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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