This document discusses the concept of smart systems and how they scale. It addresses some key questions: 1) What makes an IT system "smart", and will its ability to be smart scale as the system grows larger? As systems increase in size and scope to serve more users, there is a push towards decentralization and standardization which can make them less smart and more reactive. 2) Is an AWS datacenter a centralized or decentralized system? Large cloud providers like AWS operate massive centralized datacenters to provide standardized cloud computing resources, but aim to appear decentralized to users. 3) How can systems maintain smart, responsive behavior at large scales? One approach is to localize feedback loops so smaller, localized

1. Mark Burgess
2016
Brains,
Societies,
and
Semantic
Spaces

2. Machine, Machine Messiah
The mindless search for a higher
Controller, take me to the fire
And hold me, show me the strength
Of your singular eye
-Yes

3. “Smart” means
“fast meaningful (fit for purpose)
response to challenges in context”

4. What is fast?

5. Managers
CFEngine
Kubernetes
Puppet
Manual

6. Smart
means
stability or
growth
through fast
feedback

7. Smart
means
stability or
growth
through fast
feedback
Kubernetes
CFEngine
Puppet
Manual

8. But scale drives a
central controller
towards instability
(where dumb works)
Stable
Unstable

9. Centralized
(Vertical)
Humanized
Points of service
Identities
Home
Local
Intentional
Decentralized
(Horizontal)
Dehumanized
Logistics
Replicas
Storage
Non-local
Emergent
Does smart imply centralized?

10. This is all about scale.
If we need a fast response, we could
localise the feedback and become
relatively “smart” again, at a smaller
scale, but over a wider region.
A few large things, or many small
things?

11. Scaling feedback/supply

12. Question:
Is an AWS datacenter a centralized or a
decentralized system?

13. Question:
What makes an IT system “smart”,
and will that scale?

14. Scale/commoditization drives us to make it “dumber”
experiment - customize— productization - commoditisation - utilities

15. “IT systems are reaching the kind of size and
scope that now force us to understanding
scaling … in the physics sense.”

17. Semantics throughout space

19. Warehouse analogy

20. Cloud computing

21. Some spaces are designed exclusively
for one purpose

22. Humans are the edge of the system

23. Humans should not be in the belly of the beast …?
Autonomous infrastructure

24. Pushing at the edge …

25. Smart cities

26. Cities / herds evolved for defence,
with the side-effect of innovation

27. Studies from Sante Fe show non-queue
spacetime scaling

28. IoT - services and analytics
to adapt in real time

29. But, a smart city is more than IoT….

30. Filling space
efficiently, not
tidily.

31. It all boils down to agents, interactions, and scales
We might have to rethink scaling

32. @markburgess_osl
DESIGNING SYSTEMS FOR COOPERATION
MARK BURGESS
THINKING IN
PROMISES
“This is where a great quote goes. Excellent book!” –Joe Blough
markburgess.org/blog_smart.html

33. Scaling and spacetime (2016)

34. Complexity (strong coupling) means cost

35. Cable-Free Clos non-blocking fabrics (III) ?
Weak coupling

36. Addresses that reflect location

37. 3d printed datacenter