Kentik, the network intelligence platform, today launches Cause Analysis, a new AI-powered capability that automatically identifies and explains the cause of network traffic issues and anomalies which result in slow speeds, dropped connections, packet loss, and other service disruptions caused by factors like network congestion and hardware failures. Starting today, when sudden performance degradation, cost spikes, and traffic changes arise, any SRE or platform engineer can investigate traffic changes without needing a deep understanding of the network.
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“Over the past few years, we’ve seen the rise of the SRE and platform engineer within modern enterprises, but network experts are far and few between,” said Avi Freedman, CEO and co-founder of Kentik. “When you need to diagnose a network issue impacting customers, Cause Analysis can pinpoint changes impacting customers in seconds and explain in plain language what it could take even a network expert many query iterations to diagnose and understand.”
Designed with customers to help engineers more quickly understand the underlying network traffic contributing to real network anomalies in real workflows, Cause Analysis goes beyond alert noise reduction by leveraging artificial intelligence to pinpoint the causes of performance degradation and network outages. Behind the scenes, proprietary algorithms are running to quickly identify traffic sources and diagnose issues within complex modern networks. Those findings are then filtered through customers’ chosen LLM to render a natural language explanation of the underlying issue.
“Kentik’s new Cause Analysis feature has greatly enhanced our ability to quickly and clearly understand what’s driving network traffic. Whether we’re troubleshooting specific issues or conducting routine checks, it provides rapid, actionable insights into traffic patterns and sources,” said Chris Wilkison, Principal Network Engineer at Bluepeak. “By integrating it into our daily workflows, we’ve streamlined complex troubleshooting and significantly reduced the time required to maintain network health and performance.”
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