Adding Caching to Python Flask-Blogging Engine

This post will discuss caching support to Flask-Blogging

I deployed my blog (using Flask-Blogging extension) to a site I am building. I am currently hosting the test version on the free instance of Openshift. So these are not very powerful servers, and I wasn't expecting any great performance. Here is what I saw while using Version 0.3.2 of Flask-Blogging:

$> ab -kc 30 -t 10 https://ucarpool.org/blog/

Benchmarking ucarpool.org (be patient)
Finished 267 requests

Document Path:          /blog/
Document Length:        4882 bytes

Concurrency Level:      30
Time taken for tests:   10.061 seconds
Complete requests:      267
Failed requests:        0
Keep-Alive requests:    267
Total transferred:      1428480 bytes
HTML transferred:       1303494 bytes
Requests per second:    26.54 [#/sec] (mean)
Time per request:       1130.451 [ms] (mean)
Time per request:       37.682 [ms] (mean, across all concurrent requests)
Transfer rate:          138.65 [Kbytes/sec] received

Connection Times (ms)
              min  mean[+/-sd] median   max
Connect:        0   34  95.5      0     353
Processing:   272 1040 374.4    936    2166
Waiting:      267 1037 374.5    933    2163
Total:        546 1074 349.5    968    2166

Percentage of the requests served within a certain time (ms)
  50%    964
  66%   1039
  75%   1133
  80%   1248
  90%   1812
  95%   1910
  98%   2030
  99%   2070
 100%   2166 (longest request)

Thats a measely 26 requests/sec!

One of the features I have wanted to add to this extension is the ability to cache the pages. Blogs are typically heavy on reads, and light on writes. This makes an excellent case for caching.

In order to enable caching support, I am using Flask-Cache the caching extension for Flask. The version 0.4.0 of Flask-Blogging is released with caching support built in. Flask-Cache makes the caching backend configurable. It has support for various backends such as filesystem, redis, and memcache.

Here is resulting performance after using a filesystem based cache:

$> ab -kc 30 -t 10 https://ucarpool.org/blog/
This is ApacheBench, Version 2.3 <$Revision: 1528965 $>
Copyright 1996 Adam Twiss, Zeus Technology Ltd, http://www.zeustech.net/
Licensed to The Apache Software Foundation, http://www.apache.org/

Benchmarking ucarpool.org (be patient)
Finished 1815 requests

Document Path:          /blog/
Document Length:        4882 bytes

Concurrency Level:      30
Time taken for tests:   10.004 seconds
Complete requests:      1815
Failed requests:        0
Keep-Alive requests:    1815
Total transferred:      9710280 bytes
HTML transferred:       8860830 bytes
Requests per second:    181.43 [#/sec] (mean)
Time per request:       165.351 [ms] (mean)
Time per request:       5.512 [ms] (mean, across all concurrent requests)
Transfer rate:          947.92 [Kbytes/sec] received

Connection Times (ms)
              min  mean[+/-sd] median   max
Connect:        0    6  44.3      0     400
Processing:    80  158  46.1    150     411
Waiting:       79  156  46.1    147     410
Total:         83  164  58.9    152     518

Percentage of the requests served within a certain time (ms)
  50%    152
  66%    173
  75%    183
  80%    190
  90%    217
  95%    277
  98%    357
  99%    420
 100%    518 (longest request)

Now we are able to serve 180 requests/second. A good 7X performance gain for using a filesystem cache. Using in memory like Redis, or SSD filesystem should be even better.

   python   flask   programming  

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