Deployment & Security

ai-lib provides a stateless core that can be embedded inside your async service and scaled horizontally. For enterprise deployments with advanced security and compliance requirements, see ai-lib-pro for enhanced capabilities.

Security Practices

Basic Security (ai-lib)

• API keys loaded at process start; never logged
• Environment variable isolation for provider keys
• Proxy support for corporate networks
• No default content logging

Enterprise Security (ai-lib-pro)

• Secret Management: Integration with HashiCorp Vault, AWS Secrets Manager
• Key Rotation: Automatic secret rotation with zero downtime
• Audit Logging: Comprehensive audit trails for all requests
• RBAC: Role-based access control with fine-grained permissions
• Compliance: GDPR, SOC2, HIPAA compliance frameworks
• Encryption: End-to-end encryption for sensitive data

Deployment Options

Basic Deployment

use ai_lib::{AiClient, Provider};

// Simple deployment
let client = AiClient::new(Provider::OpenAI)?;

Enterprise Deployment (ai-lib-pro)

use ai_lib_pro::{EnterpriseClient, SecurityManager, ConfigManager};

// Enterprise deployment with security and compliance
let client = EnterpriseClient::new()
    .with_security_manager(SecurityManager::enterprise())
    .with_config_manager(ConfigManager::hot_reload())
    .with_audit_logging(true)
    .build()?;

Self-Hosting

Container Deployment

FROM rust:1.70-slim

WORKDIR /app
COPY . .
RUN cargo build --release

EXPOSE 8080
CMD ["./target/release/your-app"]

Kubernetes Deployment

apiVersion: apps/v1
kind: Deployment
metadata:
  name: ai-lib-service
spec:
  replicas: 3
  selector:
    matchLabels:
      app: ai-lib-service
  template:
    metadata:
      labels:
        app: ai-lib-service
    spec:
      containers:
      - name: ai-lib-service
        image: your-registry/ai-lib-service:latest
        ports:
        - containerPort: 8080
        env:
        - name: OPENAI_API_KEY
          valueFrom:
            secretKeyRef:
              name: ai-secrets
              key: openai-api-key

Enterprise Architecture

High Availability Setup

• Load Balancing: Multiple instances behind load balancer
• Health Checks: Automated health monitoring and failover
• Circuit Breakers: Automatic failure detection and recovery
• Monitoring: Comprehensive metrics and alerting

Security Architecture

• Network Isolation: VPC and firewall configuration
• Access Control: Multi-layer authentication and authorization
• Data Protection: Encryption at rest and in transit
• Compliance Monitoring: Real-time compliance checking

Performance Optimization

Connection Pooling

use ai_lib::{AiClientBuilder, Provider};

let client = AiClientBuilder::new(Provider::OpenAI)
    .with_max_concurrency(64)
    .with_connection_pool_size(32)
    .for_production()
    .build()?;

Caching Strategy

• Response caching for repeated queries
• Model response caching
• Provider health status caching
• Configuration caching

Monitoring and Observability

Basic Monitoring (ai-lib)

• Custom metrics integration
• Request/response timing
• Error rate tracking
• Provider health monitoring

Enterprise Monitoring (ai-lib-pro)

• Real-time Dashboard API: Live system metrics, user analytics, and cost tracking with REST endpoints
• Structured Event Analytics: Rich metadata collection including user context, performance data, and cost information
• Advanced Health Monitoring: Multi-dimensional scoring with automated alert generation and component status tracking
• Distributed Tracing: Full request tracing across services with correlation IDs and performance bottleneck identification
• Custom KPIs: Business-specific metrics with flexible tagging and real-time aggregation capabilities

Next Steps

• Explore ai-lib-pro for advanced enterprise features
• Review Security & Compliance for detailed security features
• Check Cost Management for enterprise cost controls
• Contact Enterprise Support for deployment assistance