Transcript CompSci 296.2 Self-Managing Systems Shivnath Babu

CompSci 296.2
Self-Managing Systems
Shivnath Babu
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)
2
Paper Summary
• Vision and overview paper
• Lists motivating factors
• Describes autonomic computing
• Evolving towards autonomic behavior
• Research issues
3
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
4
Time Distribution for Database Mgmt.
5
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.
6
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
7
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
8
Evolution towards Autonomic Comp.
• Basic  Managed  Predictive  Adaptive 
Autonomic
• Standards
9
Strong Points
• Presentation
10
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
11
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
12