There is also an issue of repeatability in the amount of time an
operation takes.

I looked at the logs for a request on a particular file (/history/
histroy.js in this case). Most log entries showed a CPU time of around
90-100ms like the entry below:

02-18 02:56PM 37.219 /history/history.js 200 52ms 92ms-cpu 5kb
See details
203.58.113.131 - - [18/Feb/2009:14:56:37 -0800] "GET /history/
history.js HTTP/1.1" 200 5187 "http://kbdlessons.appspot.com/
studentmainmenu.py?StudentID=TQ.USTQPD1&SessionID=32323&LanguageID=US-
TQ&ProductID=Typequick Professional (US)&CourseID=Basic
Keyboard&LessonID=Lesson2c" -I 02-18 02:56PM 37.236
returnfile=/history/history.js

But occasionally the same request produced a log entry with a cpu time
10 times greater than the usual time:

02-18 02:56PM 07.041 /history/history.js 200 693ms 1081ms-cpu 5kb
See details
203.58.113.131 - - [18/Feb/2009:14:56:07 -0800] "GET /history/
history.js HTTP/1.1" 200 5187 "http://kbdlessons.appspot.com/
graphpage.py?StudentID=TQ.USTQPD1&SessionID=32323&LanguageID=US-
TQ&ProductID=Typequick Professional (US)&CourseID=Basic
Keyboard&LessonID=Lesson2c&LastCourseID=Basic
Keyboard&LastLessonID=Lesson2c" -I 02-18 02:56PM 07.679
returnfile=/history/history.js

I am guessing that the long response time happens when the path
between the machine handling the request and the machine holding the
entity which is being retrieved is somehow clogged up or the machine
holding the entity is overloaded.

Can Google also please explain this phenomemon and the implications
for calculating charges.

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