Abstract: Disclosed is a system for providing machine learning aided diagnostics and prognostics for large distributed systems. A diagnostics module applies two-tiered analysis to detect anomalous behavior of the large scale distributed system. First, multivariate telemetry and event data emitted from the large scale distributed systems is collected by a diagnostics component, which applies multivariate analysis to identify of set of N-anomalies. Second, univariate telemetry and event data is obtained by the diagnostics component, which applies univariate analysis to the N-anomalies previously identified, ranks the results, and provides them to an AI to generate a diagnostics incident report. A prognostics module reviews the diagnostics incident report and maps each identified issue to a resolution plan. If execution of the resolution plan does not succeed in resolving the identified issue, the issue is escalated to a support team.