The debate on monoliths vs microservices as architectural patterns for modern software systems usually focuses on technological aspects, missing crucial details around organizational strategy and team dynamics. Should we start with a monolith and extract microservices or start with microservices? How many microservices is the right number? These kinds of questions indicate a confusion that is made worse by the perceived need to adopt lots of new technology in order to make microservices work. The false dichotomy between monoliths and microservices helps no-one. Instead, switched-on organizations start with the team cognitive load required to build and run a part of the software system. If a team is not able to fully understand the details of a service or subsystem, there is little chance of the team being able to own and support it. The resulting team-sized services are by definition suitable in size and complexity for a single team to own, develop, and run. No longer do we care how many lines of code there are in a single service or whether it is a “monolith”: what we care about is that a team can own and run the software effectively. Using team cognitive load as the guiding principle - assessed by the team via measures such as supportability, deployability, testability, operability, prioritization difficulties and domain complexity - organizations can optimize for sustainable ownership and evolution of software systems. This talk draws on research and case studies from the book Team Topologies by Matthew Skelton and Manuel Pais (IT Revolution Press, 2019) together with first-hand consulting experience from the authors with organizations around the world.

1. TeamTopologies.com
@TeamTopologies
Forget ‘Monoliths vs Microservices’: focus on
Team Cognitive Load
Matthew Skelton & Manuel Pais
co-authors of Team Topologies
@matthewpskelton @manupaisable
SEACON 2019, London - 12 Nov 2019
#seacon2019

2. 2
Monoliths vs Microservices
Team Cognitive Load
Case Studies
Getting started

3. Team Topologies
3
Organizing business and
technology teams for fast flow
Matthew Skelton & Manuel Pais
IT Revolution Press
Order via stores worldwide: teamtopologies.com/book

4. 4
Book signing ✍
TODAY @ 16:00 !
Thanks to

5. Monoliths vs
Microservices
5

6. 6

7. “Start with monolith and
extract microservices.”
- Tammer Saleh
7
https://www.infoq.com/presentations/cloud-anti-patterns

8. “Don’t start with a
monolith when your goal is
a microservices
architecture”
- Stefan Tilkov
8
http://martinfowler.com/articles/dont-start-monolith.html

9. “If you can't build a
monolith, what makes you
think microservices are
the answer?”
- Simon Brown
9
http://www.codingthearchitecture.com/2014/07/06/distributed_big_balls_of_mud.html

10. 10
WTF?!?!
* where to focus?

11. “Software that
fits in your head”
- Daniel Terhorst-North
11
https://speakerdeck.com/tastapod/microservices-software-that-fits-in-your-head?slide=62

12. 12
“Software that
fits in our heads”

13. 4 key metrics: ‘Accelerate’
13
lead time
deployment frequency
mean time to restore (MTTR)
change fail percentage

14. Software that is ‘too big for
our heads’ works against
organizational agility
14

15. Team Cognitive Load
15

16. COGNITIVE LOAD:
The total amount of
mental effort being used
in the working memory
- John Sweller
16

17. Intrinsic
Extraneous
Germane
17
“How are
classes
defined in
Java?”

18. Intrinsic
Extraneous
Germane
18
“How do I
deploy this
app,
again?”

19. Intrinsic
Extraneous
Germane
19
“How do
bank
transfers
work?”

20. Intrinsic (skills)
Extraneous (mechanism)
Germane (domain focus)
20

21. (Intrinsic)
] Extraneous [
Germane
21

22. More: ‘Hacking Your Head’
22
Jo Pearce
(@jdpearce)
https://www.slideshare.net/JoPearce5/hacking-your-head-managing-information-overload-extended

23. Limit the size of software
services/products to the
cognitive load that the
team can handle.
23

24. 24
“Software that
fits in our heads”

25. A ‘team-first’
approach to software
boundaries
25

26. Team size ≲ 9 *
* possibly 15
26

27. 27
Each service must be fully
owned by a team with
sufficient cognitive capacity
to build and operate it.

28. Whole-team
techniques (mobbing)
28

29. Well-chosen domain
boundaries (DDD)
29

30. Developer Experience
#DevEx
30

31. Operator Experience
#operability
31

32. Thinnest Viable Platform
(TVP)
32

33. 4 fundamental topologies
33
Stream-aligned team
Enabling team
Complicated Subsystem team
Platform team

34. 4 fundamental topologies
34
Flow of change

35. 3 core interaction modes
35
Flow of change
X-as-a-Service
Facilitating
Collaboration

36. “...trend analysis, simulations, rapid
prototyping, scenario planning,
gaming, environmental scanning
… give clues to the context and
competitive environment.”
- Dr. Naomi Stanford,
“Guide to Organisation Design” (The Economist)
36

37. Case Studies
37

38. CaseStudy
38

39. CaseStudy
39
2016
(early)

40. CaseStudy
40
2016
(late)
CMS

41. CaseStudy
Framework
41
2017
(early)
CMS
Products

42. CaseStudy
Framework
42
Products
2017
(late)
CMS

43. Team became too large
⇔
System became monolithic
Blocked flow of work across streams
43

44. Listen to ‘triggers for evolution’
❏ Software grows too large
❏ Over specialization (Brent)
❏ Increased coordination needs
44

45. CaseStudy
45

46. CaseStudy
46
CD Enablement
Infrastructure
Automation
Test
Automation
Build & CI
Support

47. CaseStudy
47
CD Enablement Infrastructure
Automation
Test
Automation
Build & CI
Support

48. It’s not always about software size...
More broadly, align size and number
of domains of responsibility
with team cognitive capacity.
48

49. Aim for teams with high cohesion internally
(think autonomy, mastery & purpose)
Aim for low bandwidth comms
between smaller teams
49

50. Listen to ‘triggers for evolution’
❏ Awkward interactions
❏ People not invested, burn out
❏ Frequent context switching
50

51. Getting started with
team cognitive load
51

52. How well can the team as a unit “grok”
the systems they own and develop?
Explicit cognitive load
52

53. Push some things into a Platform?
Explicit cognitive load
53

54. Are skills or capabilities missing?
Explicit cognitive load
54

55. What would change if we adopted the
3 team interaction patterns?
Collaboration, X-as-a-Service, Facilitating
Team Interactions
55

56. Collaboration, X-as-a-Service, Facilitating
How would teams react & behave?
Team Interactions
56

57. How is your Platform defined?
Thinnest Viable Platform
57

58. What is the thinnest platform that
could work?
Thinnest Viable Platform
58

59. What’s needed to run and support it?
Thinnest Viable Platform
59

60. Team Topologies
60
Organizing business and
technology teams for fast flow
Matthew Skelton & Manuel Pais
IT Revolution Press
Order via stores worldwide: teamtopologies.com/book

61. Training
61
Day 1
Fundamentals
Day 2
Deep Dive
Day 3
Applying in Context
teamtopologies.com/training

62. Looking for case studies
62
Global manufacturing company
Large government agency
Global financial services

63. Remaining problems
63
Measuring cognitive load at scale
Assessing team communication at scale
How to nudge managers and heads of X
to become Team Topologies enablers

64. TeamTopologies.com
@TeamTopologies
Sign up for news and tips:
TeamTopologies.com

65. Thank you!
teamtopologies.com
65
Matthew Skelton, Conflux
@matthewpskelton
Manuel Pais, Independent
@manupaisable
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