CodeCamp 2018 - Architecting Systems with CQRS - Four Years Experience Report and Implementation Considerations

Nov 27, 20180 likes231 views

The document discusses Command Query Responsibility Segregation (CQRS), an architectural pattern that separates read and write operations. It summarizes three projects that were refactored using CQRS, resulting in separation of queries and commands into their own categories. The benefits of CQRS included developing and testing features in isolation, flexibility to use different technologies, optimizing reads independently from writes, and improved organization. Challenges included deciding how to implement CQRS and the initial complexity of setting it up.

CodeCamp 2018 - Architecting Systems with CQRS - Four Years Experience Report and Implementation Considerations

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Architecting Systems
with CQRS
Four Years Experience Report and
Implementation Considerations
Bojan Veljanovski
CTO at HASELT

Typical issues
- Loading more than necessary data from ORMs
when building DTOs
- Loading of multiple domain objects to build a DTO
causes non-optimal querying to the data model
- Domain objects are not optimized neither for
reading neither for writing

Typical issues
- A lot of mapping ceremony
- Hard to scale when project or team grows
- Frequent merge conflicts – more people changing
same classes
- Finding things is harder due large classes and
many dependencies

What is CQRS?
- Command
- Query
- Responsibility
- Segregation

Project A:
- 17 controllers
- 89 actions (33 queries + 56 commands)
Project B:
- 58 controllers
- 419 actions (242 queries + 177 commands)
Project C:
- 41 controllers
- 228 actions (121 queries + 107 commands)

Divide actions in two categories
- Commands (WRITE)
- Queries (READ)

Why divide writes from reads?
- Differences between writes and reads
- Changing data?
- Reading data?
- Validation?
- Executing business rules?
- Caching?
- Authorization?
- Optimization?

Command side
- Modifies state
- Checks business rules
- Does not return data
- Does one thing well (SRP)

Query side
- Does not change state (has no side effects)
- Reads data
- Aggregation
- Filtering
- Caching

CQRS and REST
- Commands = POST/PUT/DELETE requests
- Queries = GET requests

DEMO
https://github.com/bojanv91/ContosoUniversity

1. Developing, testing, and evolving
features in isolation

2. Enables flexibility - can use different
technology per command/query without
affecting the whole codebase

3. Optimize and scale reads
independently from writes

4. Low coupling – only depend on what
the action needs

5. Makes things easier to find and reason
about

6. Less places to change - what changes
together, is organized together

7. Cost-effective onboarding of new
developers on the project

8. Supports team and codebase growth
- can scale easily to new bounded
contexts and/or microservices

Challenges
- Deciding how to implement
- what makes sense for your team
- Complex to setup
- the first time
- Understanding how it works behind the scenes

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CodeCamp 2018 - Architecting Systems with CQRS - Four Years Experience Report and Implementation Considerations

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4. Architecting Systems with CQRS Four Years Experience Report and Implementation Considerations Bojan Veljanovski CTO at HASELT

5. Typical application architecture

6. Typical application architecture

10. Typical issues - Loading more than necessary data from ORMs when building DTOs - Loading of multiple domain objects to build a DTO causes non-optimal querying to the data model - Domain objects are not optimized neither for reading neither for writing

11. Typical issues - A lot of mapping ceremony - Hard to scale when project or team grows - Frequent merge conflicts – more people changing same classes - Finding things is harder due large classes and many dependencies

12. What is CQRS? - Command - Query - Responsibility - Segregation

13. Project A: - 17 controllers - 89 actions (33 queries + 56 commands) Project B: - 58 controllers - 419 actions (242 queries + 177 commands) Project C: - 41 controllers - 228 actions (121 queries + 107 commands)

14. Divide actions in two categories - Commands (WRITE) - Queries (READ)

15. Why divide writes from reads? - Differences between writes and reads - Changing data? - Reading data? - Validation? - Executing business rules? - Caching? - Authorization? - Optimization?

16. Command side - Modifies state - Checks business rules - Does not return data - Does one thing well (SRP)

17. Query side - Does not change state (has no side effects) - Reads data - Aggregation - Filtering - Caching

18. CQRS and REST - Commands = POST/PUT/DELETE requests - Queries = GET requests

19. Our way to CQRS

24. Users Service

25. After CQRS (A Command)

26. After CQRS (A Query)

27. After CQRS (Feature Folder)

28. After CQRS (Controller)

29. DEMO https://github.com/bojanv91/ContosoUniversity

30. Results, observations, and challenges

31. Project A: - 17 controllers - 89 actions (33 queries + 56 commands) Project B: - 58 controllers - 419 actions (242 queries + 177 commands) Project C: - 41 controllers - 228 actions (121 queries + 107 commands)

32. 1. Developing, testing, and evolving features in isolation

33. 2. Enables flexibility - can use different technology per command/query without affecting the whole codebase

34. 3. Optimize and scale reads independently from writes

35. 4. Low coupling – only depend on what the action needs

36. 5. Makes things easier to find and reason about

37. 6. Less places to change - what changes together, is organized together

38. 7. Cost-effective onboarding of new developers on the project

39. 8. Supports team and codebase growth - can scale easily to new bounded contexts and/or microservices

40. Challenges - Deciding how to implement - what makes sense for your team - Complex to setup - the first time - Understanding how it works behind the scenes

41. Further Reading

42. DEMO https://github.com/bojanv91/ContosoUniversity

43. Thanks! Any Questions?

CodeCamp 2018 - Architecting Systems with CQRS - Four Years Experience Report and Implementation Considerations

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