batch-inference
CommunityAutomate batch scoring with shared model code.
AuthorDuqueOM
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Batch inference reuses the service's feature engineering and model artifact to score millions of rows in a single run, avoiding real-time API latency.
Core Features & Use Cases
- Shared predict path between real-time and batch modes to ensure consistency and reduce drift.
- Output is partitioned Parquet with fields: prediction_id, entity_id, model_version, prediction_score, timestamp for easy downstream consumption.
- Scheduling, backfill, and monitoring via Kubernetes CronJob to run nightly or per Schedule with guardrails and observability.
Quick Start
Provide the service name and code path, then run the scaffold to generate batch.py and cronjob YAML.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: batch-inference Download link: https://github.com/DuqueOM/ML-MLOps-Portfolio/archive/main.zip#batch-inference Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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