Operations | Monitoring | ITSM | DevOps | Cloud

Everett Sinclair, Network Administrator at Conway Corporation, explains why Kentik became their “one pane of glass” for cloud-based network visibility, rapid troubleshooting, and smarter peering and caching decisions. With Kentik’s SaaS network intelligence platform, Conway gets updates automatically, avoids server rebuilds, and can deploy cloud agents remotely to run simple metric tests close to customer locations.

AI is changing network operations (NetOps) from static automation into adaptive, data-driven systems that can summarize incidents, retrieve knowledge, and guide remediation with human oversight. In this talk, Phil Gervasi breaks down what “AI for NetOps” really means in practice, including the difference between classical ML and large language models (LLMs), why data pipelines matter more than model tuning, and how patterns like RAG (retrieval augmented generation), text-to-SQL, and agentic workflows turn raw telemetry into decisions.

Five customers explain why Kentik is essential for understanding traffic, controlling network cost, and planning for growth. Hear from Sorin Esanu (Race Communications), Michael Leclaire (MetroNet), John Lubeck (Midco), Wallace Lee (Imperva), and Everett Sinclair (Conway Corporation) on how they use Kentik to see “the bits on the wire,” dig deeper than traditional reporting tools, and turn network data into better customer experiences.

Three service provider customers share how Kentik AI Advisor helps them move faster, troubleshoot smarter, and put network data in more hands across the team. Hear from Everett Sinclair (Conway Corporation), Michael Leclaire (MetroNet), and John Lubeck (Midco) on why they chose Kentik to unify flow analytics, baselining, and anomaly detection in one platform, and how Kentik AI features make it easier to explore, explain, and act on what’s happening in their networks.

"When we started, maybe ten percent of our traffic went to a CDN. Now it's ninety percent on the CDNs or local caches and ten percent goes to transit. We've really flipped the whole script." — John Lubeck, Midco.

A BGP session goes down because a transit provider exceeded the maximum prefix limit. How do you find the root cause — fast? In this 10-minute demo, we walk through two approaches using Kentik AI Advisor. First, we troubleshoot step by step using natural language: asking AI Advisor to identify the affected interface, check for interface flapping, and review syslog messages until we find the maximum-prefix violation. Then we show how custom network context and natural language runbooks let AI Advisor do the entire investigation autonomously — following the same four steps a senior engineer would.

In this demo, we use Kentik AI Advisor to troubleshoot a real-world BGP misconfiguration that brings down a peering session with a transit provider. You’ll see how AI Advisor works both as a dedicated page and as an in-portal overlay, using natural language to identify the affected interface, correlate SNMP and syslog data, and pinpoint a maximum-prefix issue as the root cause. Then we accelerate and standardize the workflow with custom network context and AI-powered runbooks, so every engineer can troubleshoot BGP alerts like an expert.

Happy Holidays from your friends at Kentik! We hope you enjoy our traditional, heartwarming tale of a data packet struggling to reach its destination.

Learn how artificial intelligence is transforming network operations through Kentik's AI Advisor platform. Philip Gervasi and Sean McGinley discuss the evolution from traditional network visibility to network intelligence, emphasizing that AI should augment, rather than replace, network engineers. They demonstrate how Kentik's AI Advisor uses natural language interfaces to perform automated root cause analysis, troubleshooting, and cost optimization.

Introducing Kentik AI Advisor. AI with a comprehensive understanding of your network that thinks critically and advises how to design, operate, and protect infrastructure at scale. With the rise of hybrid cloud networks and the growing demands of AI infrastructure, network teams are under pressure to balance cost, performance, and security, often with limited resources that delay critical strategic initiatives.