Watch how to use a multimodal LLM such as Gemini to analyze data in a BigQuery data lake and automatically generate schema layouts.

According to an IDC study, Sauce Labs is a leader in quality management and mobile app testing. But what really differentiates us from other mobile and web app testing vendors?

Functional testing is important in the software development process and is employed by around 90% of development teams, according to Huttle Research. It ensures software performs as intended through different methodologies such as white box, black box, and gray box testing. However, choosing the right approach can be complex, involving considerations like project requirements, team expertise, and specific software characteristics.

Cypress and Selenium are two of the most popular website testing tools. Each has advantages, so it can be tough to know which is the best fit for you. That’s why we’ve compared and contrasted the two, so you know which is best for specific use cases. As makers of our own web testing tool, we’re very familiar with what makes one work well. In this article, we’ll give you a complete, unbiased breakdown of Cypress vs Selenium.

One of the worst-kept secrets among data scientists and AI engineers is that no one starts a new project from scratch. In the age of information there are thousands of examples available when starting a new project. As a result, data scientists will often begin a project by developing an understanding of the data and the problem space and will then go out and find an example that is closest to what they are trying to accomplish.

The adoption of eBPF (Extended Berkeley Packet Filter) has revolutionized high-performance applications, tracing, security, and packet filtering within the Linux kernel. Specifically, TC-BPF, a type of eBPF program attached to the Traffic Control (TC) layer, has emerged as a powerful tool for packet manipulation in both ingress and egress. This blog delves into the practical application of TC-BPF to redirect DNS queries in a Docker environment.

Intelligent automation removes barriers to scaling automation that have hindered business productivity for years. This powerful fusion of technologies automates complex processes, empowering organizations to adapt to change faster and more effectively than ever before.

AI injects “intelligence” into automation, enabling systems to execute tasks, comprehend complex data, make informed decisions, and learn from outcomes. Unlike technologies such as robotic process automation (RPA), which follow predetermined rules, AI leverages data to evaluate situations and determine the best course of action. Now that we've explored how AI augments traditional automation tools, let's delve deeper into the realm of intelligent automation.

Hey there! We're back for our third edition of Tips and Tricks. As we said in our first posts on Drizzle ORM and Template Databases in PostgreSQL, our new Tips and Tricks mini blog series is going to share some helpful insights and cool tech that we've stumbled upon while working on technical stuff. Today's topic is short and sweet. It'll be on CPU utilization and what that metric indicates. If you enjoy it and want to learn more, I encourage you to check out the "further reading" links.