Static code analysis is an important tool to ensure a project meets the right code standards and quality. In Elixir, the most popular package for this is Credo. Not only does it offer dozens of pre-made checks, but it also allows you to create your own. In this article, we will walk you through creating a Credo check. We will see how to write the code, enable the check in the Credo config, and make it nice to use. Let’s start!
Excellent performance is key for any application, regardless of the framework or language. Today’s digital consumers demand speed and precision, and will quickly quit a sluggish app. That's why performance monitoring, especially Real User Monitoring (RUM), is important for every developer to implement. We recently launched RUM for BugSnag, providing developers the visibility they need to ensure great application performance.
We live in a highly interconnected world, and that interconnectedness couldn’t have existed without the tremendous contributions from the telecommunications industry. With 5G technology finally becoming mainstream, IoT growing at a rapid rate, and AI tech gaining prominence, the telecom industry is surely up for an exciting future. This faster-than-ever growth comes with the need for robust, continuous telecom testing to always maintain a high standard of service quality.
Application programming interfaces (APIs) serve as the backbone of today’s digital economy. They connect applications and web services with each other to exchange information and deliver thousands of digital experiences to users every day. With such significance, APIs can’t afford to be buggy, and software testers must frequently test them to identify and address potential issues. However, there’s a catch. Sometimes an API is not fully developed, or is simply too expensive to access.
Java performance optimization is crucial for several reasons. First and foremost, it directly impacts the user experience. Faster and more responsive applications lead to a better user experience, reducing loading times and response delays. Users expect applications to be snappy and efficient, and optimization helps achieve this, enhancing user satisfaction.
Large language models (LLMs) are all the rage, fueled by the release of OpenAI's ChatGPT in late 2022, initially powered by the LLM GPT-3. Aside from the news hype, what can LLMs actually, getting-down-to-brass-tacks, nitty-gritty do for your business? Here, we’ll look at three examples of problems they can solve. But first, a quick definition of LLMs.
