F8 tech talk_pinterest_v4

1. Discover Pinterest Engineering

2. Agenda ! Mobile & Growth: Monetization & Data: Deploying & Shipping Code: Wendy & Dannie Pawel Chris & Jeremy

3. Wendy Lu Mobile Scaling User Education on Mobile The Experience Framework Dannie Chu Growth

4. User Education

5. Motivation?

6. User Education leads to Engagement

7. First Pin Education

8. Challenges

9. 1. Preserve a great user experience

10. Conﬂicting Education

11. Never-ending Stream of Nags

12. Nag that never goes away

13. 2. Targeting

14. Are you a new user? Invite some friends!

15. Do you have an empty homefeed? Make it better!

16. 3. Rapid Experimentation

17. Experiment with messaging w/o requiring a release

18. 4. Keep the client code clean

19. Solution?

20. The Experience Framework

21. Conﬂicting Experiences

22. Experiences and Placements Nag Placement Home view Placement Pin Tutorial Card Placement

23. AB Experimentation, Simple Client Code

24. Experiences are delivered to the client at runtime

25. Experience Framework Decision Engine Configuration Handlers Admin DashboardAPI Servers AB Experiments Framework Kafka (logging) HBase (User States,   Experience States) API Servers API ServersCascading/ MapRed User State Batch Loader Clients SDK SDK What experience should the user see? Experience Framework

26. Deep Dive: Nags

27. What are nags? •Important information which we occasionally display at the top of a user’s feed •Can be a Call to Action “Conﬁrm your email” or an announcement “You can now add a map to any board!”

28. Enter: The Experience Framework

29. Enter: The Experience Framework •Each time we reload the home feed, ask the experience framework: What should I show in this nag?

30. Single Nag Manager that relies on the experience framework to give it the contents to render Nag Manager •Experiment with nag messaging, call to actions, images •Add any new nag dynamically, controlled from the backend. •Cool-down management - should not see more than one nag in a set period of time

31. What does that nag data look like? Handling actions "bg_img_url_2x" = "http://mobile- assets.pinterest.com/iphone/nags/invite- mail@2x.png" "title_text" = "Pinspire your friends!" "detailed_text" = "Know someone who'd like Pinterest? Invite them along." "button1_text" = "No, Thanks”! "button1_uri" = ""! "button2_text" = "Invite Friends"! "button2_uri" = "pinterest://invite_friends"

32. Handling Actions •All initialization and presentation of view controllers is handled through a central “Navigation Manager.” • Centralizes code to create and present view controllers • Consistency to other platforms for deep links •Allows dynamic insertion of nags from the backend without having to write new client code and submit a new release

33. [[NavigationManager sharedManager] handleURL:[NSURL URLWithString:@“pinterest:// invite_friends]]; Navigation Manager self.presentationDelegate presentInviteFriends

34. Deep Dive: New User Experience

35. New User Experience What is NUX? ! •The set of initial tutorials and education presented to a user after they register

36. Personalize a user’s content immediately after signup Connect with Friends Choose Interests

37. Next, teach users how to Pin

38. Experiment between classic user ed and NUX

39. Experiment between classic user ed and NUX •When doing experiments where we need to call the network to get the user’s treatment group, need to make sure we’re not adding perceived latency • Structure view controllers in a way that you can asynchronously load in the modules dependent on the treatment group • If need to transition to diﬀerent view controllers, set a time out in which we transition to the control treatment • “Be Fast or Fail Fast”

40. 1 step vs. 2 steps vs. 3 steps Experiment with diﬀerent versions of NUX

41. Experiment with diﬀerent versions of NUX •Backend controls all strings, allowing us to dynamically experiment with diﬀerent text (Messaging, titles, calls-to-action)

42. steps = ( { "continue_button_text" = Continue; "detailed_text" = "Tap a network to find people who share your interests."; "follow_button_text" = "Follow selected people"; step = 1; "title_text" = "First things first"; "total_steps" = 2; }, { "completion_message" = "Finding Pins for you..."; "continue_button_text" = "Tap at least {0} more to continue"; "detailed_text" = "Tap whatever you're interested in these days."; "finish_text" = Finish; "num_interests" = 5; "skip_text" = "Pinterest is much more interesting when you tell us what you like."; step = 2; "title_text" = "Pick 5 interests"; "total_steps" = 2; } ); After signup, request all data for NUX Enter: Experience Framework

43. Supports dynamic number and order of steps NUXViewController : UINavigationController •Maps an array of display data to an array of view controllers          •Protocol method advanceToNextStep called by each child view controller • Checks the array it keeps for the next view controller to push JSON dict for Intro JSON dict for Friend Selector JSON dict for Interests Selector NUXIntroViewController NUXConnectViewController NUXInterestsViewController

44. Wins from Experience Framework •Single place in the backend that manages all experiences for all platforms •Dynamically trigger display of content •Conﬂict resolution for educations that touch the same views •Experiment with ﬂows, messaging, and images

45. engineering.pinterest.com

46. Pawel Garbacki Software Engineer, Monetization Pinterest Secor Zero-data-loss log persistence service

47. Pinterest is a data driven company •Data matters • 100+ experiments active at a given point in time • 1500+ tracked metrics • 200+ log types

48. We produce a lot of data •We produce a lot of data • PBs of data in S3, growing by Tens of TB a day • Hundreds of production hadoop jobs, processing about half a PB of data each day

49. Singer   (logging agent) App Data pipeline Local Disk S3Kafka   (log collector) Secor   (log saver) Storm (realtime stats) Hive (hadoop analytics) Redshift (ad hoc queries)

50. Singer   (logging agent) App Local Disk S3 Kafka (log collector) Secor (log saver) Storm (realtime stats) Hive (hadoop analytics) Redshift (ad hoc queries) Data pipeline 20B messages/day

51. Kafka 101 •Distributed pub-sub service •Designed for high throughput Producer Producer Producer Consumer Consumer Consumer Kafka cluster

52. Anatomy of a topic •Topic is a category to which messages are published •Partition is a ‘shard’ of a topic controlling the level of consumption parallelism •Messages are assigned unique identiﬁers called oﬀsets 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8 9 10 11 12 Writes Partition 0 Partition 1 Partition 2

53. Save the day •Kafka is optimized for local writes •Local disk capacity is good for a few days worth of data •Data needs to be saved (at least) daily to long term storage - Amazon S3

54. How soon is “eventually” •Amazon S3 is a cloud ﬁle system •Eventual consistency model • No guarantees on when uploaded data will become visible to the readers • No monotonicity - data available in the past may magically disappear

55. Secor design guidelines •Objectives: • Persist Kafka logs to S3 • Cause no data loss • Work properly with eventual consistency model •Properties: • Horizontal scalability • Fault tolerance • Customizability

56. No-S3-reads principle •Secor never reads data from S3 • Lightweight metadata is stored in strongly consistent state repository •Strategic choice of file names • s3n://logs/<topic>/ <generation>_<partition>_<start_offset> • <generation> represents software compatibility version • Inconsistencies introduced by consumer failures get fixed automatically by file overwrites

57. Date clustering •Data processing tools rely on date- partitioned directory structure • s3n://logs/event/dt=2014-04-04/ •Timestamps extracted from messages on the ﬂy •Support for pluggable parsers for thrift, json, etc.

58. https://github.com/pinterest/secor

59. Chris Danford (@chrisdanford) Jeremy Stanley (@rouxbot) Web Team From Development to Production The life of web features

60. Develop Review Deploy Measure

62. Developing - Ideal state •able to iterate quickly •easy errors caught automatically •easy-to-understand and powerful abstractions

63. Fast iteration Developing •Build tasks and dependencies modeled as a graph •“cumberbatch” watches for changes of ﬁle contents •“orchestrator” knows tasks and dependencies •build the minimum tasks to heal damage in the graph •maximize parallelization of tasks •built on Grunt - access to large library of build tasks

64. Self-healing build graph sprite/*.png sprite task sprite.png sprite.scss Sass task component/*.scss components.css imagemin task Autoprefixer task CSSlint task

67. Self-healing build graph, example 2 sprite/*.png sprite task sprite.png sprite.scss Sass task component/*.scss components.css imagemin task Autoprefixer task CSSlint task

68. Self-healing build graph, example 2 sprite/*.png sprite task sprite.png sprite.scss Sass task component/*.scss components.css imagemin task Autoprefixer task CSSlint task

69. Linting Developing •catches easy bugs •enforces consistent style •pyﬂakes •pep8 •jshint •CSSLint •custom RegEx linting

70. RegEx-based linter $(‘.item’).addClass(‘selected’); BoardPicker.js this.$(‘.item’).addClass(‘selected’);

71. Static analysis / type safety Developing •Google Closure Compiler •template static analysis • validation of template inheritance • extract used option variable names •Thrift clients for service calls (Python) and shared constants (JavaScript)

72. Closure Compiler - type safety

73. Generated constants from Thrift

74. Abstractions Developing •component framework • styles are scoped to the component • DOM access is scoped to the component’s DOM • “events up, methods down” • scaﬀolding script •live component catalog - discovery of existing components •autopreﬁxer, spriting - remove boilerplate

75. component catalog

76. spriting .thumbsUpButton {! @include inline-image(‘sprites/main/thumbUp');! } Usage

78. Reviewing - Ideal state •the most-relevant person is reviewing changes •integration-type issues are caught

79. Code Reviews Reviewing •local test runner script runs Jasmine and Node tests parallelized •“PR watcher” tool - visibility of relevant PRs •code review process - R+, E+

80. Parallelized Jasmine tests in PhantomJS

81. Github Watcher tool

82. Integration problems are caught Reviewing •PRs trigger a build and tests - 3 minutes •latest.pinterest.com is continuously deployed from “head” •Selenium integration tests run against every deploy

83. Pull request builds

84. Selenium

86. Deploying - Ideal state •code deploys are invisible to users •frequent and non-disruptive to developers •immediate rollback when there’s a problem

87. User experience Deploying •stickiness to a version •ﬂip nearly instantaneously between builds • reduce version thrashing • worry less about (style mismatches, JS errors due to data format mismatch with server) •asset versioning

88. Serving multiple application versions new! sessions old! sticky! sessions A B all! sessions B 1 2

89. Serving multiple application versions, cont’d 3 4 new! canary! sessions all! non-canary! sessions B C new! sessions old! sticky! sessions B C

90. Asset versioning logo.png rename hash file! contents logo.59aa9183.png bundle.css background-image: logo.png background-image: logo.59aa9183.png update references bundle.css bundle.907389d8.css rename hash file! contents

91. When things go wrong Deploying •experiments dashboard - turn oﬀ experiments instantaneously •version rollback is nearly instantaneous

93. Monitoring health A/B Dashboard •A/B dashboard key metrics •Sentry •Stats dashboard •Alarms - Monit, PagerDuty

94. A/B Dashboard

95. Sentry

96. Sentry error emails

97. Results

98. Results •5 engineers on web team •all teams at Pinterest developing their own web features on our platform •components re-used across teams •2 scheduled deploys a day •anomalies in key metrics surfaced immediately •100s of simultaneous experiments

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F8 tech talk_pinterest_v4