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Theo Schlossnagle - @postwait Founder @Circonus
Monitoring the #DevOps Way (and the future of monitoring)
DevOps
So many definitions of DevOps…
Applying software engineering practices to improve operations and infrastructure management.
Spreading operational acumen through the organization (specifically into product engineering)
https://www.flickr.com/photos/jamieanne/5744219523
The days of “is it up” are long over.
Monitoring has changed Significant challenges in operability and accessibility
The days of “is it up” are long over.
Monitoring has changed Significant challenges in operability and accessibility
The days of “is it up” are long over.
Monitoring has changed Significant challenges in operability and accessibility
The days of “is it up” are long over.
Monitoring has changed Significant challenges in operability and accessibility
The days of “is it up” are long over.
Monitoring has changed Significant challenges in operability and accessibility
Managing risk and exploiting opportunity
Operability
Monitoring (data collection and analysis) is hard.
Now add “always available” and “always immediate.”
Many companies squander opportunity in engineering by building monitoring solutions instead of more direct market value.
ALWAYS ON AND ALWAYS WORKING… EVEN WHEN YOU’RE INFRASTRUCTURE ISN’T
https://www.flickr.com/photos/coastguardnews/2291992191
https://www.flickr.com/photos/ussnewyork/5403986347
Embracing today’s engineering organizations
Accessibility
If it isn’t accessible via an API, it isn’t accessible.
Configuration, analysis, alerting, visualization… it all must be accessible or it simply won’t integrate.
This is how engineers work.
The dynamic nature of the the cloud forces your hand.
used with permission from Stacey Mason @stcymsn
Looking for information in the data
Millions of streamsIs simply too much to look at
We now must leveraging mathematics(e.g. statistics and machine learning) to surface interesting information
https://www.flickr.com/photos/vickyb/493019855
Solving this at scale
Once you solve the scale problem, what are the opportunities?
1000 measurements / second?How about 1 million? or 1 billion?
Imagine the insight.
Now imagine the data science problems.
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