feat: Add granular telemetry signals decorator params and error classification#5963
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rsareddy0329 wants to merge 8 commits into
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feat: Add granular telemetry signals decorator params and error classification#5963rsareddy0329 wants to merge 8 commits into
rsareddy0329 wants to merge 8 commits into
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…r params and error classification X-AI-Prompt: Implement granular telemetry signals for training, evaluation, and deployment X-AI-Tool: Kiro IDE
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nargokul
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Jun 22, 2026
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| if "validation" in error_type.lower() or "invalid" in error_msg or "must be" in error_msg: | ||
| return "validation_error" |
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"must be" seems vague could be anything .
Is there like a more exhaustive map of this ? Has this problem been solved elsewhere already in another library or so ?
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| if "accessdenied" in error_msg or "not authorized" in error_msg or "forbidden" in error_msg: | ||
| return "auth_error" |
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How does spacing/cases sensitivity work in these cases ?
If I get "access denied" the classification would be incorrect right
| return "unknown" | ||
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| def _attr_to_key(attr: str) -> str: |
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Can we use existing snake to camel conversions ?
| func_name="BedrockModelBuilder.deploy", | ||
| telemetry_params=[ | ||
| ("model_package", TelemetryParamType.ATTR_EXISTS), | ||
| ("imported_model_kms_key_id", TelemetryParamType.KWARG_EXISTS), |
| feature=Feature.MODEL_CUSTOMIZATION, | ||
| func_name="BedrockModelBuilder.deploy", | ||
| telemetry_params=[ | ||
| ("model_package", TelemetryParamType.ATTR_EXISTS), |
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Model Package is fine .
How is Model data being stored here ?
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| @_telemetry_emitter( | ||
| feature=Feature.MODEL_CUSTOMIZATION, |
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I think a model dimension can be added to parameters as well
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Can we add for pipelines as well ?
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