up arrow Concurrency and the Single Siege

We’re frequently asked about concurrency. When a siege is finished, one of its characteristics is “Concurrency” which is described with a decimal number. This stat is known to make eyebrows furl. People want to know, “What the hell does that mean?”

In computer science, concurrency is a trait of systems that handle two or more simultaneous processes. Those processes may be executed by multiple cores, processors or threads. From siege’s perspective, they may even be handled by separate nodes in a server cluster.

When the run is over, we try to infer how many processes, on average, were executed simultaneously the web server. The calculation is simple: total transactions divided by elapsed time. If we did 100 transactions in 10 seconds, then our concurrency was 10.00.

Bigger is not always better

Generally, web servers are prized for their ability to handle simultaneous connections. Maybe your benchmark run was 100 transactions in 10 seconds. Then you tuned your server and your final run was 100 transactions in five seconds. That is good. Concurrency rose as the elapsed time fell.

But sometimes high concurrency is a trait of a poorly functioning website. The longer it takes to process a transaction, the more likely they are to queue.  When the queue swells, concurrency rises. The reasons for this rise can vary. An obvious cause is load.  If a server has more connections than thread handlers, requests are going to queue. Another is competence – poorly written apps can take longer to complete then well-written ones.

We can illustrate this point with an obvious example. I ran siege against a two-node clustered website. My concurrency was 6.97. Then I took a node away and ran the same run against the same page. My concurrency rose to 18.33. At the same time, my elapsed time was extended 65%.

Sweeping conclusions

Concurrency must be evaluated in context. If it rises while the elapsed time falls, then that’s a Good Thing™. But if rises while the elapsed time increases, then Not So Much™. When you reach the point where concurrency rises and elapsed time is extended, then it might be time to consider more capacity.