Posts by Phil Gervasi

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.

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.

Most of the applications we use today are delivered over the internet. That means there’s valuable application telemetry embedded right in the network itself. To solve today’s application performance problems, we need to take a network-centric approach that recognizes there’s much more to application performance monitoring than reviewing code and server logs.

We’re fresh off KubeCon NA, where we showcased our new Kubernetes observability product, Kentik Kube, to the hordes of cloud native architecture enthusiasts. Learn about how deep visibility into container networking across clusters and clouds is the future of k8s networking.

At first glance, a DDoS attack may seem less sophisticated than other types of network attacks, but its effects can be devastating. Visibility into the attack and mitigation is therefore critical for any organization with a public internet presence.

A packet capture is a great option for troubleshooting network issues and performing digital forensics, but is it a good option for always-on visibility considering flow data gives us the vast majority of the information we need for normal network operations?

There is a critical difference between having more data and more answers. Read our recap of Networking Field Day 29 and learn how network observability provides the insight necessary to support your app over the network.

At Networking Field Day: Service Provider 2, Steve Meuse showed how Kentik’s OTT analysis tool can help a service provider better understand the services running on their network. Doug Madory introduced Kentik Market Intelligence, a SaaS-based business intelligence tool, and Nina Bargisen discussed optimizing peering relationships.

Investigating a user’s digital experience used to start with a help desk ticket, but with Kentik’s Synthetic Transaction Monitoring, you can proactively simulate and monitor a user’s interaction with any web application.

The theme of augmenting the network engineer with diverse data and machine learning really took the main stage at the World of Solutions. Read Phil Gervasi’s recap.

By peeling back layers of your users’ interactions, you can investigate what’s going on in every aspect of their digital experience — from the network layer all the way to application.

When something goes wrong with a service, engineers need much more than legacy network visibility to get a complete picture of the problem. Here’s how synthetic monitoring helps.

In the old days, we used a combination of several data types, help desk tickets, and spreadsheets to figure out what was going on with our network. Today, that’s just not good enough. The next evolution of network visibility goes beyond collecting data and presenting it on pretty graphs. Network observability augments the engineer and finds meaning in the huge amount of data we collect today to solve problems faster and ensure service delivery.