An example operation may include one or more of receiving a request associated with a key-value pair stored in a database, determining whether a state of the key-value pair has changed since a most recently received request, and in response to a determination that the state of the key-value pair has changed, generating a data block that includes a changed state of the key-value pair and adding the generated data block to a hash-linked chain of data blocks.

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.

A cloud network is a complex environment in which hundreds and thousands of users or entities can each host, create, modify, and develop multiple virtual machines. Each virtual machine can have complex behavior unknown to the provider or maintainer of the cloud. Technologies disclosed include methods, systems, and apparatuses to monitor the complex environment to detect network anomalies using machine learning techniques. In addition, techniques to modify and adapt to user feedback are provided allowing the developed models to be tuned for specific use cases, virtual machine types, and users.

A faulty node is identified in a cloud native environment by retrieving a topology that describes a relationship between a plurality of nodes in a network, retrieving a list of alarms in the network, determining a child node in the network located at the bottom of the topology that has a first alarm based on the alarm list, determining a parent node of the child node located above the child node and below or on an apex node of the network that has a second alarm based on the topology, determining whether the parent node is an apex node in the network based on the topology, and based on a determination that the parent node is the apex node in the network, identify the parent node as the faulty node.

A network management apparatus according to an embodiment includes: a storage device configured to store information indicating a correspondence relationship between information objects related to a logical layer, information objects related to a physical layer in a network configuration, and information objects related to a facility layer which are objects in which the information objects related to the physical layer are housed; an acquisition unit configured to acquire an information object related to an occurrence path of a failure in the logical layer of the network configuration, from the storage device; and a search unit configured to search for, among the information objects related to the facility layer stored in the storage device, an information object related to the facility layer and the physical layer associated with the information object related to the occurrence path of the failure acquired from the acquisition unit, as a candidate for a facility that causes the failure.

A method for determining a fault root cause includes obtaining first fault information, where the first fault information includes M alarms, and M is an integer greater than or equal to 1; determining, from N pieces of known fault information based on the M alarms, at least one piece of known fault information that matches the first fault information, where each of the N pieces of known fault information includes a plurality of alarms; and determining, based on a fault root cause of the at least one piece of known fault information, information related to a root cause of the first fault information. The root cause of the first fault information is determined by using the known fault information that matches the first fault information.

A network management system (NMS) is described that provides a granular troubleshooting workflow at an application session level using an application session-specific topology from a client device to a cloud-based application server. During an application session of a cloud-based application, a client device running the application exchanges data through one or more access point (AP) devices, one or more switches at a wired network edge, and one or more network nodes, e.g., switches, routers, and/or gateway devices, to reach a cloud-based application server. For a particular application session, the NMS generates a topology based on network data received from a subset of network devices, e.g., client devices, AP devices, switches, routers, and/or gateways, that were involved in the particular application session over a duration of the particular application session. In this way, the NMS enables backward-looking troubleshooting of the particular application session.

Rapid failure detection and recovery in wireless communication networks is needed in order to meet, among other things, carrier class Ethernet transport channel standards. Thus, resilient wireless packet communications is provided using a hardware-assisted rapid transport channel failure detection algorithm and a Gigabit Ethernet data access card with an engine configured accordingly. In networks with various topologies, this is provided in combination with their existing protocols, such as rapid spanning tree and link aggregation protocols, respectively.

Embodiments of a device and method are disclosed. In an embodiment, a method for network device troubleshooting involves at a cloud server, connecting to a neighboring network device of a faulty network device, where the neighboring network device and the faulty network device are located within a network deployed at a customer site, and where the neighboring network device communicates with the faulty network device according to a short-range wireless communications protocol, and at the cloud server, performing a network device troubleshooting operation on the faulty network device using the neighboring network device as a proxy.

This disclosure describes techniques that include determining the health of one or more routing engines included within a router. In one example, this disclosure describes a method that includes performing, by a first routing engine included within a router, routing operations, wherein the router includes a plurality of routing engines, including the first routing engine and a second routing engine; receiving, by a computing system, data including health indicators associated with the first routing engine; applying, by the computing system, a machine learning model to the data to determine, from the health indicators, a health status of the first routing engine, wherein the machine learning model has been trained to identify the health status from the health indicators; and determining, by the computing system and based on the health status of the first routing engine, whether to switch routing operations to the second routing engine from the first routing engine.