In this post we are going to look at how you can spot trends in your performance test results and use this trend analysis to help shape the way you address performance testing. Performance testing can generate a large volume of performance test data and using this data to define your future performance testing coverage, scope and volumes can really add benefit to your non-functional testing process.

Today, we are excited to unveil a suite of innovations that will transform your testing processes and elevate the quality of your software. From harnessing the power of AI for automated regression testing with TrueTest to expanding the capabilities of TestOps and redefining test automation with Katalon Studio 10, these new releases are designed to help you stay ahead in the ever-evolving world of software testing. Let's dive in!

Imagine this: You’ve just rolled out a small update to your application, but suddenly a core feature stops working. Sound familiar? That’s where automated regression testing comes to the rescue. It's like having a diligent, tireless assistant that constantly checks your software for unintended side effects every time you make a change. Let’s dive into how automated regression testing can transform your software development process, saving you time, money, and sleepless nights.

In the landscape of API development, strict adherence to established standards is crucial for sustaining consistency, ensuring reliability, and enabling seamless compatibility across evolving environments. With the release of Katalon Studio 9.7, we are excited to introduce OpenAPI schema compliance validation. This significant enhancement extends our schema compliance testing capabilities to include OpenAPI and Swagger specifications.

Databricks is lighting the way for organizations to thrive in an increasingly AI-driven world. The Databricks Platform is built on lakehouse architecture, empowering organizations to break down existing data silos, store enterprise data in a single centralized repository with unified data governance powered by Unity Catalog, and make the data available to a variety of user groups to support diverse analytics use cases.

Shopping cart abandonment is the silent killer of eCommerce profits. Despite businesses investing heavily in customer acquisition and optimizing user experience, cart abandonments are still a major issue. And for every abandoned cart, potential revenue slips through the cracks. But what exactly causes shoppers to abandon their carts? Is it the unexpected shipping costs, a complicated checkout process, or something else entirely?

Data is increasingly becoming critical for the public sector — from guiding decisions in higher education to enhancing citizen services and streamlining government operations. Government agencies are overwhelmed with data, whether it be structured, like incident logs, or unstructured, like satellite images. Harnessing the vast amount of data can become a burden for any organization, yet the insights have the potential to significantly improve quality of life and strengthen national security.

What are the differences between generative AI vs. large language models? How are these two buzzworthy technologies related? In this article, we’ll explore their connection. To help explain the concept, I asked ChatGPT to give me some analogies comparing generative AI to large language models (LLMs), and as the stand-in for generative AI, ChatGPT tried to take all the personality for itself.

Modernizing legacy systems is often a daunting task, often filled with risks and uncertainties. The Strangler Pattern offers a proven, incremental approach to replace these outdated systems by gradually building new features around them, eventually phasing out the old system. The Strangler Pattern is a software modernization strategy that incrementally replaces parts of a legacy system with new functionality, allowing both systems to coexist until the legacy system is fully phased out.

Today, we are thrilled to announce the public preview of AWS Regions on Koyeb! During last launch week, we introduced the private preview of AWS Regions. We announced our first region, the famous, us-east-1 (N. Virginia) region, and started onboarding our first users. What’s new with this public preview? In addition to the us-east-1 location now being available to everyone on the platform, you can now deploy to this region via the control panel and the CLI!