Methods and system are presented for monitoring database processes to generate machine learning predictions. A plurality of database processes executed on database implementations can be monitored, wherein the monitoring includes determining a start time, an end time, and a number of rows impacted by portions of the database processes, and the monitored database processes generate instances of machine learning data including at least the number of rows impacted and an associated duration of time. Using a machine learning component and the machine learning data, a duration of time can be predicted for a candidate database process for execution on a database implementation.

A system and method for automated chatbot testing to provide training and quality assurance of conversational artificial intelligence systems, comprising a chatbot testing administrator interface which allows chatbot makers to define what a chatbot is supposed to do, create test scripts to test the performance of the chatbot, and review the results of the chatbot tests, a chatbot testing server which provides and interface between chatbot testing agents and the administrator interface, instantiates chatbot agents and distributes them across available hardware and runs testing programs which activate, configure, and deactivate chatbot testing agents as needed. A plurality of chatbot agents may be running in parallel to provide automated testing based upon test script configuration.

Described are systems and methods of detecting processes causing degradation of machine performance using heuristics. A device may identify a plurality of time intervals having a use of a resource on a machine above a threshold. The device may identify a percentage of the use of the resource by each of a plurality processes on the machine using the resource during each time interval of the plurality of time intervals. The device may determine a score for each process of the plurality processes based at least on a function of the percentage of the use of the resource over one or more of the plurality of time intervals in which each process used the resource. The device may provide, for display, a selection of one or more processes from the plurality of processes ranked by the score.

In computer-implemented method, computer system, and/or computer program product, a processor(s) obtains a test (of steps(s)) to verify program code for deployment in distributed computing system. The processor(s) determines pre-defined operations correlating to the step(s). The processor(s) automatically distributes the pre-defined operations to a resources of a distributed computing system, for execution. The processor(s) monitors the execution and saves at least one screenshot as each step. The processor(s) generates a user interface with a status indicator. The processor(s) continuously update the user interface, based on the monitoring, to reflect a progression of the portion of the one or more resources through the step(s).

An example method of implementing a monitoring interface for an information technology environment comprises: identifying machine data reflecting activity in the information technology environment comprising a plurality of entities providing a service; executing a search query to derive, from the machine data, a value of a key performance indicator (KPI) reflecting performance of the service; and causing display of a monitoring interface including: an identifier of the service, a color coded indication of a state of the KPI, and a visual representation of time series data associated with the service.

Aspects of the present disclosure relate to the visualization of product usage utilizing telemetry data associated with the product. More specifically, a first object identifier associated with an object, such as a method, function, or other portion of code, may be provided as part of the telemetry data together with an execution time stamp. A second object identifier may also be received, where the second object identifier is associated with object execution subsequent to the first object. Based on the first and second object identifier, an object pair may be determined and graphed at a path execution tree. In some instances, the object pairs may be filtered in accordance with a number of occurrences within a certain period of time, where a high number of occurrences is indicative of an intended path of one or more users.

Systems and methods herein describe receiving identification from a data pipeline, accessing first data offset information for a first data origin and second data offset information for a second data origin, bisecting the first data origin using the first data offset information, processing the data pipeline with the bisected first data offset information and the second data offset information, receiving a notification indicating a data pipeline status, and causing presentation of the notification on a graphical user interface of a computing device.

A cluster health reporting engine may be a software tool which generates compiled health data reported by data collection hosts, being health data of computing resources of backend computing clusters whose failure during the ordinary course of data query and processing functions may impede the normal functioning of those data query and processing functions. Such techniques may generate compiled health data reported by a data collection host for a particular host of a computing cluster, enabling administrative personnel to quickly narrow specificity of health data reported. Such techniques may aggregate health data reported by a data collection host over a dimension of hosted services, and may configure a reporting sub-system to visualize this aggregated health data, enabling administrative personnel to quickly view storage capacity consumed by various hosted services and identify hosted services or sub-services generating adverse health data by visual highlighting.

Systems and methods for using instrumentation for maintenance of a user-configured program in a cloud computing environment are herein disclosed as comprising, in an implementation, intercepting operation data pertaining to the user-configured program, including a start time, an execution time interval, an operation, and an origin of the operation, canonicalizing the intercepted operation data by stripping operation-specific variable data from the operation data, aggregating the canonicalized operation data based on the start time, the canonicalized operation data, and the origin of the operation, and storing the aggregated operation data within a time series database in the execution time interval based on the start time.

A system and method for comparative performance monitoring of software release versions is disclosed. A remote network management platform may include a computational instance for managing a network. Transactions between a server of the computational instance and a client device in the managed network may be logged to a database. Transactions may be carried out by a release version of a set of program code units executing on the server. A software application executing on a computing device may retrieve and analyze a first set of transactions carried out by a first release version of the set of program code units to determine a first set of performance metrics, and do the same for a second set of transactions carried out by a second release version of the set of program code units to determine a second set of performance metrics. A classification filter may be applied to the metrics, and a quantitative comparison of the filtered first and second sets of performance metrics may be displayed on graphical user device.