A remote network management platform may include persistent storage containing: (i) data related to a managed network, and (ii) a persona of a user. The remote network management platform may also include a platform application associated with a web-based user interface and using a portion of the data. The remote network management platform may also include a recommendation engine with access to a set of rules or a machine learning (ML) model corresponding to the platform application. The recommendation engine may be configured to: (i) read, from the persistent storage, the portion of the data and the persona; (ii) apply, to the portion of the data and the persona, the set of rules or the ML model to generate one or more recommendations; and (iii) transmit, by way of the web-based user interface and to the user, representations of the one or more recommendations.

The invention relates to a system for monitoring and controlling a dynamic network such as an oil, gas, or water pipeline. The system includes a plurality of sensors for measuring aspects of a state of the network with each sensor being associated with a segment of the network and connected to a virtual sensor which accumulates and pre-processes measurements from the sensors for each segment of the network. The system further includes a network topology processor for storing the topology of the network and relating sensors and virtual sensors to segments of the network and neighbouring sensors and virtual sensors in accordance with the topology and a reinforcement learning artificial neural network (ANN) based nonlinear state estimation and predictive control model which uses measurements from the sensors and virtual sensors to model the state of the network and estimate sequential states of the network.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining a terminal idle time. In some implementations, a server can obtain communication data from a plurality of devices in a communication network, wherein the communication data indicates levels of network traffic for the device over time. The server can generate an idle period forecasting model configured to predict occurrence of future communication idle periods in which communication activity is predicted to be below a threshold. The server can provide the idle period forecasting model to each of the plurality of devices such that the devices can respectively use the idle period forecasting model to locally predict future communication idle periods of the devices.

This document describes modeling and simulation techniques to select a cloud architecture profile based on correlations between application workloads and resource utilization. In some aspects, a method includes obtaining infrastructure data specifying utilization of computing resources of an existing computing system. Application workload data specifying tasks performed by one or more applications running on the existing computing system is obtained. One or more models are generated based on the infrastructure data and the application workload data. The model(s) define an impact on utilization of each computing resource in response to changes in workloads of the application(s). A workload is simulated, using the model(s), on a candidate cloud architecture profile that specifies a set of computing resources. A simulated utilization of each computing resource of the candidate cloud architecture profile is determined based on the simulation. An updated cloud architecture profile is generated based on the simulated utilization.

The present invention extends to methods, systems, and computer program products for tool registry for automating DevOps toolchains. Submission of a DevOps tool, authentication information, and tool configuration data is received from a user. Subsequently, the DevOps tool is selected for inclusion in a DevOps job. The DevOps tool including the authentication information and tool configuration data is automatically accessed from the tool registry. The DevOps tool is configured in accordance with the accessed authentication information and accessed tool configuration data as part of the DevOps job and for interaction with the one or more other DevOps tools. The DevOps job is deployed.

The present disclosure generally relates to systems, methods and software for quantitatively evaluating an improvement on an active communication network when an impairment, such as a developing impairment, is addressed by one or more repair options via proactive network maintenance.

Methods, systems and computer products provide access to historical data over a real-time tunnel in an architecture including an operational technology (OT) network, a de-militarized zone (DMZ) and an information technology (IT) network. The OT network interleaves real-time data and historical data over a first tunnel connection, a first firewall and a second firewall in conjunction with a DMZ and an IT network by (a) performing pull replication of the historical data, (b) daisy chaining the historical data, or (c) a combination of (a) and (b).

There is provided a method and system for communication network management. There is provided an active TE architecture and procedure that rely on the epistemic uncertainty obtained from traffic forecasting models. According to embodiments, the traffic forecasting models can predict the mean of the network traffic demand and can extract one or more of the features relating epistemic uncertainty and the aleatoric uncertainty. According to embodiments, the epistemic uncertainty is used to vary the sampling frequency of network statistics in TE applications, for specific times or specific flows. A time-window can be used to predict network traffic can be varied (e.g. increased or decreased) to adjust the epistemic uncertainty.

A system and method for a virtual desktop system is disclosed. The system includes a master fabric region including resources for provisioning a desktop. The system includes a plurality of expansion fabric regions. Each of the expansion fabric regions including replicated resources for provisioning the desktop from the master fabric region. The system includes a control plane having a global pool. A client device application operated by a user associated with the global pool accesses a desktop from either the master fabric region or one of the expansion fabric regions. The control plane is operable to add a new expansion fabric region to the plurality of expansion fabric regions or eliminate one of the plurality of expansion fabric regions.

Technologies for allocating resources of managed nodes to workloads to balance multiple resource allocation objectives include an orchestrator server to receive resource allocation objective data indicative of multiple resource allocation objectives to be satisfied. The orchestrator server is additionally to determine an initial assignment of a set of workloads among the managed nodes and receive telemetry data from the managed nodes. The orchestrator server is further to determine, as a function of the telemetry data and the resource allocation objective data, an adjustment to the assignment of the workloads to increase an achievement of at least one of the resource allocation objectives without decreasing an achievement of another of the resource allocation objectives, and apply the adjustments to the assignments of the workloads among the managed nodes as the workloads are performed. Other embodiments are also described and claimed.