This article demonstrates how to Load Test an application deployed in a Kubernetes cluster, verify that the autoscaling is working, and identify potential performance bottlenecks. When you deploy an application to production on Kubernetes, you'll need to monitor traffic and scale up the application to meet heavy workloads during various times of the day. You'll also need to scale down your application to avoid incurring unnecessary costs.

Kong for Kubernetes is a Kubernetes Ingress Controller and a full-fledged edge-router which can route traffic to any destination of your choice. In addition to Ingress management, it provides enhanced security and management capabilities. With Kong, you can use Kubernetes not just for running your workloads but also for securing and monitoring connectivity between your workloads – all managed via Kubernetes manifests and CI/CD processes.

Kong for Kubernetes is a Kubernetes Ingress Controller based on the Kong Gateway open source project. Kong for K8s is fully Kubernetes-native and provides enhanced API management capabilities. From an architectural perspective, Kong for K8s consists of two parts: A Kubernetes controller, which manages the state of Kong for K8S ingress configuration, and the Kong Gateway, which processes and manages incoming API requests.

Container technology promises to usher in the biggest step change in infrastructure economics since server virtualization. By some estimates, customers are saving as much as 50% on infrastructure costs by switching from hosting cloud native applications in their own data centers to hosting containerized versions of those applications in a private, hybrid or public cloud.

When Jackie Edwards wrote “Keep On Running” back in 1965, he certainly wasn't thinking about the future of computing. But, it's the Spencer Davis Group grooves that is the soundtrack playing in my head when I think about Kubernetes and the business value it brings. Enabling your environment to “Keep On Running” is just one of many of Kubernetes’ value adds.

If you are a developer who uses containers, chances are you and your team have heard about Kubernetes. At its core, Kubernetes is a container operating system for the web, but has grown to be much more. Sure, Kubernetes can manage your containers, network traffic, and bring up a crashed ad, but it has also become a widely adopted platform with a growing community.

k6 v0.26.0 is here! This release contains mostly bug fixes, though it also has several new features and enhancements! They include a new JS compatibility mode option, exporting the end-of-test summary to a JSON report file, speedups to the InfluxDB and JSON outputs, http.batch() improvements, a brand new CSV output, multiple layered HTTP response body decompression, being able to use console in the init context, a new optional column in the summary, and Docker improvements!

We announced the release of Kuma – a modern, universal control plane for service mesh back in September 2019. Since then, a roaring wave of community feedback and contribution has flooded the project. And that’s a good thing, so thank you to everyone who has given their time to helping Kuma grow. One recurring feedback we got was that the community was excited to see a platform-agnostic service mesh.

This article follows our first blog post related to Kraken’s deployment on Kubernetes. It is a step by step guide explaining how to deploy the InfluxDb/Telegraf/Grafana stack used to generate load testing reports on Kraken.

Kraken is a load testing solution currently deployed on Docker. In order to use several injectors (Gatling) while running a load test, its next version might rely on Kubernetes. This blog post belongs to a series that describe how to use Minikube, declarative configuration files and the kubectl command-line tool to deploy Docker micro-services on Kubernetes. It focuses on the installation of an Angular 8 frontend application served by an NGinx Ingress controller.