Abstract: In one embodiment, a device receives, at a first large language model executed by a device, textual input from a user of a network regarding a networking issue in the network. The device issues, by the first large language model and to a second large language model, one or more questions regarding the network based on the textual input. The device receives, at the first large language model and from the second large language model, one or more answers to the one or more questions. The device generates, by the first large language model, a textual response to the textual input for presentation to the user.

Abstract: In one embodiment, a device identifies, based on traceroute information for a path in a network between an endpoint client and an online application, a particular segment of the path as most likely to cause degraded performance along the path. The device makes, using a prediction model, a prediction that routing traffic for the online application via the path will result in degraded quality of experience for the online application. The device obtains, based on the prediction, additional traceroute information in the network, to identify a bypass path in the network between the endpoint client and the online application that bypasses the particular segment. The device causes traffic for the online application to be routed along the bypass path.

Abstract: In one embodiment, a device obtains trace data indicative of application programming interface calls made during sessions between clients and an application accessible via a network. The device identifies, based on the trace data, a set of calls among the application programming interface calls that are frequently co-occurring. The device quantifies a latency savings expected to occur were the set of calls to be consolidated into a singular call instead of being made separately. The device provides, to a user interface, a recommendation to consolidate the set of calls into a consolidated call that indicates the latency savings.

Abstract: In one embodiment, a device maps network addresses associated with a user to a plurality of geographical locations, at least one of which is an office location of an enterprise. The device obtains quality of experience metrics for an online application accessed by the user. The device makes, based on the quality of experience metrics, a determination as to whether the office location of the enterprise would afford better application experience to the user. The device provides an indication of the determination for display.

Abstract: In one embodiment, a device initiates, using a chaos engineering tool, performance of randomized actions in a network via which an online application is accessible. The device obtains telemetry data from the network. The device computes correlations between the telemetry data and the randomized actions. The device uses the correlations to determine a root cause of an event in the network with respect to the online application.

Abstract: In one embodiment, a device obtains telemetry data associated with a particular online application accessed via a wireless network. The device computes statistics regarding traffic associated with the particular online application in the wireless network. The device generates a wireless configuration for an access point of the wireless network based on the telemetry data and the statistics. The device provides the wireless configuration for use by the access point when communicating with a client of the particular online application.

Abstract: In one embodiment, a device identifies available resources of a tunnel in a first software defined network. The device provides, based on the available resources, an indication that the tunnel is available to convey traffic sent by a second software defined network. The device receives, based on the indication, a request to convey traffic sent by the second software defined network via the tunnel in the first software defined network. The device configures a peering node in the first software defined network to connect the second software defined network to the tunnel to allow the traffic sent by the second software defined network to be conveyed via the tunnel.

Abstract: In one embodiment, a device receives application performance metrics generated by an online application accessible via a network and indicative of a particular state of the online application. The device performs testing of the online application by replicating a plurality of network impairments. The device associates, based on results of the testing, a particular network impairment from plurality of network impairments with the particular state of the online application. The device provides an indication of the particular network impairment as a cause of the particular state of the online application.

Abstract: In one embodiment, a device generates a plurality of recommendations for a network, each recommendation indicating a suggested action to optimize quality of experience of a corresponding application accessible via the network. The device assigns scores to different possible groupings of the plurality of recommendations. The device selects a particular grouping from among the plurality of recommendations, based on their scores. The device provides the particular grouping for implementation in the network.

Abstract: In one embodiment, a device determines a mapping between a network destination and Border Gateway Protocol (BGP) peers located across a plurality of autonomous systems for which the network destination is reachable. The device causes, based on the mapping, performance of probing tests along a plurality of paths to the network destination and via the BGP peers, to obtain path performance measurements for the plurality of paths. The device uses a prediction model to generate predicted performance metrics for the plurality of paths based on the path performance measurements. The device configures, based on the predicted performance metrics for the plurality of paths, the BGP peers with BGP peering policies to convey application traffic associated with the network destination via particular path from among the plurality of paths.

Abstract: In one embodiment, a device obtains quality of experience labels for an online application accessible via a network. The device also obtains telemetry data from the network that is associated with quality of experience labels. The device makes, based on the quality of experience labels and telemetry data, a determination as to whether the online application is similar to a second online application for which a prediction model is already available. The device trains, based on the determination, a prediction model for the online application to predict a quality of experience metric for the online application.

Abstract: In one embodiment, a device obtains application data captured by an intermediate node in a network by inserting monitoring code into traffic associated with one or more online applications accessible via the network. The device identifies, based on the application data, a workflow of actions performed by a user of the one or more online applications. The device determines that a particular stage of the workflow is associated with a quality of experience metric for the one or more online applications being degraded. The device provides a recommended change in the network for presentation by a user interface that is expected to optimize the quality of experience metric for the one or more online applications.

Abstract: In one embodiment, a device obtains a plurality of characteristics of different portions of a network for which a predictive networking engine is available. The device provides the plurality of characteristics of the different portions of a network to a user interface. The device receives, via the user interface, a set of one or more constraints to limit recommendations by the predictive networking engine for a selected portion of the network from among the different portions of the network. The device configures the predictive networking engine to prevent it from generating recommendations for the selected portion of the network according to the set of one or more constraints.

Abstract: In one embodiment, a device makes a determination that user application experience is degraded for a client endpoint of an online application due to a current path in a network that conveys application traffic associated with the online application. A device identifies a bypass path in the network for the application traffic. The device provisions an optimization gateway along the bypass path to forward the application traffic from the client endpoint to the online application. The device causes an endpoint agent executed by the client endpoint to send the application traffic to the optimization gateway for forwarding to the online application via the bypass path.

Abstract: In one embodiment, a device obtains a set of one or more configuration parameters of an online application accessed by a plurality of clients via a network. The device obtains path information regarding paths in the network via which the plurality of clients accesses the online application. The device determines an updated configuration parameter predicted by a prediction model to increase application experience of the online application based on the path information and the set of one or more configuration parameters. The device provides the updated configuration parameter for use by the online application.

Abstract: In one embodiment, a device identifies a plurality of paths between a pair of network addresses, wherein one of the pair of network addresses is associated with an online application. The device obtains telemetry data from the plurality of paths for the online application. The device computes, based on the telemetry data, fate sharing metrics for the plurality of paths. The device controls routing of application traffic between the pair of network addresses, based on the fate sharing metrics for the plurality of paths.

Abstract: In one embodiment, the device obtains telemetry data for traffic between endpoints in a plurality of local networks and an online application, the telemetry data including local interface data regarding local interfaces used by the endpoints to access the online application and data indicative of which points of presence (PoPs) were traversed by the traffic. The device identifies sessions of the online application in which an application experience metric was degraded. The device determines a root cause of the application experience metric being degraded for the sessions by assessing the telemetry data associated with the sessions. The device provides the root cause to a user interface for presentation.

Abstract: In one embodiment, a device discovers one or more network interfaces that an endpoint in a local network could use to access an online application. The device identifies a plurality of connectivity options available to the endpoint to access the online application via an external network. The device makes a prediction that a path that comprises a particular connectivity option from among the plurality of connectivity options and a particular network interface from among the one or more network interfaces will provide an optimal quality of experience metric associated with the online application. The device causes the endpoint to use the path to connect to the online application.

Abstract: In one embodiment, a device identifies a plurality of online applications whose traffic is conveyed via an interface of a networking entity of a network. The device computes a relationship between a quality of experience metric for a particular online application in the plurality of online applications and a traffic volume associated with the interface for the plurality of online applications. The device makes, based on the relationship, a determination that degradation of the quality of experience metric for the particular online application is due to the traffic volume associated with the interface for the plurality of online applications. The device reconfigures, based on the determination, the networking entity to prioritize traffic for the particular online application.

Abstract: In one embodiment, a device obtains media data captured by an endpoint of an online application that results from conducting a test in a network that subjects traffic of the online application to a particular network path degradation pattern. The device receives user feedback regarding the media data from one or more user interfaces. The device computes, based on the user feedback, a quality of experience metric for the online application associated with the particular network path degradation pattern. The device causes a configuration change to be made with respect to the online application, based on the quality of experience metric.