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EventSourcing .NET

Tutorial, practical samples and other resources about Event Sourcing in .NET. See also my similar repositories for JVM and NodeJS.

• EventSourcing .NET
  • 1. Event Sourcing
    • 1.1 What is Event Sourcing?
    • 1.2 What is Event?
    • 1.3 What is Stream?
    • 1.4 Event representation
    • 1.5 Event Storage
    • 1.6 Retrieving the current state from events
    • 1.7 Strongly-Typed ids with Marten
  • 2. Videos
    • 2.1. Practical Event Sourcing with Marten
    • 2.2. Keep your streams short! Or how to model event-sourced systems efficiently
    • 2.3. Let's build event store in one hour!
    • 2.4. CQRS is Simpler than you think with C#11 & NET7
    • 2.5. Practical Introduction to Event Sourcing with EventStoreDB
    • 2.6. How to deal with privacy and GDPR in Event-Sourced systems
    • 2.7 Let's build the worst Event Sourcing system!
    • 2.8 The Light and The Dark Side of the Event-Driven Design
    • 2.9 Implementing Distributed Processes
    • 2.10 Conversation with Yves Lorphelin about CQRS
    • 2.11. Never Lose Data Again - Event Sourcing to the Rescue!
  • 3. Support
  • 4. Prerequisites
  • 5. Tools used
  • 6. Samples
    • 6.1 Pragmatic Event Sourcing With Marten
    • 6.2 ECommerce with Marten
    • 6.3 Simple EventSourcing with EventStoreDB
    • 6.4 Implementing Distributed Processes
    • 6.5 ECommerce with EventStoreDB
    • 6.6 Warehouse
    • 6.7 Warehouse Minimal API
    • 6.8 Event Versioning
    • 6.9 Event Pipelines
    • 6.10 Meetings Management with Marten
    • 6.11 Cinema Tickets Reservations with Marten
    • 6.12 SmartHome IoT with Marten
  • 7. Self-paced training Kits
    • 7.1 Introduction to Event Sourcing
    • 7.2 Build your own Event Store
  • 8. Articles
  • 9. Event Store - Marten
  • 10. CQRS (Command Query Responsibility Separation)
  • 11. NuGet packages to help you get started.
  • 12. Other resources
    • 12.1 Introduction
    • 12.2 Event Sourcing on production
    • 12.3 Projections
    • 12.4 Snapshots
    • 12.5 Versioning
    • 12.6 Storage
    • 12.7 Design & Modeling
    • 12.8 GDPR
    • 12.9 Conflict Detection
    • 12.10 Functional programming
    • 12.12 Testing
    • 12.13 CQRS
    • 12.14 Tools
    • 12.15 Event processing
    • 12.16 Distributed processes
    • 12.17 Domain Driven Design
    • 12.18 Whitepapers
    • 12.19 Event Sourcing Concerns
    • 12.20 This is NOT Event Sourcing (but Event Streaming)
    • 12.21 Architecture Weekly
  • License

1. Event Sourcing

1.1 What is Event Sourcing?

Event Sourcing is a design pattern in which results of business operations are stored as a series of events.

It is an alternative way to persist data. In contrast with state-oriented persistence that only keeps the latest version of the entity state, Event Sourcing stores each state change as a separate event.

Thanks to that, no business data is lost. Each operation results in the event stored in the database. That enables extended auditing and diagnostics capabilities (both technically and business-wise). What's more, as events contains the business context, it allows wide business analysis and reporting.

In this repository I'm showing different aspects and patterns around Event Sourcing from the basic to advanced practices.

Read more in my articles:

• 📝 How using events helps in a teams' autonomy
• 📝 When not to use Event Sourcing?

1.2 What is Event?

Events represent facts in the past. They carry information about something accomplished. It should be named in the past tense, e.g. "user added", "order confirmed". Events are not directed to a specific recipient - they're broadcasted information. It's like telling a story at a party. We hope that someone listens to us, but we may quickly realise that no one is paying attention.

Events:

• are immutable: "What has been seen, cannot be unseen".
• can be ignored but cannot be retracted (as you cannot change the past).
• can be interpreted differently. The basketball match result is a fact. Winning team fans will interpret it positively. Losing team fans - not so much.

Read more in my articles:

• 📝 What's the difference between a command and an event?
• 📝 Events should be as small as possible, right?
• 📝 Anti-patterns in event modelling - Property Sourcing
• 📝 Anti-patterns in event modelling - State Obsession

1.3 What is Stream?

Events are logically grouped into streams. In Event Sourcing, streams are the representation of the entities. All the entity state mutations end up as the persisted events. Entity state is retrieved by reading all the stream events and applying them one by one in the order of appearance.

A stream should have a unique identifier representing the specific object. Each event has its own unique position within a stream. This position is usually represented by a numeric, incremental value. This number can be used to define the order of the events while retrieving the state. It can also be used to detect concurrency issues.

1.4 Event representation

Technically events are messages.

They may be represented, e.g. in JSON, Binary, XML format. Besides the data, they usually contain:

• id: unique event identifier.
• type: name of the event, e.g. "invoice issued".
• stream id: object id for which event was registered (e.g. invoice id).
• stream position (also named version, order of occurrence, etc.): the number used to decide the order of the event's occurrence for the specific object (stream).
• timestamp: representing a time at which the event happened.
• other metadata like correlation id, causation id, etc.

Sample event JSON can look like:

{
  "id": "e44f813c-1a2f-4747-aed5-086805c6450e",
  "type": "invoice-issued",
  "streamId": "INV/2021/11/01",
  "streamPosition": 1,
  "timestamp": "2021-11-01T00:05:32.000Z",

  "data":
  {
    "issuedTo": {
      "name": "Oscar the Grouch",
      "address": "123 Sesame Street"
    },
    "amount": 34.12,
    "number": "INV/2021/11/01",
    "issuedAt": "2021-11-01T00:05:32.000Z"
  },

  "metadata":
  {
    "correlationId": "1fecc92e-3197-4191-b929-bd306e1110a4",
    "causationId": "c3cf07e8-9f2f-4c2d-a8e9-f8a612b4a7f1"
  }
}

Read more in my articles:

• 📝 Mapping event type by convention
• 📝 [Explicit events serialisation in Event