DevOps Practices and Challenges at Didi Ride‑Hailing: From Development to Operations
Didi’s ride‑hailing R&D team addresses efficiency and stability challenges of a large micro‑service ecosystem by unifying a Go stack, common framework, and data models, using eBPF traffic recording for automated regression testing, and applying AIOps alert filtering, knowledge‑graph root‑cause analysis, and a localization robot for rapid fault recovery, while targeting full CI/CD automation with static analysis, service‑mesh observability, and chaos engineering.
