""" Microservices Architecture for Secure Ticketing Platform Design Pattern: Event-Driven Microservices with API Gateway """ import json import hashlib import datetime from typing import Dict, List, Optional, Any from dataclasses import dataclass from enum import Enum class ServiceType(Enum): API_GATEWAY = "api_gateway" AUTH_SERVICE = "auth_service" TICKET_SERVICE = "ticket_service" PAYMENT_SERVICE = "payment_service" FRAUD_DETECTION = "fraud_detection" PRICING_ENGINE = "pricing_engine" NOTIFICATION_SERVICE = "notification_service" BLOCKCHAIN_VERIFIER = "blockchain_verifier" @dataclass class MicroService: name: str service_type: ServiceType port: int dependencies: List[str] health_endpoint: str scaling_config: Dict[str, Any] class TicketingArchitecture: """Core architecture definition for scalable ticketing platform""" def __init__(self): self.services = self._initialize_services() self.message_broker = "redis_cluster" self.database_cluster = "postgresql_ha" self.cache_layer = "redis_cluster" def _initialize_services(self) -> List[MicroService]: """Define all microservices with their configurations""" return [ MicroService( name="api-gateway", service_type=ServiceType.API_GATEWAY, port=3000, dependencies=["auth-service", "ticket-service"], health_endpoint="/health", scaling_config={"min_instances": 2, "max_instances": 10, "cpu_threshold": 70} ), MicroService( name="auth-service", service_type=ServiceType.AUTH_SERVICE, port=3001, dependencies=[], health_endpoint="/health", scaling_config={"min_instances": 2, "max_instances": 5, "cpu_threshold": 60} ), MicroService( name="ticket-service", service_type=ServiceType.TICKET_SERVICE, port=3002, dependencies=["auth-service", "pricing-engine", "fraud-detection"], health_endpoint="/health", scaling_config={"min_instances": 3, "max_instances": 15, "cpu_threshold": 75} ), MicroService( name="payment-service", service_type=ServiceType.PAYMENT_SERVICE, port=3003, dependencies=["auth-service", "fraud-detection"], health_endpoint="/health", scaling_config={"min_instances": 2, "max_instances": 8, "cpu_threshold": 65} ), MicroService( name="fraud-detection", service_type=ServiceType.FRAUD_DETECTION, port=3004, dependencies=[], health_endpoint="/health", scaling_config={"min_instances": 2, "max_instances": 6, "cpu_threshold": 80} ), MicroService( name="pricing-engine", service_type=ServiceType.PRICING_ENGINE, port=3005, dependencies=[], health_endpoint="/health", scaling_config={"min_instances": 1, "max_instances": 4, "cpu_threshold": 70} ), MicroService( name="notification-service", service_type=ServiceType.NOTIFICATION_SERVICE, port=3006, dependencies=["ticket-service"], health_endpoint="/health", scaling_config={"min_instances": 1, "max_instances": 3, "cpu_threshold": 50} ), MicroService( name="blockchain-verifier", service_type=ServiceType.BLOCKCHAIN_VERIFIER, port=3007, dependencies=["ticket-service"], health_endpoint="/health", scaling_config={"min_instances": 2, "max_instances": 5, "cpu_threshold": 60} ) ] def generate_service_mesh(self) -> Dict[str, Any]: """Generate service mesh configuration""" mesh_config = { "mesh_type": "Istio", "services": [], "traffic_routing": {}, "security_policies": { "mtls": "strict", "auth_policy": "jwt_validation" } } for service in self.services: mesh_config["services"].append({ "name": service.name, "port": service.port, "dependencies": service.dependencies }) return mesh_config def get_deployment_manifest(self) -> Dict[str, Any]: """Generate Kubernetes deployment manifests""" return { "api_version": "v1", "kind": "ServiceList", "services": [ { "name": service.name, "image": f"ticketing/{service.name}:latest", "port": service.port, "replicas": service.scaling_config["min_instances"], "resources": { "requests": {"cpu": "100m", "memory": "128Mi"}, "limits": {"cpu": "500m", "memory": "512Mi"} }, "health_check": service.health_endpoint } for service in self.services ] } # Architecture validation def validate_architecture(): """Validate the microservices architecture""" arch = TicketingArchitecture() # Check service dependencies dependency_graph = {} for service in arch.services: dependency_graph[service.name] = service.dependencies # Check for circular dependencies def has_cycle(graph, node, visited, rec_stack): visited[node] = True rec_stack[node] = True for neighbor in graph.get(node, []): if not visited.get(neighbor, False): if has_cycle(graph, neighbor, visited, rec_stack): return True elif rec_stack.get(neighbor, False): return True rec_stack[node] = False return False visited = {} rec_stack = {} for service_name in dependency_graph: if not visited.get(service_name, False): if has_cycle(dependency_graph, service_name, visited, rec_stack): raise ValueError(f"Circular dependency detected involving {service_name}") return { "validation": "passed", "services_count": len(arch.services), "architecture_type": "event_driven_microservices" } if __name__ == "__main__": # Generate architecture architecture = TicketingArchitecture() # Output configuration print("=== Ticketing Platform Architecture ===") print(f"Total Services: {len(architecture.services)}") print(f"Message Broker: {architecture.message_broker}") print(f"Database Cluster: {architecture.database_cluster}") # Validate architecture validation_result = validate_architecture() print(f"\nValidation Result: {validation_result['validation']}") # Generate deployment config deployment = architecture.get_deployment_manifest() print(f"\nDeployment Configuration Generated: {len(deployment['services'])} services")