Design a Docker-Based Environment for Automated Graphics Tests on NVIDIA/AMD GPUs

Context

You need to design a reproducible, secure, and debuggable CI environment that runs automated graphics tests (e.g., Vulkan/OpenGL/EGL) in Docker on Linux hosts equipped with NVIDIA and/or AMD GPUs. The system should work headlessly and scale across CI agents.

Requirements

Describe a concrete approach covering:

1. Base images to use for NVIDIA and AMD, including dev vs. runtime variants.
2. Driver and runtime integration (e.g., NVIDIA Container Toolkit, ROCm/DRM), device exposure, and ICD/loader handling.
3. Headless rendering strategy (EGL/Vulkan vs. Xvfb) and test harness basics.
4. Image layering and caching strategy to speed builds.
5. Reproducibility: version pinning, driver/toolchain alignment, and environment capture.
6. Security: least-privilege containers, capabilities, device nodes, secrets management.
7. Debugging inside containers: tools, logging, profiling, core dumps, validation layers.
8. Handling flaky graphics tests: stabilization techniques and retry/quarantine policies.
9. Measuring and reducing CI runtime: metrics to track and optimizations to apply.

Deliverables

• High-level architecture (host vs. container responsibilities; per-vendor specifics).
• Example Dockerfiles (builder vs. runner), run flags, and minimal CI runner configuration.
• A checklist of metrics and concrete actions to reduce runtime while keeping determinism.