Visualizing reqstat

The reqstat tool was written to provide a vmstat like output of total web requests happening in real time. This really lightweight monitoring leverages memcached and has a trivial impact for immediate benefit.

$ ./reqstat 5 5
  epoch,time,rps,avg_req,last,%comp,---,threshold,exceed,last_excess
  1307723122,162522,25,125.92,75.25,48,---,150,9,175.55
  1307723127,162527,24,107.33,6.97,48,---,150,6,188.45
  1307723132,162532,25,118.39,97.63,50,---,150,8,151.37
  1307723137,162537,22,120.51,88.62,42,---,150,5,168.56
  1307723142,162542,26,106.62,6.12,51,---,150,6,167.81

While this is useful, I can see 22-26 requests per second, averaging 106-120 ms, visualizing this gives more information immediately available like:

It is easy to look at an average and lose site of the larger picture. What are the outliers, how many are there? Visualizing of larger samples (a later example which will show 10,000 rps across multiple servers) shows that the granularity is also critical.

This graphic is produced with Flot . A very simply javascript library. You can also use gnuplot , an example script is included in github .

This output is the result of benchmarking, this being generated from reqstat output with a script in my monitor git repository.

Tagged with: Data Visualization

Related Posts

How long does it take the ReadySet cache to warm up?

During my setup of benchmarking I run a quick test-sysbench script to ensure my configuration is right before running an hour+ duration test. When pointing to a Readyset cache where I have cached the 5 queries used in the sysbench test, but I have not run any execution of the SQL, throughput went up 10x in 5 seconds.

Read more

Monitoring Latency with Throughput

Higher throughput does not imply improved performance. This is a common problem when the need for an application to support more users, you provide higher concurrency and that appears to show the capability to support higher throughput.

Read more

Using Readyset Caching with AWS RDS MySQL

Readyset is a next-generation database caching solution that offers a drop-in; no application code changes; approach to improve database performance. If you are using a legacy application where it is difficult to modify SQL statements, or the database is overloaded due to poorly-designed SQL access patterns, implementing a cache is a common design strategy for addressing database reliability and scalability issues.

Read more