Abstract: Examples provide a network testing solution using a remote-controlled testing device. A test device includes a computing device for executing network performance testing logic and a cellular device. The test device controls the cellular device via a series of commands issued to the cellular device by the computing device. The test device is placed onto or inside a vehicle. As the vehicle moves through a geographical area, the test device automatically and autonomously performs network testing operations. The test data generated during the test is periodically uploaded to a central controller. The central controller aggregates test data received from a plurality of test devices assigned to a plurality of vehicles for a given campaign. The aggregated test data is analyzed and filtered to generate performance test results. A user can dynamically set up each campaign and assign test devices and vehicles to each campaign using a graphical user interface.

Abstract: Examples provide a network testing solution using a remote-controlled testing device. A test device includes a computing device for executing network performance testing logic and a cellular device. The test device controls the cellular device via a series of commands issued to the cellular device by the computing device. The test device is placed onto or inside a vehicle. As the vehicle moves through a geographical area, the test device automatically and autonomously performs network testing operations. The test data generated during the test is periodically uploaded to a central controller. The central controller aggregates test data received from a plurality of test devices assigned to a plurality of vehicles for a given campaign. The aggregated test data is analyzed and filtered to generate performance test results. A user can dynamically set up each campaign and assign test devices and vehicles to each campaign using a graphical user interface.

Abstract: Examples provide a network testing solution using a remote-controlled testing device. A test device includes a computing device for executing network performance testing logic and a cellular device. The test device controls the cellular device via a series of commands issued to the cellular device by the computing device. The test device is placed onto or inside a vehicle. As the vehicle moves through a geographical area, the test device automatically and autonomously performs network testing operations. The test data generated during the test is periodically uploaded to a central controller. The central controller aggregates test data received from a plurality of test devices assigned to a plurality of vehicles for a given campaign. The aggregated test data is analyzed and filtered to generate performance test results. A user can dynamically set up each campaign and assign test devices and vehicles to each campaign using a graphical user interface.

Abstract: Systems and methods for automated monitoring and troubleshooting of unknown dependencies in a virtual infrastructure are disclosed. In particular, systems and methods disclosed herein enable automation of processes for detecting network errors for virtual machines residing on virtual infrastructures and retrieving network addresses and physical ports associated with the errors. Aspects of the technology use the IEEE MAC address of the virtual instance to triage the L2 connectivity to determine the physical port to which the virtual instance is attached and then automatically report the port to the network operator. The system also provides a method of saving virtual instances that are in a faulty state so that instances can be investigated further by automated monitoring tools.

Abstract: Systems and methods for automated monitoring and troubleshooting of unknown dependencies in a virtual infrastructure are disclosed. In particular, systems and methods disclosed herein enable automation of processes for detecting network errors for virtual machines residing on virtual infrastructures and retrieving network addresses and physical ports associated with the errors. Aspects of the technology use the IEEE MAC address of the virtual instance to triage the L2 connectivity to determine the physical port to which the virtual instance is attached and then automatically report the port to the network operator. The system also provides a method of saving virtual instances that are in a faulty state so that instances can be investigated further by automated monitoring tools.

Abstract: A load-balancing computing device receives a load-balance request for a processing of a workload request associated with a workload. The load-balancing computing device selects a member node of a distributed computing system to process the workload request. The member node is selected from amongst a pool of member nodes of the distributed computing system. The selecting includes: determining a member node for a baseline assignment for the workload; and selecting a member node based on an outcome of a mathematical operation performed on an identifier of the workload, the baseline cardinality of member nodes, and on the cardinality of member nodes in the pool. Next, the processing of the workload request is assigned to the selected member node.

Abstract: An apparatus referred to as a profiling server monitor receives data corresponding to the operation of physical hardware in a virtual computing environment. An example is power consumption data. The profiling server monitor analyzes the data received and determines an operation to perform or a business rule to follow in order to, as one example, reduce power consumption of the virtual computing environment.

Abstract: A load-balancing computing device receives a load-balance request for a processing of a workload request associated with a workload. The load-balancing computing device selects a member node of a distributed computing system to process the workload request. The member node is selected from amongst a pool of member nodes of the distributed computing system. The selecting includes: determining a member node for a baseline assignment for the workload; and selecting a member node based on an outcome of a mathematical operation performed on an identifier of the workload, the baseline cardinality of member nodes, and on the cardinality of member nodes in the pool. Next, the processing of the workload request is assigned to the selected member node.

Abstract: A load-balancing computing device receives a load-balance request for a processing of a workload request associated with a workload. The load-balancing computing device selects a member node of a distributed computing system to process the workload request. The member node is selected from amongst a pool of member nodes of the distributed computing system. The selecting includes: determining a member node for a baseline assignment for the workload; and selecting a member node based on an outcome of a mathematical operation performed on an identifier of the workload, the baseline cardinality of member nodes, and on the cardinality of member nodes in the pool. Next, the processing of the workload request is assigned to the selected member node.

Abstract: A load-balancing computing device receives a load-balance request for a processing of a workload request associated with a workload. The load-balancing computing device selects a member node of a distributed computing system to process the workload request. The member node is selected from amongst a pool of member nodes of the distributed computing system. The selecting includes: determining a member node for a baseline assignment for the workload; and selecting a member node based on an outcome of a mathematical operation performed on an identifier of the workload, the baseline cardinality of member nodes, and on the cardinality of member nodes in the pool. Next, the processing of the workload request is assigned to the selected member node.