Machine learning operations (MLOps) has become the backbone of efficient artificial intelligence (AI) development. Blending ML with development and operations best practices, MLOps streamlines deploying ML models via continuous testing, updating, and monitoring. But as ML and AI use cases continue to expand, a need arises for specialized tools and best practices to handle the particular conditions of complex AI apps — like those using large language models (LLMs).

An IDE (integrated development environment) is software that combines all the functions needed for development in one place. Without an IDE, developers would need to use both a text editor to enter code and a separate compiler to make the program understandable to the computer. An IDE combines these features into one tool, making development more efficient.

In this article, you will get an easy-to-understand explanation of what an API (application programming interface) is and how you can use them to enhance your software applications or services.

For Android developers, test automation on CI/CD platforms such as CircleCI has become an indispensable part of the development workflow. But merely implementing automated testing is no longer enough to remain competitive and continue to develop at speed. Developers must also work to continuously monitor, maintain, and improve their test automation. As an application grows in complexity, the scale of development grows, as does the number of automated tests.