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.

API (application programming interface) document works as a developer’s compass for navigating complex services. In this guide, we provide straightforward insights into crafting excellent API documentation. At the end of this article, you will know how to succeed as both creators and consumers of APIs through effective documentation.

Is exploratory testing a solo practice? Is only the QA team responsible for quality? Are the great insights of an exploratory session shared with the team? We’ve been asking ourselves and our users these questions and we’re happy to launch version 3 of the Xray Exploratory App, designed to establish the foundations of collaboration in exploratory testing.

If you'd like to run load tests in a simple way, and possibly share them, while benefiting from a simplified configuration, with a focus on writing your test plan, and its test typology, this article is for you! Docker offers virtualization services that simplify the replication of working environments. Furthermore, each virtualized service is isolated from unrelated services on other containers or the host machine, ensuring portability across host machines and the network.

Understanding how to make a GET request to an API using Python is an essential skill for developers. This article will guide you through the process, demonstrating how to use Python’s ‘requests’ library to fetch data, handle the full JSON object in response, and manage API errors efficiently. Step into the practical world of Python GET API calls without any detours.

An API (Application Programming Interface) is a set of rules and protocols that let software programs communicate with each other. It acts as an intermediary between different software or services. For example, when using a mobile app to book a hotel room, the API allows the app to communicate with the hotel’s booking system. While many REST API developers have their way of doing things, some factors in API development are generally considered essential.

Maintaining standards in an ever-growing codebase that multiple developers contribute to can be difficult and tedious. Ensuring that the codebase follows best practices and does not deviate from the standards is essential for any project. But this is typically something that can only be enforced manually by code reviews and other similar processes. As with any other manual task, this can be time-consuming, tedious, and error-prone. That's where architecture testing comes in.

Application programming interfaces (APIs) have quickly become vital to modern businesses. APIs work by allowing different systems to talk to each other and share data. The commercial use of APIs and web APIs has skyrocketed over the last decades in accordance with the rise in app development, mobile apps, and e-commerce. However, how do you estimate API development time? Well, API creation and the development time frame will always vary from project to project.