![© J. Allspaw and P. Hammond 2009 © J. Allspaw and P. Hammond 2009](/var/ezflow_site/storage/images/archive/2014/23/building-better-software-on-schedule-with-devops/lin_illu_sept-1.png/104842-1-eng-US/lin_illu_sept-1.png_medium.png)
© J. Allspaw and P. Hammond 2009
Building better software on schedule with DevOps
Collaboration Station
Buzzword alert! The term DevOps, which includes components of software development and operations, is being bandied about wherever you look: You'll find abundant references to DevOps in blogs, books, articles, training courses, and software.
This new style of cooperation between developers and admins was released on an unsuspecting audience by John Allspaw and Paul Hammond (among others) at California's Velocity Conference 2009. Their slides [1] describe how techies from the photo community Flickr achieve 10 or more deploys per day.
The approach described by Allspaw and Hammond is now part of everyday business in other Internet companies. "My impression is that you can no longer survive economically as a company with the old work models," said Schlomo Schapiro, System Architect with Immobilienscout24, in an interview with the author.
IT professionals describe themselves as DevOps specialists with increasing frequency, and some companies even have DevOps departments. The "2014 State of DevOps Report" [2] indicates that 31 percent of more than 9,000 respondents see their position as a DevOps Engineer. According to the survey, 16 percent work in a DevOps department.
The report, with 46 percent of respondents from the United States and 25 percent from Europe, was commissioned by Puppet Labs, IT Revolution Press, and ThoughtWorks. Keep in mind that these companies offer software, publications, and services related to DevOps, which means the way this work method is described is likely to be more positive.
My analysis of these self-assessments showed the following: Departments with above average performance use DevOps techniques. The deployment frequency, the time required for changes, and the mean time to recover are used as the metrics for determining the IT department's performance in the case study. This
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