Architecture
Buildly Product Labs is built on a modern, scalable microservices architecture that follows proven patterns for enterprise-grade applications. This page outlines the key architectural patterns and design principles that power the platform.
Architecture Overview
Buildly follows a component-driven microservices architecture that emphasizes modularity, scalability, and maintainability. The platform is designed around several core architectural patterns that work together to provide a robust foundation for product management workflows.
Note
Architecture Diagram Coming Soon: A visual diagram showing the relationship between frontend, gateway, core services, and logic services will be added here.
Core Architectural Patterns
1. API Gateway Pattern
Single Point of Entry
All client requests flow through a centralized API gateway that provides:
Unified API Surface: Single URL endpoint (
dev-api.myapp.io)Service Discovery: Automatic registration and discovery of backend services
Load Balancing: Intelligent request distribution across service instances
Rate Limiting: Protection against abuse and overload
API Versioning: Support for multiple API versions
Service Registration Flow:
Frontend Application (dev-app.myapp.io)
↓
API Gateway (dev-api.myapp.io)
↓
Buildly Core + Logic Services
↓
- /documents → Documents Service
- /crm → CRM Service
- /appointments → Appointments Service
2. Microservices Architecture
Logic Services
Buildly implements a pure microservices pattern where each business capability is implemented as an independent service:
Documents Service: File management and document workflows
CRM Service: Customer relationship management
Appointments Service: Scheduling and calendar management
Custom Services: Domain-specific business logic
Key Characteristics:
Independence: Each service can be developed, deployed, and scaled independently
OpenAPI Standard: All services follow OpenAPI/Swagger specifications
Database per Service: Each service owns its data store
Technology Agnostic: Services can use different programming languages and frameworks
3. Data Mesh Pattern
Unified Data Layer
The Data Mesh pattern enables seamless data integration across distributed services:
Data Aggregation:
Service 1 Data → UUID, Name, Type, Description
Service 2 Data → UUID, Name, Type, Description
Service 3 Data → UUID, Name, Type, Description
↓
Data Mesh (Buildly Core)
↓
Aggregated REST API Response
Benefits:
Cross-Service Joins: Query data across multiple services seamlessly
Data Consistency: Maintain referential integrity across service boundaries
Performance Optimization: Intelligent caching and query optimization
Schema Evolution: Handle data model changes gracefully
5. Workflow Template Pattern
Reusable Process Orchestration
Buildly implements configurable workflow templates that can be reused across services:
Template Structure:
Workflow Template
├── Level 1 → Related Level → Related Workflow
└── Level 2 → Related Level 1 → Related Workflow 2
Capabilities:
Process Trees: Build complex multi-step workflows
Navigation Flows: Define user journey patterns
Cross-Service Workflows: Orchestrate processes across multiple services
Template Reusability: Share workflow patterns across projects
6. Module Pattern (Core Extensions)
Pluggable Architecture
Buildly Core supports modules that run within the core application:
Connection Modules: Service integration and communication
Security Modules: Authentication and authorization extensions
Data Transport Modules: Message queuing and event processing
Partner Integration Modules: Third-party system connectors
Deployment Architecture
Container-First Design
Buildly is designed for modern container orchestration platforms:
Kubernetes Deployment:
Namespace Isolation: Each application gets its own Kubernetes namespace
Pod Management: Automatic pod creation for Buildly Core and Logic Services
Service Mesh: Istio/Linkerd integration for service communication
Auto-Scaling: Horizontal pod autoscaling based on load
Database Strategy:
Database per Service: Each Logic Service has its own database
Cluster Management: Databases deployed in managed clusters
Backup & Recovery: Automated backup strategies per service
Migration Support: Database schema evolution and migration tools
Cloud-Native Patterns
Infrastructure as Code:
Automated Provisioning: Infrastructure deployment via Terraform/CloudFormation
Environment Parity: Consistent environments from development to production
Blue-Green Deployments: Zero-downtime deployment strategies
Monitoring & Observability: Integrated logging, metrics, and tracing
Security Architecture
Defense in Depth
Multiple Security Layers:
Network Security: VPC isolation, security groups, and network policies
API Security: OAuth 2.0, JWT tokens, and API rate limiting
Application Security: Input validation, output encoding, and CSRF protection
Data Security: Encryption at rest and in transit
Infrastructure Security: Container scanning and vulnerability management
Compliance & Governance:
GDPR Compliance: Data privacy and user consent management
SOC 2 Type II: Security and availability controls
OWASP Top 10: Protection against common web vulnerabilities
Audit Logging: Comprehensive audit trails for compliance
Performance & Scalability
Horizontal Scaling
Auto-Scaling Capabilities:
Load-Based Scaling: Automatic scaling based on CPU/memory usage
Queue-Based Scaling: Scale based on message queue depth
Predictive Scaling: ML-driven capacity planning
Multi-Region Deployment: Global distribution for low latency
Performance Optimization:
Caching Layers: Redis/Memcached for session and application caching
CDN Integration: Static asset delivery via CloudFront/CloudFlare
Database Optimization: Connection pooling and query optimization
Async Processing: Background job processing for long-running tasks
Monitoring & Observability
Three Pillars of Observability
Metrics:
Application Metrics: Response times, throughput, error rates
Infrastructure Metrics: CPU, memory, disk, network utilization
Business Metrics: Feature usage, user engagement, conversion rates
Logging:
Structured Logging: JSON-formatted logs with correlation IDs
Centralized Logging: ELK/EFK stack for log aggregation
Log Retention: Configurable retention policies per environment
Tracing:
Distributed Tracing: OpenTracing/Jaeger for request flow visualization
Performance Profiling: APM tools for bottleneck identification
Error Tracking: Sentry/Rollbar for real-time error monitoring
Development Workflow
CI/CD Pipeline
Continuous Integration:
Automated Testing: Unit, integration, and end-to-end test suites
Code Quality: SonarQube/CodeClimate for static analysis
Security Scanning: Container and dependency vulnerability scanning
Build Automation: Docker image building and registry management
Continuous Deployment:
GitOps Workflow: Infrastructure and application deployment via Git
Environment Promotion: Automated promotion from dev → staging → production
Rollback Capabilities: One-click rollback to previous versions
Feature Flags: Gradual feature rollout and A/B testing
Developer Experience
Local Development:
Docker Compose: One-command local environment setup
Hot Reloading: Real-time code changes without restarts
Mock Services: Stub external dependencies for isolated testing
Development Tools: Integrated debugging and profiling tools
Future Architecture Evolution
Emerging Patterns
Planned Enhancements:
Event-Driven Architecture: Implement event sourcing and CQRS patterns
GraphQL Federation: Unified GraphQL schema across microservices
Serverless Functions: Edge computing for specialized workloads
AI/ML Pipeline: Integrated machine learning model deployment
Technology Roadmap:
Service Mesh: Advanced traffic management and security
Multi-Cloud: Avoid vendor lock-in with multi-cloud deployments
Edge Computing: Reduce latency with edge node deployment
Blockchain Integration: Immutable audit trails and smart contracts
Getting Started for Developers
Repository Structure:
buildly-ecosystem/
├── buildly-core/ # Core gateway and auth service
├── buildly-ui-angular/ # Frontend application framework
├── logic-services/ # Business logic microservices
│ ├── documents-service/
│ ├── crm-service/
│ └── appointments-service/
└── infrastructure/ # Deployment and infrastructure code
├── kubernetes/
├── terraform/
└── docker/
Quick Start:
Clone Repositories: Get the core platform and desired logic services
Environment Setup: Configure local development environment with Docker
Service Development: Build new logic services using provided templates
Integration Testing: Test service integration with Buildly Core
Deployment: Deploy to Kubernetes cluster using provided manifests