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Irakli Nadareishvili - O'Reilly SACon 2018, London
The document discusses the concept of asynchronicity in microservices, highlighting three main types: asynchronous flows, data streams, and event sourcing (CQRS). It explains how these patterns can enhance scalability and resiliency in systems, while also increasing complexity. Furthermore, it details common solutions, such as promises, publish/subscribe queues, and the Akka actor model, illustrating the benefits of each approach.
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Similar to Irakli Nadareishvili - O'Reilly SACon 2018, London
Irakli Nadareishvili - O'Reilly SACon 2018, London
- 1. Asynchronicity in Microservices ThreeMain Forms of Asynchronicity – Understanding the Patterns O’Reilly SACon, London, October 2018 Irakli Nadareishvili Sr. Director, Shared Technology, Capital One.
- 2. Irakli Nadareishvili Senior Director,SharedTech, Capital One • API & Microservices Governance • Capital One’s Developer Tooling • Co-author of “Microservice Architecture” inadarei
- 3. 11 “Speed and Safetyat Scale and in Harmony” Need for coordination is why we constantly compromise between speed and safety. Microservices Way: inadarei
- 4. Microservicesclosethealignmentloop! AgileProcess: Operations: Product: DevOps & CI/CID LeanProduct Dev Pattern: Thinking In Small Batches Architecture: Microservices inadarei
- 5. Data:Batch-sizeIsaStrongPredictorofPerformance Source: Accelerate, byNicole Forsgren, PhD, Jez Humble, and Gene Kim
- 6. 6Confidential Async + #Microservices= Internet’s favorite pastime
- 7. 7 There is actuallymore than one type of asynchronicity, and the proper usage patterns are significantly different, when and if applied properly.
- 8. Asynchronous Flows Data Streams Event-Sourcing(and CQRS) AGENDA
- 9.
- 10. 1010Confidential Any type ofasynchronous job execution, where caller doesn’t have to wait for a response in a blocking way, increases scalability and resiliency of the system, granted: typically at the expense of increased complexity. Common solutions: • Promises, async/await & coroutines • Publish/Subscribe Queues • Webhooks • Reactive Programming • Akka Actor Model
- 11. Promises (Node.js) 11Example codefrom: http://promises123.com.
- 12. Async/Await (Python) 12Example codefrom: http://promises123.com.
- 13. Goroutines (Go) 13Example codefrom: http://promises123.com.
- 14. Reactive Programming 14 Higher-level abstractionover messaging using Observables and functional programming.
- 15. Publish/Subscribe Queues 15 Senders generateevents, receivers are workers able and interested in processing those Graphics source: https://docs.microsoft.com/en-us/previous-versions/msp-n-p/dn589781(v=pandp.10) Pub/Sub provides significantly superior level of flexibility, in that: multiple kinds of receivers, implemented with heterogenous tech stack can subscribe to the same events using a uniform approach and implementation. Example: 1. Message: loan application submitted 2. Received by fraud-check worker 3. Received by credit-check worker 4. Received by AML-check worker 5. Received by OFAC-check worker 6. …
- 16. Webhooks – HTTPCallbacks with Payload 16 W3C Standard: WebSub https://www.w3.org/TR/websub/ Graphics source: https://www.w3.org/TR/websub/#high-level-protocol-flow WebSub allows abstracting Pub/Sub model away from specific, non-web protocols used by concrete message broker systems and projecting the interactions onto the standard HTTP layer, with main benefit being ubiquitous familiarity with the protocol, built-in caching and internet- level scalability features.
- 17. Akka Actor Model 17 ActorModel-based abstraction for concurrent and distributed systems, primarily in Scala and Java Diagram source: https://doc.akka.io/docs/akka/2.5/guide/actors-intro.html “Everything is an Actor” model to concurrency by Carl Hewitt (1973). Actor is an entity that, in response to a message, can: 1. Send messages to other actors 2. Create new actors 3. Define message-processing behavior.
- 18. Akka Actor Model- Clustering 18 Akka provides gossip-based HA cluster impl. with advanced features like sharding & persistence. Diagram source: https://doc.akka.io/docs/akka/2.5/common/cluster.html#intro
- 19.
- 20. Data Analytics &Machine Learning Applications 20 Could be powered by Kafka Streams configured/optimized differently from their pub/sub usage Diagram source: https://www.confluent.io/blog/build-deploy-scalable-machine-learning-production-apache-kafka/
- 21. Data Lake 21 Business-relevant datastreamed into a Data Lake from all data/event sources Diagram source: https://aws.amazon.com/big-data/datalakes-and-analytics/what-is-a-data-lake/
- 22. 22 3. Event Sourcing(and CQRS)
- 23. Command Query ResponsibilitySegregation (CQRS) 23 Separating actions (state changes) from perceptions (reads, notification) in system architecture EventStore Alexa VoiceSkill BFFAPI … Microservice 1 … … Microservice 2 … … Microservice 4 … MobileWebApp … Microservice 3 … BFFAPIBFFAPI Topic 1 Topic 2.1 Topic 2.2 Topic 4.1 Topic 4.2 Topic 4.3 Subscribe publish publish publish Subscribe Subscribe Subscribe Query Query Query Query
- 24.
- 25. Event-Sourcing Explained 25 “Current state”-oriented,relational model – favors data-sharing, toxic for microservices Customer Demographics Credit-Worthiness Data Deposits (10) Accounts (3) Withdrawals (10) Documents (7)
- 26. Event-Sourcing Explained 26 Events-Based DataModel – solves data-sharing issues in Microservices Credit Data Received Customer Created Checking Account Added Credit Card Acc. Added Mortgage Acc. Added Money Deposited Money Deposited Money Withdrawn Money Withdrawn Money Withdrawn Document Added Money Deposited Money Deposited Document Generated Money Withdrawn Document Added Money Withdrawn
- 27.
- 28. Projections 28 Give us currentstate based on events, and are as simple as: function (state, event) “In Event Sourcing, current state is a left-fold of previous behaviors” – Greg Young
- 29. Tooling 29 Event Store: 1. EventStorehttps://eventstore.org/ 2. Cassandra 3. Any DB capable of storing many rows of data . Read Model: 1. ElasticSearch 2. PostgreSQL 3. Anything optimized for the kind of queries you want to run.
- 30. Command Query ResponsibilitySegregation (CQRS) 30 Separating actions (state changes) from perceptions (reads, notification) in system architecture EventStore Alexa VoiceSkill BFFAPI … Microservice 1 … … Microservice 2 … … Microservice 4 … MobileWebApp … Microservice 3 … BFFAPIBFFAPI Topic 1 Topic 2.1 Topic 2.2 Topic 4.1 Topic 4.2 Topic 4.3 Subscribe publish publish publish Subscribe Subscribe Subscribe Query Query Query Query
- 31. Asynchronous Flows Data Streams Event-Sourcing(and CQRS) ASYNC TYPES inadarei
- 32.