Abstract: Embodiments visualize the execution of a disaster recovery plan. During a transfer of computing nodes from a source site to a target site, a map user interface (UI) is displayed. The map UI includes a first region corresponding to the geographic location of the source site and a second region corresponding to the geographic location of the target site. An animated progress indicator representing termination of computing nodes at the source site is displayed in the first region. Simultaneously, another animated progress indicator representing initiation of computing nodes at the target site, and further representing a reverse animation of the other animated progress indicator, is displayed in the second region.

Abstract: Embodiments visualize the execution of a disaster recovery plan. During a transfer of computing nodes from a source site to a target site, a map user interface (UI) is displayed. The map UI includes a first region corresponding to the geographic location of the source site and a second region corresponding to the geographic location of the target site. An animated progress indicator representing termination of computing nodes at the source site is displayed in the first region. Simultaneously, another animated progress indicator representing initiation of computing nodes at the target site, and further representing a reverse animation of the other animated progress indicator, is displayed in the second region.

Abstract: In one embodiment, a method and apparatus for Kalman filtering for grid computing telemetry and workload management is disclosed. The method includes monitoring telemetry data at a node of a grid computing engine with a Kalman filter, determining whether the monitored telemetry data is outside of a bounds of a predictive model of the Kalman filter, signaling an error condition for the node if the monitored telemetry data is outside of the bounds, and addressing the error condition by correcting a problem experienced at the node corresponding to the error condition. Other embodiments are also disclosed.

Abstract: In one embodiment, a method and apparatus for Kalman filtering for grid computing telemetry and workload management is disclosed. The method includes monitoring telemetry data at a node of a grid computing engine with a Kalman filter, determining whether the monitored telemetry data is outside of a bounds of a predictive model of the Kalman filter, signaling an error condition for the node if the monitored telemetry data is outside of the bounds, and addressing the error condition by correcting a problem experienced at the node corresponding to the error condition. Other embodiments are also disclosed.