Systems | Development | Analytics | API | Testing

Speedscale vs. LocalStack for Realistic Mocks

API mocking plays a crucial role in modern software development allowing developers to simulate external API endpoints. It’s an effective way to isolate your application for testing and ensure that code changes don’t inadvertently break critical dependencies. Essentially, API mocking helps you create robust, reliable software by allowing you to test how your application interacts with external services.

Sauce AI for Insights - Product Demo

See Sauce AI for Insights in action and discover how you can eliminate hours of manual work, accelerate release cycles, and ship with confidence. This on-demand demo walks you through our suite of purpose-built AI Agents that transform complex test data and workflows into instant, actionable intelligence. In this video, you will see how Sauce AI.

The Infrastructure Behind Strapi Cloud: Serverless, High-Performance, Built on Koyeb

Strapi Cloud delivers fully-managed, cloud-hosted instances of Strapi in minutes. With thousands of projects deploying every day, the team needed high-performance infrastructure to provide a seamless, production-ready experience. Strapi wanted to focus on innovation and improving Strapi, not managing infrastructure. In just weeks, Strapi Cloud moved to Koyeb, gaining a serverless, multi-tenant cloud offering with zero operational overhead.

Continuous Integration Explained: How CI Streamlines Development

Software development is complex, but your workflow doesn't have to be. As teams grow and projects scale, it's important to manage the frequent integration of code changes from multiple developers into a shared source code repository. Modern DevOps practices, including Continuous Integration, become essential for maintaining speed without sacrificing quality. In this blog, we explain what is continuous integration (CI), how continuous integration works, and how to successfully implement it.

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.

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.

Panel Discussion - AI in Automation: Accelerating Scripts and Execution | Testflix 2025

AI in automation is rapidly emerging as a powerful enabler for testers. From automation script generation utilities to simplifying API testing and framework development, these capabilities promise to accelerate productivity. But as testers embrace assistants like Copilot and Cursor, big questions emerge - What does this mean to the future of open-source frameworks like Selenium and Playwright? How should testers balance the speed of AI-generated code with the need for reliability and maintainability? ⁠How do we measure productivity gains from AI-paired programming? And AI doesn't stop at coding.

Faster Testing: How Modern Teams Ship High-Quality Software Quickly

Software teams today are challenged to provide high quality releases at a much faster pace than ever before. As software development cycles become shorter, user expectations continue to increase and products become more complicated, testing becomes a bottleneck in the overall delivery process. Rather than reducing testing, the goal is to evolve testing to be faster, smarter, more automated and more dependable.

8 AI Testing Tools Used for Test Generation, Analysis, and Maintenance

I still remember when our CI/CD pipeline crashed at 3 AM because one tiny UI element moved two pixels and every automated test failed. That single night proved how fragile traditional testing and script-based automation really are. AI-powered testing tools changed everything for our team almost overnight. They brought AI test automation, self-healing tests, and intelligent test generation that actually adapted instead of breaking.