production-guide.md•4.5 kB
# Production Deployment Guide
## 🏗️ Infrastructure Recommendations
### Container Orchestration
```yaml
# kubernetes-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: mcp-mssql-server
spec:
replicas: 3
selector:
matchLabels:
app: mcp-mssql-server
template:
metadata:
labels:
app: mcp-mssql-server
spec:
containers:
- name: mcp-mssql-server
image: mcp-mssql-server:latest
resources:
limits:
memory: "512Mi"
cpu: "500m"
requests:
memory: "256Mi"
cpu: "250m"
env:
- name: NODE_ENV
value: "production"
- name: LOG_LEVEL
value: "warn"
```
### Load Balancer Configuration
- Use NGINX or HAProxy for load balancing
- Implement health checks on `/health` endpoint
- Configure connection pooling at infrastructure level
### Monitoring Stack
- **Prometheus**: Metrics collection
- **Grafana**: Dashboards and alerting
- **Jaeger**: Distributed tracing
- **ELK Stack**: Centralized logging
## 🔒 Security Checklist
### Network Security
- [ ] Use VPN or private networks for database connections
- [ ] Implement TLS/SSL encryption for all connections
- [ ] Configure firewall rules to restrict access
- [ ] Use Azure Private Endpoints or AWS PrivateLink
### Authentication & Authorization
- [ ] Implement Azure AD or Active Directory integration
- [ ] Use service principals instead of SQL authentication
- [ ] Rotate connection credentials regularly
- [ ] Implement role-based access control (RBAC)
### Data Protection
- [ ] Enable database encryption at rest
- [ ] Use encrypted connection strings in environment variables
- [ ] Implement data masking for sensitive fields
- [ ] Regular security vulnerability scanning
## 📊 Performance Optimization
### Database Tuning
```sql
-- Recommended database settings
ALTER DATABASE MCPTest SET AUTO_CREATE_STATISTICS ON
ALTER DATABASE MCPTest SET AUTO_UPDATE_STATISTICS ON
ALTER DATABASE MCPTest SET PAGE_VERIFY CHECKSUM
```
### Connection Optimization
```typescript
const optimizedPoolConfig = {
max: 20, // Adjust based on database limits
min: 2, // Keep minimum connections warm
idleTimeoutMillis: 30000,
acquireTimeoutMillis: 60000,
createTimeoutMillis: 30000,
destroyTimeoutMillis: 5000,
reapIntervalMillis: 1000,
createRetryIntervalMillis: 200
};
```
## 🚀 CI/CD Pipeline
### GitHub Actions Workflow
```yaml
name: MCP MSSQL Server CI/CD
on:
push:
branches: [main]
pull_request:
branches: [main]
jobs:
test:
runs-on: ubuntu-latest
services:
mssql:
image: mcr.microsoft.com/mssql/server:2022-latest
env:
ACCEPT_EULA: Y
SA_PASSWORD: ${{ secrets.SA_PASSWORD }}
options: >-
--health-cmd "/opt/mssql-tools18/bin/sqlcmd -C -S localhost -U sa -P $SA_PASSWORD -Q 'SELECT 1'"
--health-interval 10s
--health-timeout 3s
--health-retries 10
steps:
- uses: actions/checkout@v3
- uses: actions/setup-node@v3
with:
node-version: '18'
- run: npm ci
- run: npm run build
- run: npm test
- run: npm run test:integration
build-and-push:
needs: test
runs-on: ubuntu-latest
if: github.ref == 'refs/heads/main'
steps:
- uses: actions/checkout@v3
- name: Build and push Docker image
env:
REGISTRY: ghcr.io
IMAGE_NAME: ${{ github.repository }}
run: |
echo ${{ secrets.GITHUB_TOKEN }} | docker login $REGISTRY -u ${{ github.actor }} --password-stdin
docker build -t $REGISTRY/$IMAGE_NAME:latest .
docker push $REGISTRY/$IMAGE_NAME:latest
```
## 🔄 High Availability Setup
### Multi-Region Deployment
- Deploy MCP servers in multiple Azure regions
- Use Azure SQL Database with geo-replication
- Implement intelligent routing based on latency
### Disaster Recovery
- Automated database backups every 6 hours
- Cross-region backup replication
- Documented recovery procedures (RTO: 15 min, RPO: 1 hour)
## 📈 Scaling Recommendations
### Horizontal Scaling
- Deploy multiple MCP server instances behind load balancer
- Use Azure Container Instances or AWS Fargate for auto-scaling
- Implement connection pooling at application level
### Database Scaling
- Use Azure SQL Database elastic pools
- Implement read replicas for query distribution
- Consider sharding for very large datasets