[jira] [Created] (METRON-594) Replay Telemetry Data through Profiler

["Nick Allen (JIRA)" <ji...@apache.org>]

Nick Allen created METRON-594:
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             Summary: Replay Telemetry Data through Profiler
                 Key: METRON-594
                 URL: https://issues.apache.org/jira/browse/METRON-594
             Project: Metron
          Issue Type: Improvement
            Reporter: Nick Allen


The Profiler currently consumes live telemetry, in real-time, as it is streamed through Metron.  A useful extension of this functionality would allow the Profiler to also consume archived, historical telemetry.  Allowing a user to selectively replay archived, historical raw telemetry through the Profiler has a number of applications. The following use cases help describe why this might be useful.

Use Case 1 - Model Development
When developing a new model, I often need a feature set of historical data on which to train my model.  I can either wait days, weeks, months for the Profiler to generate this based on live data or I could re-run the raw, historical telemetry through the Profiler to get started immediately.  It is much simpler to use the same mechanism to create this historical data set, than a separate batch-driven tool to recreate something that approximates the historical feature set.

Use Case 2 - Model Deployment 
When deploying an analytical model to a new environment, like production, on day 1 there is often no historical data for the model to work with.  This often leaves a gap between when the model is deployed and when that model is actually useful.  If I could replay raw telemetry through the profiler a historical feature set could be created as part of the deployment process.  This allows my model to start functioning on day 1.

Use Case 3 - Profile Validation
When creating a Profile, it is difficult to understand how the configured profile might behave against the entire data set.  By creating the profile and watching it consume real-time streaming data, I only have an understanding of how behaves on that small segment of data.  If I am able to replay historical telemetry, I can instantly understand how it behaves on a much larger data set along with all the anomalies and exceptions that exist in all large data sets.




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