plugins/docker-master/skills/docker-2025-features/SKILL.md
Latest Docker features (2025-2026) including Docker AI, Enhanced Container Isolation, BuildKit improvements, and Moby. PROACTIVELY activate for: (1) Docker AI / Ask Gordon assistant, (2) Enhanced Container Isolation (ECI) for hardened runtime, (3) Moby 25+ engine features, (4) BuildKit advancements (cache mounts, secrets, SBOM, provenance), (5) Docker Compose v2 features (watch mode, profiles, includes), (6) Docker Desktop new settings (Resource Saver, Synchronized File Shares, virtiofs), (7) Docker Build Cloud, (8) Docker Scout for vulnerability scanning, (9) WSL2 backend updates, (10) ContainerD integration. Provides: feature reference, version-detection snippets, BuildKit cache/secret recipes, Compose v2 watch examples, and migration notes.
npx skillsauth add JosiahSiegel/claude-plugin-marketplace docker-2025-featuresInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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MANDATORY: Always Use Backslashes on Windows for File Paths
When using Edit or Write tools on Windows, you MUST use backslashes (\) in file paths, NOT forward slashes (/).
Examples:
D:/repos/project/file.tsxD:\repos\project\file.tsxThis applies to:
NEVER create new documentation files unless explicitly requested by the user.
This skill covers the latest Docker features introduced in 2025, ensuring you leverage cutting-edge capabilities for security, performance, and developer experience.
What it is: Mount an image directory structure directly inside a container without extracting to a volume.
Key capabilities:
How to use:
# Mount entire image
docker run --rm \
--mount type=image,source=mydata:latest,target=/data \
alpine ls -la /data
# Mount specific path from image
docker run --rm \
--mount type=image,source=mydata:latest,image-subpath=/config,target=/app/config \
alpine cat /app/config/settings.json
Use cases:
What it is: Debug endpoints now accessible through standard versioned API paths.
Previously: Only available at root paths like /debug/vars
Now: Also accessible at /v1.48/debug/vars, /v1.48/debug/pprof/*
Available endpoints:
/v1.48/debug/vars - Runtime variables/v1.48/debug/pprof/ - Profiling index/v1.48/debug/pprof/cmdline - Command line/v1.48/debug/pprof/profile - CPU profile/v1.48/debug/pprof/trace - Execution trace/v1.48/debug/pprof/goroutine - Goroutine stacksHow to use:
# Access debug vars through versioned API
curl --unix-socket /var/run/docker.sock http://localhost/v1.48/debug/vars
# Get CPU profile
curl --unix-socket /var/run/docker.sock http://localhost/v1.48/debug/pprof/profile?seconds=30 > profile.out
Latest versions in Engine 28.3.3:
CVE-2025-54388: Fixed firewalld reload issue where published container ports could be accessed from local network even when bound to loopback.
Impact: Critical for containers binding to 127.0.0.1 expecting localhost-only access.
Raspberry Pi OS 32-bit (armhf):
What it is: Model Context Protocol (MCP) server catalog with 100+ verified, containerized tools.
Key capabilities:
How to access:
Use cases:
What's new:
docker model requests command for monitoringHow to use:
# List running models
docker model ls
# View model details (new: model cards)
docker model inspect llama2-7b
# Monitor requests and responses (NEW)
docker model requests llama2-7b
# Performance metrics
docker stats $(docker model ls -q)
What it is: Docker Desktop automatically updates internal components without requiring full application restart.
Benefits:
Configuration:
CVE-2025-10657 (v4.47): Fixed Enhanced Container Isolation Docker Socket command restrictions not working in 4.46.0.
CVE-2025-9074 (v4.46): Fixed malicious container escape allowing Docker Engine access without mounted socket.
What it is: AI-powered assistant integrated into Docker Desktop and CLI for intelligent container development.
Key capabilities:
How to use:
# Enable in Docker Desktop Settings > Features > Docker AI (Beta)
# Ask questions in natural language
"Optimize my Python Dockerfile"
"Why is my container restarting?"
"Suggest secure nginx configuration"
Local Model Runner:
What it is: Additional security layer that restricts Docker socket access and container escape vectors.
Security benefits:
How to enable:
# Docker Desktop Settings > Security > Enhanced Container Isolation
# Or via CLI:
docker desktop settings set enhancedContainerIsolation=true
Use cases:
Compatibility:
What it is: Built-in AI model execution engine allowing developers to run large language models locally.
Features:
How to use:
# Install via Docker Desktop Extensions
# Or use CLI:
docker model run llama2-7b
# View running models:
docker model ls
# Stop model:
docker model stop MODEL_ID
Benefits:
What it is: Test Kubernetes deployments with multi-node clusters directly in Docker Desktop.
Previously: Single-node only Now: 2-5 node clusters for realistic testing
How to enable:
# Docker Desktop Settings > Kubernetes > Enable multi-node
# Specify node count (2-5)
Use cases:
What it is: High-level build orchestration tool for complex multi-target builds.
Previously: Experimental Now: Generally available and production-ready
Features:
# docker-bake.hcl
target "app" {
context = "."
dockerfile = "Dockerfile"
tags = ["myapp:latest"]
platforms = ["linux/amd64", "linux/arm64"]
cache-from = ["type=registry,ref=myapp:cache"]
cache-to = ["type=registry,ref=myapp:cache,mode=max"]
}
target "test" {
inherits = ["app"]
target = "test"
output = ["type=local,dest=./coverage"]
}
# Build all targets
docker buildx bake
# Build specific target
docker buildx bake test
1. Faster Container Startup:
2. Better Resource Management:
3. Storage Driver Enhancements:
1. Enhanced Seccomp Profiles:
{
"defaultAction": "SCMP_ACT_ERRNO",
"architectures": ["SCMP_ARCH_X86_64", "SCMP_ARCH_AARCH64"],
"syscalls": [
{
"names": ["read", "write", "exit"],
"action": "SCMP_ACT_ALLOW"
}
]
}
2. Improved AppArmor Integration:
3. User Namespace Improvements:
What it is: Convert local compose.yaml files to Kubernetes manifests in a single command.
Key capabilities:
How to use:
# Convert compose file to Kubernetes manifests
docker compose convert --format kubernetes > k8s-manifests.yaml
# Or use compose-bridge directly
docker compose-bridge convert docker-compose.yml
# Apply to Kubernetes cluster
kubectl apply -f k8s-manifests.yaml
Example conversion:
# docker-compose.yml
services:
web:
image: nginx:latest
ports:
- "80:80"
volumes:
- data:/usr/share/nginx/html
volumes:
data:
# Converts to Kubernetes:
# - Deployment for 'web' service
# - Service exposing port 80
# - PersistentVolumeClaim for 'data'
Use cases:
1. Version Field Obsolete:
# OLD (deprecated):
version: '3.8'
services:
app:
image: nginx
# NEW (2025):
services:
app:
image: nginx
The version field is now ignored and can be omitted.
1. Develop Watch with initial_sync:
services:
app:
build: .
develop:
watch:
- action: sync
path: ./src
target: /app/src
initial_sync: full # NEW: Sync all files on start
2. Volume Type: Image:
services:
app:
volumes:
- type: image
source: mydata:latest
target: /data
read_only: true
3. Build Print:
# Debug complex build configurations
docker compose build --print > build-config.json
4. Config No-Env-Resolution:
# View raw config without environment variable substitution
docker compose config --no-env-resolution
5. Watch with Prune:
# Automatically prune unused resources during watch
docker compose watch --prune
6. Run with Quiet:
# Reduce output noise
docker compose run --quiet app npm test
1. Git SHA-256 Support:
# Use SHA-256 based repositories
ADD https://github.com/user/repo#sha256:abc123... /src
2. Enhanced COPY/ADD --exclude:
# Now generally available (was labs-only)
COPY --exclude=*.test.js --exclude=*.md . /app
3. ADD --unpack with --chown:
# Extract and set ownership in one step
ADD --unpack=true --chown=appuser:appgroup archive.tar.gz /app
4. Git Query Parameters:
# Fine-grained Git clone control
ADD https://github.com/user/repo.git?depth=1&branch=main /src
5. Image Checksum Verification:
# Verify image integrity
FROM alpine:3.19@sha256:abc123...
# BuildKit verifies checksum automatically
1. Improved Frontend Verification:
# Always use official Docker frontends
# syntax=docker/dockerfile:1
# Pin with digest for maximum security
# syntax=docker/dockerfile:1@sha256:ac85f380a63b13dfcefa89046420e1781752bab202122f8f50032edf31be0021
2. Remote Cache Improvements:
version field, use new features (type: image volumes, watch improvements, --print, --quiet), and test under Compose v2.40+.For migration paths to Docker Desktop 4.38+, troubleshooting of new 2025 features (compose-bridge, hardened-mode quirks, BuildKit history), and the recommended feature-adoption timeline, see references/migration-troubleshooting-timeline.md.
development
This skill should be used when the user asks to train, debug, scale, or improve ML models. PROACTIVELY activate for: (1) PyTorch, TensorFlow/Keras, JAX, Flax, Hugging Face Trainer/Accelerate training loops, (2) distributed training, DDP/FSDP/DeepSpeed, TPU/GPU setup, (3) mixed precision AMP/bf16, gradient accumulation, checkpointing, seeding, (4) overfitting, imbalance, loss functions, regularization, LR schedules, warmup, (5) memory optimization, gradient checkpointing, offloading, quantization-aware training. Provides: reproducible training best practices across deep learning and classical ML.
development
This skill should be used when the user asks to productionize, track, version, govern, monitor, or automate ML systems. PROACTIVELY activate for: (1) MLflow, Weights & Biases, Neptune, Comet, ClearML experiment tracking, (2) model registry, model versioning, artifact lineage, reproducibility, (3) Kubeflow, SageMaker Pipelines, Vertex AI Pipelines, Azure ML pipelines, Databricks workflows, (4) CI/CD, continuous training/evaluation, A/B tests, canary/shadow deployments, (5) drift detection, model monitoring, data validation, responsible AI governance. Provides: end-to-end MLOps architecture and operational safeguards.
development
This skill should be used when the user asks to optimize, export, serve, compress, or accelerate ML inference. PROACTIVELY activate for: (1) latency, throughput, p95/p99, batching, concurrency, KV cache, memory, or cost issues, (2) quantization INT8/INT4, GPTQ, AWQ, bitsandbytes, pruning, sparsity, distillation, (3) ONNX export, ONNX Runtime, TensorRT, TorchScript, torch.compile, XLA, OpenVINO, Core ML, TFLite, (4) Triton, TorchServe, TF Serving, BentoML, Seldon, KServe configuration, (5) edge deployment, CPU/GPU/TPU/Inferentia serving. Provides: hardware-aware inference optimization and safe benchmarking.
testing
This skill should be used when the user asks to tune hyperparameters, run sweeps, optimize search spaces, or use AutoML. PROACTIVELY activate for: (1) Optuna, Ray Tune, FLAML, AutoGluon, Hyperopt, Nevergrad, KerasTuner, W&B sweeps, (2) grid search, random search, Bayesian optimization, TPE, Gaussian processes, evolutionary search, (3) ASHA, Hyperband, successive halving, multi-fidelity optimization, population-based training, (4) learning-rate finder, batch-size search, early stopping, pruning, (5) reproducible sweep design and experiment analysis. Provides: budget-aware hyperparameter search strategy.