Book Image

The Insider's Guide to Arm Cortex-M Development

By : Zachary Lasiuk, Pareena Verma, Jason Andrews
Book Image

The Insider's Guide to Arm Cortex-M Development

By: Zachary Lasiuk, Pareena Verma, Jason Andrews

Overview of this book

Cortex-M has been around since 2004, so why a new book now? With new microcontrollers based on the Cortex-M55 and Cortex-M85 being introduced this year, Cortex-M continues to expand. New software concepts, such as standardized software reuse, have emerged alongside new topics including security and machine learning. Development methodologies have also significantly advanced, with more embedded development taking place in the cloud and increased levels of automation. Due to these advances, a single engineer can no longer understand an entire project and requires new skills to be successful. This book provides a unique view of how to navigate and apply the latest concepts in microcontroller development. The book is split into two parts. First, you’ll be guided through how to select the ideal set of hardware, software, and tools for your specific project. Next, you’ll explore how to implement essential topics for modern embedded developers. Throughout the book, there are examples for you to learn by working with real Cortex-M devices with all software available on GitHub. You will gain experience with the small Cortex-M0+, the powerful Cortex-M55, and more Cortex-M processors. By the end of this book, you’ll be able to practically apply modern Cortex-M software development concepts.
Table of Contents (15 chapters)
Part 1: Get Set Up
Part 2: Sharpen Your Skills

Other cloud development possibilities

There are other tools and environments possible to leverage in cloud-based development. This section covers some other options that you may want to consider for your projects, or at least be aware of.

Cloud virtual machines

Another way to develop in the cloud is by using virtual machines. We saw in Chapter 4 and Chapter 5 how to use an Amazon Machine Image (AMI) from AWS Marketplace for development. We learned how to use ssh to connect to the AWS EC2 instance and run applications such as the machine learning examples on the Corstone-300 Fixed Virtual Platform.

One thing we didn’t cover is using VS Code in the AMI for development work. There are two common ways to use VS Code with a virtual machine.

One way is to use an ssh connection. The VS Code Remote SSH extension can make the connection to a remote virtual machine. Various articles for connecting VS Code to a remote machine via ssh are available, and we recommend searching...