DDD BELGIUM 2017 - The Dark Side of Event Sourcing

Evolving software systems often includes data schema changes, and those cause the need for data conversion. This is no different in event sourced systems.

Converting data between schemas while continuing the operation of the system is a challenge.

In this talk, we will look at the possible conversion operations, the techniques to execute them, and strategies for deployment with zero-downtime.

We will look at the possibilities and the trade-offs for designing and implementing upgrades for event sourced systems.

Transcript

1. The Dark Side of Event Sourcing Managing Data Conversion Michiel Overeem, Marten Spoor, Slinger Jansen
2. AFAS Software 400 employees 100 million euro revenue
4. x 10.000
5. Adaptable Model-based and User-specific Software Ecosystems
6. Copyright Nasa Goddard
7. How can an event sourced system be upgraded efficiently when the (implicit) event schema changes?
9. type Attribute = string * System.Object type Event = string * Attribute[] type EventStream = string * (Event[] * System.DateTime)[] type EventStore = EventStream[] The structure of an Event Store
10. But there is also a schema Which streams are known in the system? Which events are allowed in which streams? Which attributes are allowed in which events?
11. Example schema: webshop Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … AddedToChart ChangedQuantity …
12. Store level operations Add / remove streams Merge streams / split / … streams Stream level operations Add / remove events Merge events / split / … events Event level operations Add / update / remove attributes Merge attributes / split / … attributes How can we change it?
13. Multiple versions: always extend Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … AddedToChart ChangedQuantity …
14. Multiple versions: always extend Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … AddedToChart ChangedQuantity … Article Stream AddedToAssortment SoldOut …
15. Multiple versions: always extend Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … AddedToChart ChangedQuantity … Article Stream AddedToAssortment SoldOut … ChangedQuantity_V2
16. Is this maintainable? Becomes the codebase to complex?
17. Weakening the schema Which attributes can occure in which events? Which events can occure in which streams? Which streams can originate in the system?
18. Weak schema’s Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … AddedToChart ChangedQuantity …
19. Weak schema’s Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … AddedToChart ChangedQuantity … ChangedQuantity
20. Explosion of code paths? And still not all operations are possible.
21. Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … Upcasters: Evolve the events AddedToChart ChangedQuantity …
22. Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … Upcasters: Evolve the events AddedToChart ChangedQuantity … ChangedQuantity_V2 CustomerSignedUp_V2
23. What is the run-time overhead? Are all operations possible?
24. Beware of the projectors! Order of upgrading components still matters!
25. Beware of the projectors! Order of upgrading components still matters!
26. Beware of the projectors! Order of upgrading components still matters!
27. Store level operations Add / remove streams Merge streams / split / … streams Stream level operations Add / remove events Merge events / split / … events Event level operations Add / update / remove attributes Merge attributes / split / … attributes Can we perform all operations?
28. Store level operations Add / remove streams Merge streams / split / … streams Stream level operations Add / remove events Merge events / split / … events Event level operations Add / update / remove attributes Merge attributes / split / … attributes Can we perform all operations?
29. Copyright Stephen Cairns Technical versus functional immutability
30. Lazy transformation
31. But when is this finished? Mixed appends and updates.
32. In place transformation Just find the events and fix them.
33. Not for the faint of heart!
34. Copy and transformation
35. Change all the things! Auto backup. Could be very slow.
36. Multiple versions Weak schema Upcasters Lazy transformation In place transformation Copy and transformation Functional suitability +/- - +/- +/- + + Comparing the approaches
37. Multiple versions Weak schema Upcasters Lazy transformation In place transformation Copy and transformation Maintainability Comparing the approaches - +/- +/- +/- + +
38. Multiple versions Weak schema Upcasters Lazy transformation In place transformation Copy and transformation Performance efficiency + + + +/- +/- - Comparing the approaches
39. Multiple versions Weak schema Upcasters Lazy transformation In place transformation Copy and transformation Reliability + + + - - + Comparing the approaches
40. Copyright SpaceX
41. Schema versioning Multiple versions Weak schema Upcasters Lazy transformation In place transformation Copy and transformation Schema evolution
42. Runtime techniques Multiple versions Weak schema Upcasters Lazy transformation In place transformation Copy and transformation Non-runtime techniques
43. Big flip
44. Big flip
45. Big flip
46. Big flip
47. Big flip
48. Blue-Green
49. Blue-Green
50. Blue-Green
51. Blue-Green
52. Blue-Green
53. Rolling upgrade
54. Rolling upgrade
55. Rolling upgrade
56. Rolling upgrade
57. Rolling upgrade
58. But for schema evolution we need another strategy for database deployment.
59. Blue-Green
60. Blue-Green
61. Blue-Green
62. Expand- Contract
63. Expand- Contract
64. Expand- Contract
65. Expand- Contract
66. Combining everything into a framework Data upgrade Deployed with Executed by Executed by Data upgrade Application upgrade Lazy transformation Upcasting In place transfor- mation Multiple versions Copy and transfor- mation Basic & Complex Event Basic & Complex Stream Basic Store Complex Store Big Flip Rolling Upgrade Blue-Green Expand- Contract Blue- Green Deployed with Combined with Weak schema
67. But what about the query side?
68. Early interview results
69. Do you read your events ever again? No? Then just change the snapshot.
70. Move out all events belonging to old aggregates.
71. Nobody uses lazy transformation.
72. Domain driven design helps in preventing changes.
73. There is a lack of experience sharing.
74. What’s next? 1. Do interviews. Interested? Contact me! https://goo.gl/forms/7tuBKW39EPkWnZLG3 1. Write a follow up paper with more information. 2. Publish the experiences in some form.
75. Your context determines the best upgrade strategy. m.overeem@afas.nl @michielovereem