Leveraging the power of Reactive Architectures

Microservices, Reactive, and Distributed Systems Vienna

Transcript

1. Leveraging the power of Reactive Architectures Microservices, Reactive and Distributed Systems Vienna Vienna, August 2021
2. @duffleit @duffleit david.leitner@squer.at David Leitner Coding Architect
3. Reactive? Programming with, or designing upon, asynchronous data streams.
4. asynchronous data streams. Space Time Collections Iterator Generator Value Getter Setter Promise Deferred Resolver Stream Reader Emitter
5. The relationship between them is implicit, an idea that only exists in the mind of the programmers. It should be explicit, a part of the language, and existing for all time. Counter and doubled should be bound.
6. the Destiny Operator paulstovell.com/reactive-programming
7. 1 map(x => x*2) 2 3 6 Reactive Programming, is Programming with Streams.
10. C’mon, show me a down-to-earth example.
11. YAMS — Yet Another Mail Service NEW 2021-04-11 — An important Email 2021-04-09 — Another important Email 2021-04-08 — Do you want to join my network? 2021-04-05 — Nigerian prince wants to send you money X your inbox contains 4 mails 1 NEW Mail Reload Controller Rest Client update UI Element update UI update UI
12. YAMS — Yet Another Mail Service NEW 2021-04-11 — An important Email 2021-04-09 — Another important Email 2021-04-08 — Do you want to join my network? 2021-04-05 — Nigerian prince wants to send you money X your inbox contains 4 mails 1 NEW Mail Reload Websocket Client Email Email count() count() collect() filter() subscribe Email map()
13. YAMS — Yet Another Mail Service NEW 2021-04-11 — Hello Reactive Systems Vienna! 👋 2021-04-09 — Another important Email 2021-04-08 — Do you want to join my network? 2021-04-05 — Nigerian prince wants to send you money X your inbox contains 5 mails 2 NEW Mail Websocket Client Email Email count() count() collect() filter() subscribe Email NEW 2021-04-11 — An important Email map()
14. We move from a pull-based design, to an asynchronous push-based design.
15. Reactive Programming Reactive Architectures We take the same concepts from reactive programming and move them up to the system architecture.
16. “The Universal BBC Architecture” Back in 2010… Allard Buijze Box Cylinder Box
17. Internet has 4.7 Billion users. Facbook has 2.8 Billion users. Youtube has 2.1 Billion users. 2010 2020 The Internet has 1.4 Billion users. A single website may now handle twice as much traffic as the entire internet a decade ago.
19. The Reactive Manifesto Message Driven Responsive Elastic Resilient NFR Supported by Enabled by Scalability Extendibility
20. Microservice A Microservice B Message Driven Responsive Elastic Resilient Value Form Means
21. Microservice A Microservice B Message Driven Responsive Elastic Resilient Value Form Means Microservice B Microservice B
22. Microservice A Microservice B Message Driven Responsive Elastic Resilient Value Form Means Microservice B Stream
23. Microservice A Microservice B Message Driven Responsive Elastic Resilient Value Form Means requests pile up
24. Message Driven Responsive Elastic Resilient Value Form Means Microservice A Stream Microservice B
25. We support Back-Pressure Stream Provider Consumer events are stored until consumed Stream Provider Consumer A Consumer C Consumer B scaling out consumers We can horizontally scale by Location Transparency
26. We move from a synchronous pull-based architecture, to an asynchronous push-based architecture.
27. Push, Pull, Whaaaaaat?
28. Microservice A Microservice B Microservice C Web Application
29. Microservice A Microservice B Microservice C Web Application Microservice C with high latency First Generation Integrated Synchronous without Backpressure Support
30. Microservice A Microservice B Microservice C Web Application Microservice C with high latency Second Generation Partially Asynchronous & Backpressure Support Queue isolates bottleneck Queue
31. Web Application Stream Microservice usually Backend-For-Frontend (BFF) Microservice A Microservice B Microservice C Thirds Generation Stream Centric and Fully Asynchronous
32. Events as the System State Stream of Transactions Max sent Tim 100€ Max sent Maria 70€ Tim sent Maria 25€ ➡ Current Balance Max - 100€ Tim + 100€ Maria + 70€ - 170€ + 75€ + 95€ Stream-table duality
33. Web Application Stream Microservice usually Backend-For-Frontend (BFF) Microservice A Microservice B Microservice C Migration via Change-Data-Capture Legacy Database New User Added User Updated Change-Data-Capture DB Log
34. www.squer.link/migration-strategies
35. Events as the System State Stream of Transactions Max sent David 100€ Max sent Maria 70€ David sent Maria 25€ Current Balance Max - 100€ David + 100€ Maria + 70€ - 170€ + 75€ + 95€ Stream-table duality the truth, the whole truth, nothing but the truth. Event Souring
36. Web Application Stream Microservice usually Backend-For-Frontend (BFF) Microservice A Microservice B Microservice C Thirds Generation Stream Centric and Fully Asynchronous
37. Web Application Eventstore Microservice usually Backend-For-Frontend (BFF) Microservice A Microservice B Microservice C Thirds Generation Stream Centric and Fully Asynchronous
38. Web Application Eventstore Microservice usually Backend-For-Frontend (BFF) Lambda A Lambda B Lambda C Thirds Generation Stream Centric and Fully Asynchronous
39. Web Application Stream Microservice usually Backend-For-Frontend (BFF) Microservice A Microservice B Microservice C Thirds Generation Stream Centric and Fully Asynchronous
40. Stream Centric Systems are the only way to build autonomous Microservices.
41. by: twitter.com/swardley
42. Stream Centric Systems are the only way to build autonomous Microservices.
43. Microservice A Microservice B Microservice C UI
44. Account Summary Service Transaction Service User Service Web Banking Categorization Service Config Service The rise of the Entity Service Antipattern High Presure Low Resilience Z Y X Payment Service
45. Account Summary Journey Transaction Service User Service Web Banking Categorization Service Config Service The rise of the Entity Service Antipattern High Presure Low Resilience Z Y X Payment Journey Paymet Customer Journeys Account Overview Customer Journeys Low service Autonomy Weak Independent Deployability Weak Independent Scalability
46. Account Summary Journey Transaction Service User Service Web Banking Categorization Service Config Service Payment Journey projection projection We never write to projections, we only read from them. CQRS in a nutshell websockets Strong Service Autonomy at Runtime Smaller Deployment Footprint Good Horizontal Scalability Account Summary Journey projection
47. Lambda A Web Application Lambda B Lambda C Stream GraphQL Microservice A Microservice B Microservice C Web Application ➡ pull-based push-based
48. www.squer.at
49. Focus on Realtime Integration Insurance Calculation
50. GraphQL Step 1 Step 2 Step 2 Car Brand Build Year Car Model Insurance Agent Customer ✅ This Is Correct Alfa Romeo Giulia, 2020 110PS, Diesel Products Users Configurations Eventstore GraphQL car brand has changed Alfa Romeo 2020 Giulia, 110PS
51. GraphQL Step 1 Step 2 Step 2 Car Brand Build Year Car Model Insurance Agent Alfa Romoe 2020 Giulia, 110PS Customer ✅ This Is Correct Alfa Romeo Giulia, 2020 110PS, Diesel Step 1 Step 2 Step 2 Coverage 200 € 🏁 Sign Digital Do you accept 70% coverage for 200€? Products Users Configurations Eventstore GraphQL
52. GraphQL Step 1 Step 2 Step 2 Car Brand Build Year Car Model Insurance Agent Customer ✅ This Is Correct Alfra Romeo Giulia, 2020 110PS, Diesel Step 1 Step 2 Step 2 Coverage 250 € 🏁 Sign Digital Do you accept 90% coverage for 250€? Products Users Configurations Eventstore GraphQL Customers expect realtime syncronisation between channels.
53. Focus on Resilience High Available Banking
54. Mobile Banking Usage Show balance & last transactions: 93% Initiate new payment: 3% Any other functionality: 4%
55. Transactions Web Banking Users Accounts Stream GraphQL Projection Projections 1⃣ Projections act as read-models for a specific client. 2⃣ They subscribe to events & hydrate the projection. 3⃣ The client only reads from the projection.
56. Transactions Web Banking Users Accounts Stream GraphQL Projection Projections 1⃣ Projections act as read-models for a specific client. 2⃣ They subscribe to events & hydrate the projection. 3⃣ The client only reads from the projection. Projection
57. GraphQL Mobile Client Projection Transactions Web Banking Users Accounts Stream GraphQL Projection Projections 1⃣ Projections act as read-models for a specific client. 2⃣ They subscribe to events & hydrate the projection. 3⃣ The client only reads from the projection. Only one hard problem in computer science left. 😎 Projection Show balance & last transactions working, 93% of customers still happy. With a concept like optimistic UIs even more.
58. lousy memes Ok let‘s sum up! lousy memes within lousy memes High Resilience & Scalability
59. Architectural Styles always buy you options. This stuff is cool, Reactive Architectures buy you Resilience, Realtime Capabilities, Elasticity, & Extendibility. you pay by complexity. 💵 e.g. perpetual, or eventual inconsistency
60. Maybe start small, and shift to reactive systems once needed.
61. by: twitter.com/swardley
62. @duffleit @duffleit david.leitner@squer.at David Leitner Coding Architect squer.at/slides this presentation
63. @duffleit