In today’s fast-changing digital world, software testing has become a crucial part of the software development life cycle (SDLC), in which the product’s quality, functionality, and performance are assured. Over the years, there have been various software testers who have made substantial contributions to the trends in the software industry through their expertise, online presence and advocacy for best practices.
An open-source container management engine called Kubernetes is used to automatically launch, scale, and handle containerized apps. The fundamental unit of a Kubernetes program is a pod. Instead of managing containers, Kubernetes controls pods, and pods enclose containers. A number of containers, storage, IP addresses, and settings that control how containers should operate inside the pod can all be found in a pod. You can operate two closely linked containers together with sidecar containers.
You can find the issue by reading the stack trace after a program fails. A stack trace, however, only reveals the status of the application at the time of failure and not before the error was met. Logging packages can help with this. They provide specifics about the behavior of the program before the failure and transmit them to the location you specify, such as a file or a monitoring tool. Node.js has access to a wide variety of logging tools, but not all of them are made equal.
When transferring data, especially in the context of Extract, Transform, and Load (ETL), the choice of protocol matters. Both SFTP and FTP provide solutions, but their intrinsic differences could greatly influence the outcome in terms of security and functionality. Here's everything you need to know about SFTP vs. FTP for ETL.
Exceptions are a commonly used feature in the Ruby programming language. The Ruby standard library defines about 30 different subclasses of exceptions, some of which have their own subclasses. The exception mechanism in Ruby is very powerful but often misused. This article will discuss the use of exceptions and show some examples of how to deal with them.
First published on the BSA site along with DXC Technology Data analytics and generative AI are revolutionizing the approach organizations take to software development, testing, and delivery, enabling standardization and scalability across the board, including test automation and management. Like other sectors, financial institutions struggle to match the rate of transformation necessary to maintain a competitive edge.
Many questions arise whenever adopting exploratory testing (ET), primarily due to misunderstandings about what it means. The fact that exploratory testing is mainly unstructured, especially compared to the traditional scripted testing approach that is highly detailed and restrictive, makes it harder to connect it to the word “plan.” Sometimes, users call it ad hoc. Does all this mean that we can’t prepare ourselves for exploratory testing and establish some level of plan for it?
Artificial intelligence (AI) has taken the world by storm. ChatGPT was the ultimate proof of concept, demonstrating the power of large language models and AI in easy-to-understand terms. So naturally, business leaders are eager to unlock the productivity benefits that come from integrating AI into business operations. But despite their eagerness, organizations still need to do some work to prepare for AI integration.
