Automatic collection of relevant logs associated with a service disruption

A system for improving performance of root-cause analysis associated with an event that disrupts normal operation of a cloud service provided via a distributed network that includes a radio access network and a core network, the system comprising:

• a processing system;
• and
• a computer readable medium having encoded thereon computer readable instructions that when executed by the processing system cause the system to perform operations comprising:
• monitoring for the event that disrupts the normal operation of the cloud service provided via the distributed network;
• determining, based on the monitoring, that the event that disrupts the normal operation of the cloud service provided via the distributed network has occurred;
• in response to determining that the event that disrupts the normal operation of the cloud service provided via the distributed network has occurred, triggering collection of a plurality of first logs related to a plurality of metrics associated with the event that disrupts the normal operation of the cloud service provided via the distributed network, wherein:
• the plurality of first logs is collected for a predefined period of time;
• the plurality of first logs is collected from a plurality of components, in the distributed network, configured to provide the cloud service at different geographic locations;
• and
• the plurality of first logs includes an increased level of verbosity compared to a corresponding plurality of second logs related to the plurality of metrics that is collected during the normal operation of the cloud service provided via the distributed network;
• upon expiration of the predefined period of time, halting the collection of the plurality of first logs;
• parsing the plurality of first logs to produce a report that correlates abnormal data points based on timestamps;
• generating a log bundle that contains the plurality of first logs and the report;
• and
• providing the log bundle thereby enabling the improved performance of the root-cause analysis associated with the event that disrupts normal operation of the cloud service provided via the distributed network.

A computer readable storage medium having encoded thereon computer readable instructions that, when executed by a system, cause the system to perform operations comprising:

• monitoring for the event that disrupts the normal operation of the cloud service provided via the distributed network;
• determining, based on the monitoring, that the event that disrupts the normal operation of the cloud service provided via the distributed network has occurred;
• in response to determining that the event that disrupts the normal operation of the cloud service provided via the distributed network has occurred, triggering collection of a plurality of first logs related to a plurality of metrics associated with the event that disrupts the normal operation of the cloud service provided via the distributed network, wherein:
• the plurality of first logs is collected for a predefined period of time;
• the plurality of first logs is collected from a plurality of components, in the distributed network, configured to provide the cloud service at different geographic locations;
• and
• the plurality of first logs includes an increased level of verbosity compared to a corresponding plurality of second logs related to the plurality of metrics that is collected during the normal operation of the cloud service provided via the distributed network;
• upon expiration of the predefined period of time, halting the collection of the plurality of first logs;
• parsing the plurality of first logs to produce a report that correlates abnormal data points based on timestamps;
• generating a log bundle that contains the plurality of first logs and the report;
• and
• providing the log bundle thereby enabling the improved performance of the root-cause analysis associated with the event that disrupts normal operation of the cloud service provided via the distributed network.