Revitalizing Aging Architectures with Microservices and the Reactive Platform

When you need to react quickly to competitive threats, but your existing architecture is anything but nimble, what do you do? You will hear the story of how Walmart Canada revitalized its aging architecture with a microservices model built for speed and performance - that efficiently leveraged its JVM infrastructure - to achieve major e-commerce success in just 12 months.

Results:

1. Conversions up 20%
2. Mobile orders up 98%
3. No downtime during Black Friday or Boxing Day

Transcript

1. Revitalizing Aging Architectures with Microservices
2. Typesafe Reactive Platform » Play - RESTful API framework » Akka - Distributed computing framework » Spark - General purpose in- memory compute engine » ConductR, Monitoring, and commercial features
3. Why replatform?
4. 2005 architecture
5. 2015 architecture
6. 2020 architecture
7. Size of the internet today
8. The world by 2020 » 4 billion connected people » 25+ million apps » 25+ billion embedded systems » 40 zettabytes (40 trillion gigabytes) » 5,200 GB of data for every person on Earth
9. Walmart Canada
10. Business Impact
11. The goal » ~100% availability ("nine nines")
12. The goal » ~100% availability ("nine nines") » Consistent responsiveness under varying load conditions
13. The goal » ~100% availability ("nine nines") » Consistent responsiveness under varying load conditions » Predictable spikes of traffic, e.g, Black Friday » Less predictable spikes of traffic, e.g, marketing campaign driving traffic
14. The goal » ~100% availability ("nine nines") » Consistent responsiveness under varying load conditions » Predictable spikes of traffic, e.g, Black Friday » Less predictable spikes of traffic, e.g, marketing campaign driving traffic » Enable LOBs to rapidly adapt to market conditions
15. A Revitalized Architecture
16. Walmart's Business Uplift » Conversions up 20% » Mobile orders up 98% » No downtime Black Friday or Boxing Day
17. Walmart's Operational Savings » Moved off expensive hardware » On cheap virtual x86 servers » 20% - 50% cost savings » ~ 40% compute cycles
18. Where to begin?
23. asynchronous, non-blocking, real-time, highly- available, loosely coupled, scalable, fault-tolerant, concurrent, reactive, event-driven, push instead of pull, distributed, low latency, high throughput...
24. asynchronous, non-blocking, real-time, highly- available, loosely coupled, scalable, fault-tolerant, concurrent, reactive, event-driven, push instead of pull, distributed, low latency, high throughput... Too complicated. We need a simple vocabulary.
25. Reactive A maturity model for modern distributed systems. » Responsive » Resilient » Elastic » Message-driven
26. Why, What, How Reactive (principles) » responsive, resilient, elastic, message-driven
27. Why, What, How Reactive (principles) » responsive, resilient, elastic, message-driven Microservices (strategy) » bounded contexts (DDD), event sourcing, CQRS, eventual consistency
28. Why, What, How Reactive (principles) » responsive, resilient, elastic, message-driven Microservices (strategy) » bounded contexts (DDD), event sourcing, CQRS, eventual consistency Tools (implementation) » Typesafe Reactive Platform (Play, Akka, Spark)
29. Heritage system
30. Future system
31. Clustered microservices » responsive to events, load, failure, users » embrace new concepts and patterns » cluster computing » distribution of data » new patterns like circuit breakers
32. Async boundary
33. Async boundary
34. Synchronous
35. Asynchronous
38. Microservices Ecosystem plus: » service registry » service discovery » architecture visualization » security
39. Play
40. Play Anatomy Stateless » Session is stored in the browser cookie Actions » User-defined functions that run in a different context than the request loop
41. Play at its core » Familiar MVC paradigm » Embraces flows of data » WebSockets, SSE » Reactive Streams (experimental in Play 2.4) » File uploads » Integration with Akka » Distribute work via messaging
42. Akka
43. Actor model » Distribution » Location transparency » Isolation
44. Supervision
45. Typical error channel
46. Dedicated error channel
47. Validation errors
48. Clustering
49. Spark & Fast Data
51. Streams? » A series of elements over time » Events, chunks of files » No beginning, no end
52. Akka Streams » Per-event processing » Back-pressure » Not distributed » Reactive Streams compliant » Integrate with Spark Streaming
53. What Typesafe offers
54. Typesafe ConductR Manage Typesafe Reactive Platform applications across a cluster
55. Typesafe Monitoring Know exactly what your Reactive system is doing
56. Commercial features » Akka Split Brain Resolver » Akka 2.3 Cluster Support for Docker » Play User Quotas » Play SOAP
57. Project Success Subscription » Certified build » Compatibility verifications » Security alerts » Binary updates » Long-term support » Legal protection
58. Thank you! Visit https://www.typesafe.com/products/typesafe- reactive-platform to get started Contact info » Twitter: @kvnwbbr » Email: kevin.webber@typesafe.com