The production of software is a complex, collaborative process that stretches our ability as human beings to cope with its demands. Many people working in software development spend their careers without seeing what good really looks like. Our history is littered with inefficient processes creating poor quality output, too late to capitalise on the expected business value. How have we got into this state? How do we get past it? What does good really look like? Continuous Delivery changes the economics of software development for some of the biggest companies in the world, whatever the nature of their software development, find out how and why.

1. Dave Farley
http://www.davefarley.net
@davefarley77
http://www.continuous-delivery.co.uk
The Rationale For
Continuous Delivery
Or
What Does ‘Good’ Look Like?

2. The State of Software Development

3. The State of Software Development
Source: KPMG (New Zealand)
Date: 2010
In a study of project management practices:
1) 70% of organizations have suffered at least one
project failure in the last 12 months
2) 50% of respondents indicated that their projects
consistently failed to achieve what they set out to
achieve.

4. The State of Software Development
Source: KPMG (New Zealand)
Date: 2010
In a study of project management practices:
1) 70% of organizations have suffered at least one
project failure in the last 12 months
2) 50% of respondents indicated that their projects
consistently failed to achieve what they set out to
achieve.
Source: KPMG – Global IT Management Survey
Date: 2005
In a survey of 600 projects worldwide:
1) 49% of organisations had suffered a project failure in
the past 12 months
2) 2% of organisations reported that all of their projects
achieved their desired benefits.

5. The State of Software Development
Source: KPMG (New Zealand)
Date: 2010
In a study of project management practices:
1) 70% of organizations have suffered at least one
project failure in the last 12 months
2) 50% of respondents indicated that their projects
consistently failed to achieve what they set out to
achieve.
Source: KPMG – Global IT Management Survey
Date: 2005
In a survey of 600 projects worldwide:
1) 49% of organisations had suffered a project failure in
the past 12 months
2) 2% of organisations reported that all of their projects
achieved their desired benefits.
Source: Logica Management Consulting
Date: 2008
In a survey of 380 senior execs in Western Europe:
1) 35% of organisations abandoned a major project in
the last 3years
2) 37% of business change programmes fail to deliver
benefits.

6. The State of Software Development
Source: KPMG (New Zealand)
Date: 2010
In a study of project management practices:
1) 70% of organizations have suffered at least one
project failure in the last 12 months
2) 50% of respondents indicated that their projects
consistently failed to achieve what they set out to
achieve.
Source: KPMG – Global IT Management Survey
Date: 2005
In a survey of 600 projects worldwide:
1) 49% of organisations had suffered a project failure in
the past 12 months
2) 2% of organisations reported that all of their projects
achieved their desired benefits.
Source: Logica Management Consulting
Date: 2008
In a survey of 380 senior execs in Western Europe:
1) 35% of organisations abandoned a major project in
the last 3years
2) 37% of business change programmes fail to deliver
benefits.
Source: The McKinsey Group with Oxford University
Date: 2012
In a study of 5,400 large scale projects (> $15m):
1) 17% of projects go so badly that they threaten the
existence of the company performing them.
2) On average large projects run 45% over budget and
7% over time while delivering 56% less value than
predicted.

7. If Software Projects Worked…

8. If Software Projects Worked…

9. Failure Success
If Software Projects Worked…

10. Failure Success
If Software Projects Worked…

11. (C)opyright Dave Farley 2015
We Have Got The Model Wrong!
Source: Malin Christersson http://www.malinc.se/math/trigonometry/geocentrismen.php

12. (C)opyright Dave Farley 2015
We Have Got The Model Wrong!
Source: Malin Christersson http://www.malinc.se/math/trigonometry/geocentrismen.php

13. The State of Software Development
Has Been Err…. Sub-Optimal

14. The State of Software Development
Has Been Err…. Sub-Optimal

15. The State of Software Development
Has Been Err…. Sub-Optimal
But there are signs of change…

16. What Have We Tried?

17. What Have We Tried?

18. What Have We Tried?

19. What Have We Tried?

20. What Have We Tried?

21. What Have We Tried?

22. What Have We Tried?

23. What Have We Tried?

24. What Have We Tried?

25. What Have We Tried?

26. What Have We Tried?

27. (C)opyright Dave Farley 2015

28. (C)opyright Dave Farley 2015
Waterfall - Precisely Where We Went Wrong
Managing The Development of Large Software Systems - Dr Winston W. Royce (1970)

29. (C)opyright Dave Farley 2015
Waterfall - Precisely Where We Went Wrong
Managing The Development of Large Software Systems - Dr Winston W. Royce (1970)
The IEEE has a lot to answer for!

30. (C)opyright Dave Farley 2015
Waterfall - Precisely Where We Went Wrong
Managing The Development of Large Software Systems - Dr Winston W. Royce (1970)

31. (C)opyright Dave Farley 2015
Waterfall - Precisely Where We Went Wrong
Managing The Development of Large Software Systems - Dr Winston W. Royce (1970)

32. (C)opyright Dave Farley 2015
Waterfall - Precisely Where We Went Wrong
Managing The Development of Large Software Systems - Dr Winston W. Royce (1970)

33. (C)opyright Dave Farley 2015
“…the implementation described above is risky and invites failure.”
<snip>
“The testing phase which occurs at the end of the development
cycle is the first event for which timing, storage, input/output
transfers, etc., are experienced as distinguished from analysed.
These phenomena are not precisely analysable.”
Waterfall - Precisely Where We Went Wrong
Managing The Development of Large Software Systems - Dr Winston W. Royce (1970)

34. (C)opyright Dave Farley 2015
Waterfall - Precisely Where We Went Wrong
Managing The Development of Large Software Systems - Dr Winston W. Royce (1970)

35. (C)opyright Dave Farley 2015
Waterfall - Precisely Where We Went Wrong
Managing The Development of Large Software Systems - Dr Winston W. Royce (1970)

36. (C)opyright Dave Farley 2015
Waterfall - Precisely Where We Went Wrong
Managing The Development of Large Software Systems - Dr Winston W. Royce (1970)

37. Learning From Our Mistakes

38. Learning From Our Mistakes
“Insanity is doing the
same thing over and
over again and
expecting different
results.”
Albert Einstein

39. What Do We Really Want?
Customer
Feedback
Business Idea

40. What Do We Really Want?
Customer
Feedback
Business Idea
Quickly
Cheaply
Reliably

41. A Question….

42. A Question….
What is the most successful
invention in human history?

43. A Question….
SCIENCE

44. The Scientific Method
Characterisation Make a guess based on experience and observation.
Hypothesis Propose an explanation.
Deduction Make a prediction from the hypothesis.
Experiment Test the prediction.
Repeat!

45. Smart Automation - a repeatable, reliable process for releasing
software
Unit Test CodeIdea
Executable
spec.
Build Release
What Really Works?

46. Smart Automation - a repeatable, reliable process for releasing
software
Unit Test CodeIdea
Executable
spec.
Build Release
What Really Works?

47. Smart Automation - a repeatable, reliable process for releasing
software
Unit Test CodeIdea
Executable
spec.
Build Release
“It doesn’t matter how intelligent you are, if
you guess and that guess cannot be backed
up by experimental evidence – then it is still a
guess!”
- Richard Feynman
What Really Works?

48. Cycle-Time
103 days
Typical Traditional Cycle Time
10 days
64 days

49. Cycle-Time
Commit Stage
Compile
Unit test
Analysis
Build Installers
Automated
acceptance
testing
Automated
performance
testing
Manual testing
Release
57 mins
3 mins 20 mins
20 mins
30 mins
4 mins
Typical CD Cycle Time
103 days
Typical Traditional Cycle Time
10 days
64 days

50. What Is Continuous Delivery?
“Our highest priority is to satisfy the customer through early
and continuous delivery of valuable software.”
The first principle of the agile manifesto.
The logical extension of continuous integration.
A holistic approach to development.
Every commit creates a release candidate.
Finished means released into production!

51. The Principles of Continuous Delivery
Create a repeatable, reliable process for releasing software.
Automate almost everything.
Keep everything under version control.
If it hurts, do it more often – bring the pain forward.
Build quality in.
Done means released.
Everybody is responsible for the release process.
Improve continuously.

52. The Principles of Continuous Delivery
Create a repeatable, reliable process for releasing software.
Automate almost everything.
Keep everything under version control.
If it hurts, do it more often – bring the pain forward.
Build quality in.
Done means released.
Everybody is responsible for the release process.
Improve continuously.
“If Agile software development
was the opening act to a great
performance, Continuous
Delivery is the headliner.”
Forrester Research 2013

53. Example Continuous Delivery Process
Artifact
Repository
Local Dev. Env.
Deployment Pipeline
Acceptance
Commit
Component
Performance
System
Performance
Production Env.
Deployment
App.
Commit
Acceptance
Manual
Perf1
Perf2
Staged
Production
Source
Repository
Manual Test Env.
Deployment
App.
Data
Migration

54. “This may work for small projects but can’t possibly scale”

55. “This may work for small projects but can’t possibly scale”
The Google Build Process
• Single Monolithic Repository
• Continuous Build & Test on Commit For:
• > 60 Million builds per year and growing exponentially.
• > 100 Million lines of code.
• All tests are run on every commit, (>20 commits per minute).
• > 100 Million test cases executed per day.

56. “This is too risky, releasing all the time is a recipe for disaster”

57. “This is too risky, releasing all the time is a recipe for disaster”
The Amazon Build Process
• Mean time between deployment - 11.6 seconds
• Mean hosts simultaneously receiving a deployment - 10,000
• 75% reduction in outages triggered by deployment
• 90% reduction in outage minutes triggered by deployment
• ~0.001% of deployments cause an outage
• Instantaneous rollback
• Reduction in complexity

58. “This may work for simple web sites but my
technology is too complex”

59. “This may work for simple web sites but my
technology is too complex”
• Transformation of Development Approach for all LaserJet
Firmware Products
• Large Complex Project
• Multiple Products
• Four Year Timeframe
• 10x Developer Productivity Increase
HP Laserjet Firmware Team Experience

60. HP LaserJet Firmware Team
10% Code Integration
20% Detailed Planning
25% Porting Code
25% Product Support
15% Manual Testing
~5% Innovation
2% Continuous Integration
5% Agile Planning
15% Architectural Integrity
10% Unified Support
5% Automated Testing
3% Improving Tools
10% Writing Tests
~40% Innovation
2008 2011

61. The Results
A Practical Approach to Large scale Agile Development (Gruver, Young and Fulgrhum)
• Overall development costs reduced by ~40%
• Programs under development increased by ~140%
• Development cost per program down by 70%
• Resources now driving innovation increased by 5x

62. The Impact of Continuous Delivery on Software
Source: “ Lianping Chen Paddy Power (http://www.sciencedirect.com/science/article/pii/S0164121217300353)

63. The Impact of Continuous Delivery on Software
90% lower
defect rate
Source: “ Lianping Chen Paddy Power (http://www.sciencedirect.com/science/article/pii/S0164121217300353)

64. Source: “2014 State of DevOps report”, Jez Humble, Gene Kim, Nicole Forsgren Velasquez, Puppet Labs (2014)
The Impact of Continuous Delivery on Software

65. Source: “2014 State of DevOps report”, Jez Humble, Gene Kim, Nicole Forsgren Velasquez, Puppet Labs (2014)
8000x faster
deployment
lead times
The Impact of Continuous Delivery on Software

66. Source: “2017 State of DevOps report”, Jez Humble, Gene Kim, Nicole Forsgren Velasquez, Puppet Labs (2014)
The Impact of Continuous Delivery on Software

67. Source: “2017 State of DevOps report”, Jez Humble, Gene Kim, Nicole Forsgren Velasquez, Puppet Labs (2014)
21% Less time
spent on
unplanned work
and rework
The Impact of Continuous Delivery on Software

68. Source: “2017 State of DevOps report”, Jez Humble, Gene Kim, Nicole Forsgren Velasquez, Puppet Labs (2014)
The Impact of Continuous Delivery on Software

69. Source: “2017 State of DevOps report”, Jez Humble, Gene Kim, Nicole Forsgren Velasquez, Puppet Labs (2014)
44% More time
on new work
The Impact of Continuous Delivery on Software

70. Source: “2017 State of DevOps report”, Jez Humble, Gene Kim, Nicole Forsgren Velasquez, Puppet Labs (2014)
The Impact of Continuous Delivery on Software

71. Source: “2017 State of DevOps report”, Jez Humble, Gene Kim, Nicole Forsgren Velasquez, Puppet Labs (2014)
50% lower
change-failure
rates
The Impact of Continuous Delivery on Software

72. Source: “2017 State of DevOps report”, Jez Humble, Gene Kim, Nicole Forsgren Velasquez, Puppet Labs (2014)
The Impact of Continuous Delivery on Software

73. Source: “2017 State of DevOps report”, Jez Humble, Gene Kim, Nicole Forsgren Velasquez, Puppet Labs (2014)
50% Less time
spent
fixing security
issues
The Impact of Continuous Delivery on Software

74. Source: “2014 State of DevOps report”, Jez Humble, Gene Kim, Nicole Forsgren Velasquez, Puppet Labs (2014)
The Impact of Continuous Delivery on Software

75. Source: “2014 State of DevOps report”, Jez Humble, Gene Kim, Nicole Forsgren Velasquez, Puppet Labs (2014)
50%
Higher Market cap
growth over 3
years
The Impact of Continuous Delivery on Software

76. Who Practices CD?

77. Who Practices CD?

78. Q&A
http://www.continuous-delivery.co.uk
Dave Farley
http://www.davefarley.net
@davefarley77