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Feature Store Serving | Skills Pool

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Feature Store Serving

Feature Store Serving workflows for quantitative research, implementation, and production controls. use when tasks involve offline-online feature parity and freshness guarantees.

GhostOf0days0 스타2026. 2. 10.

직업
카테고리: 이커머스

스킬 내용

objective

Execute feature store serving work with reproducible research, explicit controls, and deployable outputs.

workflow

define source contracts, schema versions, and freshness objectives.
ingest data with replay support and deterministic normalization.
validate keys, timestamps, and point-in-time join behavior.
monitor quality metrics continuously and quarantine degraded feeds.
publish only when lineage, ownership, and quality thresholds are satisfied.

required diagnostics

freshness, completeness, null-rate, and duplicate-rate trends.
schema drift and breaking-change frequency across sources.
point-in-time join integrity for features and labels.
backfill and replay consistency versus canonical snapshots.
offline-online parity gaps and delayed feature arrival

risk controls

관련 스킬

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Feature Store Serving

npx skillvault add GhostOf0days/ghostof0days-codex-quant-skills-feature-store-serving-skill-md

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작성자: GhostOf0days
스타: 0
업데이트: 2026. 2. 10.
직업

이 페이지의 내용

enforce hard thresholds for freshness and data-quality metrics.

enforce quarantine and fallback paths for corrupted feeds.

enforce full lineage metadata before downstream release.

outputs

run python scripts/feature_store_serving_diagnostics.py input.csv --output diagnostics.json and keep the json artifact.
write an implementation memo using references/feature-store-serving-playbook.md with assumptions, tests, limits, and rollout plan.

resources

use scripts/feature_store_serving_diagnostics.py for deterministic diagnostics.
use references/feature-store-serving-playbook.md for the domain-specific checklist and delivery structure.

02

workflow

03required diagnostics

04risk controls

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