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Sam Guckenheimer - Moving to One Engineering System


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This is the story of transforming Microsoft to One Engineering System with a globally distributed 24x7x365 service on the public cloud. We’ll show you round the system that handles the load of some of the most demanding engineering teams in the world and share some stories about how they got there.

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Sam Guckenheimer - Moving to One Engineering System

  1. 1. About Me Sam Guckenheimer Product Owner, Visual Studio Cloud Services 14 years Microsoft 30 years software industry @SamGuckenheimer
  2. 2. Microsoft Org Chart ~2011 Unintended consequence: No reuse would go unpunished.
  3. 3. There cannot be a more important thing for an engineer, for a product team, than to work on the systems that drive our productivity. So I would, any day of the week, trade off features for our own productivity. I want our best engineers to work on our engineering systems, so that we can later on come back and build all of the new concepts we want. 4 Purpose of One Engineering System
  4. 4. An engineering north star… …the source across the company is available to anyone …any dev can offer improvements to anything in the company …the IP the company has built up over the years is made of re-usable components …anybody can find and potentially re-use components from anywhere else …devs are rewarded for creating popular components …there is zero lag from when a dev makes a change & when the rest of the company sees it … build and test time is directly proportional to the change made …devs can move to another team and already know how to work
  5. 5. Demo
  6. 6. 0 50 100 150 200 250 300 VSTS 3GB Linux 0.6GB Windows 270GB 57k files 1.7GB initial pack file 5.5MB index file 110k files 8GB initial pack file 16MB index file 500 users 3.5M files 86GB initial pack file 400MB index file 4k users Git repo sizes
  7. 7. Git experience on Windows repo (with GVFS on TFS) Git GVFS Improve ment clone 12hrs 2.5mins 288x checkout 3hrs 30secs 360x status 8mins 2.3sec 209x commit 30mins 6.9secs 261x
  8. 8. Live Site Culture and Engineering Live Site Health Time to Detect Time to Communicate Time To Mitigate Customer Impact Incident prevention items Aging live site problems Customer support metrics SLA per customer account (SLA, MPI, top drivers) Engineering Bug cap per engineer Aging bugs in important categories Pass rate & coverage by test level Velocity Time to build Time to self test Time to deploy Time to learn (Telemetry pipe) Usage Acquisition Engagement Dedication Churn Feature usage
  9. 9. Common Telemetry Pipeline Combines high volume ingestion fast queries over very large data sets text search structured and unstructured data
  10. 10. We Create Transparency
  11. 11. Is It Working?
  12. 12. Self-forming teams
  13. 13. Engineering System – 1ES Day
  14. 14. Is 1ES Working? 4x active user growth in 2 years to 75,000