You know about different types of testing that follow a hierarchy: unit testing, integration testing, regression testing, acceptance testing, and more. But do you know all these testing types can be executed using different approaches? For instance, a popular approach to Unit testing is TDD (test-driven development). TDD involves creating the unit test code before building the application. Similarly, Incremental testing is a common and most used approach for Integration testing.

In the first three articles in this four-post series, my colleague Jason English and I explored DataOps observability, the connection between DevOps and DataOps, and data-centric FinOps best practices. In this concluding article in the series, I’ll explore DataOps resiliency – not simply how to prevent data-related problems, but also how to recover from them quickly, ideally without impacting the business and its customers.

The GPT euphoria got doused with some reality recently as Samsung employees realized they were sending false information to customers and Italy outright banned ChatGPT. The hype and concerns further accelerated last week with the godfather of AI, Hinton, resigning from Google, President Biden summoning AI leaders to Washington, and several stocks nose-diving on the threats generative AI poses to their business models.

Developer productivity is a complex subject for which there is no magic bullet. However, economic pressure, increased market competition and shorter delivery circles force many organisations to improve their efficiency and to open up new models of operations. Measuring, maintaining and eventually improving engineering productivity in an increasingly hybrid workplace are important discussions many organisations are having right now.

As firms embrace digital transformation, it is crucial to build continuous delivery methodologies that allow for the speedy deployment of software applications. An organization that uses continuous delivery fosters quicker innovation and expedites the delivery of products and services to customers. Building standardized tooling and pipes for a bi-modal operating model is one of the best practices in a continuous delivery company.

Change data capture (CDC) allows you to move your data in real time. Learn what matters when choosing a solution for your organization.

Software testing is an essential part of software development, and test data management (TDM) plays a crucial role in ensuring the quality of a software product. As testing becomes more complex and data-intensive, managing test data effectively is becoming increasingly challenging. In this article, we will explore the importance of test data management and how it can be streamlined with the help of Katalon.

The rapid growth in software delivery as a solution for all business needs for organizations has intensified the demand for efficient and comprehensive software testing processes. Ensuring the quality, reliability, and security of software products is of paramount importance as they become increasingly integrated into various aspects of our lives.

Katalon and OctoPerf play a critical role in the continuous performance testing process, where OctoPerf helps to build the performance activity, and Katalon triggers the build activity and pushes performance reports into the Katalon platform. By integrating Katalon into OctoPerf, you can ensure that you have comprehensive end-to-end test coverage in a fully automated way. The integration between these two solutions will help you automate the build, test, and deployment of your applications.

This years I/O can be easily summed up by just one phrase: “AI”. AI absolutely everywhere. Sundar Pichai started, mentioned numerous times and ended the Keynote by mentioning AI. Some of the main announcements around AI for developers included the general availablity of “Bard” supporting 20 programming languages and use of the “PaLM 2” based models with some like “Gecko” small enough to run on mobile devices.