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# Attune Worker Containers
This directory contains Docker configurations for building Attune worker containers with different runtime capabilities.
## Overview
Attune workers can run in containers with specialized runtime environments. Workers automatically declare their capabilities when they register with the system, enabling intelligent action scheduling based on runtime requirements.
## Worker Variants
### Base Worker (`worker-base`)
- **Runtimes**: `shell`
- **Base Image**: Debian Bookworm Slim
- **Size**: ~580 MB
- **Use Case**: Lightweight workers for shell scripts and basic automation
- **Build**: `make docker-build-worker-base`
### Python Worker (`worker-python`)
- **Runtimes**: `shell`, `python`
- **Base Image**: Python 3.11 Slim
- **Size**: ~1.2 GB
- **Includes**: pip, virtualenv, common Python libraries (requests, pyyaml, jinja2, python-dateutil)
- **Use Case**: Python actions and scripts with dependencies
- **Build**: `make docker-build-worker-python`
### Node.js Worker (`worker-node`)
- **Runtimes**: `shell`, `node`
- **Base Image**: Node 20 Slim
- **Size**: ~760 MB
- **Includes**: npm, yarn
- **Use Case**: JavaScript/TypeScript actions and npm packages
- **Build**: `make docker-build-worker-node`
### Full Worker (`worker-full`)
- **Runtimes**: `shell`, `python`, `node`, `native`
- **Base Image**: Debian Bookworm
- **Size**: ~1.6 GB
- **Includes**: Python 3.x, Node.js 20, build tools
- **Use Case**: General-purpose automation requiring multiple runtimes
- **Build**: `make docker-build-worker-full`
## Building Worker Images
### Build All Variants
```bash
make docker-build-workers
```
### Build Individual Variants
```bash
# Base worker (shell only)
make docker-build-worker-base
# Python worker
make docker-build-worker-python
# Node.js worker
make docker-build-worker-node
# Full worker (all runtimes)
make docker-build-worker-full
```
### Direct Docker Build
```bash
# Using Docker directly with BuildKit
DOCKER_BUILDKIT=1 docker build \
--target worker-python \
-t attune-worker:python \
-f docker/Dockerfile.worker \
.
```
## Running Workers
### Using Docker Compose
```bash
# Start specific worker type
docker-compose up -d worker-python
# Start all workers
docker-compose up -d worker-shell worker-python worker-node worker-full
# Scale workers
docker-compose up -d --scale worker-python=3
```
### Using Docker Run
```bash
docker run -d \
--name worker-python-01 \
--network attune_attune-network \
-e ATTUNE_WORKER_NAME=worker-python-01 \
-e ATTUNE_WORKER_RUNTIMES=shell,python \
-e ATTUNE__DATABASE__URL=postgresql://attune:attune@postgres:5432/attune \
-e ATTUNE__MESSAGE_QUEUE__URL=amqp://attune:attune@rabbitmq:5672 \
-v $(pwd)/packs:/opt/attune/packs:ro \
attune-worker:python
```
## Runtime Capability Declaration
Workers declare their capabilities in three ways (in order of precedence):
### 1. Environment Variable (Highest Priority)
```bash
ATTUNE_WORKER_RUNTIMES="shell,python,custom"
```
### 2. Configuration File
```yaml
worker:
capabilities:
runtimes: ["shell", "python"]
```
### 3. Auto-Detection (Fallback)
Workers automatically detect available runtimes by checking for binaries:
- `python3` or `python` → adds `python`
- `node` → adds `node`
- Always includes `shell` and `native`
## Configuration
### Key Environment Variables
| Variable | Description | Example |
|----------|-------------|---------|
| `ATTUNE_WORKER_NAME` | Unique worker identifier | `worker-python-01` |
| `ATTUNE_WORKER_RUNTIMES` | Comma-separated runtime list | `shell,python` |
| `ATTUNE_WORKER_TYPE` | Worker type | `container` |
| `ATTUNE__DATABASE__URL` | PostgreSQL connection | `postgresql://...` |
| `ATTUNE__MESSAGE_QUEUE__URL` | RabbitMQ connection | `amqp://...` |
| `RUST_LOG` | Log level | `info`, `debug`, `trace` |
### Resource Limits
Set CPU and memory limits in `docker-compose.override.yml`:
```yaml
services:
worker-python:
deploy:
resources:
limits:
cpus: '2.0'
memory: 2G
reservations:
cpus: '0.5'
memory: 512M
```
## Custom Worker Images
### Extend Python Worker
Create a custom worker with additional packages:
```dockerfile
# Dockerfile.worker.ml
FROM attune-worker:python
USER root
# Install ML packages
RUN pip install --no-cache-dir \
pandas \
numpy \
scikit-learn \
torch
USER attune
ENV ATTUNE_WORKER_RUNTIMES="shell,python,ml"
```
Build and run:
```bash
docker build -t attune-worker:ml -f Dockerfile.worker.ml .
docker run -d --name worker-ml-01 ... attune-worker:ml
```
### Add New Runtime
Example: Adding Ruby support
```dockerfile
FROM attune-worker:base
USER root
RUN apt-get update && apt-get install -y \
ruby-full \
&& rm -rf /var/lib/apt/lists/*
USER attune
ENV ATTUNE_WORKER_RUNTIMES="shell,ruby"
```
## Architecture
### Multi-stage Build
The `Dockerfile.worker` uses a multi-stage build pattern:
1. **Builder Stage**: Compiles the Rust worker binary
- Uses BuildKit cache mounts for fast incremental builds
- Shared across all worker variants
2. **Runtime Stages**: Creates specialized worker images
- `worker-base`: Minimal shell runtime
- `worker-python`: Python runtime
- `worker-node`: Node.js runtime
- `worker-full`: All runtimes
### Build Cache
BuildKit cache mounts dramatically speed up builds:
- First build: ~5-6 minutes
- Incremental builds: ~30-60 seconds
Cache is shared across builds using `sharing=locked` to prevent race conditions.
## Security
### Non-root Execution
All workers run as user `attune` (UID 1000)
### Read-only Packs
Pack files are mounted read-only to prevent modification:
```yaml
volumes:
- ./packs:/opt/attune/packs:ro # :ro = read-only
```
### Network Isolation
Workers run in isolated Docker network with only necessary service access
### Secret Management
Use environment variables for sensitive data; never hardcode in images
## Monitoring
### Check Worker Registration
```bash
docker-compose exec postgres psql -U attune -d attune -c \
"SELECT name, worker_type, status, capabilities->>'runtimes' as runtimes FROM worker;"
```
### View Logs
```bash
docker-compose logs -f worker-python
```
### Check Resource Usage
```bash
docker stats attune-worker-python
```
### Verify Health
```bash
docker-compose ps | grep worker
```
## Troubleshooting
### Worker Not Registering
**Check database connectivity:**
```bash
docker-compose logs worker-python | grep -i database
```
**Verify environment:**
```bash
docker-compose exec worker-python env | grep ATTUNE
```
### Runtime Not Detected
**Check runtime availability:**
```bash
docker-compose exec worker-python python3 --version
docker-compose exec worker-python node --version
```
**Force runtime declaration:**
```bash
ATTUNE_WORKER_RUNTIMES=shell,python
```
### Actions Not Scheduled
**Verify runtime match:**
```sql
-- Check action runtime requirement
SELECT a.ref, r.name as runtime
FROM action a
JOIN runtime r ON a.runtime = r.id
WHERE a.ref = 'core.my_action';
-- Check worker capabilities
SELECT name, capabilities->>'runtimes'
FROM worker
WHERE status = 'active';
```
## Performance
### Image Sizes
| Image | Size | Build Time (Cold) | Build Time (Cached) |
|-------|------|-------------------|---------------------|
| worker-base | ~580 MB | ~5 min | ~30 sec |
| worker-python | ~1.2 GB | ~6 min | ~45 sec |
| worker-node | ~760 MB | ~6 min | ~45 sec |
| worker-full | ~1.6 GB | ~7 min | ~60 sec |
### Optimization Tips
1. **Use specific variants**: Don't use `worker-full` if you only need Python
2. **Enable BuildKit**: Dramatically speeds up builds
3. **Layer caching**: Order Dockerfile commands from least to most frequently changed
4. **Multi-stage builds**: Keeps runtime images small
## Files
- `Dockerfile.worker` - Multi-stage worker Dockerfile with all variants
- `README.worker.md` - This file
- `../docker-compose.yaml` - Service definitions for all workers
## References
- [Worker Containerization Design](../docs/worker-containerization.md)
- [Quick Start Guide](../docs/worker-containers-quickstart.md)
- [Worker Service Architecture](../docs/architecture/worker-service.md)
- [Production Deployment](../docs/production-deployment.md)
## Quick Commands
```bash
# Build all workers
make docker-build-workers
# Start all workers
docker-compose up -d worker-shell worker-python worker-node worker-full
# Check worker status
docker-compose exec postgres psql -U attune -d attune -c \
"SELECT name, status, capabilities FROM worker;"
# View Python worker logs
docker-compose logs -f worker-python
# Restart worker
docker-compose restart worker-python
# Scale Python workers
docker-compose up -d --scale worker-python=3
# Stop all workers
docker-compose stop worker-shell worker-python worker-node worker-full
```