This document discusses lessons from ecosystem management that can be applied to developing a technical ecosystem. Some key ideas covered include: 1. Ecosystems are multi-dimensional and boundaries are permeable; manage for overall integrity. 2. Collect primary data through monitoring and engage in planned and natural experiments to continuously learn and adapt. 3. Achieve inter-agency cooperation as ecosystems involve many interconnected parts; humans are embedded within nature. 4. Adaptive management and organizational change may be needed as understanding of the system evolves over time. Values drive goals more than facts or logic.

1. Dropping Science on Your
Developer Ecosystem -
lessons from Ecosystem
Management
@thesteve0
Steven Citron-Pousty
PaaS Dust Spreader
OpenShift – Red Hat

3. Slide with Tech ecosystem

4. Science!!
chase_elliott from flickr

5. Slide with High School picture
• If we go back to High School science
Deserttrumpet on flickr

6. Ecosystems are real
• Well they are actually a model – but with the
good and the bad

7. And Conservation Biologists use This
Model

8. They had a problem that needed to
move beyond individual species at best
Single species = emergency room
Mass Energy and Env Affairs on flickr

9. Which Animal Forced the Issue

11. Yellowstone – satellite

12. Yellowstone - map

13. Yellowstone – ecosystem

14. Grizzly bear

15. Wolf

18. Grizzly Denali picture

19. So what are some of the ideas that I
will focus on today

20. Main ideas of ecosystem management
• Ecosystems are multi-dimensional
• Boundaries are only as real as you want them to be
• Manage for overall integrity
• Always collect and synthesize primary data
• Engage in monitoring
• Inter-Agency cooperation
• Humans embedded in nature
• Adaptive Management – experiment and learn
• Open to organizational change as fits the system
• Values are more important than facts and logic

21. Values and Goals
• You get this from social, economic, and
political
• Most important
• Not science or quantitative but drives
everything

22. Science!!
chase_elliott from flickr

25. Keystone
• Keystone species – otter
• Bottom of the food chain – menhanden

26. Who are the keystones in your
ecosystem?

30. Who are your menhaden?

31. Planned (some forethought) vs Natural
Experiments (need long-term
monitoring before)

32. OpenShift Example
Adaptive management and planned
experiments

33. No difference
data: responses out of sent
sample estimates:
prop A prop B
0.04800000 0.05333333
95 percent confidence interval:
-0.02169480 0.01102814
X-squared = 0.3396, df = 1, p-value = 0.5601
alternative hypothesis: two.sided
Type I = saying there is a difference when there isn’t
Type II = saying there is no difference when there is

34. What action can you turn into an
experiment?

35. Natural Experiment

39. OpenShift Example

42. What monitoring are you doing?

43. What adaptations can you make based
on knowledge gained?

44. Take homes
• Be more quant
• Do experiments don’t just do
• Take advantage of natural experiments
• Manage your ecosystem for key indicators
• Diversity is important
• Take the analogy of ecosystems farther and
learn from them

46. r vs. K life history strategies and you

47. Where are you on the curve?