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Beyond the spotify model - Team Topologies - Agile Yorkshire 2019-03-20 - Matthew Skelton

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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

Bio: Matthew Skelton is the Founder and Head of Consulting at Conflux. He has been building, deploying, and operating commercial software systems since 1998. As Head of Consulting at Conflux, he specialises in Continuous Delivery, operability and organisation dynamics for software in manufacturing, ecommerce, and online services, including cloud, IoT, and embedded software.

Recognised by TechBeacon in 2018 as one of the top 100 people to follow in DevOps, Matthew curates the well-known DevOps team topologies patterns at devopstopologies.com and is co-author of the books Continuous Delivery with Windows and .NET (O’Reilly, 2016), Team Guide to Software Operability (Skelton Thatcher Publications, 2016), and Team Topologies (IT Revolution Press, 2019).
Matthew founded Conflux in 2017 to offer training and consulting to organisations building and running software systems.

Twitter: @matthewpskelton
LinkedIn: matthewskelton
Slideshare: matthewskelton


From a talk at Agile Yorkshire on 20 March 2019 http://www.agileyorkshire.org/event-announcements/wed20thmarch-andybutcherautonomyandchoreography-usingconwayslawtotacklethecompanyscalingproblem

Publicada em: Software
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Beyond the spotify model - Team Topologies - Agile Yorkshire 2019-03-20 - Matthew Skelton

  1. 1. TeamTopologies.com @TeamTopologies Beyond the Spotify model using Team Topologies for organisation dynamics with software delivery Matthew Skelton, Conflux co-author of Team Topologies - @matthewpskelton Agile Yorkshire, 20 March 2019, Leeds
  2. 2. 2
  3. 3. 3 The Spotify Model Limitations Team Topologies Getting started
  4. 4. 4
  5. 5. 5
  6. 6. The Spotify model of team design for software delivery 6
  7. 7. 7 Henrik Kniberg & Anders Ivarsson, 2012 https://blog.crisp.se/wp-content/uploads/2012/11/SpotifyScaling.pdf
  8. 8. 8 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
  9. 9. 9 The Spotify model has been hugely helpful to 100s of organizations
  10. 10. The Spotify model helps to... 10
  11. 11. 11 Encourage flow of change
  12. 12. 12 Establish and clarify team responsibilities
  13. 13. 13 Promote good kinds of team collaboration
  14. 14. 14 Plan and budget for cross-team enablers
  15. 15. 15 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
  16. 16. Limitations of the Spotify model 16
  17. 17. “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 17
  18. 18. There is No Spotify Model 18 Marcin Floryan, 2016 https://www.infoq.com/presentations/spotify-culture-stc
  19. 19. 19 Software sizing and cognitive load
  20. 20. 20 Heuristics for Conway’s Law
  21. 21. 21 Patterns for team interactions
  22. 22. 22 Triggers for change and evolution
  23. 23. 23 We also need to address Software sizing and cognitive load Heuristics for Conway’s Law Patterns for team interactions Triggers for change and evolution
  24. 24. Team Topologies 24
  25. 25. topology the way in which constituent parts are interrelated or arranged Greek: τοπολογία (τόπος == ‘place’) 25
  26. 26. Team Topologies 26 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
  27. 27. Origins - DevOps Topologies 27 CC BY-SA devopstopologies.com
  28. 28. 28 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
  29. 29. 29 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
  30. 30. Team Topologies 30 Organizing business and technology teams for fast flow Matthew Skelton and Manuel Pais Publication date: Sept 2019 IT Revolution Press Pre-order from Amazon.com: https://teamtopologies.com/book
  31. 31. “innovative tools and concepts for structuring the next generation digital operating model” Charles T. Betz, Principal Analyst, Forrester Research 31
  32. 32. Team Topologies for fast flow Conway’s Law Team-first Thinking Team Interactions Sensing for Evolution 32
  33. 33. 33 Software sizing and cognitive load
  34. 34. 34 Team-first Thinking
  35. 35. 35 Team-first Thinking The team is the means of delivery
  36. 36. 36 Team-first Thinking Design for team cognitive load
  37. 37. 37 Team-first Thinking Choose boundaries for team ownership
  38. 38. 38 Team-first Thinking Physical and digital workspace
  39. 39. 39 Team-first Thinking The team is the means of delivery Design for team cognitive load Choose boundaries for team ownership Physical and digital workspace
  40. 40. 40 Heuristics for Conway’s Law
  41. 41. 41 Conway’s Law
  42. 42. 42 Conway’s Law Heuristic for ‘natural’ expected design
  43. 43. 43 Conway’s Law Mirroring in tech system + human system
  44. 44. 44 Conway’s Law Reverse Conway to mitigate worst effects
  45. 45. 45 Conway’s Law Constraint on solution search space
  46. 46. 46 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
  47. 47. 47 Patterns for team interactions
  48. 48. 48 Team Interactions
  49. 49. 49 Team Interactions 3 defined Interaction Modes
  50. 50. 50 Team Interactions Collaboration: 2 teams working together
  51. 51. 51 Team Interactions X-as-a-Service: 1 provides, 1 consumes
  52. 52. 52 Team Interactions Facilitating: 1 team helps another
  53. 53. 53 Team Interactions 3 defined Interaction Modes Collaboration: 2 teams working together X-as-a-Service: 1 provides, 1 consumes Facilitating: 1 team helps another
  54. 54. 4 fundamental topologies 54 Stream-aligned team Enabling team Complicated Subsystem team Platform team
  55. 55. 4 fundamental topologies 55 Flow of change
  56. 56. 3 core interaction modes 56 Flow of change X-as-a-Service Facilitating Collaboration
  57. 57. 57 Triggers for change and evolution
  58. 58. 58 Sensing for Evolution
  59. 59. 59 Sensing for Evolution Not all teams in the org look the same
  60. 60. 60 Sensing for Evolution Discover, then push to Platform
  61. 61. 61 Sensing for Evolution Awkward team interactions are signals
  62. 62. 62 Sensing for Evolution Evolve the org with changing ecosystem
  63. 63. 63 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
  64. 64. Getting started with the Team Topologies approach 64
  65. 65. Getting started 65 Explicit cognitive load Large Conway mismatches Team Interactions Thinnest Viable Platform
  66. 66. 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 66
  67. 67. Getting started 67 Explicit cognitive load Large Conway mismatches Team Interactions Thinnest Viable Platform
  68. 68. Are there major mismatches between the team interactions and the required software / system architecture? What could be easily adjusted? Large Conway mismatches 68
  69. 69. Getting started 69 Explicit cognitive load Large Conway mismatches Team Interactions Thinnest Viable Platform
  70. 70. What would change if we adopted the 3 team interaction patterns? Collaboration, X-as-a-Service, Facilitating How would teams react & behave? Team Interactions 70
  71. 71. Getting started 71 Explicit cognitive load Large Conway mismatches Team Interactions Thinnest Viable Platform
  72. 72. How is your Platform defined? What is the thinnest platform that could work? What’s needed to run an support it? Thinnest Viable Platform 72
  73. 73. Getting started 73 Explicit cognitive load Large Conway mismatches Team Interactions Thinnest Viable Platform
  74. 74. Review 74
  75. 75. 75 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
  76. 76. 76 We also need to address Software sizing and cognitive load Heuristics for Conway’s Law Patterns for team interactions Triggers for change and evolution
  77. 77. Team Topologies for fast flow Conway’s Law Team-first Thinking Team Interactions Sensing for Evolution 77
  78. 78. Getting started 78 Explicit cognitive load Large Conway mismatches Team Interactions Thinnest Viable Platform
  79. 79. Sign up for news and tips: TeamTopologies.com 79
  80. 80. Thank you! info@teamtopologies.com 80 Matthew Skelton, Conflux @matthewpskelton Manuel Pais, Independent @manupaisable Copyright © Conflux Digital Ltd 2018-2019. All rights reserved. Registered in England and Wales, number 10890964 Icons made by Freepick from www.flaticon.com - used under license

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