1. CompSci 296.2 Self-Managing Systems
Shivnath Babu
In this talk my aims are:
- to give an overview of the work that we have been doing at Stanford on adaptive processing in the stream system and what we are doing now
[past and current work]
- facilitate some interesting discussion. Hope the title is provoking enough
I will not be comparing our system with eddies explicitly, although I am doing some work in that respect with DeWitt and one of his students.

2. Today TA hours Scribing Paper discussion
Summary of current work in self-managing systems
Ideas for projects
Will be continued on Thursday (but there is a different paper for Thursday)

3. Paper Summary Vision and overview paper Lists motivating factors
Describes autonomic computing
Evolving towards autonomic behavior
Research issues

4. Motivating Factors for Autonomic Computing
Increasing size and complexity
Increasing administration cost
Increasing time for administration (clarification)
Operator errors  outages
Hard to deal with change

5. Time Distribution for Database Mgmt.

6. Ongoing Database Administration
Ongoing database administration tasks, such as performance tuning, space management, system resource tuning and backup & recovery, accounts for the biggest chunk of a database administrator’s time. According to a survey conducted by Oracle, DBAs typically spend about 55% of their time performing these activities.

7. Irving Wladawsky-Berger
Autonomic Computing
“… So that instead of the technology behaving in its usual pedantic way and requiring a human being to do everything for it, it starts behaving more like the `intelligent' computer we all expect it to be, and starts taking care of its own needs. If it doesn't feel well, it does something. If someone is attacking it, the system recognizes it and deals with the attack. If it needs more computing power, it just goes and gets it, and it doesn't keep looking for human beings to step in.”
Irving Wladawsky-Berger

8. Fundamentals of Autonomic Computing
Self-configuring
Dynamic addition, change
Self-healing
Recovering from “failure”
Self-optimizing
(Query) optimizers, index “advisor”, dealing with change
Self-protecting
Intruders, operator errors

9. Evolution towards Autonomic Comp.
Basic  Managed  Predictive  Adaptive  Autonomic
Standards

10. Strong Points
Presentation

11. Weak Points
Separating “mechanisms” from “policies” – separating goals from steps
Comparisons with competing projects
In-depth discussion of a system (e.g., databases, web servers)
No discussion of whether autonomic computing is the right solution to the problem

12. Discussion Goals Vs. steps
Self-* (consider different systems/settings)
Relative importance, mechanisms, algorithms
Evolution Vs. revolution
Facts, e.g., causes of outages
Placing current systems on the autonomic spectrum
Complexity of autonomic computing itself