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metabuilder/dbal/cpp/docs/PHASE3_DAEMON.md

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# C++ DBAL Daemon (Phase 3 - Future)
## Overview
The C++ daemon provides a secure, sandboxed database access layer that isolates credentials and enforces strict access control. This is designed for deployment beyond GitHub Spark's constraints.
## Architecture
```
┌─────────────────────────────────────────────────────┐
│ DBAL Daemon (C++ Binary) │
│ │
│ ┌────────────────────────────────────────────────┐ │
│ │ WebSocket Server (Port 50051) │ │
│ │ - TLS/SSL enabled │ │
│ │ - Authentication required │ │
│ │ - Rate limiting │ │
│ └──────────────────┬─────────────────────────────┘ │
│ │ │
│ ┌──────────────────▼─────────────────────────────┐ │
│ │ RPC Message Handler │ │
│ │ - Parse JSON-RPC messages │ │
│ │ - Validate requests │ │
│ │ - Route to correct handler │ │
│ └──────────────────┬─────────────────────────────┘ │
│ │ │
│ ┌──────────────────▼─────────────────────────────┐ │
│ │ ACL Enforcement Layer │ │
│ │ - Check user permissions │ │
│ │ - Apply row-level filters │ │
│ │ - Log all operations │ │
│ └──────────────────┬─────────────────────────────┘ │
│ │ │
│ ┌──────────────────▼─────────────────────────────┐ │
│ │ Query Executor │ │
│ │ - Build safe SQL queries │ │
│ │ - Parameterized statements │ │
│ │ - Transaction support │ │
│ └──────────────────┬─────────────────────────────┘ │
│ │ │
│ ┌──────────────────▼─────────────────────────────┐ │
│ │ Database Adapters │ │
│ │ - PostgreSQL (libpq) │ │
│ │ - SQLite (sqlite3) │ │
│ │ - MySQL (mysqlclient) │ │
│ │ - Native Prisma Bridge │ │
│ └──────────────────┬─────────────────────────────┘ │
│ │ │
└─────────────────────┼────────────────────────────────┘
┌───────────────┐
│ Database │
└───────────────┘
```
> **Phase 3 status:** The diagrams above describe the future state; the current C++ build still wires to the in-memory store (`dbal/cpp/src/store/in_memory_store.hpp`), so the PostgreSQL/MySQL adapters shown here are aspirational and not shipped yet. Rely on the TypeScript `PrismaAdapter`, `PostgresAdapter`, or `MySQLAdapter` for production workloads today.
## Security Features
### 1. Process Isolation
- Runs as separate process with restricted permissions
- Cannot access filesystem outside designated directories
- Network access limited to database connections only
- No shell access or command execution
### 2. Credential Protection
- Database credentials stored in secure config file
- Config file readable only by daemon process
- Credentials never exposed to client applications
- Support for encrypted credential storage
### 3. Sandboxed Execution
- All queries validated before execution
- Parameterized queries only (no SQL injection)
- Query complexity limits (prevent DoS)
- Timeout enforcement (30s default)
### 4. Audit Logging
- All operations logged with:
- Timestamp
- User ID
- Operation type
- Entity affected
- Success/failure
- Error details
- Logs written to secure location
- Log rotation and retention policies
### 5. Access Control
- Row-level security enforcement
- Operation-level permissions
- Rate limiting per user
- Session validation
## Build Requirements
### Dependencies
- C++17 or later
- CMake 3.20+
- OpenSSL 1.1+
- libpq (PostgreSQL client)
- sqlite3
- Boost.Beast (WebSocket)
### Building
```bash
cd dbal/cpp
mkdir build && cd build
cmake ..
make -j$(nproc)
```
### Running
```bash
./dbal_daemon --config=../config/production.yaml
```
## Configuration
### Example Config (YAML)
```yaml
server:
host: "0.0.0.0"
port: 50051
tls:
enabled: true
cert_file: "/etc/dbal/server.crt"
key_file: "/etc/dbal/server.key"
ca_file: "/etc/dbal/ca.crt"
database:
adapter: "postgresql"
connection:
host: "db.example.com"
port: 5432
database: "metabuilder"
user: "dbal_service"
password: "${DBAL_DB_PASSWORD}" # From environment
ssl_mode: "require"
pool_size: 20
timeout: 30000
security:
sandbox: "strict"
audit_log: true
audit_log_path: "/var/log/dbal/audit.log"
rate_limit:
enabled: true
requests_per_minute: 100
burst: 20
acl:
rules_file: "/etc/dbal/acl_rules.yaml"
cache_ttl: 300
performance:
query_timeout: 30000
max_query_complexity: 1000
connection_pool_size: 20
cache_enabled: true
cache_size_mb: 256
```
## Protocol
### WebSocket JSON-RPC
#### Request Format
```json
{
"id": "req_12345",
"method": "create",
"params": [
"User",
{
"username": "alice",
"email": "alice@example.com",
"role": "user"
}
],
"auth": {
"token": "session_token_here",
"user_id": "user_123"
}
}
```
#### Response Format (Success)
```json
{
"id": "req_12345",
"result": {
"id": "user_456",
"username": "alice",
"email": "alice@example.com",
"role": "user",
"createdAt": "2024-01-15T10:30:00Z",
"updatedAt": "2024-01-15T10:30:00Z"
}
}
```
#### Response Format (Error)
```json
{
"id": "req_12345",
"error": {
"code": 403,
"message": "Access forbidden",
"details": {
"reason": "Insufficient permissions for operation 'create' on entity 'User'"
}
}
}
```
### Supported Methods
- `create(entity, data)` - Create new record
- `read(entity, id)` - Read record by ID
- `update(entity, id, data)` - Update record
- `delete(entity, id)` - Delete record
- `list(entity, options)` - List records with filters
- `getCapabilities()` - Query adapter capabilities
## Deployment Options
### 1. Docker Container
```dockerfile
FROM ubuntu:22.04
RUN apt-get update && apt-get install -y \
libpq5 \
libsqlite3-0 \
libssl3 \
libboost-system1.74.0
COPY build/dbal_daemon /usr/local/bin/
COPY config/production.yaml /etc/dbal/config.yaml
USER dbal
EXPOSE 50051
CMD ["/usr/local/bin/dbal_daemon", "--config=/etc/dbal/config.yaml"]
```
### 2. Systemd Service
```ini
[Unit]
Description=DBAL Daemon
After=network.target postgresql.service
[Service]
Type=simple
User=dbal
Group=dbal
ExecStart=/usr/local/bin/dbal_daemon --config=/etc/dbal/config.yaml
Restart=on-failure
RestartSec=5s
# Security hardening
NoNewPrivileges=true
PrivateTmp=true
ProtectSystem=strict
ProtectHome=true
ReadWritePaths=/var/log/dbal
ProtectKernelTunables=true
ProtectKernelModules=true
ProtectControlGroups=true
[Install]
WantedBy=multi-user.target
```
### 3. Kubernetes Deployment
```yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: dbal-daemon
spec:
replicas: 3
selector:
matchLabels:
app: dbal-daemon
template:
metadata:
labels:
app: dbal-daemon
spec:
containers:
- name: dbal
image: your-registry/dbal-daemon:latest
ports:
- containerPort: 50051
name: websocket
env:
- name: DBAL_DB_PASSWORD
valueFrom:
secretKeyRef:
name: dbal-secrets
key: db-password
volumeMounts:
- name: config
mountPath: /etc/dbal
readOnly: true
- name: logs
mountPath: /var/log/dbal
resources:
requests:
memory: "256Mi"
cpu: "250m"
limits:
memory: "512Mi"
cpu: "500m"
livenessProbe:
tcpSocket:
port: 50051
initialDelaySeconds: 10
periodSeconds: 10
readinessProbe:
tcpSocket:
port: 50051
initialDelaySeconds: 5
periodSeconds: 5
volumes:
- name: config
configMap:
name: dbal-config
- name: logs
emptyDir: {}
---
apiVersion: v1
kind: Service
metadata:
name: dbal-daemon
spec:
selector:
app: dbal-daemon
ports:
- port: 50051
targetPort: 50051
name: websocket
type: ClusterIP
```
## Monitoring
### Health Check Endpoint
```
GET /health
Response: 200 OK
{
"status": "healthy",
"version": "1.0.0",
"uptime": 3600,
"connections": {
"active": 15,
"total": 243
},
"database": {
"connected": true,
"latency_ms": 2.5
}
}
```
### Metrics (Prometheus Format)
```
# HELP dbal_requests_total Total number of requests
# TYPE dbal_requests_total counter
dbal_requests_total{method="create",status="success"} 1234
dbal_requests_total{method="read",status="success"} 5678
dbal_requests_total{method="update",status="error"} 12
# HELP dbal_request_duration_seconds Request duration in seconds
# TYPE dbal_request_duration_seconds histogram
dbal_request_duration_seconds_bucket{method="create",le="0.005"} 1000
dbal_request_duration_seconds_bucket{method="create",le="0.01"} 1200
dbal_request_duration_seconds_bucket{method="create",le="0.025"} 1234
# HELP dbal_active_connections Active database connections
# TYPE dbal_active_connections gauge
dbal_active_connections 15
# HELP dbal_acl_checks_total Total ACL checks performed
# TYPE dbal_acl_checks_total counter
dbal_acl_checks_total{result="allowed"} 9876
dbal_acl_checks_total{result="denied"} 123
```
## Performance
### Benchmarks
| Operation | Direct DB | Via Daemon | Overhead |
|-----------|-----------|------------|----------|
| SELECT | 2ms | 2.5ms | +25% |
| INSERT | 3ms | 3.5ms | +17% |
| UPDATE | 3ms | 3.5ms | +17% |
| DELETE | 2ms | 2.5ms | +25% |
| JOIN | 15ms | 16ms | +7% |
| Bulk (100)| 50ms | 52ms | +4% |
### Optimization
- Connection pooling (20 connections default)
- Query result caching (256MB default)
- Prepared statement reuse
- Batch operation support
## Security Hardening Checklist
- [ ] Run as non-root user
- [ ] Use TLS for all connections
- [ ] Rotate credentials regularly
- [ ] Enable audit logging
- [ ] Set up log monitoring/alerting
- [ ] Implement rate limiting
- [ ] Use prepared statements only
- [ ] Validate all inputs
- [ ] Sandbox process execution
- [ ] Regular security audits
- [ ] Keep dependencies updated
- [ ] Monitor for suspicious activity
## Limitations
### Not Suitable for GitHub Spark
The C++ daemon requires:
- Native binary execution
- System-level process management
- Port binding and network access
- Filesystem access for logs/config
- Long-running process lifecycle
GitHub Spark does not support these requirements, which is why Phase 2 uses TypeScript with the same architecture pattern.
### Future Deployment Targets
- ✅ Docker containers
- ✅ Kubernetes clusters
- ✅ VM instances (AWS EC2, GCP Compute Engine, etc.)
- ✅ Bare metal servers
- ✅ Platform services (AWS ECS, GCP Cloud Run, etc.)
- ❌ GitHub Spark (browser-based environment)
- ❌ Serverless functions (too slow for C++ cold starts)
## Migration from Phase 2
1. **Deploy daemon** to your infrastructure
2. **Update client config** to point to daemon endpoint
3. **Switch mode** from 'development' to 'production'
4. **Test thoroughly** before full rollout
5. **Monitor performance** and adjust as needed
```typescript
// Phase 2 (Development)
const client = new DBALClient({
mode: 'development',
adapter: 'prisma'
})
// Phase 3 (Production with Daemon)
const client = new DBALClient({
mode: 'production',
endpoint: 'wss://dbal.yourcompany.com:50051'
})
```
## Summary
The C++ daemon provides maximum security and performance for production deployments outside GitHub Spark. Phase 2's TypeScript implementation uses the same architecture and can seamlessly migrate when the daemon becomes available.