Bun and Node.js are two JavaScript runtime technologies to run JavaScript on the server. Node.js is the undisputed king of server-side development with JavaScript, but Bun has gained popularity thanks to its unbelievable performance capabilities. The real question is, though: does it really make sense to use Bun instead of Node.js? Let's learn about Bun and Node.js, dig into their characteristics, and explore some scenarios where Bun can be a better alternative to Node.js.

In today’s digital age, citizens expect seamless interactions with government agencies, mirroring the efficiency and user-friendliness they encounter in the private sector. However, achieving exceptional citizen experience (CX) requires routine testing and close attention to software quality and performance. As agencies navigate the complexities of delivering digitized services, continuous automated testing (CAT) is a game-changer in enhancing CX while maintaining speed and reliability.

In modern web applications, real-time communication has become more than a feature: it's gradually evolved into a necessity. Users expect instant updates, live interactions, and dynamic content. In Rails applications, Action Cable has long been the go-to solution, harnessing WebSockets to fulfill these demands. In this article, we introduce: Let's get started!

As the wave of AI sweeps through the technology landscape, many have hopped on board. Interestingly enough, and often overlooked, is that many AI capabilities are served through APIs. Fancy user interfaces integrate with the actual mechanisms where the magic happens: the APIs. So, when generating revenue through AI platforms, the APIs drive the revenue.

Whether you love, hate or remain indifferent towards data, it’s impossible to deny its importance in today’s business landscape. Businesses across all sectors and industries collect data and perform data analysis, to better understand their customers and business processes, in an effort to boost productivity, reduce expenditure and gain competitive advantage.

Let’s pose a hypothetical scenario. You're the API product owner at the Paris, Texas Regional Airport. You're in charge of two main APIs: Flights API and Scheduling API. Flights API is primarily used by local research institutions that are interested in read-only access to information about departures and arrivals. Scheduling API is primarily used by airline partners who are interested in updating information about their flights and gates.

Not long ago, I was handed a problem that’s no stranger to the world of programming: making asynchronous threads communicate effectively within the same process. Given the widespread nature of this issue, I expected to find an existing solution to resolve it. My search led me to the concept of message queue, which seemed promising for streamlining this communication challenge.

Today, we’re excited to share that Serverless GPUs are available for all your AI inference needs directly through the Koyeb platform! We're starting with GPU Instances designed to support AI inference workloads including both heavy generative AI models and lighter computer vision models. These GPUs provide up to 48GB of vRAM, 733 TFLOPS and 900GB/s of memory bandwidth to support large models including LLMs and text-to-image models.

Embedding analytics into your application? New browser restrictions are on the way for Google Chrome that can block some third-party content that uses cookies from being accessible to users by default, in addition to restrictions in Safari and Firefox you may have already seen.

The ever-growing threat landscape of hackers, cyberattacks, and data breaches makes data security a top priority, especially when integrating analytics capabilities directly into customer-facing applications. To make informed decisions, it’s crucial to understand how embedded analytics platforms function from a security standpoint.