In a scalable environment, you can't plan on 100% utilization. It takes time to provision a new server. A server that is at 100% utilization can't process additional incoming requests in a timely manner, which results in dropped or erroneous requests from the users' perspective. So the server in question must send a trigger well before it reaches 100% utilization so that no requests are dropped. Earlier in the chapter, I suggested a 60-80% target utilization before scaling. The exact number will highly depend on your specific choice software and hardware stack. Given your custom utilization target, we can calculate the number of users your infrastructure is expected to serve on average per instance. Using this information, you can calculate a more accurate cost per user, which should allow the right-sizing of your IT budget, given your specific needs. It is equally as bad to underspend as it is to overspend. You may be foregoing growth, security, data, reliability, and resilience than it may be acceptable.

In the next section, we will walk through the calculation of an optimal target server utilization metric so that you can calculate a more accurate per user cost; then, we will explore scaling that can occur during preplanned time frames and software deployments.