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

Thanks!Dan Kuebrich

dan@appneta.com@dankosaur