The client is a global provider of investment and financial software services and software for the global financial services industry with offices around the world. Its comprehensive platform-level products and deep-level customized services are widely trusted by international banks, funds and insurance industry giants. From the world's largest institutions to local companies, approximately 13,000 financial services organizations use their products and services to manage their investments.
As a technology service company trusted by international financial giants and with the increasing number of mobile Internet users and increasingly mature financial system in recent years, the company faces the following problems:
Because the platform-level service system has to meet the business requirements of banks, funds and insurance industry, the system foundation is so huge that it becomes more and more difficult support traditional code analysis and function testing.
The system backend is equipped with a large number of independent functional modules and specific combinations. During the implementation in a long-term complex business environment, the efficiency of execution is too low to meet the user requirements.
The whole business gets more complex, and with the increase of the whole process, each link may become a bottleneck to the system.
Daily processing of internal and external, domestic and international settlement data continues increasing for international financial institutions. Whether the current system framework can meet the needs for the increasing settlement data at present or in the future, still needs to be discussed.
Service Value
Potential memory leaks can be easily found out by using automated performance testing tools and analyzing the collected test data systematically.
The root cause for low execution efficiency was figured out through analyzing the business processes and sampling analysis of the system status when backend functional modules are executing.
After several rounds of testing, the PEG team helped clients understand the data and business applicable capacity for daily user scenarios and provided a reference for capacity planning and future capacity growth.