Deploying Embedded Applications Faster with Containers

Container technology is fundamentally changing how systems are being developed, tested, deployed, and managed. People are most familiar with containers as part of cloud-native architectures in which applications are decoupled from the infrastructure — including hardware and operating systems — on which they are running.

The benefits of this approach include being able to automate the software pipeline to remove manual errors, standardize tools, and accelerate the rate of product iterations. With a CI/CD pipeline, companies can leverage continuous integration (CI) where code changes are merged in a central repository with continuous delivery (CD), thereby providing the ability to automate the entire software delivery process and deliver highquality software faster.

Embedded developers can also benefit from the infrastructure-agnostic, scalable execution environment enabled by containers. Imagine a design process — from development to test to deployment to production to management — in which developers can share resources, pipelines, and results across the team. Instead of being limited by the number of development boards available, companies could exploit the elasticity of the cloud to set up multiple instances of a system on demand.

However, traditional embedded application development and deployment has significant differences compared to a cloud-native architecture:

• It is tightly coupled to specific hardware. 
• It is written in lower-level languages such as C/C++. 
• It interacts directly with hardware (e.g., peripherals). 
• It requires specialized development and management tools. 
• It tends to have a long lifecycle and stateful execution. 
• It faces an increasing diversity of end hardware and software deployed in the field.

To bridge container technology to the embedded world requires that embedded development adapt to a cloud native–inspired workflow, but in a way that maintains the requirements of applications, including real-time determinism, optimized memory footprint, an integrated tool chain for cross-compiling and linking, tools for security scanning and quality assurance, and the ability to secure the build environment.

This article will explore the use of containers in the embedded design process and address how to meet the specific performance and cybersecurity challenges particular to embedded devices operating at the edge.