Methods and apparatus to monitor server loads are disclosed. An example load monitor includes a first virtual machine to replicate a first server; a router interface to cause a router to redirect a portion of requests destined for the first server to the first virtual machine, the first virtual machine to serve the redirected requests; a collector to collect first metric data from the first virtual machine related to processing of the redirected requests; and an overload indicator to indicate an overload condition at the first server based on the first metric data collected from the first virtual machine.

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.

Disclosed herein are systems, devices, and methods related to assets and predictive models and corresponding workflows that are related to the operation of assets. In particular, examples involve assets configured to receive and locally execute predictive models, locally individualize predictive models, and/or locally execute workflows or portions thereof.

A server system includes an origin server acting as a source of deployment and at least one target server acting as a destination of deployment. The origin server further includes a virtual machine implementing an execution-facilitating process for facilitating the target server to deploy a predetermined program in an executable condition, and a migration part configured to migrate the virtual machine to the target server. After migration of the virtual machine from the origin server to the target server, the virtual machine carries out an execution-facilitating process for facilitating the origin server to deploy a predetermined program in an executable condition at least one time. This eliminates the necessity of providing a specific server dedicated to the execution-facilitating process, thus reducing the number of servers subjected to execution-facilitating processes.

The technology disclosed herein enables migrating a software build job from a first computing node to a second computing node. An example method may comprise detecting, by a processor, a first software build job executing on a first computing node; detecting a second software build job in a waiting state; determining that the first computing node is capable of executing the second software build job; responsive to determining that a second computing node is capable of executing the first software build job, migrating the first software build job to the second node; and executing the second software build job on the first node.

Providing workload mobility between disparate execution environments, including: identifying, by a workload migration module, a workload executing in a first environment, wherein the workload includes a software application that is being executed and data that is accessed by the software application; identifying, by a workload migration module, a second environment for servicing the workload; and deploying, by a workload migration module, the workload in the second environment.

Embodiments relate to a system, a program product, and a method to support a migration operation. Risk factors associated with a migration operation are assessed. The assessment includes assigning respective risk score values to the identified risk factors, assigning respective weight values to the identified risk factors, and calculating a composite risk score based on the assigned risk score values and the assigned weight values. At least one remediation action is recommended to reduce risk to the migration operation. The at least one recommended remediation action is implemented prior to execution of the migration operation. A migration plan incorporating the remediation action for the migration operation is generated. At least one machine learning (ML) model is employed in connection with (a) the subjecting of the identified risk factors to the assessment and/or (b) the recommending of at least one remediation action to reduce risk to the migration operation.

Techniques to facilitate a migration process of source data to cloud storage are described. These techniques use configuration information with pre-configured settings for the migration process by leveraging such information to build a component to execute the migration process. These settings can be used to identify computing modules (including interfaces) for generating a script for loading the source data to a storage location managed by a cloud storage service. The script may rely upon a data model for organizing the source data, which also is provided in the settings. Once the source data is available, the source data is converted into a suitable migration dataset and communicated with the script to the cloud storage service in a single operation. Other embodiments are described and claimed.

Techniques disclosed herein relate to migrating virtual computing instances such as virtual machines (VMs). In one embodiment, VMs are migrated across different virtual infrastructure platforms by, among other things, translating between resource models used by virtual infrastructure managers (VIMs) that manage the different virtual infrastructure platforms. VM migrations may also be validated prior to being performed, including based on resource policies that define what is and/or is not allowed to migrate, thereby providing compliance and controls for borderless data centers. In addition, an agent-based technique may be used to migrate VMs and physical servers to virtual infrastructure, without requiring access to an underlying hypervisor layer.

System and method for managing migration of trusted execution environments (TEEs) based on migration policies utilizes a source migration agent in the source host computer and a destination migration agent in a destination host computer to migrate a source TEE in the source host computer to the destination host computer. A migration policy data of the source TEE is first transmitted to the destination migration agent from the source migration agent to determine whether the destination host computer satisfies migration policies specified in the migration policy data. In response to a determination that the destination host computer satisfies the migration policies specified in the migration policy data, a destination TEE is created in the destination host computer and memory pages of the source TEE are transmitted to the destination TEE. The memory pages are then restored at the destination TEE for execution.