Juniper Networks Patente

Techniques are disclosed for a computing system that compares media access control (MAC) address profiles associated with the MAC address of a device to detect anomalies between the MAC address profiles. In one example, the computing system obtains a current profile of a MAC address associated with a device requesting access to a network at a location. The computing system compares the current profile of the MAC address to one or more historical profiles of the MAC address over time or concurrent profiles of the MAC address at other locations. The computing system detects an anomaly between the current profile of the MAC address and at least one of the historical profiles or the concurrent profiles of the MAC address. The computing system generates a notification identifying the anomaly.

Techniques are disclosed for using prompt engineering and statistical root cause analysis (RCA) to increase the accuracy of machine learning RCA. In an example, a computing system generates a prompt for root cause analysis of an application-layer anomaly within system of elements across a plurality of layers. The prompt comprises a cross-layer topology graph of the elements across the plurality of layers, diagnostics information for the elements, and a list of the elements and corresponding diagnostics information ordered according to a likelihood of being a source of a root cause of the application-layer anomaly. The computing system provides the generated prompt to a machine learning model to obtain, based at least in part on the generated prompt, a response comprising the root cause of the application-layer anomaly. The computing system outputs the response.

Techniques are disclosed for end-to-end assurance of application workloads. For example, a computing system receive time series data comprising performance indicators for elements of layers of a system having host computing devices executing application workloads. The computing system creates, based on mapping, using the time series data, Graphics Processing Units (GPUs) of a compute layer to network devices of a network layer, a dependency graph representing cross-layer relationships between elements of different layers of the layers. The computing system determines an anomaly in the performance of one of the application workloads. The computing system determines, based on a dependency within the dependency graph of the application workload on an element of the network layer, an issue with the element as a root cause of the anomaly in the performance of the workload, and performs a remedial action for the issue with the element of the network layer.

Techniques are disclosed for a conversational assistant system that employs a machine learning system to act as an intermediary between natural language questions of a user and one or more Application Programming Interfaces (APIs) implemented by a network analysis system. In one example, the conversational assistant system receives API definition files including sets of function definitions and corresponding function descriptions and a natural language question from a user device. The conversational assistant system processes the API definition files and the natural language question to obtain function definitions invoking API endpoints of the APIs. The conversational assistant system sequentially invokes, based on the function definitions, the API endpoints to obtain responses from the APIs implemented by the network analysis system. The conversational assistant system generates, based at least in part on the responses from the APIs, a natural language answer for output at an output device.

In general, techniques are described for a computing system that generates a first graph representative of a of a first application topology of a distributed application at a first time that includes a first plurality of nodes of a computing infrastructure across a plurality of layers. The computing system generates a second graph representative of a second application topology of the distributed application at a second time. The computing system determines, based on a comparison of the first graph and the second graph, that a path has changed. Based on the determination that the path has changed, the computing system outputs an indication that an alarm indicative of an issue in the computing infrastructure is caused by the change to the path.

This disclosure describes techniques that include assessing trust in a system based on subjective factors. In one example, this disclosure describes a method that includes determining, by the computing system, a prerequisite score for a network entity in a computer network; determining, by the computing system, a subjective score for the network entity based on one or more subjective factors for the network entity, wherein each of the one or more subjective factors for the network entity corresponds to a subjective characteristic of the network entity; determining, by a computing system, a trust score for the network entity based on the prerequisite score and the subjective score; and modifying, by the computing system, operation of the computer network based on the trust score for the network entity

Techniques are described for configuration and application of intent-based network access control (NAC) policies for authentication and authorization of multi-tenant, network access server (NAS) devices to access enterprise networks of organizations. A network management system configures intent-based NAC policies for an organization. A cloud-based NAC system may apply an appropriate intent-based NAC policy in response to an authentication request from a NAS device. The NAC system identifies a vendor of the NAS device, matches incoming attributes in the authentication request to a set of normalized match rules of the intent-based NAC policy, and translates a set of abstracted policy results corresponding to the set of normalized match rules into a vendor-specific set of return attributes based on the vendor of the NAS device. The NAC system sends the vendor-specific set of return attributes to the NAS device to enable the NAS device to access the enterprise network of the organization.

Example devices and techniques are described. An example device includes one or more processors and one or more memories storing instructions. When executed, the instructions cause the one or more processors to determine a respective configured ambient temperature for each of a plurality of network devices. The instructions cause the one or more processors to determine a respective current traffic load on each of the plurality of network devices. The instructions cause the one or more processors to determine, for each of the plurality of network devices and based on the respective configured ambient temperatures and the respective current traffic loads, a respective estimated power usage value. The instructions cause the one or more processors to sum the respective estimated power usage values to generate an overall estimated power usage value and output a representation of the overall estimated power usage value.

Techniques are disclosed for improved energy efficiency of network devices of a network system. For example, a computing system obtains time series data comprising information about computing devices of a computer network. The computing devices access other devices of the computer network via network devices that exchange network traffic of the computing devices. The computing system applies a machine learning system, trained with historical time series data, to the obtained time series data to predict a requirement of one or more of the network devices for exchanging network traffic of the computing devices for a next time interval. The computing system adjusts, based at least in part on the predicted requirement for the next time interval, operation of the one or more of the network devices.

A method includes deploying a network device within a fabric having a management network by attaching the network device through the management network to a port of a role allocator, wherein the role allocator includes one or more ports designated as first level port connections and one or more other ports designated as second level port connections. If the deployed network device is attached to one of the ports designated as first level port connections, the deployed network device is configured as a first level device. If the deployed network device is attached to one of the ports designated as second level port connections, the deployed network device is configured as a second level device.

Techniques are disclosed for a network device that performs gradual failover of sessions from a first link to a second link. For example, a network device forwards network traffic of a plurality of sessions over the first link. The network device determines that a performance of the first link does not satisfy a performance requirement. Based on the determination, the network device forwards network traffic of a first portion of the plurality of sessions over a second link and not the first link. The network device determines that a performance of the second link satisfies the performance requirement while carrying the network traffic of the first portion. Based on the determination, the network device forwards network traffic of a second, larger portion of the plurality of sessions over the second link and not the first link.

Techniques are described for onboarding a plurality of devices using a network management system (NMS). The NMS has memory and one or more processors coupled to the memory, the one or more processors configured to obtain onboarding information of a first device of a plurality of devices; assign, based on obtaining onboarding information of the first device, the first device to a group of devices to be managed by the network management system; and based on assigning the first device to the group of devices to be managed by the NMS, automatically assign a second device of the plurality of devices to the group of devices to be managed by the network management system.

Techniques are disclosed that enable a system to determine whether an error associated with a cloud-based authentication, authorization, and accounting (AAA) service has occurred. The techniques include obtaining, for a plurality of network access service (NAS) devices at a site, data indicative of authentication attempts for client devices with a cloud-based AAA service. The techniques include identifying, based on the data, whether one or more errors occurred for the authentication attempts; and correlating the one or more errors across the plurality of NAS devices at the site to determine whether the one or more errors are indicative of an issue associated with the AAA service. The techniques further include determining at least one remediation action for the issue associated with the AAA service.

A method for provisioning automatic configurations may involve detecting a connection between a computing device and an additional computing device that runs a first protocol and is communicatively coupled to a controller via a network fabric. In one example, the method may also involve determining, via a second protocol, that the computing device is unconfigured for operation in the network fabric. Additionally or alternatively, the method may further involve enabling the controller to configure the computing device for operation in the network fabric via a provisioning mechanism in response to determining that the computing device is unconfigured for operation in the network fabric. Various other devices, systems, and methods are also disclosed.

A system for load-balancing traffic based on flow attributes and intents may include at least one storage device and/or circuitry. In this example, the storage device may be configured to store data that identifies a set of load-balancing options available for network traffic. Additionally or alternatively, the circuitry may be configured to (1) identify a set of attributes of a packet corresponding to a traffic flow, (2) determine, based at least in part on the set of attributes, an intent of the traffic flow, and (3) assign a load-balancing option included in the set of load-balancing options to the traffic flow based at least in part on the intent and the set of attributes. Various other devices, systems, and methods are also disclosed.

A user interface as described herein provides improved visibility of the network topology of a network, including for complex and large-scale networks. In one example, a computing system outputs, for display at a display device, a user interface comprising an arrangement of icons into layers. Each icon of the icons corresponds to a network element of network elements of a network system, and each layer of the layers corresponding to a topological layer of the network system. Based at least in part on an indication of user input, the system modifies the arrangement by performing a geometric translation of first icons of the icons arranged into one or more first layers of the layers, without performing a geometric translation of second icons arranged into one or more second layers of the layers. The system outputs, for display at the display device, the user interface comprising the modified representation.

In general, this disclosure describes techniques for analyzing anomalies in a network. In an example, a method comprises obtaining, by a system, a graph query and a network graph for a network, wherein the network graph includes one or more nodes having one or more properties that indicate a plurality of anomalies for the network; executing, by the system, the graph query on the network graph for the network to determine a matching subgraph of the network graph, wherein the graph query matches on the one or more nodes and the one or more properties; and based on the determination of the matching subgraph, outputting an indication of an association of the plurality of anomalies.

An example Radio Access Network Intelligent Controller (RIC) for a radio access network (RAN) is described. The RIC includes processor circuitry and memory coupled to the processor circuitry. The memory stores instructions, when executed, to cause the processor circuitry to execute one or more applications configured to determine one or more changes to make to the RAN in an open-loop mode. In the open-loop mode, the one or more applications are unable to automatically make the one or more changes to make to the RAN. The instructions also cause the processor circuitry to control a user interface (UI) to present data indicative of the one or more changes to make to the RAN for display to a user.

Techniques are described for a network management system (NMS) configured to determine a root cause of an issue in performance of an application session, and perform one or more actions to remedy the issue. For example, the NMS is configured to obtain application performance data of an application session including a plurality of users; determine, based on the application performance data, a contributing user that contributed to an issue in performance of the application session; obtain network data or non-network data of one or more devices of a network associated with the contributing user; determine, based on the network data or non-network data of the one or more devices of the network associated with the contributing user, a root cause of the issue in performance of the application session; and perform an action to remedy the root cause of the issue in performance of the application session.

Techniques are described for a system comprising memory and one or more processors in communication with the memory. The one or more processors may be configured to obtain network data of a plurality of access point (AP) devices at a site. The one or more processors may further be configured to determine a capacity on a first radio band for an AP device of the plurality of AP devices. The one or more processors may further be configured to determine an availability associated with the first radio band with respect to one or more neighboring AP devices of the AP device. The one or more processors may further be configured to perform, based on the capacity and the availability, an action.

An example Radio Access Network Intelligent Controller (RIC) determines that operation of a first instance of an application satisfies one or more criteria for scaling the application, the first instance of the application processing cluster messages generated by the RAN. The RIC, in response to determining that the operation of the first instance of the application satisfies the one or more criteria, determines a first virtual cluster and a second virtual cluster of the RAN. The first virtual cluster includes first one or more resources of the RAN and the second virtual cluster includes second one or more resources of the RAN. The RIC instantiates a second instance of the application. The RIC routes cluster messages from the second one or more resources of the second virtual cluster to the second instance of the application.

In general, techniques are described for a computing device including a virtual router, a pod comprising a container, and a network plugin. The virtual router includes a virtual router agent. The network plugin includes processing circuitry configured to receive, from the virtual router agent, an indication of an interface type for a virtual network for the pod and to configure, for the pod, a virtual network interface having the interface type, the virtual network interface for communicating on the virtual network.

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A controller device manages a plurality of network devices. The controller device includes one or more processing units configured to receive an upgrade request; determine an upgrade graph having nodes each representing one of the network devices or a network service provided by the network, and also having one or more edges each connecting two of the nodes and representing a network redundancy or service dependency; compute and assign, an edge weight to each edge by combining results of at least one objective function, each of the at least one objective functions having a minimum objective or maximum objective for the network; partition the upgrade graph into a plurality of sub-groups based on the edge weights; determine an upgrade schedule; and upgrade software of each of the plurality of network devices according to the upgrade schedule.

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