Systems | Development | Analytics | API | Testing

E2E Testing is a method to test a software from the consumer’s perspective. It involves simulating real scenarios, including user interfaces, backend testing. The purpose of E2E testing is to validate the application’s overall behavior, including its functionality, reliability, performance, and security. E2E Testing helps in identifying issues when one or more components interact with each other. It is usually done after integration testing, which tests individual component.

In today’s high-speed world of software delivery, performance engineering can’t afford to be a bottleneck. Teams are shifting left, moving fast, and integrating feedback loops earlier and more often, but performance feedback still too often lags. If your performance testing still hinges on last-mile validations or project-based assessments, you’re not alone. Many teams are struggling with how to evolve their practices from siloed testing to scalable, integrated performance engineering.

We’re excited to announce Ably LiveObjects, launched with a radical vision: to enable any application to work with live, shared data that synchronizes instantly for users everywhere. Shared access to live data is no longer a nice-to-have - it’s becoming a foundational building block of every realtime digital experience.

Agentic AI has the potential to revolutionize workplace processes in nearly every sector by improving business decision-making, workflow efficiency and customer interactions and experiences. While interest in agentic AI is widespread, the motivation to use it differs by industry. Cloudera surveyed 1,484 enterprise IT leaders across 14 countries to better understand their approach to agentic AI in 2025, including how specific industries plan to implement the technology.

The need for impeccable mobile applications is unequivocal. Users want intuitive interfaces, smooth functionality, and uniform performance across various devices and operating systems. Development teams have a considerable difficulty in satisfying these requirements while expediting release cycles. Conventional mobile app testing services, although fundamental, often fail to keep pace with the velocity and complexity of contemporary application development.

Smarter AI starts long before the model is trained. It begins with the quality of the data you feed it. Data that reflects real-world nuance, cultural context, and human behavior is what sets strong systems apart.

When it comes to error monitoring in mobile apps, iOS and Android take distinct approaches due to their unique architectures and tools. Here’s a quick breakdown of the key differences.

Tracking API performance is essential to ensure smooth operations, enhance user experience, and prevent costly downtime. Here’s how to do it effectively.

In today’s rapidly evolving tech world, coding isn’t just about writing lines of code — it’s about crafting them smarter, faster, and with greater precision. This is where AI coding assistants come in: intelligent tools designed to streamline development workflows, catch errors early, suggest enhancements, and even generate complete blocks of code, empowering developers to work more efficiently than ever before.

Automation testing is designed to make your life easier by speeding up your releases, catching bugs before your users do, and providing you with some much-needed peace of mind. So why is it that so many teams pour time and energy into UI automation and still end up with slow, flaky runs and missed bugs in production? It might surprise you to know that most of these problems come down to a few common mistakes that are easily avoidable once you know what to look for.