Live testing is to test software in real-world situations with real users instead of simulated data. This approach allows testers to check software quality in actual usage scenarios and real-world conditions. They do have their own risks to take into consideration, since we are interacting with real users and live systems here. In this article, we will explore the concept of live testing in-depth, and how you can better do live testing with the right tools and approach.

Customer experiences matter. And many businesses struggle to improve them. More often than not, a bad process is to blame: manual tasks, data spread across too many systems, or even just old ad hoc workflows that linger on because that’s how it’s always been done. But the cost of ignoring these issues is high.

I’m brand new to writing KIPs (Kafka Improvement Proposals). I’ve written two so far, and my hands sweat every time I hit send on an email with ‘ KIP’ in the title. But I’ve also learned a lot from the process: about Apache Kafka internals, the process of writing KIPs, the Kafka community, and the most important motivation for developing software: our end users. What did I actually write? Let’s review KIP-941 and KIP-1020.

In our previous blog, we explored how to build a modern web server using BunJs and Prisma, integrating robust authentication mechanisms with JWT tokens. Now, it’s time to ensure our application is reliable and error-free through thorough testing. In this blog, we’ll dive into testing methodologies using Cucumber JS and Keploy, both are a powerful tools that streamline the testing process and enhance the quality of our application.

To effectively guide the evolution of a software system and ensure its long-term stability and maintainability, it’s crucial to understand the phenomena of architectural drift and erosion.

While designers and SEO experts are united in their focus on addressing user experience and user intent when designing a website, there are some areas where they don’t always see eye to eye. These include labeling for users vs. labeling for search engines and consolidation of content vs. expansion of content. Is there a way to address the needs of both sides while creating the best possible user outcome? Absolutely.

The regulatory and business demands of financial services require teams to collaborate with consistency and accuracy—a difficult task when it comes to enterprise risk management (ERM). Business units often complete their risk management strategic objectives independently, and since each may have its own taxonomies and processes, human errors may go unnoticed, increasing potential risk.

On April 24, we released Snowflake Arctic with a key goal in mind: to be truly open. In line with that goal, the Snowflake AI Research team is writing a series of cookbooks to describe how to pretrain, fine-tune, evaluate, and serve large-scale mixture-of-experts (MoEs) such as Arctic.

This guide provides a streamlined approach to the API development process, detailing the essential phases from the initial concept to the realization of a fully operational API. You’ll discover how to plan, design, and implement your own API and ensure it’s reliable and secure. With practical insights and actionable advice, you’ll learn the nuances of API development, from understanding the needs of your users to creating a scalable infrastructure that can handle growth.

3. Elevate risk governance to the next level. NatWest is the UK's leading business bank and second-largest retail mortgage provider. Lengthy change implementation processes hindered risk governance at the bank. Initiating change projects or launching products and applications meant navigating layers of policy checks and approvals, which could take up to 73 days.