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# CQRS and Event Sourcing without the pixie dust

Microservices aren't magic. An event bus alone just creates a distributed ball of mud. Learn how true CQRS and event sourcing achieve genuine architectural modularity.

- **Speakers:** Allard Buijze
- **Event:** World Congress 2021
- **Published:** June 29, 2021
- **Duration:** 43:27
- **URL:** https://www.wearedevelopers.com/videos/163-cqrs-and-event-sourcing-without-the-pixie-dust

## Summary

Transitioning from monolithic architectures to microservices often promises cleaner codebases, but simply increasing deployment units without genuine modularity only creates a distributed "big ball of mud." True architectural modularity demands a shift toward message-driven principles, breaking apart the misconception that routing all operations through an event bus magically dissolves system coupling. A clear distinction must be made between event streaming and event sourcing; while the former is merely passing messages to another database, true event sourcing relies on a component using its own immutable, append-only log of past decisions to dictate future behavior, ensuring an irrefutable audit trail and dealing naturally with complex domains.

Because an append-only event log answers how a system arrived at its current state but struggles to quickly query what that current state is (like calculating a real-time bank balance), Command Query Responsibility Segregation (CQRS) becomes essential. CQRS decouples the application into separate command models for mutating state and projection models for querying data. Embracing this pattern requires development teams to accept eventual consistency, recognizing that the rigid pursuit of synchronized state across services often yields catastrophic eventual inconsistency over time.

Applying these principles practically requires differentiating between three distinct message types: commands (instructing actions), events (emitting facts), and queries (requesting state). Demonstrated through a Java-based bike rental application using the Axon Framework, this strict message segregation enables true "location transparency." Components do not need to know where their collaborating services reside, allowing engineers to dynamically extract logic, split monoliths into independent deployment units, and scale systems under load without altering the underlying business behavior.

**Keywords:** cqrs, event sourcing, microservices architecture, axon framework, domain-driven design, event storming, location transparency, eventual consistency, command query responsibility segregation, architectural modularity, event streaming vs event sourcing, message-driven design, distributed systems architecture, java backend development

## Chapters

1. **The evolution of monolithic layered architectures** (00:03) — How the traditional layered architectural pattern inevitably evolves into an unmaintainable big ball of mud.
1. **Splitting monoliths into distributed microservices architectures** (02:52) — Increasing the number of deployment units without increasing modularity results in a distributed big ball of mud.
1. **Combating technical debt and anti-modularity forces** (05:48) — Day-to-day workarounds and deferred refactoring actively degrade application architecture over time by accumulating unstructured dependencies.
1. **Decoupling microservices using event-driven communication models** (06:56) — Using publish-subscribe event models reduces direct service coupling but can obscure execution flow and logical dependency tracking.
1. **The false promises of event-driven microservices** (10:48) — Applying simplistic monolithic methodologies to modern message brokers often reproduces identical coupling issues inside distributed systems.
1. **Differentiating event streaming from true event sourcing** (13:12) — Event sourcing uses historical past decisions to explicitly dictate future application states rather than safely streaming update notifications between tables.
1. **Preserving historical state interactions for reliable auditability** (17:41) — Persisting absolute raw state modification sequences ensures uncompromised audit trails and simplifies managing inherently complex conceptual domain representations.
1. **Managing current state with CQRS and data projections** (20:52) — CQRS safely circumvents the query limitations of aggregated event logs by cleanly separating write models from read-optimized data projections.
1. **Building disciplined domain models for event-driven systems** (24:02) — Sustaining a successful event-centric integration strategy requires embracing domain-driven design modeling techniques instead of purely relying upon broker technologies.
1. **Defining commands, events, and queries in messaging** (28:09) — Understanding the explicit routing behaviors of different interaction patterns provides significantly better runtime decoupling between bounded domain functionalities.
1. **Achieving location transparency across distributed deployment units** (31:10) — Designing modules to communicate agnostically removes the brittle requirement to explicitly hardcode particular network recipient locations.
1. **Implementing CQRS and event sourcing in Java** (32:49) — Demonstrating a robust command validation model that safely enforces consistent backend business behaviors under concurrent transaction loads inside a monolithic setup.
1. **Dynamically splitting monoliths into distributed microservice components** (36:17) — Extracting previously composed backend modules into independent operational runtimes verifies the deployment agility produced by strict interface decoupling.

## Related Moments

- [Core principles of transitioning to full event sourcing](https://www.wearedevelopers.com/videos/91-from-event-streaming-to-event-sourcing-101) (from "From event streaming to event sourcing 101")
- [Transitioning from synchronous microservices to event sourcing](https://www.wearedevelopers.com/videos/168-kafka-streams-microservices) (from "Kafka Streams Microservices")
- [Clarifying terminology around different event computing software forms](https://www.wearedevelopers.com/videos/538-event-messaging-and-streaming-with-apache-pulsar) (from "Event Messaging and Streaming with Apache Pulsar")
- [Introducing beneficial architectural patterns like event sourcing](https://www.wearedevelopers.com/videos/218-seven-myths-three-reasons-one-goal) (from "Seven Myths, Three Reasons, One Goal")
- [Audience Q&A on monolithic versioning and configuration boundaries](https://www.wearedevelopers.com/videos/363-automagic-configuration-in-python) (from "Automagic Configuration in Python")
- [Pushing data streams into isolated read models](https://www.wearedevelopers.com/videos/494-the-rise-of-reactive-microservices) (from "The Rise of Reactive Microservices")

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- [Dev Digest 138 - Are you secure about this?](https://www.wearedevelopers.com/magazine/486-dev-digest-138-are-you-secure-about-this)
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