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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 deleted file mode 100644 index 86ca3c4..0000000 --- a/docs/prediction_docs/Section_1_Use_cases_and_scenarios.rst +++ /dev/null @@ -1,23 +0,0 @@ -========================= -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. |