Four Principles of Engineering Scalable, Big Data Software Systems from CMU

 

Four Principles of Engineering Scalable, Big Data Software Systems By Ian Gorton
Senior Member of the Technical Staff
Software Solutions Division

  • First Principle: System Costs Must Grow More Slowly Than System Capacity
  • Second Principle: The More Complex a Solution, the Less Likely it Will Scale
  • Third Principle: Avoid Managing Conversational State Outside the Data Tier
  • Fourth Principle: You Can’t Manage What You Don’t Monitor

http://blog.sei.cmu.edu/post.cfm/four-principles-engineering-big-data-systems-195