How to break apart a monolithic system safely without destroying your team - Matthew Skelton - Velocity EU 2016

1. How to break apart a monolithic system safely without destroying your team Matthew Skelton, Skelton Thatcher Consulting @matthewpskelton 07 November 2016, Amsterdam, NL - #velocityconf

2. Today Cognitive load for teams ‘Monolith’ Code Forensics Team-first boundaries Monolith-splitting recipe

3. For now, let’s forget: Microservices CQRS / Event Sourcing Queues (Architectural changes)

4. Team-first digital transformation 30+ organisations UK, US, EU, India, China

5. How to break apart a monolithic system safely without destroying your team

6. Safer, more rapid changes to software systems (Business Agility)

7. A ‘team-first’ approach to software subsystem boundaries

8. TEAM

9. TEAM capabilities appetite & aptitude understanding responsibilities

10. (assumption) the team is stable, slowly changing, and long-lived #NoProjects

11. Conway’s Law

12. “organizations which design systems ... are constrained to produce designs which are copies of the communication structures of these organizations” – Mel Conway, 1968 http://www.melconway.com/Home/Conways_Law.html

13. Front-end developers Back-end developers

14. ‘Reverse Conway’ Tobbe Gyllebring (@drunkcod)

15. homomorphic force (#Conway  #Yawnoc) HT @allankellynet (same) (shape)

16. Cognitive load for teams

17. Cognitive load the total amount of mental effort being used in the working memory (see Sweller, 1988)

18. Cognitive load Intrinsic Extraneous (Irrelevant ) Germane (Relevant)

19. ‘Hacking Your Head’: Jo Pearce See http://www.slideshare.net/JoPearce5/hacking-your-head-managing-information-overload-45-mix @jdpearce

20. We have SCIENCE!

21. Science since 1988 (!) • Driskell et al, 1999 ‘Does Stress Lead to a Loss of Team Perspective?’ Group Dynamics: Theory, Research, and Practice 3, no. 4 (1999): 291. • Fan et al, 2010 ‘Learning HMM-Based Cognitive Load Models for Supporting Human-Agent Teamwork’. Cognitive Systems Research 11, no. 1 (2010): 108–119. • Ilgen & Hollenbeck, 1993 ‘Effective Team Performance under Stress and Normal Conditions: An Experimental Paradigm, Theory and Data for Studying Team Decision Making in Hierarchical Teams with Distributed Expertise’. DTIC Document, 1993. • Johnston et al, 2002 ‘Application of Cognitive Load Theory to Developing a Measure of Team Decision Efficiency’. DTIC Document, 2002. • Sweller, John, 1994 ‘Cognitive Load Theory, Learning Difficulty, and Instructional Design’. Learning and Instruction 4 (1994): 295–312. • Sweller, John, 1988. ‘Cognitive Load during Problem Solving: Effects on Learning’. Cognitive Science 12, no. 2 (1988): 257–285.

22. “stress impacts team performance … by narrowing or weakening the team-level perspective required for effective team behavior.” – Driskell et al, 1999 Group Dynamics: Theory, Research, and Practice 1999, Vol. 3, No. 4,291-302

23. (not just ‘pop’ science!)

24. ‘Monolith’

25. monolith μόνο λίθος “single stone” Reiner Flassig - CC BY-SA 2.0 de - Wikipedia

26. “Don’t start with a monolith when your goal is a microservices architecture” – Stefan Tilkov, innoQ http://martinfowler.com/articles/dont-start-monolith.html

27. “Start monolithic and extract” – Tammer Saleh, Pivotal https://www.infoq.com/presentations/cloud-anti-patterns

28. A ‘team-first’ approach to software subsystem boundaries

29. Types of software monoliths •Application monolith •Joined at the DB •Monolithic build (rebuild everything) •Monolithic releases (coupled) •Monolithic thinking (standardisation)

30. Application monolith Single block of code Deployed as a unit

31. Joined at the DB Difficult to change separately (but not impossible) Risk is (probably) elevated Chris Collyer, http://www.stone-circles.org.uk/stone/pentreifan.htm

32. Monolithic builds One gigantic CI build just to get a new version of any component

33. Monolithic releases Smaller components bundled together into a ‘release’

34. Monolithic thinking ‘One-size-fits-all’ for teams Assumption that minimising variation is A Good Thing

35. Dangers of splitting a monolith •Reduced domain consistency •Data duplication (unintentional) •Additional operational complexity due to distributed system and async messaging •Degraded UX across the product

36. Splitting a monolith Reiner Flassig - CC BY-SA 2.0 de - Wikipedia Choose the right technique for splitting Understand the nature of the monolith

37. ‘Fracture planes’ for code •Business domain bounded context •Regulatory compliance •Change cadence •Risk •Performance isolation •User personas •Team location

38. ‘Fracture planes’ for code Ask: Could we consume this thing as a service?

39. ‘Fracture planes’ for code Ask: Could we provide this thing as a service?

40. Code Forensics

41. Forensics Your Code as a Crime Scene Adam Tornhill

42. Adam Tornhill Code, Crime, Complexity: Analyzing software with forensic psychology Adam Tornhill TEDxTrondheim youtube.com/watch?v=qJ_hplxTYJw

43. ‘Code Maat’ tool

44. Adam Tornhill, http://www.adamtornhill.com/articles/crimescene/codeascrimescene.htm Code City plus Code Maat forensics

45. Beware of badly-named subsystems

46. "information-poor abstract names are magnets for extra [unwanted] responsibilities" – Adam Tornhill p.185, Your Code as a Crime Scene

47. Team-first boundaries

48. DevOpsTopologies.com

49. Team types Component team Platform / ’substrate’ team Supporting / ‘productivity’ team Product/Feature team

50. Team types devopstopologies.com Platform / ’substrate’ team Product/Feature team

51. Team types devopstopologies.com Component team Platform / ’substrate’ team Product/Feature team

52. Team types devopstopologies.com Component team Platform / ’substrate’ team Product/Feature team Supporting / ‘productivity’ team

53. Code repositories Align repositories to subsystem boundaries Avoid monolithic-y repos like TFS* * Don’t get me started on TFS, grrr…

54. Code repositories Repo 1 Build Test Deploy Run Repo 2 Build Test Deploy Run Repo 3 Build Test Deploy Run

55. “You can use a monorepo only if your organisation has published a scientific paper on Computer Science. Otherwise, use one repo per deployable runnable thing.” – Matthew Skelton LondonCD meetup group, 11 Oct 2016 

56. Find natural or available ‘fracture planes’ for splitting a monolith (with the team in mind)

57. Industry experience Examples from recent work with clients Different monoliths Different ‘fracture planes’

58. Software for R&D teams Customers: over 80% of top 20 global pharma companies

59. 2014: Monolithic: builds, releases Pharma GxP: traceability Changes slow and tricky

60. Fracture plane: business domain

61. Fracture plane: technology

62. Compose with packages Logging for insights Technology splits Improved traceability

63. Major UK broadcaster (TV + online) Increasing digital delivery of content

64. 2014: Wide mix of technologies Need for visibility of changes Need for rapid turnaround

65. Fracture planes: read-only, location & cadence

66. Split off Reporting (read-only) Split on change cadence Increased change throughput

67. UK’s second largest credit reference agency Customers: major banks + large orgs

68. 2014: 6-weekly monolithic release Outage-sensitive customers

69. Fracture planes: risk & business domain

70. Split releases based on risk Align teams to value streams More rapid release cadence

71. Software for Internal Comms Customers: FTSE 100 & Fortune 1000

72. 2015: Successful system (monolithic) ISO 27001 compliance Aim to expand the org (x N)

73. Fracture plane: business domain

74. Optimise split for team engagement & personas Minimise ISO 27001 footprint Aided organisation expansion

75. When not to split a monolith •‘Heritage’ ERP system (‘cloudified’) •No native Unit Test framework •20-30 min startup times •VMs need 56GB RAM (yes) •CI builds take 50 mins

76. Monolith-splitting recipe Tried and tested!

77. Monolith-splitting recipe 1. Instrument the monolith – logging 2. Grok data flows and fault responses 3. Align teams to available segments 4. Split off segments one-by-one

78. Instrument the monolith

81. search by event Event ID {Delivered, InTransit, Arrived}

82. transaction trace Correlation ID 612999958…

83. Technical Domain public enum EventID { // Badly-initialised logging data NotSet = 0, // An unrecognised event has occurred UnexpectedError = 10000, ApplicationStarted = 20000, ApplicationShutdownNoticeReceived = 20001, PageGenerationStarted = 30000, PageGenerationCompleted = 30001, MessageQueued = 40000, MessagePeeked = 40001, BasketItemAdded = 60001, BasketItemRemoved = 60002, CreditCardDetailsSubmitted = 70001, // ... }

84. BasketItemAdded = 60001 BasketItemRemoved = 60002

85. Instrument the monolith Correlation ID Logs Event ID

86. use logging as a channel/vector to make distributed systems more testable use logging as a channel/vector to make distributed systems more testable

87. Grok data flows and fault responses

88. Grok data flows and fault responses Correlation ID Event ID Unexpected collaborating subsystems Undetected fault condition

89. Grok data flows and fault responses Correlation ID Event ID Adjust subsystem boundaries Fix poor fault responses

90. runbooktemplate.info Run Book dialogue sheets

91. Align teams to available segments

92. Align teams to available segments

93. Align teams to available segments Map to business domain

94. Align teams to available segments Identify likely components or ‘platform’ elements

95. Split off segments one-by-one

96. Split off segments one-by-one

97. Split off segments one-by-one Separate: - Builds - Infrastructure - Deployments - Versions - Lifecycle

98. Team needs / responsibilities / capabilities come first

99. use logging as a channel/vector to make distributed systems more testable Invest in Build & Release Engineering

100. Monolith-splitting recipe * 1. Instrument the monolith – logging 2. Grok data flows and fault responses 3. Align teams to available segments 4. Split off segments one-by-one (5. Invest in Build & Release Engineering) * The simplistic version

101. Monolith-splitting recipe * 1. Instrument 2. Grok behaviour 3. Align teams 4. Split off segments 5. Invest in Build & Release * The simplistic version

102. Monolith-splitting recipe * * The simplistic version 1. Instrument 2. Grok behaviour 3. Align teams 4. Split off segments 5. Invest in Build & Release

103. Determine monolith type (Apply ‘Code Forensics’) Find ‘fracture planes’ Assess cognitive load for teams Use the monolith-splitting recipe How to break apart a monolithic system safely without destroying your team

104. Further material

105. Books & articles • Working Effectively with Legacy Code, by Michael Feathers • Building Microservices by Sam Newman (O’Reilly, 2015) • Managing Cognitive Load for Team Learning by Jo Pearce http://12devsofxmas.co.uk/2015/12/day-3-managing-cognitive-load- for-team-learning/ • Continuous Delivery with Windows and .NET by Matthew Skelton and Chris O’Dell (O’Reilly, 2016) http://cdwithwindows.net/ • Team Guide to Software Operability by Matthew Skelton and Rob Thatcher (Skelton Thatcher Publications, 2016) http://operabilitybook.com/ • Ye Olde Monolith by Pter Pilgrim https://dzone.com/articles/ye-olde- monolith

106. Training • From Monolith to Microservices (online training) – Sam Newman, author of Building Microservices http://www.oreilly.com/live-training/from-monolith-to- microservices.html • Run Book template & Run Book dialogue sheets http://runbooktemplate.info/

107. Talks & slides • Hacking Your Head – Managing Information Overload, by Jo Pearce - http://www.slideshare.net/JoPearce5/hacking-your- head-managing-information-overload-45-mix / http://conferences.oreilly.com/oscon/open-source- eu/public/schedule/detail/53013 • Principles of Microservices by Sam Newman @ Devoxx 2015 https://www.youtube.com/watch?v=PFQnNFe27kU

108. Research papers • Driskell, James E., Eduardo Salas, and Joan Johnston. ‘Does Stress Lead to a Loss of Team Perspective?’ Group Dynamics: Theory, Research, and Practice 3, no. 4 (1999): 291. • Fan, Xiaocong, Po-Chun Chen, and John Yen. ‘Learning HMM-Based Cognitive Load Models for Supporting Human-Agent Teamwork’. Cognitive Systems Research 11, no. 1 (2010): 108–119. • Ilgen, Daniel R., and John R. Hollenbeck. ‘Effective Team Performance under Stress and Normal Conditions: An Experimental Paradigm, Theory and Data for Studying Team Decision Making in Hierarchical Teams with Distributed Expertise’. DTIC Document, 1993. http://oai.dtic.mil/oai/oai?verb=getRecord&metadataPrefix=html&identifier=ADA284683. • Johnston, Joan H., Stephen M. Fiore, Carol Paris, and C. A. Smith. ‘Application of Cognitive Load Theory to Developing a Measure of Team Decision Efficiency’. DTIC Document, 2002. http://oai.dtic.mil/oai/oai?verb=getRecord&metadataPrefix=html&identifier=ADA525820. • Sweller, John. ‘Cognitive Load Theory, Learning Difficulty, and Instructional Design’. Learning and Instruction 4 (1994): 295–312. • Sweller, John. ‘Cognitive Load during Problem Solving: Effects on Learning’. Cognitive Science 12, no. 2 (1988): 257–285.

109. Determine monolith type (Apply ‘Code Forensics’) Find ‘fracture planes’ Assess cognitive load for teams Use the monolith-splitting recipe How to break apart a monolithic system safely without destroying your team

110. thank you Matthew Skelton @matthewpskelton skeltonthatcher.com