Since the development of operation and maintenance, Ops has gone from manual operation and maintenance, process standardization operation and maintenance, and platform automation operation and maintenance to DevOps. In recent years, Ops has been combined with big data and AI, expanding DataOps and AIOps. This is a historical necessity and will also bring high efficiency to enterprise it operation and maintenance. AIOps means higher efficiency, lower cost and shorter solution time.
Compared with the traditional operation and maintenance tools, the advantages of AIOps are obvious: the traditional operation and maintenance tools have a single index collection dimension, and they will be checked by a large number of operation and maintenance indicators when judging faults, which will waste time, and the traditional operation and maintenance data depends more on expert experience;
Moreover, AIOps can be analyzed through the underlying big data platform, and through the full learning and judgment of AI technology, it can directly trace the source and reduce the noise of the alarm, and show the root and location of the fault to the operation and maintenance personnel at the first time, which greatly improves the work efficiency and the time for handling the fault.