A system comprising: at least one computer processor; a classification engine executing on said at least one computer processor and configured to analyze trace data collected from a plurality of executing applications, said classification engine analyzes a time series of said trace data and classifies said time series as corresponding to a production or development usage of a first executing application, wherein said classification engine classifies based on metadata associated with said time series, wherein said classification engine is configured to: analyze the metadata, if the metadata analysis produces a definitive classification, tag the trace data using that classification, else attempt to correlate the trace data with other trace datasets, if a statistical similarity is determined and the other dataset has a known classification, apply the other dataset's classification to the trace data, else use a model of classified datasets to compare and classify the trace data, if there is a statistically significant match, apply the classification to the trace data, else tag the trace data as unclassified, the system being configured to determine production related metrics, wherein the production related metrics are derived from the time series corresponding to a production usage, wherein the production related metrics are performance or operational characteristics that indicate how well the first executing application operates in a production environment. at least one computer processor; a classification engine executing on said at least one computer processor and configured to analyze trace data collected from a plurality of executing applications, said classification engine analyzes a time series of said trace data and classifies said time series as corresponding to a production or development usage of a first executing application, wherein said classification engine classifies based on metadata associated with said time series, wherein said classification engine is configured to: analyze the metadata, if the metadata analysis produces a definitive classification, tag the trace data using that classification, else attempt to correlate the trace data with other trace datasets, if a statistical similarity is determined and the other dataset has a known classification, apply the other dataset's classification to the trace data, else use a model of classified datasets to compare and classify the trace data, if there is a statistically significant match, apply the classification to the trace data, else tag the trace data as unclassified, analyze the metadata, if the metadata analysis produces a definitive classification, tag the trace data using that classification, else attempt to correlate the trace data with other trace datasets, if a statistical similarity is determined and the other dataset has a known classification, apply the other dataset's classification to the trace data, else use a model of classified datasets to compare and classify the trace data, if there is a statistically significant match, apply the classification to the trace data, else tag the trace data as unclassified, the system being configured to determine production related metrics, wherein the production related metrics are derived from the time series corresponding to a production usage, wherein the production related metrics are performance or operational characteristics that indicate how well the first executing application operates in a production environment. <EOS>