Systems | Development | Analytics | API | Testing

As modern software delivery processes accelerate, QA teams inevitably feel pressure to maintain quality at scale. SeaLights addresses this challenge by providing deep visibility into test coverage across every stage of the software development lifecycle. It helps teams identify untested code changes, optimize execution, and deliver confidence at release time.

Behind every smooth user experience is a maze of APIs quietly handling requests, responses, and data flows. This makes APIs critical connectors that enable applications to communicate and share data seamlessly. When these vital conduits fail, the consequences can be severe—system outages, data breaches, and frustrated users. API testing is the unsung hero ensuring your digital world runs smoothly and securely.

Artificial intelligence (AI) is widely used today, from voice assistants to Netflix recommendations, but AI models do not always behave as intended. Testing an app before it is released is standard practice, and similarly, AI models should be thoroughly tested. Testing an AI model can verify that the model’s decisions are accurate, fair, and safe.

AI coding tools are everywhere; they have changed the way we used to code. These days, people are doing vibe coding with the help of these tools. From suggesting code snippets to explaining errors in plain English, these assistants are becoming as common as Stack Overflow tabs. There are only two names that keep popping up in everyone’s conversation when it comes to AI coding tools: Cursor and GitHub Copilot. But here’s the real question: Cursor vs.

The test case review process is how we make sure every test case is clear, correct, and ready to run. We treat it as a simple habit that protects quality before execution. When you follow a strong Test Case Review Process, you reduce rework and raise confidence. You also align teams on what matters and how coverage should look. In this guide, we show you how to review test cases effectively with practical steps and examples. We keep it focused, useful, and easy to apply in your next sprint. Let's dive in!

The longer your test cycles run, the slower your product ships. This is one of the core challenges of modern DevOps. Your CI/CD pipeline is fast until it hits the testing stage. That's where parallel testing comes in. Instead of running tests one by one, you can run them side by side. On multiple environments. Across devices. All at once. The result? Faster builds, quicker feedback, and higher deployment confidence.

Ever been confused about OpenAPI and Swagger? You’re definitely not alone. I were on the same line. These two terms get thrown around a lot in the API world, and honestly, it’s pretty easy to mix them up. It was driving me crazy! In this blog, we are going to talk about what is OpenAPI and Swagger Schema, how they are different from each other, their advantages and disadvantages and lots more. Trust me, by the end of this, you’ll be the one helping other people understand this mess.

For many engineering leads and executives, reviewing quality assurance dashboards and automation reports may feel like trying to solve a complex puzzle, one where the pieces keep changing, and the full picture only comes into focus after it’s too late.

Visual regression tests have effectively enhanced the consistency of the UI maintenance by teams. It improves the quality of the user experience, lowers the possibility of UI bugs in production, saves hours of manual quality assurance activities by automatically detecting unintentional visual changes in web applications.

In this day and age of the world wide web, users don’t wait around – neither should your app. Imagine your site going viral overnight, or a flash sale that generates thousands of users overnight. Will your server crash or expand with confidence? Welcome to Spike Testing. In this blog, we’ll explore what spike testing is, why it matters, how to do it right, and how tools like Keploy can help make your tests more stable and meaningful.