Our built-in ML model provides automated data insights through statistical rules, Machine Learning and Natural Language Processing. Actionable insights and recommendations are displayed on the dashboard without the user having to navigate through TBs of data.
The platform offers predictive analysis using User Experience Index (UEI) and Operations Performance Index (OPI) that can result in better capacity planning. Forecast bandwidth consumption for WAN links, top application flows, etc. and prepare your teams for seasonal trends. You can also measure how well the component will perform in the near future and the possibilities of errors from components.
UEI, scored on a scale of 0 to 10, indicates the end user experience of business services and can be used for detecting availability and quality of Wi-Fi signals, measure user experience of web servers, measure network connectivity and availability of services at a branch level. OPI, scored on a scale of 0 to 10, indicates the robustness of current operations and can be used for measuring future performance of application and infrastructure components.
Our built-in ML model detects anomalous behaviour considering seasonality, past trends, user feedback, inter-metric correlations that identify anomalous points in real-time, eliminating the need to configure static rule-based alerts. Detect anomalies in WAN link latencies, bandwidth consumption patterns on WAN links, traffic flows in WAN links, etc.
The platform provides real-time contextual and correlated alerts with slice & dice and granular data. Get contextual data from usage patterns, uptime, downtime, and many more metrics across multiple dimensions such as business/peak hours, time, geo, business impact, etc. It also provides static and dynamic alerts with thresholds that support alert suppression, deduplication, unified KPI views, etc.
The platform allows to aggregate, normalise, correlate and analyse event log data from the myriad of devices. It supports temporal and topology correlation along with alert suppression, alert deduplication to create high fidelity events and reduce alert fatigue. For e.g., get alerted for WAN link outage and daily power switching off in a branch which could be sent as compound alerts in the event of multiple alerts getting triggered.