Kentik Blog

In the second of our data gravity series, Ted Turner examines how enterprises can address cost, performance, and reliability and help the data in their networks achieve escape velocity.

In the early hours of Wednesday, January 25, Azure, Microsoft’s public cloud, suffered a major outage that disrupted their cloud-based services and popular applications such as Sharepoint, Teams, and Office 365. In this post, we’ll highlight some of what we saw using Kentik’s unique capabilities, including some surprising aftereffects of the outage that continue to this day.

Collecting and enriching network telemetry data with DevOps observability data is key to ensuring organizational success. Read on to learn how to identify the right KPIs, collect vital data, and achieve critical goals.

Does flow sampling reduce the accuracy of our visibility data? In this post, learn why flow sampling provides extremely accurate and reliable results while also reducing the overhead required for network visibility and increase our ability to scale our monitoring footprint.

This week marks a decade since the ALBA-1 submarine cable began carrying traffic between Cuba and the global internet. And last month’s recommendation by the US Department of Justice to deny the request by the ARCOS cable system to connect Cuba shows that, almost a decade later, geopolitics continues to shape the physical internet — especially when it comes to Cuba.

With data sets reaching record scale, it is more important than ever for network operators to understand how data gravity is impacting their bottom line and other critical factors. Learn how network observability is essential for managing data gravity.

Only two days into the new year and we had our first BGP routing leak. It was followed by a couple more in subsequent days. In this blog post, we use some of Kentik’s unique capabilities to take a look at what happened, what the impacts were, and what might prevent these in the future.

In this blog, we discuss how Kubernetes approaches networking, the gaps in networking from Kubernetes, and how Kubernetes service meshes address those gaps.

Machine learning has taken the networking industry by storm, but is it just hype, or is it a valuable tool for engineers trying to solve real world problems? The reality of machine learning is that it’s simply another tool in a network engineer’s toolbox, and like any other tool, we use it when it makes sense, and we don’t use it when it doesn’t.

This past year was another busy one for the internet. This year-end blog post highlights some of the top pieces of analysis that we published in the past 12 months. This analysis employs Kentik’s data, technology, and expertise to inform the industry and the public about issues involving the technical underpinnings of the global internet and how global events can impact connectivity.