Kentik launched Kentik AI to give any engineer, operator, architect, or developer the ability to troubleshoot complex networks quickly and easily.
The company is simultaneously launching a modern and AI-assisted Network Monitoring System (Kentik NMS) to enable teams to observe, manage, and optimize network health and performance via real-time monitoring and alerting.
"Historically, resolving complex network issues required network engineers to have years, if not decades, of experience," said Avi Freedman, CEO and Co-Founder of Kentik. "Now anyone — a developer, SRE, or business analyst — can ask questions about their network in their preferred language and get the answers they need."
Kentik has embedded Generative AI across its platform to democratize access to critical knowledge about complex systems. Through a natural language interface and guided troubleshooting workflows, Kentik now empowers teams to determine the root cause of customer-impacting issues much faster.
“We’re imagining a world where everybody can be a superstar network engineer. Where network insights are no longer limited to network experts. Where AI augments the engineer, dramatically increasing their productivity, speed of troubleshooting and remediation of issues, and as a result driving efficiencies that can’t reasonably be achieved by scaling manual resources,” said Christoph Pfister, Chief Product Officer at Kentik.
Kentik AI and platform innovations:
- Kentik Query Assistant: Kentik Query Assistant leverages a Large Language Model (LLM) infused with network context that enables users to ask questions about their network in natural language, and Kentik will use its full breadth of data to deliver an answer. This democratizes access to critical network insights that were typically available only to teams with deep network expertise.
- Kentik Journeys: Kentik Journeys provides users with an AI-assisted troubleshooting workflow to solve complex network problems. When troubleshooting, engineers ask a question, analyze the answer, then ask a new, better-informed question, drilling deeper into the issue. Kentik Journeys accelerates this process and expedites investigations with deep understanding of the user’s network.
- Kentik NMS: Kentik NMS is the first AI-assisted network monitoring system. It modernizes network monitoring technology by unifying traffic flow data with real-time, custom, and streaming device metrics in one extensible SaaS platform, allowing engineers to easily correlate heterogenous telemetry from distributed infrastructure and rapidly problem-solve.
The Latest
Monitoring your cloud infrastructure on Microsoft Azure is crucial for maintaining its optimal functioning ... In this blog, we will discuss the key aspects you need to consider when selecting the right Azure monitoring software for your business ...
All eyes are on the value AI can provide to enterprises. Whether it's simplifying the lives of developers, more accurately forecasting business decisions, or empowering teams to do more with less, AI has already become deeply integrated into businesses. However, it's still early to evaluate its impact using traditional methods. Here's how engineering and IT leaders can make educated decisions despite the ambiguity ...
2024 is the year of AI adoption on the mainframe, according to the State of Mainframe Modernization Survey from Kyndryl ...
When employees encounter tech friction or feel frustrated with the tools they are asked to use, they will find a workaround. In fact, one in two office workers admit to using personal devices to log into work networks, with 32% of them revealing their employers are unaware of this practice, according to Securing the Digital Employee Experience ...
In today's high-stakes race to deliver innovative products without disruptions, the importance of feature management and experimentation has never been more clear. But what strategies are driving success, and which tools are truly moving the needle? ...
The demand for real-time AI capabilities is pushing data scientists to develop and manage infrastructure that can handle massive volumes of data in motion. This includes streaming data pipelines, edge computing, scalable cloud architecture, and data quality and governance. These new responsibilities require data scientists to expand their skill sets significantly ...
As the digital landscape constantly evolves, it's critical for businesses to stay ahead, especially when it comes to operating systems updates. A recent ControlUp study revealed that 82% of enterprise Windows endpoint devices have yet to migrate to Windows 11. With Microsoft's cutoff date on October 14, 2025, for Windows 10 support fast approaching, the urgency cannot be overstated ...
In Part 1 of this two-part series, I defined multi-CDN and explored how and why this approach is used by streaming services, e-commerce platforms, gaming companies and global enterprises for fast and reliable content delivery ... Now, in Part 2 of the series, I'll explore one of the biggest challenges of multi-CDN: observability.
CDNs consist of geographically distributed data centers with servers that cache and serve content close to end users to reduce latency and improve load times. Each data center is strategically placed so that digital signals can rapidly travel from one "point of presence" to the next, getting the digital signal to the viewer as fast as possible ... Multi-CDN refers to the strategy of utilizing multiple CDNs to deliver digital content across the internet ...
