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BEYOND AVERAGESDan Kuebrich / appneta.com
A few of my favorite abstractions
•Abstraction lets us trade information for actionability
•Min, max, average, quantiles, stdev
•That’s a great trade!• ... right?
Averages: average at best
Averages: average at best
Averages: average at best
Averages: average at best
Percentiles: 1 of 100 slices
95%
Percentiles: 2 of 100 slices
95%
10%
Percentiles: 2 of 100 slices
95%
10%
Percentiles: 2 of 100 slices
95%
10%
Percentiles: 2 of 100 slices
95%
10%
Computers are hard
• Rarely do we have a single normal distribution underlying the data
• Different users, different requests, different resources, different instances, different times
Is there a place between Averageland and “A Beautiful Mind”?
http://now-here-this.timeout.com/2012/10/07/crazy-walls-of-clues-from-tv-film-reviewed-by-carrie-from-homeland/
HistogramsFr
eque
ncy
(eg.
# o
f cal
ls)
Value(eg. latency)
Populations revisited
95%
10%
HistogramsFr
eque
ncy
(eg.
# o
f cal
ls)
Value(eg. latency)
Populations re-revisited
95%
10%?
3d Histograms?Fr
eque
ncy
(eg.
# o
f cal
ls)
Value(eg. latency)
3d Histograms?Fr
eque
ncy
(eg.
# o
f cal
ls)
Value(eg. latency)
Time
HeatmapsFr
eque
ncy
(eg.
# o
f cal
ls)
Value(eg. latency)
HeatmapsFr
eque
ncy
(eg.
# o
f cal
ls)
Value(eg. latency)
HeatmapsFr
eque
ncy
(eg.
# o
f cal
ls)
Value(eg. latency)
HeatmapsVa
lue
(eg.
late
ncy)
Time
OK, but what about the real world?
http://www.justincarmony.com/blog/2012/06/05/customizing-graphite-charts-for-clearer-results/
Mystery #1
Mystery #1
Mystery #1
Mystery #1
Mystery #1
Mystery #2
Mystery #2
bottom 98%
Mystery #2
all of it
Mystery #3
Mystery #3: UNSOLVED
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