Kubernetes has become the de facto standard for cloud-based applications. As companies migrate more and more workloads, ensuring reliable connectivity and performance are critical not just for user applications but also for the cluster itself. In this article, we will discuss how augmenting your system monitoring with in-cluster synthetic testing can give you proactive indicators that something might be headed for trouble.

In the first post of this series, I detailed ways companies considering cloud adoption can achieve quick wins in performance and cost savings. While these benefits of the cloud certainly remain true in theory, realizing these benefits in practice can be increasingly difficult as applications and their networks become more complex.

We’re excited to announce our beta launch of Kentik Kube, an industry-first solution that reveals how K8s traffic routes through an organization’s data center, cloud, and the internet. With this launch, Kentik can observe the entire network — on prem, in the cloud, on physical hardware or virtual machines, and anywhere in between.

We often think of DDoS attacks as volumetric malicious traffic targeted against organizations that effectively take a service offline. Most frequently detected by anomalous behavior found in NetFlow, sFlow, IPFIX, and BGP data, what may not be well understood is how the DDoS mitigation works and how it’s possible to visualize the effectiveness of the mitigation during and after an attack.

Recently, I saw some discussion online about how flow data, like NetFlow and sFlow, doesn’t provide enough network visibility compared to doing full packet captures. The idea was that unless you’re doing full packet captures, you’re not doing visibility right. Because I’ve used packet captures so many times in my career, I admit there’s a part of me that wants to agree with this.