Improving the End User Experience
Enhancing Operational Efficiency
Reducing Business Risk
The increasing challenges of supporting hybrid workforces, new business services at the edge, and digital transformation are straining IT staff. Teams are actively looking for ways to make life easier for network admins to reduce trouble tickets and provide more efficient ways to resolve problems while ensuring SLAs and enhancing user experiences.
Most IT organizations are adopting artificial intelligence for operations (AIOps) as
a way of addressing this complexity. The
Saving time on daily operations requires identifying issues proactively. The anomaly detection capabilities in CoPilot look for patterns ahead of time to identify the anomalies that matter, and it recommends actions to address them early. The algorithms and data inputs are derived at multiple levels: local device, location, associated devices, and across sites. The ML even compares the performance of a customer’s network with the averaged performance of other deployments using anonymized data. This provides greater context that facilitates true outlier analysis and expedites root cause analysis.
Actionable insights and recommendations are generated that help network administrators to be more proactive. Users can trust these recommendations because the ML models are designed to provide transparency, enabling an understanding of what happens in the model from input to output. The use of Explainable ML helps users to see, verify, and trust the recommendations, building confidence in the operation automation. This helps significantly lower networking operational costs by saving time.
CoPilot leverages innovative ML technologies to analyze and interpret millions of network and end user data points, from the edge to the data center. The anomaly detection capability is implemented at multiple levels starting at the local device, installed location, associated devices, and across multiple sites where applicable. It constantly scans, compares, and computes network data from all relevant sources to define dynamic baselines, identify outliers, and provide the necessary context. Detection models are continuously calibrated against randomly injected negative test cases to reduce false positives.
Ensuring the end user experience requires refining vast amounts of data and status into easy-to-understand metrics. The Connectivity Experience feature summarizes the client’s experience into a single quality index score to easily track, identify, and troubleshoot connectivity issues.
Proactive alerting reduces the risk of minor issues becoming major outages. The recommendations generated by CoPilot isolate issues and identify likely root causes, so users can quickly drill down into details. This facilitates rapid analysis and problem resolution that would normally require high levels of technical expertise. The Digital Twin capability facilitates network assurance by allowing users to create a virtual copy of network infrastructure in a digital sandbox environment in the cloud. They can then assess if a new configuration or device would cause problems prior to deploying the infrastructure. This is a new level of network assurance that helps minimize potential risks.
The ExtremeCloud IQ CoPilot license tier is an add-on to the Pilot license tier. It leverages the centralized management capabilities of the ExtremeCloud Pilot license tier. CoPilot is a trusted digital advisor for your Extreme cloud-managed wireless and wired networks. With CoPilot, IT organizations can proactively reduce business risks and ensure the end user experience, so resources can be used more efficiently.
CoPilot includes the following advanced capabilities:
Anomaly Detection reduces the noise so users can focus on relevant data and make more informed decisions. This capability is implemented at multiple levels starting at the local device, installed location, associated devices, and across multiple sites where applicable to enable dynamic baselining. Detection models are continuously calibrated against randomly injected negative test cases to reduce false positives.
Proactive Alarms and Events reduce the risk of minor issues becoming major outages. CoPilot reduces the number of trouble tickets and escalations by looking for patterns ahead of time to identify the anomalies that matter and recommends actions to address them early.
Explainable ML algorithms are built with transparency to explain how the insights were derived, so users can trust the recommendations and automate operations with confidence. CoPilot generates understandable descriptions that enable users to see, verify, and trust the data behind every recommendation, and it provides the best options for resolution.
Connectivity Experience summarizes the client’s experience into a single quality index score to easily track, identify, and troubleshoot connectivity issues. For each wired and wireless client, CoPilot processes information from all relevant metrics to define dynamic baselines, identify outliers, and provide the necessary context to remediate issues.
Mobile App (ExtremeCloud IQ Companion) allows users to monitor and access details about the network from anywhere in near real time. The app includes a comprehensive troubleshooting toolbox, helps simplify the onboarding of devices, and creates a full installation report.
Digital Twin facilitates network assurance by allowing devices to be virtually staged before deploying them, helping to reduce risk. Users can create a digital copy of network infrastructure in a digital sandbox environment in the cloud, to assess if the new configuration or device would cause problems prior to deployment. Users can test and operationalize a new network or expand network infrastructure rapidly, then push the tested changes into production.
Automated GTAC Support makes it easier to address issues quickly and efficiently. It helps users create an Extreme Global Technical Assistance Center (GTAC) case from within ExtremeCloud IQ.
ExtremeCloud IQ also provides a full suite of cloud-optimized Open APIs for developers to create third-party applications and user experiences. This includes user onboarding mechanisms, proximity-based services, presence and location analytics, and more.