fetch_ml/deployments/configs/worker/docker-dev.yaml
Jeremie Fraeys b3a0c78903
config: add Plugin GPU Quota, plugins, and audit logging to configs
- Add Plugin GPU Quota config section to scheduler.yaml.example

- Add audit logging config to homelab-secure.yaml (HIPAA-compliant)

- Add Jupyter and vLLM plugin configs to all worker configs:

  - Security settings (passwords, trusted channels, blocked packages)

  - Resource limits (GPU, memory, CPU)

  - Model cache paths and quantization options for vLLM

- Disable plugins in HIPAA deployment mode for compliance

- Update deployments README with plugin services and GPU quotas
2026-02-26 14:34:42 -05:00

58 lines
1.4 KiB
YAML

# Development mode worker configuration
# Relaxed validation for fast iteration
host: localhost
port: 22
user: dev-user
base_path: /tmp/fetchml_dev
train_script: train.py
# Redis configuration
redis_url: redis://redis:6379
# Development mode - relaxed security
compliance_mode: dev
max_workers: 4
# Sandbox settings (relaxed for development)
sandbox:
network_mode: bridge
seccomp_profile: ""
no_new_privileges: false
allowed_secrets: [] # All secrets allowed in dev
# GPU configuration
gpu_vendor: none
# Artifact handling (relaxed limits)
max_artifact_files: 10000
max_artifact_total_bytes: 1073741824 # 1GB
# Provenance (disabled in dev for speed)
provenance_best_effort: false
# Plugin Configuration (development mode)
plugins:
# Jupyter Notebook/Lab Service
jupyter:
enabled: true
image: "quay.io/jupyter/base-notebook:latest"
default_port: 8888
mode: "lab"
security:
trusted_channels:
- "conda-forge"
- "defaults"
blocked_packages: [] # No restrictions in dev
require_password: false # No password for dev
max_gpu_per_instance: 1
max_memory_per_instance: "4Gi"
# vLLM Inference Service
vllm:
enabled: true
image: "vllm/vllm-openai:latest"
default_port: 8000
model_cache: "/tmp/models" # Temp location for dev
default_quantization: "" # No quantization for dev
max_gpu_per_instance: 1
max_model_len: 2048