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https://issues.apache.org/jira/browse/METRON-594?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16988280#comment-16988280
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Nick Allen commented on METRON-594:
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Closing as duplicate of METRON-1699.
> 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
> Priority: Major
>
> 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 it 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; including all the anomalies and exceptions that
> exist in all large data sets.
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