Architecture

Here’s an example of a State Diagram for a reservation system object. This illustrates the states that a reservation can move through and the transitions triggered by events or actions. stateDiagram-v2 state "Pending" as Pending state "Confirmed" as Confirmed state "Cancelled" as Cancelled state "Completed" as Completed %% State Transitions Pending --> Confirmed: Payment Received Pending --> Cancelled: Customer Cancels Confirmed --> Cancelled: Customer Cancels Confirmed --> Completed: Reservation Period Ends Cancelled --> Pending: Reopen Request Explanation of States and Transitions: States: ...

Below is an example of a deployment diagram for our event-based reservation system. This shows how components of the system are deployed across servers, environments, and external services in a physical setup. You can use the following Mermaid code to visualize it in a Mermaid-enabled renderer: graph TD %% Deployment Nodes subgraph ClientMachine [Client Machine] FrontendApp[Reservation Frontend App] end subgraph AppServer [Application Server] ReservationService[Reservation Service] WolverineEventBus[Wolverine Event Bus] DurableOutbox[Durable Outbox] end subgraph Messaging [Messaging Infrastructure] MessageBroker[Message Broker] end subgraph DatabaseServer [Database Server] ReservationsDB[Reservations Database] CustomersDB[Customers Database] end subgraph ExternalServices [External Systems] PaymentGateway[Payment Gateway] NotificationService[Notification Service] ResourceCatalog[Resource Catalog Service] end %% Interactions FrontendApp --> ReservationService ReservationService --> WolverineEventBus WolverineEventBus --> DurableOutbox WolverineEventBus --> MessageBroker MessageBroker --> PaymentGateway MessageBroker --> NotificationService ReservationService --> ReservationsDB ReservationService --> CustomersDB ReservationService --> ResourceCatalog Explanation Nodes: ...

Here is a conceptual Entity-Relationship Diagram (ERD) for our conceptual reservation system. This diagram includes entities such as Customer, Reservation, and Resource, along with their attributes and relationships. erDiagram %% Customer Entity Customer { int Id string FullName string Email string Phone } %% Resource Entity Resource { int Id string Name string Description int Capacity } %% Reservation Entity Reservation { int Id int CustomerId int ResourceId DateTime StartDate DateTime EndDate string Status } %% Relationships Customer ||--o{ Reservation : "creates" Resource ||--o{ Reservation : "associated with" Explanation Entities: ...

Below is an example of an Infrastructure Diagram that illustrates how our event-based reservation system might be deployed using cloud resources. This includes virtual machines, networks, containers, and external services. graph TD %% Cloud Platform subgraph CloudInfrastructure[Cloud Infrastructure -e.g., AWS, Azure, GCP-] LB[Load Balancer] VPC[VPC -Virtual Private Cloud-] subgraph AppLayer[Application Layer] EC2Instance1[Virtual Machine: Reservation Service Instance 1] EC2Instance2[Virtual Machine: Reservation Service Instance 2] Container1[Docker Container: Wolverine Event Bus] Container2[Docker Container: Durable Outbox] end subgraph DataLayer[Data Layer] DBCluster[Managed Database Cluster] BackupStorage[Cloud Backup Storage] end subgraph ExternalServices[External Integrations] PaymentGateway[Payment Gateway] NotificationService[Notification Service] ResourceCatalog[Resource Catalog API] end end %% Interactions LB --> EC2Instance1 LB --> EC2Instance2 EC2Instance1 --> Container1 EC2Instance2 --> Container2 EC2Instance1 --> DBCluster DBCluster --> BackupStorage Container1 --> PaymentGateway Container2 --> NotificationService EC2Instance1 --> ResourceCatalog Explanation of Components: Cloud Infrastructure: ...

Below is an example of a Network Diagram that depicts a possible topology for our reservation system, illustrating firewalls, routers, subnets, and connections. It is designed to enhance network security and efficiency. graph TB %% Internet Internet[Internet] --> Firewall1[Firewall] %% Perimeter Network -DMZ subgraph DMZ[Perimeter Network -DMZ-] Router[Router] APIGateway[API Gateway] end Firewall1 --> Router Router --> APIGateway %% Internal Network subgraph InternalNetwork[Internal Network] LoadBalancer[Load Balancer] ApplicationServer1[App Server 1] ApplicationServer2[App Server 2] DatabaseServer[Database Server] EventBus[Wolverine Event Bus] end APIGateway --> LoadBalancer LoadBalancer --> ApplicationServer1 LoadBalancer --> ApplicationServer2 ApplicationServer1 --> DatabaseServer ApplicationServer2 --> DatabaseServer ApplicationServer1 --> EventBus ApplicationServer2 --> EventBus %% External Services subgraph ExternalServices[External Services] NotificationService[Notification Service] PaymentGateway[Payment Gateway] end EventBus --> NotificationService EventBus --> PaymentGateway Components Breakdown: Internet: ...

Building a Robust Reservation System with Event-Driven Architecture In this post, I’ll guide you through creating a scalable reservation system using event-driven architecture. We’ll explore domain modeling, event handling, and message processing - essential concepts for modern distributed systems. The Reservation Process Flow Let’s start by visualizing the reservation workflow with a Mermaid diagram: flowchart TD A[Start Reservation Process] --> B[Receive Reservation Request] B --> C{Validate Request} C -->|Valid| D[Check Availability] C -->|Invalid| E[Return Error to Client] D --> F{Availability?} F -->|Available| G[Create Reservation] F -->|Not Available| H[Notify Client of Unavailability] G --> I[Send Confirmation via Wolverine] H --> I I --> J[Store Reservation in Postgres] J --> K[Return Success Response to Client] E --> L[End Process] K --> L This diagram shows the end-to-end process from receiving a request to returning a response, with key decision points and actions along the way. ...

1. Define Your Requirements Before diving into code, clarify the system’s core functionalities. For a reservation system, we might consider: Booking Management: Creating, updating, and canceling reservations. Availability Checking: Ensuring that double-booking or conflicts are prevented. Customer Management: Handling user details, authentication, and notifications. Resource or Venue Management: Tracking the items or spaces being reserved. Concurrency Control: Managing simultaneous booking attempts (e.g., using transactions and locks). Understanding these requirements will help guide your design decisions. ...

Designing an event-based system with Wolverine is an exciting challenge that leverages asynchronous messaging to decouple components and build a resilient architecture. Here’s a comprehensive pathway to help you get started: 1. Understand the Role of Wolverine Wolverine is a lightweight, .NET-native messaging framework designed to help you craft robust, event-driven applications. It facilitates: Message Routing: Seamlessly route events and commands to corresponding handlers. Transport Flexibility: Integrate with in-memory queues or external messaging systems such as RabbitMQ or Azure Service Bus. Resilience and Durability: Apply advanced patterns like retry, scheduling, and outbox support if needed. By using Wolverine, you can focus on business logic while the framework handles much of the messaging infrastructure. ...

Here’s an example of a Business Event Flow Diagram tailored to a reservation system, illustrating how a typical business event (e.g., “Customer makes a reservation”) flows through the organization: flowchart TD %% Event Trigger Customer[Customer Initiates Reservation] --> SubmitRequest[Submit Reservation Request] SubmitRequest --> ValidateInputs[Validate Input Data] ValidateInputs -->|Valid| CheckAvailability[Check Resource Availability] ValidateInputs -->|Invalid| RejectRequest[Reject Request with Error] CheckAvailability -->|Available| ProcessReservation[Process Reservation] CheckAvailability -->|Not Available| NotifyUnavailability[Notify Customer of Unavailability] ProcessReservation --> CreateEvent[Create Business Event: ReservationCreated] CreateEvent --> NotifyCustomer[Send Confirmation Notification] CreateEvent --> UpdateDB[Update Reservation Database] NotifyCustomer --> End[End] UpdateDB --> End[End] NotifyUnavailability --> End[End] RejectRequest --> End[End] Key Elements: Event Trigger: The workflow begins when the customer initiates the reservation request. ...

Understanding CQRS: Command Query Responsibility Segregation Command Query Responsibility Segregation (CQRS) is an architectural pattern that separates read and write operations into distinct models. This separation allows for optimization of each model independently, addressing different requirements and scaling needs. Core Components of CQRS flowchart TD Client[Client Application] --> Commands[Commands] Client --> Queries[Queries] Commands --> CommandHandler[Command Handler] Queries --> QueryHandler[Query Handler] CommandHandler --> WriteModel[Write Model/Domain Model] WriteModel --> EventStore[Event Store] EventStore --> ReadModelProjection[Read Model Projection] ReadModelProjection --> ReadModel[Read Model] QueryHandler --> ReadModel ReadModel --> QueryResults[Query Results] QueryResults --> Client Key Components and Their Responsibilities: Commands: Instructions to change state (e.g., CreateOrder, UpdateCustomer). Queries: Requests for information without state changes. Command Handler: Processes commands and applies them to the write model. Write Model: The domain model with rich business logic. Event Store: Records all state-changing events as the source of truth. Read Model Projection: Processes events to update the read model. Read Model: Optimized for querying, often denormalized for performance. Query Handler: Retrieves data from the Read Model in response to queries. The separation of write and read models allows for independent optimization, scalability, and security for both operations. ...