A visual introduction to Event Sourcing and CQRS (original) (raw)

• 1. A visual introduction to Event Sourcing and CQRS 1 @nicusX https://opencredo.com/author/lorenzo/ Lorenzo Nicora Senior Consultant @ OpenCredo

• 2. 2 A couple of concepts from DDD Aggregate (Current) State of the Aggregate Lorenzo Nicora Intro to Event Sourcing and CQRS

• 3. 3 Once upon a time… Everything is synchronous Request - Response Lorenzo Nicora Intro to Event Sourcing and CQRS

• 4. 4 Scaling up… Updates —> Locks —> Contention! <— Block <— Lorenzo Nicora Intro to Event Sourcing and CQRS

• 5. 5 Let’s go Asynchronous Pwd —> “secret” Pwd —> “12345” Pwd —> “54321” Pwd —> “secret” Pwd —> “54321” Pwd —> “12345” ===> Out of Order Asynchronous, Message-driven Request/Response ACID Transaction Distributed, Message-based —> No order guaranteed Lorenzo Nicora Intro to Event Sourcing and CQRS

• 6. 6 Command Sourcing 💡 • Append Only —> No Contention • Build State from Command history Write fast, Think later K/V Store Distributed Lorenzo Nicora Intro to Event Sourcing and CQRS

• 7. Command “Submit Order!” —> A request (imperative sentence) —> May fail —> May affect multiple Aggregates 7 Commands vs Events ✉ Rebuild Aggregate State from Commands Lorenzo Nicora Intro to Event Sourcing and CQRS

• 8. 8 Event “Order submitted” —> Statement of facts (past tense) —> Never fails —> May affect a single Aggregate ✉ Rebuild Aggregate State from Events Lorenzo Nicora Intro to Event Sourcing and CQRS

• 9. 9 Commands to Events (DDD patterns: Aggregate / Process Manager) X Y Z Lorenzo Nicora Intro to Event Sourcing and CQRS

• 10. 10 Command > Event Sourcing 💡 Think a little, Write, Think later Lorenzo Nicora Intro to Event Sourcing and CQRS

• 11. 11 Event Sourcing In many domains Commands Events Lorenzo Nicora Intro to Event Sourcing and CQRS

• 12. 12 Additional Benefits Easy Eventual Business Consistency —> Corrective Events Robust to data corruption (bugs, fat fingers…) —> Rebuild state ignoring wrong events Lorenzo Nicora Intro to Event Sourcing and CQRS

• 13. 13 Additional Benefits History (for free) Rebuild State at a point in Time Lorenzo Nicora Intro to Event Sourcing and CQRS

• 14. 14 Main Benefit Scalable —> Append only -> Fits distributed k/v stores —> Low-latency writes —> Allows asynchronous processing Lorenzo Nicora Intro to Event Sourcing and CQRS

• 15. What about reads? 15 Lorenzo Nicora Intro to Event Sourcing and CQRS

• 16. 16 Retrieving the State How do I retrieve the State? “Get details of Order ‘AB123’” ❔ not very efficient, but… …may work Lorenzo Nicora Intro to Event Sourcing and CQRS

• 17. 17 Querying (Searching) the State ❓ ❓ How do query the State? “Get all Orders delivered to ‘SE1 0NZ’” ❓ ❓ Lorenzo Nicora Intro to Event Sourcing and CQRS

• 18. 18 CQRS Command Query Responsibility Segregation 💡 Separate • Code • muService • Datastore -> Update -—> Retrieve “Query” datastore is downstream Lorenzo Nicora Intro to Event Sourcing and CQRS

• 19. 19 Not a new idea Specialised Downstream Lorenzo Nicora Intro to Event Sourcing and CQRS

• 20. 20 CQRS and Event Sourcing Lorenzo Nicora Intro to Event Sourcing and CQRS

• 21. 21 Materialised Views (of current State) Lorenzo Nicora Intro to Event Sourcing and CQRS

• 22. 22 Materialised Views (of State) Latest (known) State (Persistent) Rebuildable from Events In Memory K/V Store Graph … RDBMS Delayed 💡 Lorenzo Nicora Intro to Event Sourcing and CQRS

• 23. 23 Materialised View of State Query a RDBMS?!? Wasn’t it the old way? ❓ RDBMS is just one of our options: easy to use, easily become a bottleneck Lorenzo Nicora Intro to Event Sourcing and CQRS

• 24. 24 Materialised Views of State * Views are optimised for specific query use cases —> multiple Views from same Events * Updated asynchronously, delayed —> to Scale -> may reorder Events Lorenzo Nicora Intro to Event Sourcing and CQRS

• 25. 25 Materialised Views of State * Views can be rebuilt from Events Event Log is our Source of Truth * Easy to evolve or fix —> change or fix logic; rebuild view from events (not the View) Lorenzo Nicora Intro to Event Sourcing and CQRS

• 26. 26 Indexes Lorenzo Nicora Intro to Event Sourcing and CQRS

• 27. 27 Indexes Search Engines K/V Stores • Optimised for querying (less for retrieving) • Latest State; rebuild on the fly 💡 Lorenzo Nicora Intro to Event Sourcing and CQRS

• 28. 28 Hybrid solutions Lorenzo Nicora Intro to Event Sourcing and CQRS

• 29. 29 Hybrid solutions: e.g. Snapshots • Speed up rebuilding the current State • Use recent Events to rebuild up-to-date 💡 Long delayed Lorenzo Nicora Intro to Event Sourcing and CQRS

• 30. 30 Eventual (Business) Consistency Guess —> Compensate—> Apologies Lorenzo Nicora Intro to Event Sourcing and CQRS

• 31. 31 Eventual Consistency: Sagas StatefulOut of band Corrective Command or Event Saga Lorenzo Nicora Intro to Event Sourcing and CQRS

• 32. 32 Lesson from the Trenches Lorenzo Nicora Intro to Event Sourcing and CQRS

• 33. 33 Lesson Learned #1 If you put data in… …you will eventually have to get them out! The “Query” side is not secondary Lorenzo Nicora Intro to Event Sourcing and CQRS

• 34. 34 Lessons Learned #2 In old days: normalising one DB to support as many queries as possible With CQRS: multiple denormalised “data stores” optimised for different queries No single “Q” implementation for all your queries Lorenzo Nicora Intro to Event Sourcing and CQRS

• 35. 35 Lessons Learned #3 A central, shared Event Store may not be the best option No Event-sourced Monolith Prefer persistence per Bounded-Context Lorenzo Nicora Intro to Event Sourcing and CQRS

• 36. +++ Summing up +++ 36 Lorenzo Nicora Intro to Event Sourcing and CQRS

• 37. 37 ES/CQRS Optimal Use Cases High Volume Low Latency writes (big data) Event Sourcing + CQRS 😋 Out-of-order Commands/Events (IoT) Lorenzo Nicora Intro to Event Sourcing and CQRS

• 38. 38 ES/CQRS Drawbacks x No “One-Size-Fits-All” —> Multiple “Q” implementations x Delayed reads x No ACID Transactions x Additional complexity (!) 🙁 Lorenzo Nicora Intro to Event Sourcing and CQRS

• 39. 39 ES/CQRS Benefits + No “One-Size-Fits-All” —> “Q” are optimised for use cases + Eventual (Business) Consistency + History, Temporal queries + Robust to data corruption 😀 Lorenzo Nicora Intro to Event Sourcing and CQRS

• 40. That’s all, Folks! 40 Lorenzo Nicora Intro to Event Sourcing and CQRS

• 41. ??? Questions ??? 41 Thanks. ⏳ Lorenzo Nicora Intro to Event Sourcing and CQRS