Through the performance optimization of elastic computing, network and database IaaS/PaaS cloud resources, users can obtain the optimization of cloud infrastructure resources in the cloud environment. In the actual architecture, deployment, and O&M process, users usually take the performance optimization of applications running on the cloud environment as the measurement goal. Architecture optimization at the application architecture level needs to consider multiple aspects based on the actual situation, such as the following aspects:
The deployment methods of the application architecture: standalone, distributed, and microservices model are quite different. The standalone architecture depends on the software and hardware performance of the standalone and the utilization rate of standalone resources by the application. In addition to the performance bottleneck of the standalone, the distributed architecture also depends on the system splitting efficiency and scalability. In microservices model, the service splitting efficiency and service calling efficiency are other important factors.
Programming language implementation: Different programming language implementations affect the standalone baseline to some extent. Compiled languages such as C/C++ run time do not need to be retranslated and run directly using the compiled machine code without relying on the interpreter, thus the program execution efficiency is relatively high. Python, Ruby and other interpreted language programs are translated into machine code only run time, and each execution depends on the translation of the interpreter. While increasing flexibility, the program execution efficiency is lower than that of compiled languages.