Abstract: A network log time alignment method and an apparatus are provided. The method includes: obtaining log data stored in multiple network devices; parsing the log data to obtain features of each network device; determining associated features of the multiple network devices according to the features of each network device, where the associated features are features that are of the network devices and that have an association in space; and then, performing alignment on log time in multiple pieces of log data according to the associated features. Therefore, associated features of related devices of a network fault can be found, and log time are automatically aligned according to the associated features, thereby improving the efficiency and the accuracy of the fault location and sectionalization.

Abstract: A network log time alignment method and an apparatus are provided. The method includes: obtaining log data stored in multiple network devices; parsing the log data to obtain features of each network device; determining associated features of the multiple network devices according to the features of each network device, where the associated features are features that are of the network devices and that have an association in space; and then, performing alignment on log time in multiple pieces of log data according to the associated features. Therefore, associated features of related devices of a network fault can be found, and log time are automatically aligned according to the associated features, thereby improving the efficiency and the accuracy of the fault location and sectionalization.

Abstract: A network log time alignment method and an apparatus are provided. The method includes: obtaining log data stored in multiple network devices; parsing the log data to obtain features of each network device; determining associated features of the multiple network devices according to the features of each network device, where the associated features are features that are of the network devices and that have an association in space; and then, performing alignment on log time in multiple pieces of log data according to the associated features. Therefore, associated features of related devices of a network fault can be found, and log time are automatically aligned according to the associated features, thereby improving the efficiency and the accuracy of the fault location and sectionalization.

Abstract: A method includes: obtaining an indicator value of a user experience quality reference indicator and an indicator value of a network performance indicator that are corresponding to a target network device at a different moment in a same time period, where a user experience quality reference indicator is used to represent user experience quality, and the network performance indicator is used to represent network quality; and determining a network performance bottleneck value based on the obtained indicator value of the user experience quality reference indicator and the obtained indicator value of the network performance indicator in the same time period, where the network performance bottleneck value is used to be compared with an indicator value of a network performance indicator of a network device to determine network quality of the network device.

Abstract: A network log time alignment method and an apparatus are provided. The method includes: obtaining log data stored in multiple network devices; parsing the log data to obtain features of each network device; determining associated features of the multiple network devices according to the features of each network device, where the associated features are features that are of the network devices and that have an association in space; and then, performing alignment on log time in multiple pieces of log data according to the associated features. Therefore, associated features of related devices of a network fault can be found, and log time are automatically aligned according to the associated features, thereby improving the efficiency and the accuracy of the fault location and sectionalization.