Scam2011 syer

Identifying Performance Deviations in Thread Pools

Mark D. Syer, Bram Adams and Ahmed E. Hassanmdsyer@cs.queensu.ca

Software Analysis and Intelligence LabQueen’s University, Canada

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How to detectperformancedeviations?

Needle in a haystack!

Complexarchitectures

Ultra-Large-Scale Software Systems

Potential solutions must account for…

• Huge amounts of data• Limited system knowledge

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Potential solutions should…

• Limit manual review/analysis

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How to detectperformancedeviations?

Hundreds of machinesThousands of threads

Needle in a haystack!

Complexarchitectures

Simulate user actions

Monitor thread behaviour by collecting resource usage metrics

Simulate user actions

Monitor thread behaviour by collecting resource usage metrics

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Group threads depending on their machine ID

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Group similar behaviour

Similar

Dissimilar

Find dissimilar behaviour

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AbstractionClustering

Ranking

Group threads

Find dissimilarbehaviour

Group similarbehaviour

How to group threads?

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Abstraction

Ranking

Clustering

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Abstraction Clustering

Ranking

Machines

Threads

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does it work?

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6:00 8:004:00

Abstracting bySpace

Vs.Time

RQ1: What time period has the most deviations?

RQ2: What threads have deviations?

Deviations Injected into Thread Data

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Memory Leak Injected

Deviations Injected into Thread Data

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CPU Spike Injected

Most Deviations are Identified

Precision Recall

Top Level 100% 100%

Thread Level 100% 76.61%

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1-recall 2-recall 3-recall

86.67% 96.67% 100%

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