Systems | Development | Analytics | API | Testing

If you’ve been using Rest Assured for API testing, you know how powerful it is. The syntax looks simple and easier to understand, but things get interesting when you have to write test cases and mocks for a microservices application that has more than 2 services. In this blog, I am exactly sharing my pain of writing Rest Assured test cases for a microservices application and why I switched to Keploy not because I am working here, but to show you the real pain points Keploy solves.

Modern technology (APIs, Microservices, Cloud Platforms, Mobile Apps) is rapidly changing and becoming a target for attackers as they continue to advance and become more sophisticated. Organizations use penetration testing (a form of ethical hacking) to identify weaknesses in their systems and address them before they can be taken advantage of.

It’s easy to create APIs very quickly. However, creating APIs that are reliable when used in challenging distributed systems is much harder. Many development teams are moving quickly to ship features to the market, which has led to the verification vs validation distinction becoming the middle ground between a successful launch and an incident that could occur from a production system.

Today’s software ecosystem consists of various devices, integrations, and user environments. The same application can have different behaviours in each environment, regardless if it had passed through unit, integration and system testing stages. Therefore, beta-testing is necessary. Beta testing is the bridge between an internal QA team and a company publicly launching its application.

Every digital experience we rely on – from booking cabs to transferring money — runs on dynamic, interconnected software systems. The speed at which applications are evolving is much faster than the traditional test approach can keep up with. Manual scripting breaks whenever there is a change to the user interface; automation will require regular maintenance to fix the automated scripts; and teams are continually losing confidence in the release stability.

Modern software development moves fast. Delivering bug free code is no longer just a goal. It is a requirement. But how do you ensure your code works before you even finish writing it? The answer is TDD, or Test Driven Development. In this guide, we will answer what is TDD, explore how it transforms the development lifecycle, and share practical examples you can apply immediately.

Extensibility is conceptually found in the areas of technology (such as Software Development) and System Design. The term extensibility may seem abstract to someone with no previous background in the field; in particular, when you hear phrases like: “Extensible Software”, “Extensible Architecture”, “Extensible API” or “Extensible Testing Tools”, it could be difficult to understand exactly how these would apply in day-to-day experiences.

Modern software development is continuously operating in a high-paced environment with high-pressure expectations to produce quality applications. To meet this expectation, open source automation tools help provide a faster, smoother testing process for today’s applications by providing a single tool to test all layers, including web, mobile, API, and performance.

Have you thought about why some companies can seamlessly scale their technology while others have outages, delays, and an increase in operating costs? As the complexity of digital products and services increases, organizations will continue to experience a challenge—to stay competitive, they cannot rely on legacy manual infrastructure management. Organizations can move from slow provisioning to overcoming configuration errors, then to react quickly to changes in demand.

In the world of software testing, one crucial element often overlooked is Test Data Management (TDM). As development and testing cycles become shorter, automated, and more continuous, the need for efficient management of test data grows. Whether you’re working in Agile, DevOps, or Continuous Integration (CI), having a robust test data management system in place ensures that your tests are reliable, reproducible, and efficient.