Systems | Development | Analytics | API | Testing

Recent leaks have once again brought API and data security concerns into the spotlight. Specifically, the leaks pointed at the following as major areas to consider when thinking through your API and data security strategies: When considering the above, it’s critical to think about best practices across every stage of the API lifecycle, starting with the initial phases of API design and testing.

Kong is ranked number 1 on the G2 Momentum Grids for API Management and API Development for Spring 2025. And users seem to agree with the glowing assessment: Kong is currently the highest-rated tool based on user satisfaction in the categories of API Management and API Development on G2. We think there are plenty of reasons why Kong is king when it comes to API management and API development. But don't just take our word for it.

Quality can no longer be an afterthought and traditional testing approaches often struggle to keep up with modern applications’ complexities. This is where data-driven testing comes in - bringing predictive insights to the forefront of QA. Data-driven testing enables a strategic approach to quality, where every test is backed by insights. As the world moves into a future driven by AI, automation, and continuous testing, embracing data-driven testing became essential.

Have you ever wished you could just ask your CI platform a question instead of digging through logs or scrolling through builds? Well your wish has been granted: Bitrise MCP (Model Context Protocol) Server is here, a new, conversational way to interact with your CI.

API’s have become the backbone of modern digital ecosystems, enabling seamless integration and interaction between diverse systems, applications, and services. Organizations increasingly rely on APIs to deliver robust functionality, enhance user experiences, and drive operational efficiency. Additionally, APIs are playing an even greater role in the future of AI-driven systems.

Using AppSignal, you can monitor the performance of your Redis calls and get insights into how your application uses Redis. The AppSignal Python agent supports instrumenting Redis calls out of the box, so you can start monitoring your usage with just a few lines of code. In this post, we will cover how to instrument Redis in a Python application using AppSignal. We will build a simple URL shortener that stores data in a local Redis instance and uses AppSignal to monitor performance.

February introduced key enhancements to Katalon Studio, Runtime Engine, and TestCloud, boosting test automation efficiency, performance, and user experience. These updates reinforce our commitment to continuous improvement, enabling teams to test faster and more reliably. Here’s what’s new this month.

Are you struggling with slow deployment cycles and unpredictable performance issues? Discover how integrating LoadFocus API with Azure DevOps can revolutionize your testing approach and deliver lightning-fast, reliable applications.

The API landscape is constantly evolving, and developers like us crave tools that streamline data fetching and boost performance. For years, REST reigned supreme, but a challenger has emerged – GraphQL. So, is GraphQL truly a "better version" of REST? Let’s explore this question through code and performance comparisons.

The digital landscape is rapidly transforming, with Gartner projecting cloud-native platforms will dominate over 95% of new workloads in 2025. While this shift unlocks agility and innovation, it also introduces significant complexities. Traditional testing methods struggle to keep pace with the dynamic nature of microservices, containers, and distributed systems inherent in cloud-native applications. This is precisely why specialized cloud native testing isn't just beneficial – it's essential.