Highlight, developers of the Highlight SaaS Cloud-based network observability platform, has further deployed its Highlight Labs innovation team to harness AI-based machine learning algorithm to predict network traffic loads and trends.
The Highlight Service Observability Platform can now identify when a network is likely to reach capacity in the future by analysing historical traffic data on network circuits such as Broadband and Wi-Fi connections. It enables service providers and network managers to anticipate potential issues and take greater control of their IT infrastructure across multiple locations and diverse technologies.
This launch follows the introduction of a new AI-based anomaly detection service on the platform. This feature detects unusual or anomalous step changes in network traffic and performance, distinct from regular growth and traffic fluctuations. Abrupt shifts can be difficult to spot without constant monitoring, but with AI-driven anomaly detection, such changes are quickly identified and help network teams to maintain network stability.
Martin Saunders, COO at Highlight says: “By anticipating future bandwidth shortages and identifying anomalous disruptions, we can help our partners and customers to predict and avoid potential network issues and unaccounted-for upgrades outside of budget. The two new powerful AI-based capabilities enable our customers to further streamline the management of their essential, high-value communications.”
The Highlight Service Observability Platform provides a unified, first-pane-of-glass view of different technologies from different vendors. By standardising network data, Highlight enhances support efficiency, enables in-depth analysis of network estates, and improves coordination with service providers and external vendors.
Unlike traditional monitoring solutions, which are often complex and costly, Highlight is designed for rapid deployment and ease of use. The platform is fully operational in minutes, making it an ideal self-service observability add-on for businesses of any size, from global to smaller enterprises.
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