Monkigras - dropping science on your developer ecosystem


Published on

My Monkigras 2013 talk where I explain lessons we can learn from Ecosystem Science and Management

Published in: Technology
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Monkigras - dropping science on your developer ecosystem

  1. Dropping Science on Your Technology Ecosystem - lessons from Ecosystem Management@thesteve0Steven Citron-PoustyPaaS Dust SpreaderOpenShift – Red Hat
  2. Slide with Tech ecosystem
  3. Science!! chase_elliott from flickr
  4. Science!! chase_elliott from flickr
  5. Ecosystems are real• Well they are actually a model – but with the good and the bad AA model of the world
  6. BUT, Conservation Biologists use This Model
  7. They had a problem that needed to move beyond individual species at best Single species = emergency room Mass Energy and Env Affairs on flickr
  8. Where did it really start
  9. Yellowstone - map
  10. Yellowstone – satellite
  11. Yellowstone – ecosystem
  12. Grizzly bear
  13. Wolf
  14. Grizzly Denali picture
  15. 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
  16. Values and Goals• You get this from social, economic, and political• Most important• Not science or quantitative but drives everything
  17. Science!! chase_elliott from flickr
  18. Keystone• Keystone species – otter• Bottom of the food chain – menhanden
  19. Who are the keystones in yourecosystem?
  20. Who are your menhaden?
  21. Planned (some forethought) vs NaturalExperiments (need long-termmonitoring before)
  22. OpenShift ExampleAdaptive management and plannedexperiments
  23. No differencedata: responses out of sentsample estimates:prop A prop B0.04800000 0.0533333395 percent confidence interval:-0.02169480 0.01102814X-squared = 0.3396, df = 1, p-value = 0.5601alternative hypothesis: two.sided Type I = saying there is a difference when there isn’t Type II = saying there is no difference when there is
  24. What action can you turn into anexperiment?
  25. Natural Experiment
  26. OpenShift Example
  27. What monitoring are you doing?
  28. What adaptations can you make based on knowledge gained?
  29. 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
  30. r vs. K life history strategies and you
  31. Where are you on the curve?