Scaling Python on the Web

First session of the day was on Scaling Python on the Web; rough notes which I may clean up later:

• How fast is fast enough?
  • Don’t prematurely optimize
  • Know where the bottlenecks are, and optimize those specifically?
• Orders of magnitude: static (httpd), dynamic (python), db-queried
• Even 40 req/s in 3.4m pages/day
• Hundreds to low thousands of dynamic page views is usually good enough
• Scaling isn’t about the language, it’s about:
  • DRY: cache!
  • share nothing
• built a sample photo-app, FlickrKillr, for demonstration purposes
  • preloaded with 100k’s users, 10-20 photos each
• first iteration: CGI
  • roughly 23 requests/second
  • problems:
    • loading Python interpreter for each request
    • all resources initialized for each request (inc. db connection)

    <li>
      possible remedies:<ul>
        <li>
          run a Python web server (long-running process)
        </li>
        <li>
          make one db connection per thread instead of request
        </li>
      </ul>
    </li>
  
    <li>
      other remedies:<ul>
        <li>
          fastcgi
        </li>
        <li>
          snakelets, twisted.web, RhubarbTart
        </li>
        <li>
          mod_python
        </li>
      </ul>
    </li>
  </ul>
  

  • second iteration: python app server (CherryPy used for this demo)
    • roughly 139 requests per second
    • problems
      • global interpreter lock — can only utilize one core on a dual core machine
      • sessions in the database — prefer an in-memory session store

      <li>
        remedies:<ul>
          <li>
            run multiple instances of CherryPy (overcode GIL)
          </li>
          <li>
            but then we need to balance with something like nginx
          </li>
        </ul>
      </li>
    
      <li>
        other options<ul>
          <li>
            cherrypy in mod_python
          </li>
        </ul>
      </li>
    </ul>
    

    • version 3: load balancing with nginx
      • 217 requests/sec
      • outstanding problems
        • static files read from disk every time
        • and they’re being read/written from python

        <li>
          solutions:<ul>
            <li>
              memcached
            </li>
            <li>
              combine with memcached w/ nginx
            </li>
          </ul>
        </li>
      </ul>
      

      • version 4: caching
        • 616 req/sec (benchmarking w/ homegrown tool)
        • 1750 req/sec (benchmarking w/ ab)
      • other notes:
        • don’t forget to index
        • without an index, the fourth iteration falls down to 28 requests/sec

      http://www.polimetrix.com/pycon/demo.tar.gz