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diff --git a/docs/prediction_docs/Section_1_Use_cases_and_scenarios.rst b/docs/prediction_docs/Section_1_Use_cases_and_scenarios.rst new file mode 100644 index 0000000..86ca3c4 --- /dev/null +++ b/docs/prediction_docs/Section_1_Use_cases_and_scenarios.rst @@ -0,0 +1,23 @@ +========================= +1 Use cases and scenarios +========================= + +Telecom services often have high available requirements. Failure prediction is one of the importance features +for high available requirements. Operator can handle faults in advance based on failure prediction. +This project focuses on data collection of failure prediction. + +The data collector consists of Ceilometer and Monasca which can be extended to plugin some other open source data collectors, +e.g. Zabbix, Nagios, Cacti. Based on real-time analytics techniques and machine learning techniques, +the failure predictor analyses the data gathered by the data collector to automatically determine whether a failure will happen. +If a failure is judged, then the failure predictor sends failure notifications to the failure +management module (e.g. the Doctor module), which could handle these notifications. + +Use case 1 +========== + +Based on infrastructure metrics, it is possible to predict failure of infrastructure, e.g. Nova, Neutron, MQ. + +Use case 2 +========== + +Based on metrics of infrastructure and VM inside, it is possible to predict failure of VNF. |