Log-based failure diagnosis refers to intelligent analysis of system runtime logs to automatically discover system anomalies and diagnose system failures. Today, this technology is one of the key technologies of artificial intelligence for IT operations (AIOps), which has become a research hotspot in both academia and industry. This study first analyzes the log-based failure diagnosis process, and summarizes the research framework of fault diagnosis based on logs and four key technologies in the field:Log processing and feature extraction technology, anomaly detection technology, failure prediction technology, and fault diagnosis technology. Next, a systematic review is conducted of the achievements of scholars at home and abroad in these four key technical fields in recent years. At last, the different technologies are summarized in this field based on the research framework, and the possible challenges are looked forwarded for future research.