MySQL & Load Stats
Observe what type of information is gathered in the MySQL & Load Stats section and the way you are able to reap the benefits of it.
The CPU load is dependent upon the time period a hosting server spends executing a script every time a visitor opens a page on a specific script-driven site. Static HTML sites use barely any CPU time, but it's not the situation with the significantly more sophisticated and functional scripts, that use a database and display dynamic content. The more individuals open this sort of a website, the more load shall be produced on the web server and if the database is large, the MySQL server will be loaded also. An example of what may cause high load is a web-based store with a huge number of products. If it's popular, many people will be browsing it at the same time and if they look for items, the entire database which contains all of the products shall also be continuously accessed by the script, which will result in high load. In this light, having CPU and MySQL load stats will give you an idea of how the website is doing, if it has to be optimized or if you simply need a more effective web hosting solution - if the Internet site is very popular and the established setup cannot handle the load.
MySQL & Load Stats in Semi-dedicated Servers
Our system creates thorough stats about the two different types of load, so if you get a semi-dedicated server for your sites, you can access the data with just a few clicks inside your Hepsia hosting CP. Each kind of data is listed inside its own section. The CPU Load section shall tell you what processes created the load and how much time it took for the web server to execute all of the requests. Though statistics are produced every six hours, you can see daily and per month statistics too. In the MySQL Load section you will find a list of all the databases produced inside your semi-dedicated account manually and automatically, what number of queries were sent to each one of them, the total day-to-day queries for the account in general, plus the average hourly rate. This data shall help you figure out how well your websites perform and if each of them requires optimization of some sort.