Files
foxhunt/docker-compose.yml
jgrusewski 83629f9ca8 feat(deployment): Complete Runpod GPU deployment infrastructure
Implement comprehensive Runpod deployment with S3 volume mount architecture for
FP32 ML model training on Tesla V100 GPUs.

## Infrastructure Components

### Deployment Scripts (scripts/)
- runpod_deploy.sh: Master deployment orchestrator (8-step workflow)
- runpod_upload.sh: S3 upload for binaries and test data
- upload_env_to_runpod.sh: Secure .env credentials upload
- runpod_deploy_test.sh: Prerequisites validation

### Docker Configuration
- Dockerfile.runpod: Multi-stage CUDA 12.1 runtime (~2GB, no binaries)
- entrypoint.sh: Volume verification and training execution
- Architecture: Volume mount (NO S3 downloads in pods)

### S3 Configuration
- Bucket: se3zdnb5o4 (Iceland region: eur-is-1)
- Endpoint: https://s3api-eur-is-1.runpod.io
- Structure: binaries/, test_data/, models/, .env

### OpenTofu Infrastructure (terraform/runpod/)
- main.tf: Pod and volume resources
- variables.tf: Configuration variables
- outputs.tf: Pod connection info
- Security: NO credentials in state (uses volume .env)

## Deployment Assets Uploaded

### Training Binaries (77MB)
- train_tft_parquet (23M) - TFT-225 features
- train_mamba2_parquet (22M) - MAMBA-2 state space
- train_dqn (22M) - Deep Q-Network
- train_ppo (13M) - Proximal Policy Optimization

### Test Data (13.8 MB)
- 9 Parquet files: ES.FUT, NQ.FUT, 6E.FUT, ZN.FUT (180-day datasets)

### Credentials
- .env file (1.5 KB, private access, chmod 600)

## Documentation

### Deployment Guides
- RUNPOD_DEPLOYMENT_READY_SUMMARY.md: Complete deployment status
- RUNPOD_VOLUME_DEPLOYMENT_GUIDE.md: Step-by-step guide (42KB)
- RUNPOD_DEPLOYMENT_QUICK_START.md: Quick reference
- RUNPOD_UPLOAD_GUIDE.md: S3 upload instructions
- RUNPOD_VOLUME_CONFIGURATION_COMPLETE.md: S3 setup report
- RUNPOD_S3_PARQUET_UPLOAD_REPORT.md: Data upload verification

### Architecture Documentation
- RUNPOD_VOLUME_MOUNT_ARCHITECTURE.md: Volume mount design
- RUNPOD_S3_ARCHITECTURE_DIAGRAM.txt: S3 API vs filesystem access
- DOCKERFILE_RUNPOD_FINAL_SUMMARY.md: Docker image specification

### Decision Documentation
- RUNPOD_DEPLOYMENT_CHECKLIST.md: Go/no-go decision matrix (27KB)
- RUNPOD_DEPLOYMENT_DECISION_TREE.md: Decision workflow
- FP32_RUNPOD_DEPLOYMENT_READY.md: FP32 deployment readiness

## QAT Enhancements

### Core QAT Infrastructure
- ml/src/memory_optimization/qat.rs: Enhanced QAT observer (+226 lines)
- ml/src/memory_optimization/auto_batch_size.rs: OOM recovery (+84 lines)
- ml/src/tft/qat_tft.rs: QAT TFT wrapper (+154 lines)
- ml/src/trainers/tft.rs: QAT training integration (+433 lines)
- ml/src/qat_metrics_exporter.rs: NEW - QAT metrics export

### QAT Testing
- ml/tests/qat_integration_tests.rs: NEW - Integration test suite
- ml/tests/qat_gradient_clipping_test.rs: NEW - Gradient clipping tests
- ml/tests/qat_device_consistency_test.rs: Device mismatch tests (+205 lines)
- ml/tests/qat_accuracy_validation_test.rs: Accuracy validation
- ml/tests/qat_tft_integration_test.rs: TFT QAT integration

### QAT Documentation
- ml/docs/QAT_GUIDE.md: Comprehensive QAT guide (+616 lines)
- ml/docs/QAT_GRADIENT_CHECKPOINTING_WORKAROUND.md: NEW - Workaround guide
- QAT_BLOCKERS_ROOT_CAUSE_ANALYSIS.md: P0 blocker analysis (44KB)
- QAT_ACCURACY_VALIDATION_REPORT.md: Accuracy comparison
- QAT_GRADIENT_CLIPPING_VALIDATION_REPORT.md: Clipping validation

### QAT Monitoring
- config/grafana/dashboards/qat-training-metrics.json: NEW - Grafana dashboard

## AWS CLI Configuration

### Credentials Setup
- ~/.aws/credentials: Runpod profile configured
  - Access Key: user_2xxA3XcIFj16yfL3aBon9niiSpr
  - Secret Key: (from RUNPOD_S3_SECRET)
- ~/.aws/config: Iceland region (eur-is-1)

## Production Readiness

### FP32 Models:  READY FOR DEPLOYMENT
- DQN: 15-20s training, ~6MB GPU memory
- PPO: 7-10s training, ~145MB GPU memory
- MAMBA-2: 2-3 min training, ~164MB GPU memory
- TFT-225: 3-5 min training, ~500MB GPU memory
- Total GPU Budget: 815MB (fits on 4GB+ Tesla V100)

### QAT Models: 🔴 BLOCKED
- 24 tests implemented but DO NOT COMPILE (11 errors)
- 3 P0 blockers: device mismatch, gradient checkpointing, OOM recovery
- Timeline: 1-2 weeks to fix (13h P0 fixes + validation)

### Wave D Features:  OPERATIONAL
- 225 features fully integrated
- Feature extraction: 5.10μs/bar (196x faster than target)
- Wave D backtest: Sharpe 2.00, Win Rate 60%, Drawdown 15%
- Database migration 045: Applied cleanly, zero conflicts

## Cost Analysis

### One-Time Setup
- Network Volume: $4/month (50GB SSD)
- Upload costs: FREE (S3 API included)

### Per Training Run (TFT-225)
- GPU: Tesla V100-PCIE-16GB @ $0.29/hr
- Training Time: ~4 hours
- Cost per run: $1.16

### Monthly (20 Training Runs)
- Storage: $4.00/month
- Training: $23.20/month (20 runs × $1.16)
- Total: $27.20/month

## Security

### Credentials Management
-  NO credentials in Docker image
-  NO credentials in Terraform state
-  .env gitignored and not committed
-  .env file private on S3 (HTTP 401 on public access)
-  Docker Hub repository PRIVATE (jgrusewski/foxhunt)

### Access Control
- S3 API: Local client uploads only
- Volume mount: Pod filesystem access only
- Authentication: AWS CLI with Runpod profile required

## Next Steps

1.  COMPLETE: Build Docker image
2.  PENDING: Push to Docker Hub
3.  PENDING: Deploy pod via Runpod console
4.  PENDING: Validate training on Tesla V100

## Performance Targets

- Build time: 5-10 min
- Upload time: ~20 sec (90MB total)
- Pod startup: ~30 sec
- Training time: 3-5 min (TFT-225)
- Total deployment: ~40 min from start to first training run

## Test Status

- FP32 tests: 597/608 passing (98.2%)
- QAT tests: 0/24 passing (compilation errors)
- Overall: 2,062/2,086 passing (98.8% excluding QAT)

🤖 Generated with Claude Code (https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-24 01:11:43 +02:00

488 lines
16 KiB
YAML

version: '3.8'
services:
# PostgreSQL - Primary database for SQLx compilation and app data
postgres:
image: timescale/timescaledb:latest-pg16
container_name: foxhunt-postgres
environment:
POSTGRES_DB: foxhunt
POSTGRES_USER: foxhunt
POSTGRES_PASSWORD: foxhunt_dev_password
ports:
- "5432:5432"
volumes:
- postgres_data:/var/lib/postgresql/data
healthcheck:
test: ["CMD-SHELL", "pg_isready -U foxhunt"]
interval: 10s
timeout: 5s
retries: 5
networks:
- foxhunt-network
# Redis - Caching and real-time data
redis:
image: redis:7-alpine
container_name: foxhunt-redis
command: >
redis-server
--maxmemory 2gb
--maxmemory-policy allkeys-lru
ports:
- "6379:6379"
volumes:
- redis_data:/data
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 10s
timeout: 5s
retries: 5
networks:
- foxhunt-network
# InfluxDB - Time-series data for HFT metrics
influxdb:
image: influxdb:2.7-alpine
container_name: foxhunt-influxdb
environment:
DOCKER_INFLUXDB_INIT_MODE: setup
DOCKER_INFLUXDB_INIT_USERNAME: foxhunt
DOCKER_INFLUXDB_INIT_PASSWORD: foxhunt_dev_password
DOCKER_INFLUXDB_INIT_ORG: foxhunt
DOCKER_INFLUXDB_INIT_BUCKET: trading_metrics
DOCKER_INFLUXDB_INIT_RETENTION: 30d
ports:
- "8086:8086"
volumes:
- influxdb_data:/var/lib/influxdb2
healthcheck:
test: ["CMD", "influx", "ping"]
interval: 30s
timeout: 10s
retries: 5
networks:
- foxhunt-network
# HashiCorp Vault - Secrets management
vault:
image: hashicorp/vault:1.15
container_name: foxhunt-vault
environment:
VAULT_ADDR: http://0.0.0.0:8200
VAULT_DEV_ROOT_TOKEN_ID: foxhunt-dev-root
ports:
- "8200:8200"
volumes:
- vault_data:/vault/data
cap_add:
- IPC_LOCK
command: vault server -dev -dev-listen-address=0.0.0.0:8200
healthcheck:
test: ["CMD", "vault", "status"]
interval: 30s
timeout: 10s
retries: 5
networks:
- foxhunt-network
# Prometheus - HFT Metrics Collection
prometheus:
image: prom/prometheus:latest
container_name: foxhunt-prometheus
ports:
- "9090:9090"
volumes:
- prometheus_data:/prometheus
- ./config/prometheus/prometheus.yml:/etc/prometheus/prometheus.yml:ro
- ./config/prometheus/rules:/etc/prometheus/rules:ro
command:
- '--config.file=/etc/prometheus/prometheus.yml'
- '--storage.tsdb.path=/prometheus'
- '--storage.tsdb.retention.time=15d'
- '--web.enable-lifecycle'
- '--query.max-concurrency=50'
healthcheck:
test: ["CMD", "wget", "--no-verbose", "--tries=1", "--spider", "http://localhost:9090/-/healthy"]
interval: 30s
timeout: 10s
retries: 5
networks:
- foxhunt-network
# Grafana - HFT Trading Dashboards
grafana:
image: grafana/grafana:latest
container_name: foxhunt-grafana
ports:
- "3000:3000"
volumes:
- grafana_data:/var/lib/grafana
- ./config/grafana/dashboards:/var/lib/grafana/dashboards:ro
- ./config/grafana/provisioning:/etc/grafana/provisioning:ro
environment:
- GF_SECURITY_ADMIN_PASSWORD=foxhunt123
- GF_USERS_ALLOW_SIGN_UP=false
- GF_DASHBOARDS_DEFAULT_HOME_DASHBOARD_PATH=/var/lib/grafana/dashboards/hft-trading-performance.json
depends_on:
prometheus:
condition: service_healthy
healthcheck:
test: ["CMD-SHELL", "wget --no-verbose --tries=1 --spider http://localhost:3000/api/health || exit 1"]
interval: 30s
timeout: 10s
retries: 5
networks:
- foxhunt-network
# MinIO - S3-compatible object storage for model checkpoints and training data
minio:
image: minio/minio:latest
container_name: foxhunt-minio
ports:
- "9000:9000" # API endpoint
- "9001:9001" # Console UI
environment:
MINIO_ROOT_USER: foxhunt
MINIO_ROOT_PASSWORD: foxhunt_dev_password
MINIO_REGION_NAME: us-east-1
command: server /data --console-address ":9001"
volumes:
- minio_data:/data
healthcheck:
test: ["CMD", "mc", "ready", "local"]
interval: 10s
timeout: 5s
retries: 5
networks:
- foxhunt-network
# =========================================================================
# Application Services (gRPC microservices)
# =========================================================================
# Trading Service - Core trading logic (port 50052)
trading_service:
build:
context: .
dockerfile: services/trading_service/Dockerfile
container_name: foxhunt-trading-service
env_file:
- .env # Load JWT_SECRET and other config from .env (Wave 147)
ports:
- "50052:50051" # Map external 50052 to internal 50051
- "9092:9092" # Metrics
environment:
- DATABASE_URL=postgresql://foxhunt:foxhunt_dev_password@postgres:5432/foxhunt
- REDIS_URL=redis://redis:6379
- VAULT_ADDR=http://vault:8200
- VAULT_TOKEN=foxhunt-dev-root
- JWT_SECRET=${JWT_SECRET:-dev_secret_key_change_in_production}
- JWT_ISSUER=foxhunt-api-gateway
- JWT_AUDIENCE=foxhunt-services
# TLS Configuration - Wave H1 mTLS implementation
- TLS_ENABLED=${TLS_ENABLED:-false}
- TLS_PROTOCOL_VERSION=${TLS_PROTOCOL_VERSION:-TLS13}
- TLS_REQUIRE_CLIENT_CERT=${TLS_REQUIRE_CLIENT_CERT:-true}
- TLS_CERT_PATH=/tmp/foxhunt/certs/server-cert.pem
- TLS_KEY_PATH=/tmp/foxhunt/certs/server-key.pem
- TLS_CA_PATH=/tmp/foxhunt/certs/ca/ca-cert.pem
# mTLS Validation Options
- MTLS_ENABLE_REVOCATION_CHECK=${MTLS_ENABLE_REVOCATION_CHECK:-false}
- MTLS_CRL_URL=${MTLS_CRL_URL:-}
- KILL_SWITCH_SOCKET_PATH=/tmp/kill_switch.sock
- GRPC_PORT=50051
- RUST_LOG=info
- RUST_BACKTRACE=1
volumes:
- ./certs:/tmp/foxhunt/certs:ro
depends_on:
postgres:
condition: service_healthy
redis:
condition: service_healthy
vault:
condition: service_healthy
healthcheck:
test: ["CMD", "/usr/local/bin/grpc_health_probe", "-addr=localhost:50051"]
interval: 10s
timeout: 5s
start_period: 30s
retries: 3
networks:
- foxhunt-network
restart: unless-stopped
# Backtesting Service - Strategy testing (port 50053)
backtesting_service:
build:
context: .
dockerfile: services/backtesting_service/Dockerfile
container_name: foxhunt-backtesting-service
env_file:
- .env # Load JWT_SECRET and other config from .env (Wave 147)
ports:
- "50053:50053" # Map external 50053 to internal 50053
- "9093:9093" # Metrics
- "8083:8082" # Health check endpoint
environment:
- DATABASE_URL=postgresql://foxhunt:foxhunt_dev_password@postgres:5432/foxhunt
- REDIS_URL=redis://redis:6379
- VAULT_ADDR=http://vault:8200
- VAULT_TOKEN=foxhunt-dev-root
- JWT_SECRET=${JWT_SECRET:-dev_secret_key_change_in_production}
- JWT_ISSUER=foxhunt-api-gateway
- JWT_AUDIENCE=foxhunt-services
- BENZINGA_API_KEY=${BENZINGA_API_KEY:-demo_key_please_replace}
# DBN Data Configuration - Wave 153 Real Data Integration
- USE_DBN_DATA=${USE_DBN_DATA:-false}
- DBN_SYMBOL_MAPPINGS=${DBN_SYMBOL_MAPPINGS:-ES.FUT:/workspace/test_data/real/databento/ES.FUT_ohlcv-1m_2024-01-02.dbn}
- DBN_SYMBOL_MAP=${DBN_SYMBOL_MAP:-BTC/USD:ES.FUT,ETH/USD:ES.FUT}
# TLS Configuration - Wave H1 mTLS implementation (updated)
- TLS_ENABLED=${TLS_ENABLED:-false}
- TLS_PROTOCOL_VERSION=${TLS_PROTOCOL_VERSION:-TLS13}
- TLS_REQUIRE_CLIENT_CERT=${TLS_REQUIRE_CLIENT_CERT:-true}
- TLS_CERT_PATH=/tmp/foxhunt/certs/server-cert.pem
- TLS_KEY_PATH=/tmp/foxhunt/certs/server-key.pem
- TLS_CA_PATH=/tmp/foxhunt/certs/ca/ca-cert.pem
# mTLS Validation Options
- MTLS_ENABLE_REVOCATION_CHECK=${MTLS_ENABLE_REVOCATION_CHECK:-false}
- MTLS_CRL_URL=${MTLS_CRL_URL:-}
- RUST_LOG=info
- RUST_BACKTRACE=1
volumes:
- ./certs:/tmp/foxhunt/certs:ro
- ./test_data:/workspace/test_data:ro
depends_on:
postgres:
condition: service_healthy
redis:
condition: service_healthy
vault:
condition: service_healthy
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8082/health"]
interval: 10s
timeout: 5s
start_period: 30s
retries: 3
networks:
- foxhunt-network
restart: unless-stopped
# ML Training Service - Model training with GPU acceleration (port 50054)
ml_training_service:
build:
context: .
dockerfile: services/ml_training_service/Dockerfile
container_name: foxhunt-ml-training-service
runtime: nvidia
env_file:
- .env # Load JWT_SECRET and other config from .env (Wave 147)
ports:
- "50054:50053" # Map external 50054 to internal 50053
- "9094:9094" # Metrics
- "8095:8080" # Health endpoint (unique host port)
environment:
- DATABASE_URL=postgresql://foxhunt:foxhunt_dev_password@postgres:5432/foxhunt
- REDIS_URL=redis://redis:6379
- VAULT_ADDR=http://vault:8200
- VAULT_TOKEN=foxhunt-dev-root
- JWT_SECRET=${JWT_SECRET:-dev_secret_key_change_in_production}
- JWT_ISSUER=foxhunt-api-gateway
- JWT_AUDIENCE=foxhunt-services
# GPU Configuration
- NVIDIA_VISIBLE_DEVICES=all
- NVIDIA_DRIVER_CAPABILITIES=compute,utility
- CUDA_VISIBLE_DEVICES=0
# MinIO Configuration for Model Storage
- S3_ENDPOINT=http://minio:9000
- S3_ACCESS_KEY=foxhunt
- S3_SECRET_KEY=foxhunt_dev_password
- S3_BUCKET=ml-models
- S3_REGION=us-east-1
# Hyperparameter Tuning Configuration
- OPTUNA_STORAGE=postgresql://foxhunt:foxhunt_dev_password@postgres:5432/foxhunt
- OPTUNA_STUDY_NAME=${OPTUNA_STUDY_NAME:-foxhunt-hpt}
- OPTUNA_N_TRIALS=${OPTUNA_N_TRIALS:-100}
# TLS Configuration - Wave H1 mTLS implementation (updated)
- TLS_ENABLED=${TLS_ENABLED:-false}
- TLS_PROTOCOL_VERSION=${TLS_PROTOCOL_VERSION:-TLS13}
- TLS_REQUIRE_CLIENT_CERT=${TLS_REQUIRE_CLIENT_CERT:-true}
- TLS_CERT_PATH=/tmp/foxhunt/certs/server-cert.pem
- TLS_KEY_PATH=/tmp/foxhunt/certs/server-key.pem
- TLS_CA_PATH=/tmp/foxhunt/certs/ca/ca-cert.pem
# mTLS Validation Options
- MTLS_ENABLE_REVOCATION_CHECK=${MTLS_ENABLE_REVOCATION_CHECK:-false}
- MTLS_CRL_URL=${MTLS_CRL_URL:-}
# Logging
- RUST_LOG=info
- RUST_BACKTRACE=1
volumes:
- ./certs:/tmp/foxhunt/certs:ro
- ./models:/tmp/foxhunt/models
- ./checkpoints:/tmp/foxhunt/checkpoints
# Training data mounts
- ./test_data/real/databento/ml_training:/data/training:ro
- ./tuning_config.yaml:/app/tuning_config.yaml:ro
- ./optuna_studies:/app/optuna_studies
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: 1
capabilities: [gpu]
depends_on:
postgres:
condition: service_healthy
redis:
condition: service_healthy
vault:
condition: service_healthy
minio:
condition: service_healthy
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8080/health"]
interval: 10s
timeout: 5s
start_period: 30s
retries: 3
networks:
- foxhunt-network
restart: unless-stopped
# Trading Agent Service - Portfolio management (port 50055)
trading_agent_service:
build:
context: .
dockerfile: services/trading_agent_service/Dockerfile
container_name: foxhunt-trading-agent-service
env_file:
- .env
ports:
- "50055:50055" # gRPC
- "8084:8083" # Health (external 8084 -> internal 8083)
- "9095:9095" # Metrics
environment:
- DATABASE_URL=postgresql://foxhunt:foxhunt_dev_password@postgres:5432/foxhunt
- REDIS_URL=redis://redis:6379
- VAULT_ADDR=http://vault:8200
- VAULT_TOKEN=foxhunt-dev-root
- JWT_SECRET=${JWT_SECRET:-dev_secret_key_change_in_production}
# TLS Configuration - Wave H1 mTLS implementation
- TLS_ENABLED=${TLS_ENABLED:-false}
- TLS_PROTOCOL_VERSION=${TLS_PROTOCOL_VERSION:-TLS13}
- TLS_REQUIRE_CLIENT_CERT=${TLS_REQUIRE_CLIENT_CERT:-true}
- TLS_CERT_PATH=/tmp/foxhunt/certs/server-cert.pem
- TLS_KEY_PATH=/tmp/foxhunt/certs/server-key.pem
- TLS_CA_PATH=/tmp/foxhunt/certs/ca/ca-cert.pem
# mTLS Validation Options
- MTLS_ENABLE_REVOCATION_CHECK=${MTLS_ENABLE_REVOCATION_CHECK:-false}
- MTLS_CRL_URL=${MTLS_CRL_URL:-}
- RUST_LOG=info
- RUST_BACKTRACE=1
volumes:
- ./certs:/tmp/foxhunt/certs:ro
depends_on:
postgres:
condition: service_healthy
redis:
condition: service_healthy
vault:
condition: service_healthy
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8083/health"]
interval: 10s
timeout: 5s
start_period: 30s
retries: 3
networks:
- foxhunt-network
restart: unless-stopped
# API Gateway - Auth + routing (port 50051)
api_gateway:
build:
context: .
dockerfile: services/api_gateway/Dockerfile
container_name: foxhunt-api-gateway
env_file:
- .env # Load JWT_SECRET and other config from .env (Wave 147)
ports:
- "50051:50050" # Map external 50051 to internal 50050
- "9091:9091" # Metrics
environment:
- GATEWAY_BIND_ADDR=0.0.0.0:50050
- DATABASE_URL=postgresql://foxhunt:foxhunt_dev_password@postgres:5432/foxhunt
- REDIS_URL=redis://redis:6379
- VAULT_ADDR=http://vault:8200
- VAULT_TOKEN=foxhunt-dev-root
- TRADING_SERVICE_URL=http://trading_service:50051
- BACKTESTING_SERVICE_URL=https://backtesting_service:50053
- ML_TRAINING_SERVICE_URL=https://ml_training_service:50053
- JWT_SECRET=${JWT_SECRET:-dev_secret_key_change_in_production}
- JWT_ISSUER=foxhunt-api-gateway
- JWT_AUDIENCE=foxhunt-services
# TLS Certificate Configuration for Backtesting Service (mTLS)
# Using dev CA-signed certificates (matching Backtesting Service CA)
- BACKTESTING_TLS_CA_CERT=/tmp/foxhunt/certs/ca/ca-cert.pem
- BACKTESTING_TLS_CLIENT_CERT=/tmp/foxhunt/certs/client-cert.pem
- BACKTESTING_TLS_CLIENT_KEY=/tmp/foxhunt/certs/client-key.pem
# TLS Certificate Configuration for ML Training Service (mTLS)
# Using dev CA-signed certificates (matching ML Training Service CA)
- ML_TRAINING_TLS_CA_CERT=/tmp/foxhunt/certs/ca/ca-cert.pem
- ML_TRAINING_TLS_CLIENT_CERT=/tmp/foxhunt/certs/client-cert.pem
- ML_TRAINING_TLS_CLIENT_KEY=/tmp/foxhunt/certs/client-key.pem
# TLS Server Configuration - Wave H1 mTLS implementation
- TLS_ENABLED=${TLS_ENABLED:-false}
- TLS_PROTOCOL_VERSION=${TLS_PROTOCOL_VERSION:-TLS13}
- TLS_REQUIRE_CLIENT_CERT=${TLS_REQUIRE_CLIENT_CERT:-true}
- TLS_CERT_PATH=/tmp/foxhunt/certs/server-cert.pem
- TLS_KEY_PATH=/tmp/foxhunt/certs/server-key.pem
- TLS_CA_PATH=/tmp/foxhunt/certs/ca/ca-cert.pem
# mTLS Validation Options
- MTLS_ENABLE_REVOCATION_CHECK=${MTLS_ENABLE_REVOCATION_CHECK:-false}
- MTLS_CRL_URL=${MTLS_CRL_URL:-}
# Service Configuration
- RATE_LIMIT_RPS=100
- ENABLE_AUDIT_LOGGING=true
- RUST_LOG=info
- RUST_BACKTRACE=1
volumes:
- ./certs:/tmp/foxhunt/certs:ro
depends_on:
postgres:
condition: service_healthy
redis:
condition: service_healthy
vault:
condition: service_healthy
trading_service:
condition: service_healthy
backtesting_service:
condition: service_healthy
ml_training_service:
condition: service_healthy
healthcheck:
test: ["CMD", "/usr/local/bin/grpc_health_probe", "-addr=localhost:50050"]
interval: 10s
timeout: 5s
start_period: 30s
retries: 3
networks:
- foxhunt-network
restart: unless-stopped
volumes:
postgres_data:
redis_data:
influxdb_data:
vault_data:
prometheus_data:
grafana_data:
minio_data:
networks:
foxhunt-network:
driver: bridge