Recently, cloud computing has become a vital part that supports people’s normal lives and production. However, accompanied by the increasing complexity of the , failures constantly keep coming up and cause huge economic losses. Thus, to guarantee the performance and prevent execrable effects caused by failures, diagnostics has become of great interest for cloud service providers. Due to the characteristics of (e.g., virtualization and multi-tenancy), transplanting traditional network diagnostic tools to the face several difficulties. Additionally, many existing tools cannot solve problems in the . In this paper, we summarize and classify the state-of-the-art technologies of cloud diagnostics which can be used in the production according to their features. Moreover, we analyze the differences between diagnostics and traditional based on the characteristics of the . Considering the operation requirements of the , we propose the points that should be cared about when designing a diagnostic tool. Also, we discuss the challenges that diagnostics will face in future development.