Prepare for software releases ahead of Black Friday, Cyber Monday, and beyond.

For years, the traditional approach to automating tests relied heavily on scripted automation frameworks like Selenium, JUnit, and TestNG. While these tools are powerful and adaptable, they require a significant level of technical expertise. Testers need to write, debug, and maintain complex scripts, often leading to bottlenecks in the development process. Relying only on coded solutions limits test automation to a small portion of the team that has deep coding skills.

While many API tools are available on the market—such as enterprise service buses (ESBs) like Apigee and MuleSoft, or low-code solutions like Hasura and CData—few offer the level of flexibility that DreamFactory does. A recent project underscored just how dynamic this lightweight, enterprise-ready API generation tool can be. In this article, we'll dive into this unique project and explore how DreamFactory proved to be much more than just an API generator.

We are excited to announce that the Ably Chat SDK for JavaScript now includes support for custom contexts and hooks for React and React Native applications allowing developers working with these platforms to integrate chat features in an efficient and idiomatic way. Ably Chat is designed to meet a wide range of chat use cases, such as livestreams, in-game communication, customer support, or social interactions in SaaS products.

Learn how you could save up to 30% on your data management costs with Fivetran.

Future-proofing your analytics tech stack is essential for ensuring the longevity and success of your software applications. As the final stage of the data journey, analytics transforms raw data into actionable insights that directly impact business decisions and customer satisfaction. To effectively fulfill this role, analytics systems must possess a high degree of flexibility and scalability, seamlessly integrating with diverse applications and data sources.

It’s a new world—again. Data today isn’t what it was five or ten years ago, because data volume is doubling every two years. So, how could ETL still be the same? In the early ‘90s, we started storing data in warehouses, and ETL was born out of a need to extract data from these warehouses, transform it as needed, and load it to the destination. This worked well enough for a time, and traditional ETL was able to cater to enterprise data needs efficiently.

“May Katalon be with you whenever you run your tests.” So you’ve heard of Katalon and decided to give it a try. We’re here to help you get the best experience possible out of it. In a way, Katalon serves as your entire software testing life cycle unified in one workspace. You get to do test planning, scripting (from no-code, low-code, to full-code mode), test management, test execution, and finally test reporting.