Warm BuildKit cache in AMIs for 2.4× faster CI builds #256
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Depends on vllm-project/vllm#31477 ## Context Without a warm local cache, builds download and extract ~18GB of layers from ECR: | Layer | Size | Download | Extract | Total | |--------------|---------|----------|---------|-------| | Extensions | 4.38 GB | 75s | 14s | 89s | | CUDA deps | 3.21 GB | 51s | 32s | 83s | | PyTorch | 5.15 GB | 97s | - | 97s | | Build tools | 2.30 GB | 38s | 18s | 56s | | Other layers | ~5 GB | ~70s | ~6s | 76s | | Total | ~18 GB | ~330s | ~70s | ~400s | This ~6.5 minute overhead occurs on every cold-cache build for layers that rarely change. ## Solution ### 1. Warm Local BuildKit Cache - Run buildkitd as persistent service with remote driver - Bake cache into custom AMIs, rebuilt daily from latest postmerge - Daily rebuilds ensure AMI cache stays fresh, maximizing cache hits throughout the day - Layers remain on disk between builds → skip download + extraction entirely - Saves: ~400s per cold-cache build ### 2. Docker Buildx Bake - CI extends vLLM's docker-bake.hcl (vllm-project/vllm#31477) with ci.hcl overlay - Same build config runs in CI and AMI warm-up → cache key parity ### 3. Cache-From Configuration - Added merge-base commit to cache-from sources - Ensures cache hits for unchanged intermediate stages ### 4. EBS Throughput - Increased gp3 from 125 MB/s → 1000 MB/s - Speeds up cache import/export and registry push, cutting at least 1 minute ### 5. Network & Concurrency Tuning - Increased BuildKit/Docker parallelism - Network tuning following https://docs.aws.amazon.com/datatransferterminal/latest/userguide/tech-requirements.html ### 6. Debug Script - Added debug-machine-config.sh to print instance info, network settings, and BuildKit config - Helps verify AMI optimizations are active in CI builds Signed-off-by: Amr Mahdi <[email protected]>
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Add docker/docker-bake.hcl as the base build configuration for docker buildx bake. This is part of the effort to bake Docker build cache into CPU AMIs for faster CI builds. See vllm-project/ci-infra#256 Context: CI builds need intermediate stages cached, not just base images. To make this work, we need the exact same build configuration to run in both: 1. Regular CI image builds 2. AMI cache warm-up during AMI creation Why docker buildx bake: Docker buildx bake provides a declarative, composable build configuration using HCL. CI extends this base config with a ci.hcl overlay that adds caching, registry settings, and commit-based cache keys. Both contexts use the same build definition, ensuring consistency and cache key parity for maximum layer reuse. This file provides: - Build variables (CUDA arch lists, parallelism settings) - Common build args shared across targets - OCI labels and annotations for image metadata (most importantly the git commit SHA) - Base targets (test, openai) that CI extends Usage example: docker buildx bake -f docker/docker-bake.hcl -f ci.hcl test-ci CI will download ci.hcl from ci-infra and combine it with this file. After completing the AMI cache baking in addition to the changes in the cin-infra repo, we expect image builds that only change leaf Python stages to go from ~17 minutes to ~7 minutes (~2.4x faster), more explanation the breakdown can be found in the ci-infra PR linked Signed-off-by: Amr Mahdi <[email protected]>
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Depends on vllm-project/vllm#31477
Context
Without a warm local cache, builds download and extract ~18GB of layers from ECR:
This ~6.5 minute overhead occurs on every cold-cache build for layers that rarely change.
Solution
1. Warm Local BuildKit Cache
2. Docker Buildx Bake
3. Cache-From Configuration
4. EBS Throughput
5. Network & Concurrency Tuning
6. Debug Script