Using logs to create a solid data infrastructure

Slides from my talk at Craft Conference, Budapest, Hungary on 24 April 2015. http://martin.kleppmann.com/2015/04/24/logs-for-data-infrastructure-at-craft.html

Abstract:

How does your database store data on disk reliably? It uses a log.
How does one database replica synchronise with another replica? It uses a log.
How does a distributed algorithm like Raft achieve consensus? It uses a log.
How does activity data get recorded in a system like Apache Kafka? It uses a log.
How will the data infrastructure of your application remain robust at scale? Guess what…

Logs are everywhere. I’m not talking about plain-text log files (such as syslog or log4j) – I mean an append-only, totally ordered sequence of records. It’s a very simple structure, but it’s also a bit strange at first if you’re used to normal databases. However, once you learn to think in terms of logs, many problems of making large-scale data systems reliable, scalable and maintainable suddenly become much more tractable.

Drawing from the experience of building scalable systems at LinkedIn and other startups, this talk will explore why logs are such a fine idea: making it easier to maintain search indexes and caches, making your applications more scalable and more robust in the face of failures, and opening up your data for richer analysis, while avoiding race conditions, inconsistencies and other ugly problems.

Transcript

1. View Slide

2. View Slide

3. View Slide

4. View Slide

5. View Slide

6. View Slide

7. View Slide

8. View Slide

9. View Slide

10. View Slide

11. View Slide

12. View Slide

13. View Slide

14. View Slide

15. View Slide

16. View Slide

17. View Slide

18. View Slide

19. View Slide

20. View Slide

21. View Slide

22. View Slide

23. View Slide

24. View Slide

25. View Slide

26. View Slide

27. View Slide

28. View Slide

29. View Slide

30. View Slide

31. View Slide

32. View Slide

33. 216.58.210.78 - - [27/Feb/2015:17:55:11 +0000] "GET
    
    /css/typography.css HTTP/1.1” 200 3377 "http://martin.
    
    kleppmann.com/" "Mozilla/5.0 (Macintosh; Intel Mac OS X
    
    10_9_5) AppleWebKit/537.36 (KHTML, like Gecko)
    
    Chrome/40.0.2214.115 Safari/537.36"
    
    

    View Slide

34. View Slide

35. View Slide

36. View Slide

37. View Slide

38. View Slide

39. View Slide

40. View Slide

41. View Slide

42. View Slide

43. View Slide

44. View Slide

45. View Slide

46. View Slide

47. View Slide

48. View Slide

49. View Slide

50. View Slide

51. View Slide

52. View Slide

53. View Slide

54. View Slide

55. View Slide

56. View Slide

57. View Slide

58. View Slide

59. View Slide

60. View Slide

61. View Slide

62. View Slide

63. View Slide

64. View Slide

65. View Slide

66. View Slide

67. View Slide

68. View Slide

69. View Slide

70. View Slide

71. View Slide

72. View Slide

73. View Slide

74. View Slide

75. View Slide

76. View Slide

77. View Slide

78. References (fun stuff to read)
    
    1.  Jay Kreps: “I ♥︎ Logs.” O'Reilly Media, September 2014. http://shop.oreilly.com/product/0636920034339.do
    
    2.  Martin Kleppmann: “Designing data-intensive applications.” O’Reilly Media, to appear in 2015. http://dataintensive.net
    
    3.  Martin Kleppmann: “Turning the database inside-out with Apache Samza.” 4 March 2015. http://blog.confluent.io/
    2015/03/04/turning-the-database-inside-out-with-apache-samza/
    
    4.  Pat Helland: “Immutability Changes Everything,” at 7th Biennial Conference on Innovative Data Systems Research (CIDR),
    January 2015. http://www.cidrdb.org/cidr2015/Papers/CIDR15_Paper16.pdf
    
    5.  Shirshanka Das, Chavdar Botev, Kapil Surlaker, et al.: “All Aboard the Databus!,” at ACM Symposium on Cloud Computing
    (SoCC), October 2012. http://www.socc2012.org/s18-das.pdf
    
    6.  Mahesh Balakrishnan, Dahlia Malkhi, Ted Wobber, et al.: “Tango: Distributed Data Structures over a Shared Log,” at
    24th ACM Symposium on Operating Systems Principles (SOSP), pages 325–340, November 2013. http://
    research.microsoft.com/pubs/199947/Tango.pdf
    
    7.  C Mohan, Don Haderle, Bruce G Lindsay, Hamid Pirahesh, and Peter Schwarz: “ARIES: A Transaction Recovery
    Method Supporting Fine-Granularity Locking and Partial Rollbacks Using Write-Ahead Logging,” ACM Transactions on
    Database Systems (TODS), volume 17, number 1, pages 94–162, March 1992.
    
    8.  Patrick O'Neil, Edward Cheng, Dieter Gawlick, and Elizabeth O'Neil: “The Log-Structured Merge-Tree (LSM-Tree),”
    Acta Informatica, volume 33, number 4, pages 351–385, June 1996. http://www.cs.umb.edu/~poneil/lsmtree.pdf
    
    9.  Heidi Howard, Malte Schwarzkopf, Anil Madhavapeddy, and Jon Crowcroft: “Raft Refloated: Do We Have Consensus?,”
    ACM SIGOPS Operating Systems Review, volume 49, number 1, pages 12–21, January 2015. http://www.cl.cam.ac.uk/
    ~ms705/pub/papers/2015-osr-raft.pdf
    
    

    View Slide

79. View Slide