Systems | Development | Analytics | API | Testing

With an increasingly competitive market, ensuring software quality is essential for your business’s success. QA governance and strategy are crucial to ensure that processes are efficient, consistent, and aligned with business objectives. Managing these factors can be challenging, especially when teams deal with multiple tools, a lack of visibility about test progress, and maintaining compliance.

This article originally appeared on SD Times on May 30, 2025. We’re sharing it here for our audience who may have missed it. The headlines are seductive: AI will replace developers. Coding is dead. Ship 10x faster with half the team. It’s the kind of hype that grabs attention and fuels confusion.

Due to artificial intelligence and Large Language Models, having streamlined data communication, easy access and easy discovery is now more important than ever. Many people are unaware of it, but the llms.txt file is very important and key to what happens in the machine learning and web sectors. With this plain text file, websites and platforms can interact with LLMs, giving metadata that can impact the way AI indexes, interprets and generates their content.

Ever deployed code only to watch everything crash? We’ve all experienced that sinking feeling ,which is exactly why testing matters so much. While most developers understand that testing is vital, two important approaches : unit testing and regression testing are frequently confused, despite serving completely different functions. In this blog, we’ll clear up the confusion, examine their core methodologies, and how tools like Keploy can automate and enhance your testing processes.

In the field of software quality assurance, there are two types of testing often referenced, smoke testing and regression testing. While they are both vital to software quality, each has its own unique functions and overlaps in the software development cycle. This post explores the differences between smoke testing vs regression testing, and when and how to effectively implement each.

In 2025, QA teams are experiencing real change. Product delivery cycles are becoming shorter, Agile is maturing, and there’s increasing pressure to launch new software quicker and without flaws. There’s also evident talk surrounding AI as the biggest factor for change, and its impact is also increasing. But the truth is AI is just one factor in this story. Other trends - like continuous automation, DevOps integration, and the role of QA - are redefining the way we test and ensure quality.

Performance and stress testing are two popular testing methodologies. They focus on determining how an application behaves under regular and unexpectedly high traffic, respectively. These tests are essential for assessing a system's robustness and scalability, particularly in applications with fluctuating traffic like Node.js backends. In this article, you'll learn about stress and performance testing, why they're important, the best tools available, and how to use them in Node. Let's dive in!

At the top of many IT folks’ minds lies the looming 2027 deadline for SAP’s end-of-life for SAP ECC – and the subsequent migration to S/4HANA. Often a complex and lengthy migration process, the shift to S/4 requires careful planning and resource allocation.

Outsourcing quality assurance (QA) to a high-quality software testing service can be a good way to perform more testing at a low cost while freeing developers from test creation and maintenance. However, through surveys and interviews with numerous engineering leaders, we found that not all software testing services can deliver on these benefits. Many are notoriously slow and struggle to catch obvious bugs in critical user paths.