Systems | Development | Analytics | API | Testing

The video approval and feedback cycle can often feel cumbersome. You shoot a video, send it for review, and then find feedback all over the place that you can't comprehend without help. This is where video annotation tool come into play. These specialized tools are designed to streamline the video feedback process. Yet, simply having a tool isn't enough. The real magic lies in how fast and efficient these platforms make your workflow.

One of the biggest challenges in software testing is not having the right visibility. Too little knowledge, and you’re guessing. Too much, and you get bogged down in code.

Observability has become critical to ensuring the effective monitoring of application and system performance and health. It focuses on understanding a system’s internal state by analyzing the data it produces in the context of real-time events and actions across the infrastructure. Unlike traditional monitoring, which mainly notifies you when issues arise, observability offers the tools and insights needed to determine not only that a problem exists but also its root cause.

One of the fastest-growing trends in the datasphere today is the development and use of data products. As we move deeper into 2025 and beyond, data product usage is going to explode. In fact, according to the Gartner 2024 Hype Cycle for Data Management, Data Products are currently at the Peak of Inflated Expectations, signaling strong interest and rapid evolution in this space. You can download the entire report here. The advantages and impact of this new paradigm extend beyond data engineers.

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.

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.

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.

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.

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.

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.