Design principles for an Event Driven Architecture in an Event Driven World

According to Wikipedia, an Event-driven Architecture, is a software architecture pattern that promotes the production, detection, consumption of, and reaction to events.

There is a perfect pairing between microservice-based architectures, Domain Driven Design (DDD) and event-driven architectures. In this conference we will review what design principles are the catalyst for this symbiosis as well as practical examples in different areas including governance. Many business use cases can be articulated on top of these principles, abstracting them from both complexity and variability in the technological stack.

As a good part of the audience will already be dealing with events and microservices, we will also explain other key concepts:

* Designing a future-proof event taxonomy.
* Strategies for event enrichment, starting with the definition of that concept.
* Managing correlation or inference of events.
* Benefits from an event schema registry using for example Apache Avro.
* Traceability of events by design.
* Data conciliation patterns, and when to avoid it.

We will also take advantage of the opportunity to discuss about common challenges (and others not that common), frequent mistakes and how to avoid or mitigate them.

To conclude, we will explain some use cases that we are solving superbly based on real-time events: Communications, Order Management, Business Activity Monitoring (BAM), KYC, GDPR, ...

Transcript

1. Design principles for an event driven architecture Commit Conf 2019 Luis García & Pablo Ruiz Madrid, November 2019
2. Commercial Banking Retail Banking Why we are here 2 Luis García Castro @luiyo Pablo Ruiz Subira @prsubi
3. Introduction 3 There is a perfect pairing between microservice-based architectures, Domain Driven Design (DDD) and event-driven architectures
5. Event Taxonomy 5 Meaning Driven Business Domain Raw Purpose Driven Technical Native Standardized Atomic raw domain Derived (*) business
6. Taxonomy at microservice level 6 (*) each bus represents one specific topic in the Event Bus Domain API BB viewed from the outside Business Technical API Storage Bus Connector CORE Raw Domain Building Block internals Business Technical
7. Standard language 7 API Call API Call Ubiquitous Language Ubiquitous Language Ubiquitous Language Standard Language
8. Bounded Context Bounded Context Cohesion (strong) 8 Producer Consumer Schema Registry Send Schema Read Schema DB DB
9. Reference Data 9 Building Block A Building Block B Master Reference Data Building Block C Datalake
10. Coupling (loose) 10 Product A transaction received Fraud Engine transaction received Fraud Alert!! Communications transaction received Contact customer!! Channel Gateway Contact customer!!
11. Correlation & Inference 11 Domain A Event A Domain B Domain C Event B Domain A Event A Domain B Domain C A & B A & NOT B
12. Traceability & Lineage 12 Domain A Event Id: 1 TraceID: 1 Domain B Domain C Event Id: 2 TraceID: 1 Event Id: 3 TraceID: 1 Event Id: 4 TraceID: 1 Domain D Event Id: 5 TraceID: 5
13. Aggregation / enrichment 13 Domain A Domain B Domain C Name: Peter Surname: Parker Job: Photographer Name: Peter Surname: Parker Alias: Spiderman Domain D Name: Peter Surname: Parker
14. Orchestration 14 Orchestrator Generate Monthly Extract Product A Product B Document Mgm Product A movements Product B movements Statement request with Product A&B movements
15. Choreography 15 Product A transaction received Category Service transaction received transaction categorized Customer Reporting transaction received transaction categorized
16. Reconciliation 16 Domain A Domain B Domain C Domain D Reconciliation? Reconciliation?
17. Privacy / Data Segregation 17 Producer Clear Message <encoded message> Clear Message Producer Consumer Name: Clark Surname Kent Income: 1234.00 Name: Clark Surname Kent Income: 1234.00 Other Consumer Name: **** Surname ***** Income: 1234.00 <encoded message> Consumer Other Consumer <encoded message>
18. Technical/Business Monitoring 18 Domain A Domain B Domain C Alerting
19. One Example 19
20. Example 20 Person table Phone table Digital address table Gender type Phone type DA type PERSON
21. Example 21 Change mobile phone number bus storage API Person Core raw CDC domain Risk Comm technical Contact hst gateway technical Auth Mobile phone number changed domain partner business x2 technical
22. Example 22 Change mobile phone number bus storage API Person Core raw CDC domain Risk Comm technical Contact hst gateway technical Auth Mobile phone number changed domain partner business x2 1 Explicitly 1. Choreography 2. NOT reconciliation 3. NOT event enrichment 4. Correlation 5. Orchestration Everywhere: • Event taxonomy • Strong cohesion • Loose coupling • Lineage and traceability 2 3 4 technical 5
23. How EDA impacts a microservice based architecture 23 Feature EDA impact Loosely coupled Location transparency Strong cohesion Organized around business capabilities Each service is independently deployable Highly maintainable – Easy to maintain Highly testable – Easy to test Each service is as simple as possible Data Management Transaction Management
24. Thank you!! Questions? 24