Description
In this demo, we showcase the end-user analytics portal, highlighting how it helps monitor network health with intuitive dashboards. Watch how administrators use honeycomb visualizations to identify and address issues with services like DNS, SD-WAN, and Wi-Fi. Also, see how Selector Copilot, our conversational AI, integrates with collaboration tools to provide actionable insights, streamline troubleshooting, and facilitate team collaboration for effective issue resolution.
Video length: 4:54
Transcript
Narrator: In this end-user analytics portal demo, we’re going to start with an illustration of a high-level service dashboard representing the status of “Coke”, a stand-in for any enterprise customer. They have DNS, SDWAN, WiFi, and NLS network services. Selector dashboards allow you to quickly understand the health of services at a glance through honeycomb visualizations.
Here, a Coke administrator sees that the SD-WAN service is unhealthy, as indicated by the red honeycomb. A long press brings up a modal, allowing administrators to quickly explore contributing factors that are impacting a given class of service. A variety of insights can be represented with Selector. Here they can explore the quality of service for the WAN, an inventory of critical network devices, and a short list of active issues affecting our example network.
At times, administrators may wish to investigate certain unhealthy services more deeply. Selector allows customized drill-downs through which to gain even more insight into a given health condition affecting the network. Here, they can also see the contributing factors leading to the service being unhealthy, along with summarized, correlated anomalies associated with this service. For example, anomalies related to optics violations, discards, and errors are useful metrics to begin troubleshooting.
Key KPIs related to this service, for example CPU and memory, port status, and the health of those ports, can be displayed. Many other details can be made available — things like service configuration or time series visualizations operators may need to see at a glance.
Selector can further augment the capabilities of an operations team by allowing the team to remediate common issues directly through the Selector web interface. For the port issue, they have some example actions registered. For example, they could bounce the port and see if that resolves the issue. Alternatively, end-users can escalate to support or file a ticket directly from this portal, with contextual information pertaining to the issue automatically captured by Selector. There are many potential automations the team can rely on to remediate issues. For example, were the SD-WAN service experiencing high CPU, an operator may choose to restart the SD-WAN device itself or similarly may wish to escalate to others.
To facilitate team collaboration, Selector supports an integrated conversational AI known as Copilot. Copilot leverages a natural language interface to retrieve and render analyzed insights from the Selector analytics platform. It is accessible through preferred collaboration software such as Slack, Teams, Zoom, and similar platforms. Internally, Copilot leverages a combination of an integrated large language model to interpret natural language queries and a generative AI to summarize the results in a human-readable way.
Operators may leverage Copilot to accomplish a wide variety of tasks, both to support general awareness of the health of the environment and to support triage. They may ask questions such as who is using a given service at a given time. The natural language query is understood by the Selector system, with a contextualized response delivered back to the requesting user. The result is then made available to the rest of the team, enabling them to follow along.
Similarly, they may ask for an inventory of active devices on the network. Responses to these types of inventory queries can be further contextualized with additional information that might speed the triage process. They may further interrogate the system, asking for information about a given user’s experience with the Wi-Fi. Detailed technical information can also be surfaced, enabling detailed technical analysis of the health of a given device.
Most importantly, operators may ask a variety of technical questions related to the overall health of the system. Here, an operator interrogates the health of a link. The response is meaningfully contextualized, summarizing the results back in a human-understandable way.