Bottleneck Analysis - GOTO 2012

Adrian Cockcroft

October 03, 2024

4

Bottleneck Analysis - GOTO 2012

Adrian Cockcroft

October 03, 2024

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Transcript

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Bottle delivery data Interval Response Time Throughput 10 3.1 22
20 1.2 41 30 7.9 32 … … …
Grab some data (using R) beer <- read.csv(url("http://staash.com/beer_operation s.csv")) response
<- beer[,2] plot(response, type="S",ylab=”response”)
Bottle delivery response over time
Analysis > summary(response) Min. 1st Qu. Median Mean 3rd Qu.
Max. 1.909 2.550 2.820 3.086 3.214 67.680 > quantile(response,c(0.95,0.99)) 95% 99% 4.149556 6.922115 > sd(response) 1.941328 > mean(response) + 2 * sd(response) 6.968416
chp(throughput,response,q=1.0) (See http://perfcap.blogspot.com/search?q=chp)
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Scalability plots generated using appdynamics.com
Well behaved Lock Contention Oscillating, thread shortage Looping autoscaled Bottlenecks
http://perfcap.blogspot.com/search?q=chp @adrianco