For effective, modern, cloud-connected software systems we need to organize our teams in certain ways. Taking account of Conway’s Law, we look to match the team structures to the required software architecture, enabling or restricting communication and collaboration for the best outcomes. This talk will cover the basics of organization design using Team Topologies, exploring a selection of key team types, and how and when to use them in order to make the development and operation of your software systems as effective as possible. The talk is based on the forthcoming 2019 book Team Topologies and first-hand experience helping companies around the world with the design of their technology teams. Key takeaways: 1. Why using the “Spotify Model” of team design is not enough 2. The four fundamental team topologies needed for modern software delivery 3. The three team interaction modes that enable fast flow and rapid learning 4. How to address Conway’s Law, cognitive load, and team evolution with Team Topologies From a keynote talk at Jax DevOps 2019, London.

1. TeamTopologies.com
@TeamTopologies
Beyond the Spotify model
using Team Topologies for
fast flow and organisation evolution
Matthew Skelton, Conflux
co-author of Team Topologies - @matthewpskelton
JAX DevOps, London, 16 May 2019

2. 2
The Spotify Model
Limitations
Team Topologies
Getting started

3. 3

4. 4

5. The Spotify model of
team design for
software delivery
5

6. 6
Henrik Kniberg & Anders Ivarsson, 2012
https://blog.crisp.se/wp-content/uploads/2012/11/SpotifyScaling.pdf

7. 7
The Spotify model
Squad: semi-autonomous delivery team
Tribe: family of Squads - related work
Chapter: line management within a Tribe
Guild: cross-Tribe interest/specialist group

8. 8
The Spotify model has
been hugely helpful to
100s of organizations

9. The Spotify model
helps to...
9

10. 10
Encourage flow
of change

11. 11
Establish and
clarify team
responsibilities

12. 12
Promote good
kinds of team
collaboration

13. 13
Plan and budget
for cross-team
enablers

14. 14
The Spotify model helps to
Encourage flow of change
Establish and clarify team responsibilities
Promote good kinds of team collaboration
Plan and budget for cross-team enablers
@matthewpskelton / @TeamTopologies

15. Limitations of the
Spotify model
15

16. “This article is only a snapshot of our
current way of working - a journey in
progress, not a journey completed. By
the time you read this, things have
already changed.”
- Kniberg & Ivarsson
16

17. There is No Spotify Model
17
Marcin Floryan, 2016
https://www.infoq.com/presentations/spotify-culture-stc

18. 18
Software sizing
and cognitive
load

19. 19
Heuristics for
Conway’s Law

20. 20
Patterns for
team
interactions

21. 21
Triggers for
change and
evolution

22. 22
We also need to address
Software sizing and cognitive load
Heuristics for Conway’s Law
Patterns for team interactions
Triggers for change and evolution
@matthewpskelton / @TeamTopologies

23. Team Topologies
23

24. topology
the way in which constituent parts are
interrelated or arranged
Greek: τοπολογία (τόπος == ‘place’)
24

25. Team Topologies
25
Research over 5 years across multiple industry sectors
Informed by 50+ peer-reviewed journal articles
30+ client organizations - consulting and training since
2013 with orgs in CN, EU, IN, US, UK, +
Book: 12+ case studies from well-known organizations

26. Origins - DevOps Topologies
26
CC BY-SA devopstopologies.com
@matthewpskelton / @TeamTopologies

27. 27
Philip Fisher-Ogden,
Director of Engineering at
Netflix:
“thanks for your insightful
articulations of devops
topologies. They inspired
many discussions and
helped us to think about
what model Netflix teams
could be/are using.”
https://twitter.com/philip_pfo/status/999074792123740160

28. 28
Crystal Hirschorn,
Director of Engineering at
Condé Nast International
“Your topological models
resonated extremely well
on both the Dev and Ops
side btw! I like the balanced
arguments, e.g. different
perspectives, for each
pattern.”
https://twitter.com/cfhirschorn/status/1103387659890819073

29. Team Topologies
29
Organizing business and
technology teams for fast flow
Matthew Skelton & Manuel Pais
Publication date: Sept 2019
IT Revolution Press
Pre-order from Amazon:
https://teamtopologies.com/book

30. “innovative tools and concepts for
structuring the next generation
digital operating model”
Charles T. Betz, Principal Analyst, Forrester Research
30

31. Team Topologies for fast flow
Conway’s Law
Team-first
Thinking
Team
Interactions
Sensing for
Evolution
31

32. 32
Software sizing
and cognitive
load

33. 33
Team-first Thinking

34. 34
Team-first Thinking
The team is the means of delivery

35. 35
Team-first Thinking
Design for team cognitive load

36. 36
Team-first Thinking
Choose boundaries for team ownership

37. 37
Team-first Thinking
Physical and digital workspace

38. 38
Team-first Thinking
The team is the means of delivery
Design for team cognitive load
Choose boundaries for team ownership
Physical and digital workspace
@matthewpskelton / @TeamTopologies

39. 39
Heuristics for
Conway’s Law

40. 40
Conway’s Law

41. 41
Conway’s Law
Heuristic for ‘natural’ expected design

42. 42
Conway’s Law
Mirroring in tech system + human system

43. 43
Conway’s Law
Reverse Conway to mitigate worst effects

44. 44
Conway’s Law
Constraint on solution search space

45. 45
Conway’s Law
Heuristic for ‘natural’ expected design
Mirroring in tech system + human system
Reverse Conway to mitigate worst effects
Constraint on solution search space
@matthewpskelton / @TeamTopologies

46. 46
Patterns for
team
interactions

47. 47
Team Interactions

48. 48
Team Interactions
3 defined Interaction Modes

49. 49
Team Interactions
Collaboration: 2 teams working together

50. 50
Team Interactions
X-as-a-Service: 1 provides, 1 consumes

51. 51
Team Interactions
Facilitating: 1 team helps another

52. 52
Team Interactions
3 defined Interaction Modes
Collaboration: 2 teams working together
X-as-a-Service: 1 provides, 1 consumes
Facilitating: 1 team helps another
@matthewpskelton / @TeamTopologies

53. 4 fundamental topologies
53
Stream-aligned team
Enabling team
Complicated Subsystem team
Platform team

54. 4 fundamental topologies
54
Flow of change

55. 3 core interaction modes
55
Flow of change
X-as-a-Service
Facilitating
Collaboration

56. 56
Triggers for
change and
evolution

57. 57
Sensing for Evolution

58. 58
Sensing for Evolution
Not all teams in the org look the same

59. 59
Sensing for Evolution
Discover, then push to Platform

60. 60
Sensing for Evolution
Awkward team interactions are signals

61. 61
Sensing for Evolution
Evolve the org with changing ecosystem

62. 62
Sensing for Evolution
Not all teams in the org look the same
Discover, then push to Platform
Awkward team interactions are signals
Evolve the org with changing ecosystem
@matthewpskelton / @TeamTopologies

63. Getting started with
the Team Topologies
approach
63

64. Getting started
64
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

65. How well can the team as a unit “grok”
the systems they own and develop?
Push some things into a Platform?
Are skills or capabilities missing?
Explicit cognitive load
65

66. Getting started
66
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

67. Are there major mismatches between
the team interactions and the required
software / system architecture?
What could be easily adjusted?
Large Conway mismatches
67

68. Getting started
68
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

69. What would change if we adopted the
3 team interaction patterns?
Collaboration, X-as-a-Service, Facilitating
How would teams react & behave?
Team Interactions
69

70. Getting started
70
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

71. How is your Platform defined?
What is the thinnest platform that
could work?
What’s needed to run an support it?
Thinnest Viable Platform
71

72. Getting started
72
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

73. Review
73

74. 74
The Spotify model helps to
Encourage flow of change
Establish and clarify team responsibilities
Promote good kinds of team collaboration
Plan and budget for cross-team enablers
@matthewpskelton / @TeamTopologies

75. 75
We also need to address
Software sizing and cognitive load
Heuristics for Conway’s Law
Patterns for team interactions
Triggers for change and evolution
@matthewpskelton / @TeamTopologies

76. Team Topologies for fast flow
Conway’s Law
Team-first
Thinking
Team
Interactions
Sensing for
Evolution
76

77. Getting started
77
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

78. Team Topologies
78
Organizing business and
technology teams for fast flow
Matthew Skelton & Manuel Pais
Publication date: Sept 2019
IT Revolution Press
Pre-order from Amazon.com:
https://teamtopologies.com/book

79. Training
79
Day 1
Fundamentals
Day 2
Deep Dive
Day 3
Applying in Context
teamtopologies.com/training

80. Sign up for news and tips:
TeamTopologies.com
80

81. Thank you!
teamtopologies.com
81
Matthew Skelton, Conflux
@matthewpskelton
Manuel Pais, Independent
@manupaisable
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