When you need to react quickly to competitive threats, but your existing architecture is anything but nimble, what do you do? In this presentation, 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: Conversions up 20% Mobile orders up 98% No downtime during Black Friday or Boxing Day This webinar is based off Kevin Webber’s highly successful Gartner session, Lessons Learned: Revitalizing Walmart's Aging Architecture For Web Scale, and will include added content.

1. Revitalizing Aging Architectures with
Microservices
Kevin Webber (@kvnwbbr)
Enterprise Advocate

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. Whyreplatform?

4. 2005architecture

5. 2015architecture

6. 2020architecture

7. Size ofthe internettoday

8. Theworld by2020
» 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. WalmartCanada

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. ARevitalizedArchitecture

16. Walmart's Business Uplift
» Conversions up 20%
» Mobile orders up 98%
» No downtime Black Friday or Boxing Day

17. Walmart's OperationalSavings
» Moved off expensive hardware
» On cheap virtual x86 servers
» 20% - 50% cost savings
» ~ 40% compute cycles

18. Whereto 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. PlayAnatomy
Stateless
» Session is stored in the
browser cookie
Actions
» User-defined functions that
run in a different context
than the request loop

41. Playatits 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. Typicalerror channel

46. Dedicated error channel

47. Validation errors

48. Clustering

49. Spark & FastData

51. Streams?
» A series of elements over time
» Events, chunks of files
» No beginning, no end

52. AkkaStreams
» Per-event processing
» Back-pressure
» Not distributed
» Reactive Streams compliant
» Integrate with Spark
Streaming

53. WhatTypesafe
offers

54. Typesafe ConductR
ManageTypesafe Reactive Platformapplicationsacrossacluster

55. Typesafe Monitoring
Knowexactlywhatyour Reactive system is doing

56. Commercialfeatures
» Akka Split Brain Resolver
» Akka 2.3 Cluster Support for Docker
» Play User Quotas
» Play SOAP

57. ProjectSuccess Subscription
» Certified build
» Compatibility verifications
» Security alerts
» Binary updates
» Long-term support
» Legal protection

58. Thankyou!
Visit https://www.typesafe.com/products/typesafe-
reactive-platform to get started
Contactinfo
» Twitter: @kvnwbbr
» Email: kevin.webber@typesafe.com