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Map & Territory: A story of visibility
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Pierre-Yves Ritschard
April 19, 2013
Technology
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Map & Territory: A story of visibility
Pierre-Yves Ritschard
April 19, 2013
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Transcript
Map & Territory a story of visibility
Pierre-Yves @pyr https://github.com/pyr
https://exoscale.ch
Visibility
How do we work ?
None
How do we improve?
Avoid Shortcuts!
None
We want lower defect rates
We want to make informed decisions
Design Build Live
Visibility
Extracting meaningful state data from heterogeneous event sources, over time
Meaningful (relates to business value)
State Data (structured payload)
Heterogeneous (everyone is involved)
Over time (tracking)
How does it help my system's lifecycle ?
Map =/= Territory
Break out of our mental model
"I'll push this minor change, it cannot do any harm"
None
"I'll just add this static route"
None
Better lifecycle Informed decisions Better maps
Systems are (increasingly) complex
Web Infrastructure circa 00 (2 servers)
Visibility Circa '00
Web Infrastructure circa '12 (27 nodes)
None
Visibility Circa '12
Q: how is business doing today ? A:
Q: how is business doing today ? A: based on
these key metrics we're looking good
Figure out those key metrics
We need appropriate tooling
events across: system, components, software
The event stream approach
Plenty of small producers Few big consumers
Production: Anything that happens or moves (logs too!): Normalize &
Stream
Consumption: Aggregate Correlate Decide
Aggregation compute compound metrics (ratios, sums)
Correlation
Decision track, alert, ignore, scale
Implementing on premise, saas or in between ?
SaaS loggly, papertrail, librato, datadog, ...
On Premise collectd, logstash, graphite, statsd, riemann
The path to visibility: Find key metrics Find the right
tools Rely on an event stream Involve everyone Challenge your mental model Hopefully, improve quality and lower defect rates in the process!
Questions ?