SPT Process
Fourier Lab uses the following System Performance Tuning Process:
- Performance Analysis
- Performance Measurement
- Performance Bottleneck Review
- Performance Tuning Implementation
- Post Tuning Review

System Performance Tuning refers to the improvement of system performance through various methods. There is a need to do performance tuning when a system starts to slow down due to increase load, or when the system is under performing but upgrading or changing the system is not possible at the meantime. System Performance Tuning is usually performed when there is a performance problem, which can be real or anticipated. Most systems usually handle increased load with some degree of decreasing performance. A system's ability to accept higher load is called scalability, and modifying a system to handle a higher load is synonymous to performance tuning.
System Performance Tuning service is conducted following these steps:
One way of improving performance is by rewriting and optimising specific portions of a program so that it will run faster. The term code optimisation refers to the process of improving a particular algorithm for performing a task (code tuning). Code optimisation can also be achieved by utilizing a better algorithm than the existing code. Some examples of code optimization include improving the code so that work is done once before a loop rather than inside a loop or replacing a call to a simple selection sort with a call to the more complicated algorithm for a quicksort.
Caching is one of the key methods of removing performance bottlenecks. One of the cause of performance bottleneck is when the volume of data retrieval is higher than the capability of the system or network specification. Caching improves performance by retaining frequently used information in high speed memory, which reduces access time and thus improves performance. Caching is an effective manner of improving performance in situations where the principle of locality of reference the methods used to determine which data is stored in progressively faster storage are collectively called caching strategies.
A system can consist of independent components, each able to service requests. If all the requests are serviced by one of these systems (or a small number) while others remain idle then time is wasted waiting for used system to be available. Arranging so all systems are used equally is referred to as load balancing and can improve over-all performance.
Load balancing is often used to achieve further gains from a distributed system by intelligently selecting which machine to run an operation on based on how busy all potential candidates are, and how well suited each machine is to the type of operation that needs to be performed.