Hardware-Agnostic Edge AI: A Review of Adaptive Containerization for Vision Model Deployment Across Heterogeneous Edge Devices

A review of adaptive containerisation for deploying vision models across heterogeneous, hardware-agnostic edge devices.

A review of adaptive containerisation for deploying vision models across heterogeneous, hardware-agnostic edge devices. As a reference project it shows how a system like this is put together in practice, which parts matter and how they are tested, so that a developer can learn from it and build on it.

It suits learners who want to run software the way production teams do: containers, automated pipelines, deployment, monitoring and rollback.

The main parts are containerised services, an automated build, test and deploy pipeline, monitoring and alerting, and safe rollback. The reference build uses Docker, Kubernetes, GitHub Actions, and Terraform, with a clear project structure, setup instructions and sample data so that it can be run and extended.