Convex optimization has emerged as useful tool for applications that include data analysis and model fitting, machine learning and statistics, resource allocation, engineering design, network design and optimization, finance, and control and signal processing. We give an overview of the basic mathematics, algorithms, and software frameworks for convex optimization, and give a few examples. We describe real-time embedded convex optimization, in which small convex optimization problems are solved repeatedly in time frames measured in milliseconds.