The invention relates to implementing a system that monitors a process across multiple monitored computer systems. According to an embodiment of the present invention, the system comprises: a communications network; two or more monitored computer systems; an active monitoring agent computer system; and a database; the processors of the two or more monitored computer systems being configured to execute one or more steps of a process; the processor of the active monitoring agent computer system being configured to receive a predefined flow configuration for the process, generate a query to retrieve log data for the process, generate an alert if the process exceeds the maximum time to wait for completion for any step of the process, and store the log data in the database.

Migrating workloads to a preferred environment, including: predicting, for each of a plurality of environments, a performance load on each of a plurality of environments that would result from placing one or more of a plurality of workloads on the environment; determining a preferred environment for each of the plurality of workloads by determining a placement of each of the plurality of workloads that results in a best fit for the plurality of workloads; and deploying each of the plurality of workloads in the corresponding preferred environment.

Methods, apparatus, systems and machine-readable storage media of an edge computing device which is enabled to access and select the use of local or remote acceleration resources for edge computing processing is disclosed. In an example, an edge computing device obtains first telemetry information that indicates availability of local acceleration circuitry to execute a function, and obtains second telemetry that indicates availability of a remote acceleration function to execute the function. An estimated time (and cost or other identifiable or estimateable considerations) to execute the function at the respective location is identified. The use of the local acceleration circuitry or the remote acceleration resource is selected based on the estimated time and other appropriate factors in relation to a service level agreement.

In a network of mobile agents, data integrity can be improved by providing an agent server that can migrate between devices operating in the region of interest (ROI). The agent server distributes agent clients onto devices in the ROI and provides agent server services to the agent clients, including receiving and storing data from the agents. When the agent server device is to leave the ROI, the agent server can migrate to any device executing an agent client and continue to provide the agent server services, including data collection and aggregation, from the device to which the agent server has migrated.

In a network of mobile agents, data integrity can be improved by providing an agent server that can migrate between devices operating in the region of interest (ROI). The agent server distributes agent clients onto devices in the ROI and provides agent server services to the agent clients, including receiving and storing data from the agents. When the agent server device is to leave the ROI, the agent server can migrate to any device executing an agent client and continue to provide the agent server services, including data collection and aggregation, from the device to which the agent server has migrated.

In one embodiment, a supervisory device in a network receives a help request from a first node in the network indicative of a problem in the network detected by the first node. The supervisory device identifies a second node in the network that is hosting a repair walker agent able to address the detected problem. The supervisory device determines a network path via which the second node is to send repair walker agent to the first node. The supervisory device instructs the second node to send the repair walker agent to the first node via the determined path.

Aspects of the invention include creating and starting fast-start container images. A preview image of a container is received at a host computer. The preview image includes a subset of an original image of the container. The preview image of the container is executed, at the host computer, for a workload. Based at least in part on detecting a fault during the executing of the preview image of the container, one of the original image of the container and a portion of the original image not included in the preview image of the container is accessed for continuing execution of the workload.

Availability of computing resources is detected on a particular device in a network and a runtime core is caused to be loaded on the particular device based on the availability. The runtime core is configured to support hot-plugging of code embodying any one of a plurality of job and first code comprising a placeholder job is caused to be run on the runtime core to reserve at least a portion of the computing resources of the particular device. A particular one of the plurality of jobs to be run on the particular device is identified and the first code is replaced with second code corresponding to the particular job to replace the placeholder job on the runtime core.

Various embodiments provide a task processing method and apparatus. In those embodiments, when a first device determines that an available computing resource is less than a computing resource required by a to-be-executed AI task group, at least one second device from a valid device in a first area is selected. The first area is an area that uses the first device as a center and a valid communication distance of the first device as a radius, and the valid device in the first area is a collaborative computing device that is in the first area and that is connected to the first device. Still in those embodiments, a task in the to-be-executed AI task group is sent by the first device to each of the at least one second device; and an execution result of the sent task from the second device is received by the first device.

A method, computer system, and computer program product for optimizing a number of robots for operation of a process at a target system. The method may include providing a plurality of available robots to carry out tasks in the process at the target system. The method may monitor the target system by carrying out the process or part of the process with a varying number of robots to determine the processor utilization whilst the robots are executing a varying number of tasks. The method may balance process constraints of the execution of the process with physical system constraints of the target system by measuring a relationship between a number of tasks at a transactional level and the processor utilization. The method may output the optimized number of robots to be allocated for the process or part of the process.