Systems | Development | Analytics | API | Testing

Manual testing is still essential, but it’s often disconnected from automation. The new Manual to Automation capability in Katalon bridges that gap. It converts manual test runs into automated scripts instantly, linking them for unified coverage.

DreamFactory and Postman serve fundamentally different roles in the API development lifecycle. DreamFactory is an API generation and backend platform that automatically creates production-ready REST APIs from databases and other data sources, while Postman is an API development environment focused on testing, documentation, and collaboration. Though both platforms involve API management, DreamFactory generates and deploys APIs while Postman helps developers test and consume them.

In today’s data-driven software-as-a-service (SaaS) environments, the need for complete customer insights often requires fetching and sharing data that lives across multiple API endpoints. That’s why many of our customers want to use Confluent’s data streaming and integration capabilities to implement real-time API chaining—a technique that allows them to automatically follow relationships between APIs.

Accessibility and localization often seem like separate disciplines, each with its own set of guidelines and goals.

Digital Transformation has raised the bar for speed, scalability and reliability. Modern applications are expected to run 24/7, deliver seamless experiences and adapt quickly to market shifts. But traditional, manual-heavy QA simply cannot meet these expectations.

Earlier this year at Qlik Connect, we introduced Qlik Open Lakehouse, a fully managed, Apache Iceberg–based platform designed to make it easy and cost-effective for organizations to ingest, optimize, and manage data in open lakehouse architectures. And the first version of Qlik Open Lakehouse is generally available as of Sept 2025.

In the last ten years, software testing has advanced significantly, but today’s applications require more than just using conventional forms of automated software testing or entry-level tools that employ artificial intelligence (AI). The rise of microservice architectures, API calls, and continuous deployment has led to another category of software testing products called "Generative" AI Testing tools.

Picture this: It's 3 AM. You’re on-duty in case there is an outage. A team in the other part of the world merged PR and released a new version of K2K Replicator and it crashed. Consumer group lag is spiking to the universe. You’re paged & woken up, went to your laptop, the team already reverted PR, things are stabilising, but what really happened, you have to investigate now as postmortem has to be done.

One of the most critical ways to validate real user journeys across any application is through end-to-end testing. Modern software stacks have grown so distributed that manual E2E testing grows increasingly hard to maintain and nearly impossible to scale. This is where automation in end-to-end testing helps engineering teams with the reliability, speed, and confidence during every release.