Cato adds AI-driven XDR to SASE to reduce network outages
Cato Networks announced the availability of AI-powered tools that aim to more quickly identify outages and conduct root-cause analysis as part of its extended detection and response (XDR) and cloud-based secure access service edge (SASE) solution.
Network Stories for Cato XDR, which is part of the Cato SASE Cloud platform, uses AI algorithms that are trained to analyze network signals and detect threats and security anomalies. The AI-powered tools evaluate the alerts to identify the root cause behind network blackouts, downed links, BGP session disconnects, and SLA-related incidents. Cato AI prioritizes network incidents to help IT teams focus their efforts on the most critical incidents first, reducing the impact of potential security threats. Using generative AI, Network Stories can summarize the analysis of network events and incidents into human-relatable explanations.
“With our converged security and networking platform, we leverage advances in one domain, in this case security, to help another domain – networking,” said Shlomo Kramer, CEO and co-founder of Cato Networks, in a statement. “Our security-trained AI has been expanded to help NOC [Network Operations Center] teams become smarter, faster, and more proactive than ever.”
According to Uptime Institute’s latest outages analysis, network and connectivity issues accounted for 31% of IT outages and 53% of third-party IT provider outages last year. By identifying the true source of incidents, network teams can more quickly fix the problems and mitigate security risks with Cato Network Playbooks, a set of workflows that include step-by-step instructions on how to resolve specific issues. For instance, examples of a Network Playbook include “Socket Link Down” and “BGP Session is Disconnected.”
Internally, Cato Support’s team used Network Stories and found that the process of last-mile packet loss identification “became nearly instantaneous” rather than it taking several days to report an outage, according to Cato. “The average root-cause analysis time dropped by 30% to under 35 minutes.”
Cato SASE Cloud runs on a private global backbone of more than 75 points of presence (PoPs) connected via multiple SLA-backed network providers. The PoPs software continuously monitors the providers for latency, packet loss, and jitter to determine in real-time the best route for every packet. Cato applies optimization and acceleration to all traffic going through the backbone to enhance application performance and the user experience. To ensure all locations benefit, Cato optimizes traffic from all the edges and toward all destinations—on premises and in the cloud.
