The shift-right testing approach moves testing to later in your production cycle. Also known as “testing in production,” with shift-right, you test software after it has been deployed. It gives you continuous feedback based on real-world user interactions. However, there are major drawbacks to the approach. For example, testing in production risks disrupting your user satisfaction and can mean you catch issues too late to respond to them effectively.

Before diving into template selection, it's crucial to grasp the essence of a test plan. It's a blueprint outlining the testing strategy, objectives, scope, resources, and schedule for a software project. A well-crafted test plan ensures efficient testing, reduces defects, and improves product quality.

The inclusion of a stable test runner in Node.js(version 18+) has generated significant debate in the community, given the abundance of established third-party testing frameworks. While its arrival naturally sparks comparisons to existing tools, this article won't focus on justifying its place in the ecosystem. Instead, we'll embark on a hands-on exploration of the test runner's core capabilities, from writing and executing tests to organization and customization features.

Test data management (TDM) is a time and resource-intensive process for numerous big corporations. To illustrate, at one American insurance company, test data collection accounted for 16% of all testing activities, translating into $3 million spent on TDM for a project costing $20 million. By introducing sophisticated TDM processes, the company managed to cut testing expenses by $450,000.

We’re happy to announce that Data Apps, which have been in Public beta since September 2023, are finally here for everyone. We received great feedback from the Beta users, and we are excited to roll out Data Apps to general availability. There is also few updates, see "What's new" below. Data Apps is a functionality that allows Keboola users to create interactive web applications that can be infused with your company’s data. It’s quick and easy and only requires knowledge of Python.

In the rapidly evolving landscape of software development, efficient test data management (TDM) is crucial for ensuring high-quality applications. With the right Test Data Management tools, development teams can streamline their testing processes, reduce errors, and accelerate delivery cycles. In this blog, we will explore the 7 best test data management tools in 2024, focusing on their advantages, disadvantages, and pricing.

Technology is booming now more than ever, and every day brings new products and functionality for every unimaginable task. It is not just about mobile apps and computers anymore; instead, it is all about embedded systems and Internet-of-Things (IoT) devices that have quickly become so commonplace, both in our day-to-day lives and in industries like industrial automation.

A potential recipe for disaster proved to be the focus of every data executive’s agenda over the last year. A year ago many data leaders were caught off-guard. Employees embraced new gen AI tools with fervor, driving interest in all AI initiatives. Generative AI had penetrated the enterprise, with gen AI positioned in the Peak Of Inflated Expectation segment on the Gartner Hype Cycle for Artificial IntelligenceI, 20231.