In this study, built in performance counters are used to identify limits of a prototype real time map web application running in the Google Chrome browser on a desktop PC. The context in which the application is intended for use is one of distributed simulation. This provides the variable conditions of update frequency and number of (simulated) entities to be displayed on the map. The performance counters log the utilization of memory and CPU on the client machine, and in addition to these a metric called delay time is calculated to see how the time used to handle a certain amount of entities relates to the given time interval, determined by the update frequency. Two specific use cases in the simulation context are defined and tested, as well as baselines of browser idle use, local rendering, and excluded rendering. Furthermore, ranges of the variable conditions are tested with the other condition fixed, to see how different combinations of frequency and entity number affect resource use and delay times. Findings include that the high frequency use case results in a continuously high delay time and is not feasible for use without further optimization. Additionally, the application is unlikely to perform better given less communication since rendering and scripting impact resource use the most. The use of memory is not significantly increased from idle use at any time and CPU use is limited by the single threaded parsing of JavaScript resulting in a highest percentage of non-idle time during a test of 31%. Lastly, the growth of delay time occur later in terms of entity updates per second when the number of entities is relatively low and the update frequency is high, as opposed to a lower frequency and a higher number of entities.