While incredibly powerful, one of the challenges when building an LLM application (large language model) is dealing with performance implications.

Learn the biggest obstacles with load test automation, and how existing user traffic holds the key to scaling eCommerce software safely, and fast.

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.

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.

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.

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.

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.

Outsourced engineering teams are gaining in popularity and many investors have started to treat them as a requirement.

Figuring out what APIs are doing in Kubernetes can be difficult. Read the pros and cons of WireShark, Kubeshark and Speedscale and when to use which.

Kong Mesh 2.7 is here! And with it come a slew of new features to make our simple and powerful enterprise service mesh even easier to use and more powerful for your particular needs. In this blog post, we'll cover the new features and show how Kong Mesh 2.7 can deliver a superior service mesh experience for your organization.