A method for providing data to a client computing device from an edge computing device is discussed herein. The method may include performing a network proximity check regarding the client computing device associated with a request for data captured by the wideband sensor. The method may further include determining, based on at least one proximity metric associated with the client computing device, a route for data responsive to the request for data associated with the network proximity check, where the route is one of a route including the cloud storage or a route that does not include the cloud storage. The method may also include receiving the request for data captured by the wideband sensor associated with the network proximity check. The method may also include transmitting the data responsive to the request for data captured by the wideband sensor associated with the network proximity check to the client computing device through the determined route.

Systems, devices, and methods of classifying encrypted network communications. A Traffic Monitoring Unit operates to monitor network traffic, and to capture HTTPS-encrypted packets that are exchanged over an HTTPS connection between an end-user device and a web server. An HTTPS Traffic Classification Unit operates to detect discrete HTTPS-encrypted objects within that HTTPS connection, and to classify those discrete HTTPS-encrypted objects based on at least one of: a first Analysis Model that classifies HTTPS-encrypted objects based on a type of content that is represented in the HTTPS-encrypted object; a second Analysis Model that classifies HTTPS-encrypted objects based on a type of server-side application that is associated with the HTTPS-encrypted object. Each Analysis Model utilizes Machine Learning (ML), Deep Learning (DL), Artificial Intelligence (AI), or Statistical and Mathematical Analysis (SMA).

Systems, devices, and methods of classifying encrypted network communications. A Traffic Monitoring Unit operates to monitor network traffic, and to capture HTTPS-encrypted packets that are exchanged over an HTTPS connection between an end-user device and a web server. An HTTPS Traffic Classification Unit operates to detect discrete HTTPS-encrypted objects within that HTTPS connection, and to classify those discrete HTTPS-encrypted objects based on at least one of: a first Analysis Model that classifies HTTPS-encrypted objects based on a type of content that is represented in the HTTPS-encrypted object; a second Analysis Model that classifies HTTPS-encrypted objects based on a type of server-side application that is associated with the HTTPS-encrypted object. Each Analysis Model utilizes Machine Learning (ML), Deep Learning (DL), Artificial Intelligence (AI), or Statistical and Mathematical Analysis (SMA).

Systems and methods for monitoring, reporting, and notification of media processing entities using system variables and events are provided. According to embodiments, schemes for the monitoring, reporting, and notification may be created, updated, and deleted using a media processing entity (MPE) application programming interface (API). According to embodiments, based on the scheme being implemented by an MPE, a value of a variable of the MPE or a status of an event of the MPE, during the monitoring, or as a part of the reporting, or as a part of the notification may be sent by the MPE and received.

A network device includes a network interface for establishing a communication session with another network device, a memory to store instructions, and a processor to execute the instructions. The processor may, for each time period during the communication session, adjust a size of a receive buffer of a socket. When the processor adjusts the size, the processor, if a utilization number of the receive buffer is greater than a high threshold: may determine a first new size for the receive buffer, and set a size of the receive buffer to the first new size. If the utilization number is less than a low threshold, the processor may determine a second new size for the receive buffer; and set the size of the receive buffer to the second new size.

Aspects of the subject disclosure may include, for example, a mobile assistant device that obtains information regarding device locations of a plurality of devices; the mobile assistant device is enabled to move among at least a portion of the device locations. The mobile assistant device detects an indication of a need for maintenance, repair, and/or user attention, relating to a target device. The mobile assistant device moves to a location of the target device; obtains device information regarding a condition of the target device; and reports the device information to equipment of the user and/or a controller of the mobile assistant device. The mobile assistant device engages with the user and/or equipment of the user to provide instructions to the equipment of the user for resolving an issue relating to the target device, and can physically engage with the target device to resolve the issue. Other embodiments are disclosed.

Systems and methods herein provide for a proxy infrastructure. In the proxy infrastructure, a network element (e.g., a supernode) is connected with a plurality of exit nodes. At one of a plurality of messenger units of the proxy infrastructure, a proxy protocol request is received directly from a client computing device. The proxy protocol request specifies a request and a target. In response the proxy protocol request, a selection is made between one between one of the plurality of exit nodes. A message with the request is sent from the messenger to the supernode connected with the selected exit node. Finally, the message is sent from the supernode to the selected exit node to forward the request to the target.

A system is provided for automated cross-network monitoring of computing hardware and software status. In particular, the system may track the status of various computing resources using process automation-based operations to simulate calls made by users to the various resources that the users are authorized to access. Based on said operations, the system may assess whether the authorized pathways to the resources and/or their respective components are properly functioning by capturing information regarding the resource, its associated components, and the current status of the resource. The results of these operations may be aggregated to provide an overview of which resources and/or systems are functioning and which are not. In this way, the system may provide a detailed view of the statuses of the individual resources and components within an entity's complex computing network.

The present disclosure relates to computer-implemented methods, software, and systems for detecting outages in a cloud environment. Internal web agents installed at corresponding network segments of a first cloud platform and external web agents installed at an external second cloud platform are configured to perform network calls between themselves and the other web agents. Data from the internal web agents is automatically collected to generate structured data defining network connectivity status corresponding to the network segments of the first cloud platform based on the performed network calls between the internal and external web agents. In response to evaluating the structured data, a health status of network connectivity of the first cloud platform is determined. The health status can be provided to platform services provided by the first cloud platform and/or applications running on the first cloud platform to support managing of lifecycles of entities running on the first cloud platform.

The present disclosure relates to computer-implemented methods, software, and systems for detecting outages in a cloud environment. Internal web agents installed at corresponding network segments of a first cloud platform and external web agents installed at an external second cloud platform are configured to perform network calls between themselves and the other web agents. Data from the internal web agents is automatically collected to generate structured data defining network connectivity status corresponding to the network segments of the first cloud platform based on the performed network calls between the internal and external web agents. In response to evaluating the structured data, a health status of network connectivity of the first cloud platform is determined. The health status can be provided to platform services provided by the first cloud platform and/or applications running on the first cloud platform to support managing of lifecycles of entities running on the first cloud platform.