When you build an app, you'll often find that certain tasks do not require user interaction and are better performed in the background. Elixir provides excellent primitives, such as Task.async, to offload these tasks from the main user pipeline. Additionally, libraries like Oban offer more control over background tasks when needed. There's also FLAME, which the core Phoenix team is developing to offer a scalable solution for offloading intensive tasks to remote machines.

Large Language Models (LLM) are changing the way developers and QA engineers solve problems. They allow for quicker code generation, debugging, and automated testing, reducing development time by up to 40%. This shift has prompted 67% of senior IT leaders to focus on generative AI, with 33% planning to make it a top priority within the next 18 months. However, while LLM models offer immense potential, understanding how to get the most out of them while maintaining quality is important.

Spring Boot is an open-source micro framework maintained by a company called Pivotal. It provides Java developers with a platform to get started with an auto configurable production-grade Spring application. With it, developers can get started quickly without losing time on preparing and configuring their Spring application. This post will guide you through understanding what the micro framework is and what it’s used for.

The difference between stateful and stateless applications is essential when developing APIs. However, if you’re not a developer who’s working with stateful and stateless systems, you might not fully understand these concepts. More importantly, you may not know why stateless REST APIs are so essential to building scalable web applications? Here are the key takeaways to know about stateful vs. stateless apps.

System administrators, DBAs, and application developers all know about the need for data integration. That’s when you have to pull data from one database, application, or web service to another. Fortunately, this task is a lot less challenging than it used to be because APIs (application programming interfaces) are so popular today. APIs provide a standard way to share the data and services of one system with another, even if the two systems are otherwise incompatible.

When it comes to managing AI projects, the Command Line Interface (CLI) can be a powerful tool. With ClearML, the CLI becomes an essential resource for creating job templates, launching remote for JupyterLab, VS Code, or SSH development environments, and executing code on a remote machine that can better meet resource needs. Specifically designed for AI workloads, ClearML’s CLI offers seamless control and efficiency, empowering users to maximize their AI efforts.

A little-known fact about me is my love for scuba diving. There’s nothing quite like the feeling of being so close to nature, exploring the mysteries of the underwater world. Every chance I get, I dive into the ocean’s depths, uncovering hidden wonders that most people never get to see. That got me thinking about the similarities between data and the ocean. Just like the vast, uncharted waters of the sea, the world of data holds incredible potential—if you know how to navigate it.

Learn about some of the top mobile testing tools and frameworks available, including how you can leverage them to improve your app quality and deliver exceptional customer experiences.

The healthcare system is always on the cutting edge of new technologies—but it's also one of the most heavily breached industries. The HIPAA Journal reported that the largest healthcare information data breach between 2009 and 2024 occurred in 2015 when hackers illegally obtained the health records of nearly 79 million Anthem Health subscribers1.