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Data is the driving force of the world’s modern economies, but data teams are struggling to meet demand to support generative AI (GenAI), including rapid data volume growth and the increasing complexity of data pipelines. More than 88% of software engineers, data scientists, and SQL analysts surveyed say they are turning to AI for more effective bug-fixing and troubleshooting. And 84% of engineers who use AI said it frees up their time to focus on high-value activities.

How to leverage Fivetran and Starburst to supercharge your data lakehouse with end-to-end data pipelines.

In today's fast-paced world of media publishing, keeping up with technological advancements and changing consumer preferences is no easy task. Tight budgets, fierce competition and evolving audience behaviors add to the pressure, creating what's often termed the "content crash" — a saturation of content that makes it hard for publishers to stand out. But amidst these challenges, there's a beacon of hope: generative AI.

On July 19th, 2024, the world witnessed a large-scale computer outage caused by a faulty update from cybersecurity giant CrowdStrike. This incident, affecting millions of Windows devices globally, serves as a stark reminder of the domino effect that software errors can have. Since then, CrowdStrike and other industry experts have shared their preliminary incident report in which they outline the incident and the steps they will take to prevent future issues like this.

On July 19th, 2024, the world witnessed a large-scale computer outage caused by a faulty update from cybersecurity giant CrowdStrike. This incident, affecting millions of Windows devices globally, serves as a stark reminder of the domino effect that software errors can have. In part one of this series, we discussed the role QA methodologies can play in preventing future outages.

You’ve built an incredible AI API and are ready to release this functionality to your users. The issue is that you’re not sure exactly how to monetize it. Generally, monetizing APIs is challenging at scale, but monetizing AI APIs can be even more difficult. Some AI APIs may be charged on a “per API call” basis, but many AI APIs require charging users for input and output tokens used within an API call. Others may charge per unique user or API key.

Artificial Intelligence (AI) technology has been transforming industries and our day-to-day lives alike. Its undeniable impact has led to significant effort and investment into making AI more accessible to everyone, everywhere. Open-source AI technology and AI APIs are two examples of our commitment to AI democratization. AI APIs democratize AI by providing access to pre-trained AI models, even for developers without extensive machine learning expertise.

We are excited to announce the launch of our AI Infrastructure Control Plane, designed as a universal operating system for AI infrastructure. With this launch, we make it easier for IT teams and DevOps to gain ultimate control over their AI Infrastructure, manage complex environments, maximize compute utilization, and deliver an optimized self-serve experience for their AI Builders.

Unit tests are essential to verify the behavior of small code units in a Node.js application. This leads to clearer design, fewer bugs, and better adherence to business requirements. That's why Test-Driven Development (TDD) and Behavior-Driven Development (BDD) have become so popular in the backend development community. In this tutorial, we'll dive into unit testing and understand why it's needed in your backend.

It's 2024, and the HyperText Transfer Protocol (HTTP) is 35 years old. The fact that the vast majority of web traffic still relies on this simple, stateless form of communication is a marvel in itself. A first set of content retrieval optimizations were added to the protocol when v1.0 was published in 1996. These include the infamous caching instructions (aka headers) that the client and server use to negotiate whether content needs refreshing.