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Kentik Releases Cause Analysis

Kentik launched 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.

“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 issues.

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Kentik Releases Cause Analysis

Kentik launched 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.

“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 issues.

The Latest

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...

In MEAN TIME TO INSIGHT Episode 15, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Do-It-Yourself Network Automation ... 

Zero-day vulnerabilities — security flaws that are exploited before developers even know they exist — pose one of the greatest risks to modern organizations. Recently, such vulnerabilities have been discovered in well-known VPN systems like Ivanti and Fortinet, highlighting just how outdated these legacy technologies have become in defending against fast-evolving cyber threats ... To protect digital assets and remote workers in today's environment, companies need more than patchwork solutions. They need architecture that is secure by design ...

Traditional observability requires users to leap across different platforms or tools for metrics, logs, or traces and related issues manually, which is very time-consuming, so as to reasonably ascertain the root cause. Observability 2.0 fixes this by unifying all telemetry data, logs, metrics, and traces into a single, context-rich pipeline that flows into one smart platform. But this is far from just having a bunch of additional data; this data is actionable, predictive, and tied to revenue realization ...

64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...