So, I'm developing a new application that's in the capacity planning phase. The application is designed to scale linearly and scale is very easy to do just by adding another database server. But, at what point do you upgrade? What point in the applications life do you add new servers to serve the expectation of the users?
To figure out these questions, thresholds need to be defined. When these thresholds are exceeded then upgrades need to occur.
Here is a process (my process) of questions to ask to define thresholds: First I start out with generic questions listed below.
What is the expected amount of users who are going to use the product initially?
What is the expected usage pattern? For instance if they are adding data what is the add rate? If they are reading data what is the read rate?
Given that the first two questions are answered now ask when is it going to break. If you can answer this your golden. This is the hard part. How do you know when it's going to break and under what conditions without putting the service live. The best thing to do IMHO is to benchmark the system under typical usage patterns then double that.
In my case, I know for sure that it will work on launch and for months there after but I don't know when it's going to fail. Since getting hardware here is an involved process I need to know ahead of time when things will fail-it makes us all honest.
To get an idea on when it will break, I'm gauge'ing the passive additions that are in production now to get a baseline on how much data grows from day to day. In my case the dataset grows 10GB per day spread across 5 servers, thus 2GB per day from a single point of server view. Now I have a base line. In how many days will the application fail to perform under thresholds previously set? The thresholds set, are defined as-all data retrieval and addition must not take longer then 300ms for all components involved. So, when the passive additions on average take 20% of 300ms then I know the application is about to hit my own personal saturation point, thus I must ask for new equipment.
But, the problem is not as clear cut, really I need to answer the question does InnoDB performance degrade at O(nlogn) when adding strings to it? If not what is the degradation of string addition and retrieval when the dataset is HUGE like @40-200+ GB
(Where did I get log(n) from? Well, indexes in INNODB are B-Tree's-I/O performance should degrade at nlogn as data grows.)
Some good reading mySQL Insert-Speed
This is a little old but it's a good approximation.
Things of note:
I must watch that the merged records count stays within a few hundred thousand of the inserted record count in the insert buffer and adaptive hash index part of SHOW ENGINE INNODB STATUS IF it doesn't then INNODB is hitting it's own limitation.