Shivnath Babu

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Motivation
• Systems are becoming hard to manage
• Increasing size (both software and hardware)
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Clients
Motivation
WAN
Web server
Application servers
Database servers
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Clients
WAN
Web server
Application servers
Motivation
WAN
Database servers
WAN
WAN
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Motivation
• Systems are becoming hard to manage
• Increasing size (both software and hardware)
• Increasing heterogeneity (e.g., Grid systems)
• 24 x 7 operation
• 5 nines availability (system is down at most 5 minutes and 15 seconds per year)
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Motivation
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Downtime Costs (per Hour)
• Brokerage operations $6,450,000
• Credit card authorization
• Ebay (1 outage 22 hours)
• Amazon.com
• Package shipping services
$2,600,000
$225,000
$180,000
$150,000
• Home shopping channel
• Catalog sales center
• Airline reservation center
• Cellular service activation
$113,000
$90,000
$89,000
$41,000
• On-line network fees $25,000
• ATM service fees $14,000
Sources: InternetWeek 4/3/2000 + Fibre Channel: A Comprehensive Introduction, R. Kembel 2000, p.8.
”...based on a survey done by Contingency Planning Research."
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Motivation
• System administration cost is increasing
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Cost of Storage Administration
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Motivation
• System administration cost is increasing
– Recently, $1 storage  $9 administration cost
[Fujitsu]
– Up to 75% of overall database ownership cost is for administration [Aberdeen]
– Up to 80% of Information Technology (IT) budgets spent on maintenance [McKinsey]
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Motivation
• System administration time & effort is increasing
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Time Distribution for Database Mgmt.
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Motivation
• System administration time & effort is increasing
– >40% of computer system outages caused by operator/administrator error
Causes of system crashes Other
18%
System management
53%
Software failure
18%
10%
Hardware failure
Time (1985-1993)
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Global Storage Service Site Failures
Unknown
9%
28%
SW Human
Network
22%
41%
Hardware 0%
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Motivation
• System administration time & effort is increasing
– >40% of computer system outages caused by operator error
• System is too difficult to understand
• Decisions need to be made quickly, under pressure
• Not enough well-trained operators
• Changes are frequent
– E.g., workload, hardware, people, data
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The Real Problem
… The obstacle is complexity … Dealing with it is the single most important challenge facing the IT industry
Paul Horn, Director of Research, IBM
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The Solution
• Let the system deal with the complexity of management
• Computer-science-wide push towards
Self-Managing Systems
• IBM calls this new field Autonomic Computing
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Autonomic Computing (IBM)
Computer systems that can regulate themselves much in the same way as our autonomic nervous system regulates and protects our bodies
Paul Horn, Director of Research, IBM
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Autonomic Nervous System
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Autonomic Nervous System
• Tells you heart how fast to beat, checks your blood’s sugar and oxygen levels, and controls your pupils so the right amount of light reaches your eyes as you read these words, monitors your temperature and adjusts your blood flow and skin functions to keep it at 98.6ºF
• Is autonomic -you can make a mad dash for the train without having to calculate how much faster to breathe and pump your heart, or if you’ll need that little dose of adrenaline to make it through the doors before they close
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Autonomic Computing (IBM)
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What will we do in this class?
• Read research papers
• Listen to guest lectures
• Goal of the class: Give structure to this field, e.g.,
• Concretely defining problems that arise in this setting
• Identifying algorithms and techniques useful in this domain
• Proposing guidelines for designers of future systems and software
• Semester-long project
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Outline
• Part 1: Motivating Factors, Problems, and
Applications
– From Internet services, database management, computational grids, weather analysis and prediction, oil reservoir optimization, and others
• Part 2: Algorithms and Techniques
– Control theory, machine learning, performance modeling, stochastic optimization, massive data management, data integration, building blocks in systems, and others
• Part 3: Putting everything together, implications, and future work
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Evaluation
• Class participation 25%
• Project 75%
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Resources
• Google keywords
– Autonomic computing
– Self-managing systems
• IBM autonomic computing web page
• IBM Journal special issue on autonomic computing
• Berkeley ROC project
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In the next class
• Read an overview paper on self-managing systems
• Summary of work in this area
• Sample projects
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