Systems | Development | Analytics | API | Testing

Running Kafka in Kubernetes: What We Learned

Apache Kafka is mission-critical for many organizations—but where you deploy it matters just as much as how you use it. In this video, two OpenLogic experts discuss why they increasingly encourage customers to move their Kafka clusters to Kubernetes and utilize the Strimzi operator, and what that shift unlocks from an operational, scalability, and resilience standpoint.

Is Kubernetes actually HARD? #speedscale #kubernetes #k8s #devops #cloudnative

Thinking about learning Kubernetes in 2026? You’ll need GitOps, kubectl, and CI/CD pipelines... OR you can just use Speedscale. See how a single operator replaces a million dependencies and gives you the traffic insights you actually need to survive production.

Kubernetes is Hard. Here is the "Easy Mode" for 2026

Is Kubernetes actually hard, or are we just using the wrong tools? In 2026, the Kubernetes ecosystem has become a "dependency jungle." Between GitOps, YAML configuration, kubectl mastery, and complex CI/CD pipelines, developers are spending more time managing infrastructure than writing code. In this video, Ken breaks down the "hard parts" of K8s and introduces a more efficient workflow using Speedscale. Learn how to gain instant visibility into your cluster, pull logs without the headache, and turn real-world traffic into actionable load tests.

Kubernetes Load Testing Made Easy with Speedscale

Everybody knows working with Kubernetes is really hard. It’s highly complicated. You have to know how to work with YAMLs, there’s lots of stuff to deal with. The classic developer experience with YAML. But what if you could get complete visibility into your Kubernetes workloads and run realistic load tests without touching a single YAML file or running kubectl commands?

Best 5 Container Image Security Platforms for 2026

By 2026, container image security will no longer be evaluated in isolation. For most organizations, the image layer has become one of the primary sources of security debt, quietly accumulating vulnerabilities that multiply across services, clusters, and environments. What has changed is not just the volume of vulnerabilities, but the cost of managing them. Faster release cycles, shorter maintenance windows, and tighter compliance expectations have pushed teams to reconsider whether traditional scanning-and-patching workflows are sustainable at scale.

Run Slurm Workloads Inside Kubernetes With ClearML

By Erez Schnaider, Technical Product Marketing Manager, ClearML Slurm has powered HPC environments for years. It is battle tested, widely adopted, and deeply embedded in research and engineering workflows. Over 60% of the TOP500 supercomputers use it to manage their large infrastructure, orchestrate workloads and schedule jobs, as it is powerful and versatile with over 20 years of engineering behind it.

Kamal 2: Deploying multiple apps

Deploying more than one web application on a single server used to require a lot of infrastructure fiddling. Docker made this better, but some things that are new in Kamal 2 make deploying containerized applications even easier. Kamal is a deployment tool from Basecamp that leans on Docker and its own integrated proxy to simplify deploying web apps. Kamal 2 makes deploying more than one Rails app to the same server easier.

Building a First-Class Kubernetes Experience in Kong Konnect

This is the second post in a series about reasons to attend API Summit 2025. Check out the previous post here. To unlock Kubernetes’ full potential, many enterprises are relying on three key building blocks available in Kong Konnect today: Together, these components extend Kubernetes from being just a container orchestration platform. They lay the foundation for Kubernetes to support the exposure, governance, and operation of APIs — and the AI workflows that increasingly rely on those APIs.

Mastering Kubernetes Testing with Traffic Replay

Kubernetes has become the backbone of many modern application deployment pipelines, and for good reason as a container orchestration platform, Kubernetes automates the scaling, deployment, and management of workloads, allowing developers to make their applications easier to manage and deploy at scale without worrying about their service’s dependencies, their user’s operating system, or the intricacies of their data center or infrastructure provider.