Application-level network traffic analysis and sophisticated analysis techniques, such as machine learning and stream data processing for network traffic, require considerable computational resources. In addition, developing an application protocol analyzer is a tedious and time-consuming task. Therefore, we propose a scalable and flexible traffic analysis platform (SF-TAP) for the efficient and flexible application-level stream analysis of high-bandwidth network traffic. By using our flexible modular platform, developers can easily implement multicore scalable application-level stream analyzers. Furthermore, as SF-TAP is horizontally scalable, it manages high-bandwidth network traffic. To achieve this scalability, we separate the network traffic based on traffic flows, and forward the separated flows to multiple SF-TAP cells, each comprising a traffic capturer and application-level analyzers. This study discusses the design, implementation and detailed evaluation of SF-TAP.