Event Sourcing - Intro and Outro

Intent behind

Event sourcing is a software design pattern where every change to an application’s state is captured as an immutable event and stored in sequence, rather than storing only the latest state. Each event represents a fact about something that happened (e.g., “Order Placed”, “Amount Deposited”), and the current state can be obtained by replaying all these events in order. This lets us query the current state and reconstruct past states or see how the state evolved over time.

Analogy: Ledger vs. Snapshot

• Traditional (CRUD) approach: Only the current state is stored -- like seeing just your latest bank statement (the current balance).
• Event sourcing approach: All changes are stored as a sequence of events -- like having the full transaction ledger from day one (every deposit, withdrawal, etc.).
  With the ledger, you can explain why the balance is what it is by looking at the list of transactions, rather than a single number with no history.

How It Works

Example: A warehouse product currently shows 59 units in stock.
In a traditional system, the database might store a record that simply says quantity = 59.
In an event-sourced system, the sequence of events that led to 59 would be stored instead:

1. “Received 10 units”
2. “Received 5 units”
3. “Shipped 6 units”
4. “Inventory adjusted +50 units”

To derive the current quantity, the application starts from zero and applies each event in order (10 + 5 − 6 + 50 = 59).

Replaying Events

1. Start from an initial state.
2. Apply events one by one.
3. Arrive at the current state.

The ordered list of events for a single entity (e.g., an order or a product) is often called an event stream. Performance implifications are mitigated by snapshots. Drift in events mitigated by schema upcasting, a commmon pattern in event-driven systems or any system that relies on contracts.

Benefits of Event Sourcing

• Complete history & audit trail: Every change is recorded, making it easy to trace how and why something reached its current state.
• Rebuild past states (“time travel”): You can recreate the system’s state at any moment by replaying events up to that point.
• Flexible projections (views): Multiple read-models can be built from the same event log, each tailored to specific queries or dashboards.
• Scalability and decoupling: Writes append to a log; reads come from separate, optimized projections. This fits well with CQRS (Command Query Responsibility Segregation) and can improve performance in high-scale systems.

Final Thoughts & Trade-offs

Event Sourcing as a Knowledge Model

Event Sourcing isn’t just about capturing lossless data -- it’s about building a system that models, interprets, and understands business reality in a structured, testable way.

Events = Facts

Each event (e.g., OrderPlaced, PaymentCaptured) is an immutable record of something that happened. It encodes a business truth, not an opinion or prediction. Events are the factual bedrock of system knowledge.

Context = Sequence of Events

The full event stream for an aggregate or system provides context -- the timeline of decisions and outcomes. This sequence preserves causality, intent, and evolution, enabling deep inspection or replay.

Interpretation = Core Domain Code

Core domain logic (aggregates, policies, invariants) replays the event stream to:

• Rehydrate state
• Evaluate business rules
• Decide which commands are valid
• Emit new events

This layer gives meaning to facts -- turning raw data into domain-relevant behavior.

Understanding = Projections

Projections (read models) interpret and summarize event history into current state. They reflect the system’s understanding of the world -- often optimized for queries, business decisions, or user interfaces.

Summary Table

Why This Matters

Traditional systems store state; event-sourced systems store knowledge.

• CRUD systems overwrite data and lose reasoning over time.
• Event Sourcing captures what happened, in what order, and why -- enabling retrospective analysis, auditability, and richer business insights.
• The combination of immutable facts + domain reasoning + understanding layers makes Event Sourcing a true knowledge-centric architecture.
• Both approaches have their place in system design, the right choice depends on your specific domain requirements, team expertise, and the importance of historical context to your business processes.
• Hybrid approaches often provide the best of both worlds: using Event Sourcing for core business entities where history matters most, while employing CRUD for supporting entities where direct state access and atomic WRITE-READs are more valuable than complete history.

Closing notes: Addressing the Complexity in Systems

Event Sourcing requires deliberate structure but that doesn’t make CRUD simpler by default. CRUD systems often start lightweight but become convoluted as business logic grows. Implicit workflows, scattered conditionals, and cross-cutting concerns creep in, turning diagrams into dense webs of interactions. The simplicity is superficial: data is overwritten, intent is lost, and tracing why something happened becomes difficult. Event Sourcing embraces complexity upfront to make behavior explicit, reproducible, and evolvable.

1. Implicit vs. Explicit Knowledge: When a system doesn't explicitly capture the "why" behind changes (intent), this knowledge often exists only in developers' minds or external documentation. As team members change or time passes, this context gets lost, making future changes riskier and more complex.
2. Debugging Challenges: Without clear intent captured in the system, diagnosing issues becomes archaeological work - examining database snapshots and logs without understanding the business processes that led to the current state.
3. Compensating Mechanisms: As CRUD systems grow, teams often add workarounds to capture some aspects of history and intent - like audit tables, change logs, or state transition tables. These compensating mechanisms add accidental complexity that wasn't in the original design.
4. Scattered Logic: Without a clear model of business events and intent, logic that should be cohesive often gets distributed across multiple update operations, controllers, and services, making it harder to understand the system as a whole.
5. Cross-cutting Concerns: Features like auditing, compliance, and analytics become increasingly difficult when intent isn't captured, leading to duplicate logic and inconsistent implementations.

Event Sourcing addresses these challenges by making complexity explicit from the beginning - trading upfront design effort for long-term clarity, traceability, and evolvability. Rather than hiding complexity that will inevitably emerge, it provides a structure to manage it from the outset.