Answers: <p>This may sound mean but 6 Sigma does not translate that well to computer systems. The general ideas are valid but the numbers are not. It is intended for the meat world, not a place were we routinely do calculations on gigs or tb's of data a day. Assume you run 1 trillion operations (not much when a regular desktop computer can do ~12 billion a second) at 99.99966% success you are still failing 350k times! </p>
  
  <ul>
  <li>Yes, most of the operations on the code side will actually be made up of multiple CPU operations</li>
  <li>Yes, some of this is caught by hardware via ECC etc</li>
  </ul>
  
  <p>What would stand up would be trying to use S6 against the changes you make to a computer system (code pushes or otherwise). Not the operation of existing code (which needs a much higher level of reliability than what you'd use to evaluate PPM on a shop floor for physically created stuff).</p>
  
Answers: CC BY-SA 4.0
Answers: 2019-02-15T18:21:07.760Z
Answers: 2019-02-15T18:21:07.760Z
Answers: TheFiddlerWins
Body: <p>According to SixSigma quality level, you would succeed in 0.99966% of all iterations of same process repeated many times. </p>
  
  <blockquote>
    <p>A six sigma process is one in which 99.99966% of all opportunities to
    produce some feature of a part are statistically expected to be free
    of defects.</p>
  </blockquote>
  
  <p>So if I think about build or deployments errors, maybe going as far as SixSigma goes is for time being too much, still with continuous delivery there can be quite many iterations. Does anybody take this into consideration to make "some" sigmas?</p>
  
Tags: <quality-cotrol>
Title: Is there any motivation to achieve SixSigma or similar in DevOps?
UserDisplayName: Ta Mu
ThreadText: # Is there any motivation to achieve SixSigma or similar in DevOps?
  
  (Asked by: username_0 on 2019-02-13)
  
  According to SixSigma quality level, you would succeed in 0.99966% of all iterations of same process repeated many times.
  
  > A six sigma process is one in which 99.99966% of all opportunities to
  > produce some feature of a part are statistically expected to be free
  > of defects.
  
  So if I think about build or deployments errors, maybe going as far as SixSigma goes is for time being too much, still with continuous delivery there can be quite many iterations. Does anybody take this into consideration to make "some" sigmas?
  
  **Tags:** quality-cotrol
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2019-02-15. Score: 1
  
  This may sound mean but 6 Sigma does not translate that well to computer systems. The general ideas are valid but the numbers are not. It is intended for the meat world, not a place were we routinely do calculations on gigs or tb's of data a day. Assume you run 1 trillion operations (not much when a regular desktop computer can do ~12 billion a second) at 99.99966% success you are still failing 350k times!
  
  * Yes, most of the operations on the code side will actually be made up of multiple CPU operations
  * Yes, some of this is caught by hardware via ECC etc
  
  What would stand up would be trying to use S6 against the changes you make to a computer system (code pushes or otherwise). Not the operation of existing code (which needs a much higher level of reliability than what you'd use to evaluate PPM on a shop floor for physically created stuff).
  
  
  ---
  
  