Curating Meitu's technical expertise, valuable case studies, and innovation insights. We deliver quality technical content to foster knowledge sharing between Meitu's tech team and outstanding developers worldwide.
The article outlines how Meipai’s rapidly growing platform built a backend system that guarantees high availability, handles massive traffic, supports evolving media formats, and adopts a multi‑language development model with clear principles for language selection and systematic integration.
The talk explains how Meipai engineered a high‑availability PHP backend—leveraging PHP’s ecosystem while overcoming performance bottlenecks—to reliably serve hundreds of millions of users, detailing the architectural decisions, scaling challenges, and key lessons learned during rapid user growth.
As Meipai’s user base exploded, the platform shifted from manual curation to sophisticated personalized recommendation algorithms—leveraging machine‑learning and data‑mining techniques, iterating through multiple generations, overcoming scalability and relevance challenges, and delivering rapid solutions that inspire future recommendation system designs.
