1. From a monolith to microservices + REST The evolution of LinkedIn’s service architecture by Steven Ihde and Karan Parikh (LinkedIn)

4. Leo ●Our original codebase ●Java, Servlets, JSP, JDBC Leo Oracle 4

5. Remote Graph ●Graph: member-to-member connection graph ●Complex graph traversal problems not suited to SQL queries ●RPC was used to keep it separate from Leo ●Our first service 5

6. Remote Graph Leo Oracle Graph RPC JDBC Databus 6

7. Mid/Back Tier Services ●“Back” tier services encapsulate data domains ●“Mid” tier services provide business logic ●We applied the service pattern to many domains, e.g. member profiles, job postings, group postings 7

8. Front Tier Services ●“Front” tier services aggregate data from many domains ●Transform the data through templates to present to the client ●Should be stateless for scaling purposes 8

9. Service Explosion ●Over 100 services by 2010 ●Most new development occurring in services, not Leo ●Site release every two weeks 9

10. Architectural Challenges ●Test failures ●Incompatibilities ●Complex orchestration ●Rollback difficult or impossible ●Complex dependencies between services 10

11. Microservices? ●Services were fine grained ●But monolithic build and release process did not allow us to realize the benefits of microservice architecture 11

12. Solutions ●Continuous delivery ●Break apart the code base ●Devolution of control ●Strict backwards compatibility ●Better defined boundaries between tiers 12

13. Continuous Delivery ●Shared trunk ●Pre- and post-commit automated testing ●Easy promotion of builds to production environment 13

14. Decentralize Codebase ●Separate, independently buildable repositories ●Shared trunk within each repository ●Versioned binary dependencies between repositories 14

15. Devolution of Control ●Service owners control release schedule, release criteria ●Service owners are responsible for backwards compatibility ●Services must release independently 15

16. Backwards compatibility ●Insulates teams from each other at runtime ●Allows service owners to deploy on their own schedule without impacting clients 16

17. Boundaries Between Tiers ●Limit aggregation to the front tier ●Limit crosstalk in the back tier: “superblocks” 17

18. Boundaries Between Tiers 18

19. Java RPC ●Difficult to maintain backwards compatibility ●Verb-centric APIs ●Use case specific APIs ●Difficult to navigate the proliferation of APIs 19

20. Rest.li plus Deco equals Microservices at LinkedIn

21. What is Rest.li? “Rest.li is an open source REST framework for building robust, scalable RESTful architectures using type-safe bindings and asynchronous, non-blocking I/O.” Primarily JSON over HTTP. 21

22. Why Rest.li? ●Polyglot (frontend) ecosystem - Java, Scala, Python, Node.js, Objective-C ●Uniform service interfaces (REST) 22

23. The Rest.li stack Rest.li Data layer and RESTful operations D2 Dynamic discovery and load balancing R2 Network Communication 23

24. Request Response (R2) ●REST abstraction that can send messages over any application layer protocol (HTTP, PRPC (old custom LinkedIn protocol)) ●Client - fully asynchronous Netty ●Server - Jetty, Netty (experimental) Rest.li D2 R2 24

25. Dynamic Discovery (D2) ●Apache ZooKeeper ●Dynamic server discovery ●Client side software load balancing ●D2 service Rest.li R2 D2 25

26. Rest.li ●Data using PDSCs (Pegasus Data Schemas) ●RESTful API that developers use to build services ●CRUD + finders + actions ●API and data backwards compatibility checking R2 D2 Rest.li 26

27. 830 Rest.li resources. 90 billion Rest.li calls/day across multiple datacenters. 65% service-to-service calls.

28. What is deco? 28

29. Aside: Normalized Domain Models ●Links over inclusion (denormalization) ●URNs are fully qualified foreign keys InfluencerPost Long id String title String content URN author Member Long id String firstName String lastName String summary URN company urn:li:member:123 29

30. What is Deco? ●URN resolution library ●What data you want, not how you want it Time 1 2 3 30

31. Deco Example: Influencer Post Dummy Post by Karan Parikh at LinkedIn Hi QCon! /influencerPosts /companies /profiles 31

32. Deco Example: Influencer Post deco://influencerPosts/123?projection=(title, content, author~(firstName, lastName, company~(companyName))) 32

33. Three services. One client call. Deco.

34. Rest.li plus Deco equals Microservices at LinkedIn

35. How Rest.li enables Microservices ●Rest.li + D2 facilitate domain specific services ●Services can easily configure clients via D2 ●D2 helps us scale the architecture 35

36. How Deco enables Microservices ●Deals with service explosion ●Abstracts away services from clients 36

37. Challenges ●Coordinating a massive engineering effort. (LiX to the rescue!) ●Ensuring uniform RESTful interfaces ●Performance Rest.li API Hub 37

38. Wins ●All languages talk to the same service ●Developer productivity ●Reduction of hardware load balancers ●Ability to expose APIs directly to third parties 38

41. LinkedIn Microservices

42. Questions?

43. References and links ●Rest.li: http://rest.li/http://rest.li/ ●Rest.li API Hub: https://github.com/linkedin/rest.li-api-hubhttps://github.com/linkedin/rest.li-api-hub ●Rest.li user guide: https://github.com/linkedin/rest.li/wiki/Rest.li-User-Guidehttps://github.com/linkedin/rest.li/wiki/Rest.li-User-Guide ●Modeling resources with Rest.li: https://github.com/linkedin/rest.li/wiki/Modeling-Resources-with-Rest.li https://github.com/linkedin/rest.li/wiki/Modeling-Resources-with-Rest.li ●LinkedIn engineering blog posts about Rest.li: http://engineering.linkedin.com/architecture/restli-restful-service- architecture-scale http://engineering.linkedin.com/restli/linkedins-restli- moment http://engineering.linkedin.com/architecture/restli-restful-service- architecture-scalehttp://engineering.linkedin.com/restli/linkedins-restli- moment ●LinkedIn’s GitHub projects http://linkedin.github.io/http://linkedin.github.io/ 43