🏗️ Architecture Overview¶

System Architecture¶

The self-healing infrastructure is built on a modern, cloud-native architecture that prioritizes resilience, scalability, and automation.

High-Level Architecture¶

graph TB
    subgraph "Infrastructure Layer"
        TF[Terraform]
        K8S[Kubernetes Cluster]
        STOR[Storage]
        NET[Network]
    end

    subgraph "Platform Layer"
        MON[Monitoring Stack]
        LOG[Logging]
        SEC[Security]
    end

    subgraph "Application Layer"
        APP[Applications]
        CHAOS[Chaos Experiments]
        HEAL[Self-Healing]
    end

    subgraph "CI/CD Layer"
        GH[GitHub Actions]
        BUILD[Build Pipeline]
        DEPLOY[Deploy Pipeline]
    end

    TF --> K8S
    K8S --> MON
    K8S --> LOG
    K8S --> SEC
    K8S --> APP
    K8S --> CHAOS
    K8S --> HEAL
    GH --> BUILD
    BUILD --> DEPLOY
    DEPLOY --> K8S

Core Components¶

1. Infrastructure Management¶

• Terraform: Infrastructure as Code for provisioning and managing cloud resources
• Kubernetes: Container orchestration platform
• Storage: Persistent volumes and storage classes
• Network: Service mesh and network policies

2. Monitoring & Observability¶

• Prometheus: Metrics collection and storage
• Grafana: Visualization and dashboards
• AlertManager: Alert routing and notification
• Jaeger: Distributed tracing

3. Self-Healing System¶

• Controller: Python-based monitoring and recovery logic
• Health Checks: Automated health monitoring
• Recovery Actions: Automatic failure recovery
• Notifications: Slack integration for alerts

4. Chaos Engineering¶

• Chaos Mesh: Chaos engineering platform
• Experiments: Predefined chaos scenarios
• Scheduling: Automated chaos testing
• Analysis: Impact assessment and reporting

Design Principles¶

1. Resilience First¶

• Redundancy: Multiple instances and failover mechanisms
• Circuit Breakers: Automatic failure isolation
• Graceful Degradation: System continues operating with reduced functionality

2. Automation Everywhere¶

• Infrastructure as Code: All infrastructure defined in code
• Continuous Deployment: Automated deployment pipeline
• Self-Healing: Automatic problem detection and resolution

3. Observability¶

• Metrics: Comprehensive system metrics
• Logging: Structured logging across all components
• Tracing: Distributed request tracing
• Alerting: Proactive alerting for issues

4. Security by Design¶

• RBAC: Role-based access control
• Network Policies: Micro-segmentation
• Secrets Management: Secure credential handling
• Compliance: Security and compliance standards

Technology Stack¶

Scalability Considerations¶

Horizontal Scaling¶

• Auto-scaling: Kubernetes HPA for automatic scaling
• Load Balancing: Service mesh for traffic distribution
• Database Scaling: Read replicas and sharding

Vertical Scaling¶

• Resource Limits: CPU and memory limits
• Resource Requests: Guaranteed resources
• Node Scaling: Cluster node management

Security Architecture¶

Network Security¶

graph LR
    subgraph "External"
        INTERNET[Internet]
    end

    subgraph "DMZ"
        LB[Load Balancer]
    end

    subgraph "Cluster"
        ING[Ingress]
        SVC[Services]
        POD[Pods]
    end

    INTERNET --> LB
    LB --> ING
    ING --> SVC
    SVC --> POD

Access Control¶

• Authentication: OIDC integration
• Authorization: RBAC policies
• Audit Logging: Comprehensive audit trails
• Secret Management: Encrypted secrets storage

Performance Characteristics¶

Latency¶

• API Response Time: < 100ms for 95^th percentile
• Database Queries: < 50ms for read operations
• Service Mesh: < 10ms overhead

Throughput¶

• Request Rate: 10,000+ requests/second
• Concurrent Users: 1,000+ simultaneous users
• Data Processing: 1GB+ per minute

Availability¶

• Uptime: 99.9% availability target
• Recovery Time: < 30 seconds for most failures
• Data Durability: 99.999999% (11 nines)

Disaster Recovery¶

Backup Strategy¶

• Database Backups: Daily automated backups
• Configuration Backups: Version-controlled configurations
• Data Replication: Cross-region replication

Recovery Procedures¶

• RTO (Recovery Time Objective): 4 hours
• RPO (Recovery Point Objective): 1 hour
• Failover: Automated failover to secondary region

Cost Optimization¶

Resource Optimization¶

• Right-sizing: Optimal resource allocation
• Spot Instances: Cost-effective compute resources
• Storage Tiering: Appropriate storage classes

Monitoring and Alerts¶

• Cost Alerts: Budget monitoring and alerts
• Resource Utilization: Efficiency monitoring
• Optimization Recommendations: Automated suggestions