# Deployment Improvements

## 1. CI/CD Pipeline

### Current Issues

- **No Automated Testing**: Tests not run automatically on commits
- **No Code Quality Checks**: No automated linting or type checking
- **No Security Scanning**: No automated security vulnerability scanning
- **No Deployment Automation**: Manual deployment processes
- **No Environment Management**: No proper environment configuration management

### Proposed Solutions

#### GitHub Actions Workflow

```yaml
# .github/workflows/ci-cd.yml
name: CI/CD Pipeline

on:
  push:
    branches: [ main, develop ]
  pull_request:
    branches: [ main ]

jobs:
  test:
    runs-on: ubuntu-latest
    strategy:
      matrix:
        python-version: [3.10, 3.11]
    
    steps:
    - uses: actions/checkout@v4
    
    - name: Set up Python ${{ matrix.python-version }}
      uses: actions/setup-python@v4
      with:
        python-version: ${{ matrix.python-version }}
    
    - name: Install dependencies
      run: |
        python -m pip install --upgrade pip
        pip install -r requirements.txt
        pip install -r requirements-dev.txt
    
    - name: Run linting
      run: |
        ruff check arklex/
        black --check arklex/
        mypy arklex/
    
    - name: Run tests
      run: |
        pytest tests/ --cov=arklex --cov-report=xml
    
    - name: Upload coverage to Codecov
      uses: codecov/codecov-action@v3
      with:
        file: ./coverage.xml

  security:
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v4
    
    - name: Set up Python
      uses: actions/setup-python@v4
      with:
        python-version: 3.11
    
    - name: Run security scans
      run: |
        pip install bandit safety
        bandit -r arklex/ -f json -o bandit-report.json
        safety check
    
    - name: Upload security report
      uses: actions/upload-artifact@v3
      with:
        name: security-report
        path: bandit-report.json

  build:
    needs: [test, security]
    runs-on: ubuntu-latest
    if: github.ref == 'refs/heads/main'
    
    steps:
    - uses: actions/checkout@v4
    
    - name: Set up Docker Buildx
      uses: docker/setup-buildx-action@v2
    
    - name: Build and push Docker image
      uses: docker/build-push-action@v4
      with:
        context: .
        push: true
        tags: ${{ secrets.DOCKER_REGISTRY }}/arklex:${{ github.sha }}
        cache-from: type=gha
        cache-to: type=gha,mode=max
```

#### Docker Configuration

```dockerfile
# Dockerfile
FROM python:3.11-slim

# Set environment variables
ENV PYTHONDONTWRITEBYTECODE=1
ENV PYTHONUNBUFFERED=1
ENV PYTHONPATH=/app

# Set work directory
WORKDIR /app

# Install system dependencies
RUN apt-get update && apt-get install -y \
    gcc \
    g++ \
    && rm -rf /var/lib/apt/lists/*

# Install Python dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Copy project
COPY . .

# Create non-root user
RUN useradd --create-home --shell /bin/bash app
RUN chown -R app:app /app
USER app

# Expose port
EXPOSE 8000

# Health check
HEALTHCHECK --interval=30s --timeout=30s --start-period=5s --retries=3 \
    CMD curl -f http://localhost:8000/health || exit 1

# Run the application
CMD ["uvicorn", "arklex.main:app", "--host", "0.0.0.0", "--port", "8000"]
```

## 2. Infrastructure as Code

### Current Issues

- **No Infrastructure Automation**: Manual server setup and configuration
- **No Environment Consistency**: Different environments configured differently
- **No Scalability**: No auto-scaling or load balancing
- **No Monitoring**: No infrastructure monitoring
- **No Backup Strategy**: No automated backup and recovery

### Proposed Solutions

#### Terraform Configuration

```hcl
# infrastructure/main.tf
terraform {
  required_version = ">= 1.0"
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
  }
}

provider "aws" {
  region = var.aws_region
}

# VPC Configuration
resource "aws_vpc" "main" {
  cidr_block           = "10.0.0.0/16"
  enable_dns_hostnames = true
  enable_dns_support   = true

  tags = {
    Name = "${var.project_name}-vpc"
  }
}

# ECS Cluster
resource "aws_ecs_cluster" "main" {
  name = "${var.project_name}-cluster"

  setting {
    name  = "containerInsights"
    value = "enabled"
  }
}

# Application Load Balancer
resource "aws_lb" "main" {
  name               = "${var.project_name}-alb"
  internal           = false
  load_balancer_type = "application"
  security_groups    = [aws_security_group.alb.id]
  subnets            = aws_subnet.public[*].id

  enable_deletion_protection = false
}

# ECS Service
resource "aws_ecs_service" "main" {
  name            = "${var.project_name}-service"
  cluster         = aws_ecs_cluster.main.id
  task_definition = aws_ecs_task_definition.main.arn
  desired_count   = var.app_count
  launch_type     = "FARGATE"

  network_configuration {
    security_groups  = [aws_security_group.ecs_tasks.id]
    subnets          = aws_subnet.private[*].id
    assign_public_ip = false
  }

  load_balancer {
    target_group_arn = aws_lb_target_group.main.arn
    container_name   = "arklex"
    container_port   = 8000
  }

  depends_on = [aws_lb_listener.main]
}
```

#### Kubernetes Configuration

```yaml
# k8s/deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: arklex-deployment
  labels:
    app: arklex
spec:
  replicas: 3
  selector:
    matchLabels:
      app: arklex
  template:
    metadata:
      labels:
        app: arklex
    spec:
      containers:
      - name: arklex
        image: arklex:latest
        ports:
        - containerPort: 8000
        env:
        - name: DATABASE_URL
          valueFrom:
            secretKeyRef:
              name: arklex-secrets
              key: database-url
        - name: OPENAI_API_KEY
          valueFrom:
            secretKeyRef:
              name: arklex-secrets
              key: openai-api-key
        resources:
          requests:
            memory: "256Mi"
            cpu: "250m"
          limits:
            memory: "512Mi"
            cpu: "500m"
        livenessProbe:
          httpGet:
            path: /health
            port: 8000
          initialDelaySeconds: 30
          periodSeconds: 10
        readinessProbe:
          httpGet:
            path: /ready
            port: 8000
          initialDelaySeconds: 5
          periodSeconds: 5

---
apiVersion: v1
kind: Service
metadata:
  name: arklex-service
spec:
  selector:
    app: arklex
  ports:
  - port: 80
    targetPort: 8000
  type: LoadBalancer
```

## 3. Environment Management

### Current Issues

- **Hardcoded Configuration**: Configuration values hardcoded in code
- **No Environment Separation**: No proper dev/staging/prod separation
- **No Secret Management**: Secrets stored in plain text
- **No Configuration Validation**: No validation of configuration values

### Proposed Solutions

#### Environment Configuration

```python
# arklex/config/environments.py
from pydantic_settings import BaseSettings
from typing import Optional
from enum import Enum

class Environment(str, Enum):
    DEVELOPMENT = "development"
    STAGING = "staging"
    PRODUCTION = "production"

class Settings(BaseSettings):
    # Environment
    environment: Environment = Environment.DEVELOPMENT
    debug: bool = False
    
    # Database
    database_url: str
    database_pool_size: int = 10
    database_max_overflow: int = 20
    
    # Redis
    redis_url: Optional[str] = None
    
    # API Keys
    openai_api_key: Optional[str] = None
    anthropic_api_key: Optional[str] = None
    google_api_key: Optional[str] = None
    
    # Security
    secret_key: str
    jwt_algorithm: str = "HS256"
    jwt_expire_hours: int = 24
    
    # Rate Limiting
    rate_limit_requests: int = 100
    rate_limit_window: int = 60
    
    # Logging
    log_level: str = "INFO"
    log_format: str = "json"
    
    # Performance
    max_concurrent_requests: int = 100
    request_timeout: int = 30
    
    # Monitoring
    enable_metrics: bool = True
    metrics_port: int = 9090
    
    class Config:
        env_file = ".env"
        env_file_encoding = "utf-8"
        case_sensitive = False

# Environment-specific settings
class DevelopmentSettings(Settings):
    debug: bool = True
    log_level: str = "DEBUG"

class StagingSettings(Settings):
    debug: bool = False
    log_level: str = "INFO"

class ProductionSettings(Settings):
    debug: bool = False
    log_level: str = "WARNING"
    enable_metrics: bool = True
```

#### Secret Management

```python
# arklex/config/secrets.py
import os
from typing import Optional
import boto3
from azure.keyvault.secrets import SecretClient
from google.cloud import secretmanager

class SecretManager:
    def __init__(self, provider: str = "aws"):
        self.provider = provider
        if provider == "aws":
            self.client = boto3.client('secretsmanager')
        elif provider == "azure":
            self.client = SecretClient(
                vault_url=os.getenv("AZURE_KEY_VAULT_URL"),
                credential=DefaultAzureCredential()
            )
        elif provider == "gcp":
            self.client = secretmanager.SecretManagerServiceClient()
    
    def get_secret(self, secret_name: str) -> Optional[str]:
        """Retrieve secret from cloud provider."""
        try:
            if self.provider == "aws":
                response = self.client.get_secret_value(SecretId=secret_name)
                return response['SecretString']
            elif self.provider == "azure":
                secret = self.client.get_secret(secret_name)
                return secret.value
            elif self.provider == "gcp":
                name = f"projects/{os.getenv('GCP_PROJECT_ID')}/secrets/{secret_name}/versions/latest"
                response = self.client.access_secret_version(request={"name": name})
                return response.payload.data.decode("UTF-8")
        except Exception as e:
            print(f"Error retrieving secret {secret_name}: {e}")
            return None
```

## 4. Monitoring and Observability

### Current Issues

- **No Application Monitoring**: No APM or performance monitoring
- **No Infrastructure Monitoring**: No server and resource monitoring
- **No Alerting**: No automated alerting for issues
- **No Log Aggregation**: No centralized logging
- **No Tracing**: No distributed tracing

### Proposed Solutions

#### Prometheus Configuration

```yaml
# monitoring/prometheus.yml
global:
  scrape_interval: 15s
  evaluation_interval: 15s

rule_files:
  - "alert_rules.yml"

scrape_configs:
  - job_name: 'arklex'
    static_configs:
      - targets: ['localhost:8000']
    metrics_path: '/metrics'
    scrape_interval: 5s

  - job_name: 'node-exporter'
    static_configs:
      - targets: ['localhost:9100']

alerting:
  alertmanagers:
    - static_configs:
        - targets:
          - localhost:9093
```

#### Grafana Dashboard

```json
{
  "dashboard": {
    "title": "Arklex AI Dashboard",
    "panels": [
      {
        "title": "Request Rate",
        "type": "graph",
        "targets": [
          {
            "expr": "rate(arklex_requests_total[5m])",
            "legendFormat": "{{endpoint}}"
          }
        ]
      },
      {
        "title": "Response Time",
        "type": "graph",
        "targets": [
          {
            "expr": "histogram_quantile(0.95, rate(arklex_request_duration_seconds_bucket[5m]))",
            "legendFormat": "95th percentile"
          }
        ]
      },
      {
        "title": "Error Rate",
        "type": "graph",
        "targets": [
          {
            "expr": "rate(arklex_errors_total[5m])",
            "legendFormat": "Errors"
          }
        ]
      }
    ]
  }
}
```

## 5. Backup and Disaster Recovery

### Current Issues

- **No Automated Backups**: No database backup strategy
- **No Disaster Recovery Plan**: No recovery procedures
- **No Data Retention Policy**: No data lifecycle management
- **No Cross-Region Replication**: No geographic redundancy

### Proposed Solutions

#### Database Backup Strategy

```python
# arklex/utils/backup.py
import boto3
import psycopg2
from datetime import datetime
import os

class DatabaseBackup:
    def __init__(self, database_url: str, s3_bucket: str):
        self.database_url = database_url
        self.s3_bucket = s3_bucket
        self.s3_client = boto3.client('s3')
    
    def create_backup(self) -> str:
        """Create database backup and upload to S3."""
        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
        backup_filename = f"arklex_backup_{timestamp}.sql"
        
        # Create backup
        os.system(f"pg_dump {self.database_url} > {backup_filename}")
        
        # Upload to S3
        self.s3_client.upload_file(
            backup_filename,
            self.s3_bucket,
            f"backups/{backup_filename}"
        )
        
        # Clean up local file
        os.remove(backup_filename)
        
        return f"s3://{self.s3_bucket}/backups/{backup_filename}"
    
    def restore_backup(self, backup_key: str) -> bool:
        """Restore database from S3 backup."""
        try:
            # Download backup from S3
            local_filename = backup_key.split('/')[-1]
            self.s3_client.download_file(self.s3_bucket, backup_key, local_filename)
            
            # Restore database
            os.system(f"psql {self.database_url} < {local_filename}")
            
            # Clean up
            os.remove(local_filename)
            return True
        except Exception as e:
            print(f"Restore failed: {e}")
            return False
```

## 6. Security in Deployment

### Current Issues

- **No Container Security**: No container vulnerability scanning
- **No Network Security**: No proper network segmentation
- **No Access Control**: No proper IAM and RBAC
- **No Compliance**: No compliance monitoring

### Proposed Solutions

#### Container Security Scanning

```yaml
# .github/workflows/security-scan.yml
name: Container Security Scan
on:
  push:
    branches: [ main ]
  pull_request:
    branches: [ main ]

jobs:
  container-scan:
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v4
    
    - name: Run Trivy vulnerability scanner
      uses: aquasecurity/trivy-action@master
      with:
        image-ref: 'arklex:latest'
        format: 'sarif'
        output: 'trivy-results.sarif'
    
    - name: Upload Trivy scan results to GitHub Security tab
      uses: github/codeql-action/upload-sarif@v2
      if: always()
      with:
        sarif_file: 'trivy-results.sarif'
```

#### Network Security

```hcl
# infrastructure/security.tf
# Security Groups
resource "aws_security_group" "alb" {
  name        = "${var.project_name}-alb-sg"
  description = "Security group for ALB"
  vpc_id      = aws_vpc.main.id

  ingress {
    protocol    = "tcp"
    from_port   = 80
    to_port     = 80
    cidr_blocks = ["0.0.0.0/0"]
  }

  ingress {
    protocol    = "tcp"
    from_port   = 443
    to_port     = 443
    cidr_blocks = ["0.0.0.0/0"]
  }

  egress {
    protocol    = "-1"
    from_port   = 0
    to_port     = 0
    cidr_blocks = ["0.0.0.0/0"]
  }
}

resource "aws_security_group" "ecs_tasks" {
  name        = "${var.project_name}-ecs-tasks-sg"
  description = "Security group for ECS tasks"
  vpc_id      = aws_vpc.main.id

  ingress {
    protocol        = "tcp"
    from_port       = 8000
    to_port         = 8000
    security_groups = [aws_security_group.alb.id]
  }

  egress {
    protocol    = "-1"
    from_port   = 0
    to_port     = 0
    cidr_blocks = ["0.0.0.0/0"]
  }
}
```

## Success Metrics

### Deployment Metrics

- [ ] Zero-downtime deployments
- [ ] Automated rollback capability
- [ ] <5 minute deployment time
- [ ] 100% automated testing in CI/CD
- [ ] Zero security vulnerabilities in containers

### Infrastructure Metrics

- [ ] 99.9% uptime SLA
- [ ] <100ms response time for 95th percentile
- [ ] Auto-scaling based on load
- [ ] Cross-region disaster recovery
- [ ] Automated backup and restore

### Security Metrics

- [ ] Zero critical security vulnerabilities
- [ ] All secrets encrypted at rest
- [ ] Network segmentation implemented
- [ ] Access control audit logging
- [ ] Compliance monitoring active

## Implementation Timeline

### Phase 1: Foundation (Week 1-2)

- [ ] Set up CI/CD pipeline
- [ ] Implement Docker containerization
- [ ] Add basic monitoring
- [ ] Configure environment management

### Phase 2: Infrastructure (Week 3-4)

- [ ] Deploy to cloud infrastructure
- [ ] Implement auto-scaling
- [ ] Add load balancing
- [ ] Set up backup strategy

### Phase 3: Security & Monitoring (Week 5-6)

- [ ] Implement security scanning
- [ ] Add comprehensive monitoring
- [ ] Set up alerting
- [ ] Configure disaster recovery

### Phase 4: Optimization (Week 7-8)

- [ ] Performance optimization
- [ ] Cost optimization
- [ ] Advanced monitoring
- [ ] Compliance implementation
