Abstract: A bad change detector for operational features of digital platforms is described. Metric data from a website is acquired by the bad change detector while implementing a first version of an operational feature of the website and while implementing a second version of the operational feature. A bad change to the website is detected by measuring an inequality among values of a frequency distribution defined by a time series of the metric data. The operational feature is reverted to the first version, automatically and without user intervention, in response to detecting the bad change, thereby improving operation of computing devices that implement the website.

Abstract: A bad change detector for operational features of digital platforms is described. Metric data from a website is acquired by the bad change detector while implementing a first version of an operational feature of the website and while implementing a second version of the operational feature. A bad change to the website is detected by measuring an inequality among values of a frequency distribution defined by a time series of the metric data. The operational feature is reverted to the first version, automatically and without user intervention, in response to detecting the bad change, thereby improving operation of computing devices that implement the website.

Abstract: Technologies are shown for generating process flow graphs from system trace data that involve obtaining raw distributed trace data for a system, aggregating the raw distributed trace data into aggregated distributed trace data, generating a plurality of process flow graphs from the aggregated distributed trace data, and storing the plurality of process flow graphs in a graphical store. A first critical path can be determined from the plurality of process flow graphs based on an infrastructure design for the system and a process flow graph corresponding to the first critical path provided for graphical display. Certain examples can determine a second critical path involving a selected element of the first critical path and provide the process flow graph for the second critical path for display. Some examples pre-process the aggregated distributed trace data to repair incorrect traces. Other examples merge included process flow graphs into longer graphs.

Abstract: Process flow graphs are generated from system trace data by obtaining raw distributed trace data for a system, aggregating the raw distributed trace data into aggregated distributed trace data, generating a plurality of process flow graphs from the aggregated distributed trace data, and storing the plurality of process flow graphs in a graphical store. A first critical path can be determined from the plurality of process flow graphs based on an infrastructure design for the system and a process flow graph corresponding to the first critical path provided for graphical display. Certain examples can determine a second critical path involving a selected element of the first critical path and provide the process flow graph for the second critical path for display. Some examples pre-process the aggregated distributed trace data to repair incorrect traces. Other examples merge included process flow graphs into longer graphs.

Abstract: Technologies are disclosed for implementing a time series forecasting model. A time series forecasting model comprising a periodic component is modified to include an event-based component comprising a long-term portion representing impacts greater than one period of the periodic component, and a short-term portion representing impacts shorter than one period of the periodic component. A forecast is output using the modified time series forecasting model.

Abstract: Technologies are shown for generating process flow graphs from system trace data that involve obtaining raw distributed trace data for a system, aggregating the raw distributed trace data into aggregated distributed trace data, generating a plurality of process flow graphs from the aggregated distributed trace data, and storing the plurality of process flow graphs in a graphical store. A first critical path can be determined from the plurality of process flow graphs based on an infrastructure design for the system and a process flow graph corresponding to the first critical path provided for graphical display. Certain examples can determine a second critical path involving a selected element of the first critical path and provide the process flow graph for the second critical path for display. Some examples pre-process the aggregated distributed trace data to repair incorrect traces. Other examples merge included process flow graphs into longer graphs.