Architecture Specification¶

This page provides a comprehensive overview of the TAPPaaS architecture, including system design, core components, communication patterns, and security considerations. TAPPaaS is designed as a cloud-native platform that simplifies application deployment on Kubernetes while maintaining flexibility and enterprise-grade capabilities.

System Architecture¶

TAPPaaS follows a layered architecture pattern with clear separation between the control plane (platform management) and data plane (application runtime). The platform is built on Kubernetes and extends its capabilities with higher-level abstractions.

graph TB
    subgraph "User Interface Layer"
        CLI[TAPPaaS CLI]
        API[REST/GraphQL API]
        WebUI[Web Dashboard]
    end

    subgraph "Control Plane"
        APIServer[API Server]
        Controller[Controller Manager]
        Scheduler[Application Scheduler]
        Registry[Application Registry]
        ConfigStore[Configuration Store]
    end

    subgraph "Data Plane"
        subgraph "Runtime Layer"
            Runtime1[Application Runtime 1]
            Runtime2[Application Runtime 2]
            RuntimeN[Application Runtime N]
        end

        subgraph "Infrastructure Services"
            Ingress[Ingress Controller]
            ServiceMesh[Service Mesh]
            Storage[Storage Layer]
            Networking[Network Policy Engine]
        end
    end

    subgraph "Platform Services"
        Monitoring[Monitoring & Metrics]
        Logging[Centralized Logging]
        Security[Security & Secrets]
        BuildSvc[Build Service]
    end

    subgraph "Kubernetes Cluster"
        K8sAPI[Kubernetes API]
        Nodes[Node Pool]
    end

    CLI --> API
    WebUI --> API
    API --> APIServer
    APIServer --> Controller
    APIServer --> Scheduler
    APIServer --> Registry
    APIServer --> ConfigStore

    Controller --> K8sAPI
    Scheduler --> K8sAPI
    BuildSvc --> K8sAPI

    K8sAPI --> Nodes
    Nodes --> Runtime1
    Nodes --> Runtime2
    Nodes --> RuntimeN

    Runtime1 --> ServiceMesh
    Runtime2 --> ServiceMesh
    RuntimeN --> ServiceMesh

    ServiceMesh --> Ingress
    Ingress --> Networking

    Monitoring -.-> Runtime1
    Monitoring -.-> Runtime2
    Monitoring -.-> RuntimeN

    Logging -.-> Runtime1
    Logging -.-> Runtime2
    Logging -.-> RuntimeN

    Security --> ConfigStore
    Security --> K8sAPI

Control Plane Components¶

The control plane is responsible for managing the platform lifecycle, application deployments, and orchestrating resources. It operates independently from application workloads to ensure platform stability.

API Server¶

The API Server is the central entry point for all TAPPaaS operations and provides unified access to platform capabilities.

Key Responsibilities:

• Authentication and authorization of API requests
• Request validation and admission control
• REST and GraphQL API endpoints
• WebSocket support for real-time updates
• API versioning and backward compatibility

Communication:

• Receives requests from CLI, Web UI, and external integrations
• Interfaces with Controller Manager, Scheduler, and Registry
• Maintains connection to the Configuration Store

Configuration:

• Horizontal scaling supported for high availability
• TLS encryption for all API traffic
• Rate limiting and quota enforcement
• Audit logging of all operations

Controller Manager¶

The Controller Manager implements the reconciliation loop pattern to ensure desired state matches actual state for all managed resources.

Key Responsibilities:

• Application lifecycle management (create, update, delete)
• Deployment orchestration and rollout strategies
• Health monitoring and self-healing
• Resource quota enforcement
• Event generation and status updates

Controllers:

Communication:

• Watches Kubernetes API for resource changes
• Updates Application Registry with deployment status
• Publishes events to monitoring and logging systems

Application Scheduler¶

The Scheduler determines optimal placement of application workloads across the cluster based on resource requirements, constraints, and policies.

Key Responsibilities:

• Resource allocation and bin packing
• Affinity and anti-affinity rule enforcement
• Multi-tenancy isolation
• Node selection based on workload requirements
• Preemption and priority handling

Scheduling Factors:

• CPU and memory requirements
• Storage and network bandwidth needs
• Geographic and zone constraints
• Hardware capabilities (GPU, specialized processors)
• Cost optimization policies

Application Registry¶

The Registry maintains the catalog of all applications, their configurations, and deployment history.

Key Responsibilities:

• Application metadata storage
• Version tracking and history
• Configuration management
• Deployment artifacts storage
• Application dependencies and relationships

Data Model:

Application:
  - id: unique identifier
  - name: application name
  - namespace: tenant/project namespace
  - versions: list of application versions
  - configuration: current configuration
  - status: deployment status
  - metadata: labels, annotations, tags

Configuration Store¶

The Configuration Store provides centralized, secure storage for platform and application configurations.

Key Responsibilities:

• Hierarchical configuration management
• Environment-specific overrides
• Secret encryption and access control
• Configuration versioning and rollback
• Configuration validation and schema enforcement

Storage Backend:

• etcd for high-performance key-value storage
• Encryption at rest for sensitive data
• Automatic backups and replication
• RBAC integration for access control

Data Plane Components¶

The data plane is where application workloads run and includes all runtime infrastructure necessary to support deployed applications.

Application Runtime¶

Each application runs within an isolated runtime environment with dedicated resources and security boundaries.

Runtime Features:

• Container orchestration via Kubernetes
• Resource limits and quotas enforcement
• Health checks and liveness probes
• Environment variable injection
• Volume mounting and persistent storage
• Network isolation and service mesh integration

Runtime Types:

Networking Layer¶

The networking layer provides connectivity, service discovery, and traffic management for applications.

Components:

• Ingress Controller: External traffic routing and TLS termination
• Service Mesh: Inter-service communication, observability, and traffic control
• Network Policies: Microsegmentation and zero-trust networking
• DNS Service Discovery: Automatic service endpoint resolution

Traffic Flow:

sequenceDiagram
    participant Client
    participant Ingress
    participant ServiceMesh
    participant App1
    participant App2

    Client->>Ingress: HTTPS Request
    Ingress->>Ingress: TLS Termination
    Ingress->>ServiceMesh: Route to Service
    ServiceMesh->>ServiceMesh: mTLS Encryption
    ServiceMesh->>App1: Forward Request
    App1->>ServiceMesh: Internal API Call
    ServiceMesh->>App2: Route with Load Balancing
    App2-->>ServiceMesh: Response
    ServiceMesh-->>App1: Response
    App1-->>ServiceMesh: Final Response
    ServiceMesh-->>Ingress: Response
    Ingress-->>Client: HTTPS Response

Storage Layer¶

The storage layer provides persistent data storage with various performance and durability characteristics.

Storage Types:

Features:

• Volume snapshots and backups
• Volume expansion without downtime
• Cross-zone replication for HA
• Encryption at rest
• Storage quota management

Communication Patterns¶

TAPPaaS uses several communication patterns optimized for different use cases.

Synchronous Request-Response¶

Used for user-facing operations requiring immediate feedback.

Pattern:

• CLI/UI → API Server → Controller → Kubernetes API
• Response includes operation status and initial results
• Suitable for queries and simple operations

Example Use Cases:

• Fetching application status
• Listing deployed applications
• Retrieving logs and metrics
• Configuration queries

Asynchronous Event-Driven¶

Used for long-running operations and state changes.

Pattern:

• Client initiates operation via API
• API Server creates work item and returns operation ID
• Controller processes work asynchronously
• Client polls or subscribes to status updates

Example Use Cases:

• Application deployments
• Scaling operations
• Build processes
• Backup and restore operations

Watch/Subscribe¶

Used for real-time updates and monitoring.

Pattern:

• Client establishes WebSocket connection
• Server streams updates as events occur
• Client receives real-time notifications

Example Use Cases:

• Deployment progress tracking
• Real-time log streaming
• Metric and alert notifications
• Event monitoring

Data Flow¶

Understanding data flow through the platform is essential for troubleshooting and optimization.

Application Deployment Flow¶

flowchart TD
    Start([User Initiates Deployment]) --> CLI[CLI Sends Deployment Request]
    CLI --> APIAuth[API Server Authentication]
    APIAuth --> APIVal[API Server Validation]
    APIVal --> Registry[Update Application Registry]
    Registry --> Queue[Queue Deployment Task]
    Queue --> Controller[Controller Picks Up Task]
    Controller --> Build{Build Required?}

    Build -->|Yes| BuildSvc[Build Service Creates Image]
    BuildSvc --> Push[Push Image to Registry]
    Push --> Deploy[Create Kubernetes Resources]

    Build -->|No| Deploy

    Deploy --> Scheduler[Scheduler Assigns Nodes]
    Scheduler --> K8s[Kubernetes Creates Pods]
    K8s --> Health[Health Checks Start]
    Health --> Ready{Pods Ready?}

    Ready -->|No| Wait[Wait and Retry]
    Wait --> Health

    Ready -->|Yes| Traffic[Route Traffic to Pods]
    Traffic --> Monitor[Monitor Application]
    Monitor --> End([Deployment Complete])

Configuration Update Flow¶

1. User updates configuration via CLI/UI
2. API Server validates configuration schema
3. Configuration Store persists new configuration
4. Controller detects configuration change
5. Controller triggers rolling update
6. Pods are recreated with new configuration
7. Health checks verify new pods
8. Old pods are terminated after successful deployment

Monitoring Data Flow¶

1. Application emits metrics and logs
2. Metrics collected by Prometheus agents
3. Logs shipped to centralized logging system
4. Data indexed and stored
5. Dashboards query aggregated data
6. Alerts triggered based on rules
7. Notifications sent to configured channels

Security Architecture¶

TAPPaaS implements defense-in-depth security with multiple layers of protection.

Authentication and Authorization¶

Authentication Methods:

• API tokens for CLI and programmatic access
• OAuth2/OIDC for web UI single sign-on
• Mutual TLS for inter-component communication
• Kubernetes service accounts for workload identity

Authorization Model:

• Role-Based Access Control (RBAC)
• Attribute-Based Access Control (ABAC) for fine-grained policies
• Namespace-level isolation for multi-tenancy
• Resource quotas and limits enforcement

Network Security¶

Security Layers:

Secrets Management¶

Features:

• Encrypted storage in etcd
• Automatic secret rotation
• Integration with external secret managers (Vault, AWS Secrets Manager)
• Secret access auditing
• Fine-grained RBAC for secret access

Compliance and Auditing¶

Capabilities:

• Comprehensive audit logging
• Immutable audit trail
• Compliance reporting (SOC2, HIPAA, PCI-DSS)
• Policy enforcement and validation
• Security scanning and vulnerability detection

High Availability¶

TAPPaaS is designed for production deployments with high availability requirements.

Control Plane HA¶

• Multiple API Server replicas with load balancing
• Etcd cluster with minimum 3 nodes
• Controller Manager leader election
• Automatic failover for failed components

Data Plane HA¶

• Multi-zone application deployment
• Pod anti-affinity rules
• Automatic pod rescheduling on node failure
• Health-based traffic routing
• Persistent volume replication

Disaster Recovery¶

• Regular etcd backups
• Application configuration snapshots
• Cross-region backup replication
• Documented recovery procedures
• Tested disaster recovery runbooks

Performance and Scalability¶

TAPPaaS is designed to scale from small development clusters to large enterprise deployments.

Scaling Dimensions¶

Optimization Strategies¶

• Horizontal scaling of control plane components
• Caching at multiple layers
• Efficient resource bin packing
• Connection pooling and reuse
• Asynchronous processing for long operations

Related Documentation¶

• Core Components - Detailed component specifications
• Deployment Models - Architecture deployment patterns
• Security Model - Comprehensive security documentation
• Configuration Reference - Platform configuration options
• Operations Guide - Production operations procedures