed is loaded on the second container from the physical external memory device via a dedicated hardware link for high-speed container failure recovery.

Abstract: Embodiments include synchronization of automation files among different computing systems. Aspects include receiving a notification that an automation file on a first computing system has been updated, the notification including a first set of data including a timestamp corresponding to the update and comparing the timestamp to a second timestamp, wherein the second timestamp corresponds to the automation file stored on a second computing system. Based on determining a difference between the timestamps, aspects include transmitting a synchronization request to the second computing system. Based on receiving a notification that the second computing system successfully executed the synchronization request, aspects include updating a second set of data to match the first set of data. Based on receiving a notification that the second computing system failed to executed the synchronization request, aspects include notifying a user of a required update to the second computing system.

Abstract: In an embodiment, a computer-implemented method comprises deploying a dual-active database on a first active database site and a second active database site. The first active database site comprises a first group of disks including a first sub-group of disks and a second sub-group of disks respectively corresponding to a third sub-group of disks and a fourth sub-group of disks included in a second group of disks in the second active database site. The method further comprises storing a first set of database logs on the first sub-group of disks while a second set of database logs is being written on the second sub-group of disks. Contents of the second set of database logs are consistent with contents of the first set of database logs and function as a duplication of the first set of database logs.

Abstract: In an embodiment, a computer-implemented method comprises deploying a dual-active database on a first active database site and a second active database site. The first active database site comprises a first group of disks including a first sub-group of disks and a second sub-group of disks respectively corresponding to a third sub-group of disks and a fourth sub-group of disks included in a second group of disks in the second active database site. The method further comprises storing a first set of database logs on the first sub-group of disks while a second set of database logs is being written on the second sub-group of disks. Contents of the second set of database logs are consistent with contents of the first set of database logs and function as a duplication of the first set of database logs.

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.