Abstract: A system measures, by executing a monitoring process, first metric data associated with trade data at a first time point after the trade data is output by a first process of an application and before the trade data is input to a second process of the application, identifies the trade data at a second time point after the trade data is output by the second process and before the trade data is output by the application, measures second metric data associated with the trade data identified at the second time point, and sends, in response to a latency value obtained based on the first metric data or the second metric data exceeding a latency threshold, a latency alert to a user computing device associated with the application. The monitoring process is not a process of the application and is not linked with the first process or the second process.

Abstract: Systems and methods for improvements for processing electronic communications over computer networks. As one example, systems and methods may ensure real-time (and/or near real-time) processing of electronic communications over computer networks by detecting real-time delays in electronic communications over computer networks in an ongoing manner and in environments in which users have no access to intermediary devices using a parallel processing stream.

Abstract: A system measures, by executing a monitoring process, first metric data associated with trade data at a first time point after the trade data is output by a first process of an application and before the trade data is input to a second process of the application, identifies the trade data at a second time point after the trade data is output by the second process and before the trade data is output by the application, measures second metric data associated with the trade data identified at the second time point, and sends, in response to a latency value obtained based on the first metric data or the second metric data exceeding a latency threshold, a latency alert to a user computing device associated with the application. The monitoring process is not a process of the application and is not linked with the first process or the second process.

Abstract: A system measures, by executing a monitoring process, first metric data associated with trade data at a first time point after the trade data is output by a first process of an application and before the trade data is input to a second process of the application, identifies the trade data at a second time point after the trade data is output by the second process and before the trade data is output by the application, measures second metric data associated with the trade data identified at the second time point, and sends, in response to a latency value obtained based on the first metric data or the second metric data exceeding a latency threshold, a latency alert to a user computing device associated with the application. The monitoring process is not a process of the application and is not linked with the first process or the second process.

Abstract: Systems and methods for harvesting excess compute capacity across different compute domains involve a monitoring engine that collects resource utilization data continuously in real time for each of a plurality of server nodes in each of a plurality of different compute domains via a network. An elastic compute workload management engine receives the collected resource utilization data from the monitoring engine via the network, extracts excess workload from one or more server nodes with excess workload demand in a first one of the plurality of different compute domains via the network and inserts the extracted excess workload into one or more server nodes with currently available compute capacity in a second one of the plurality of different compute domains via the network.