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View All on GitHub AI/ML • Machine Learning
AI Summary: This issue aims to increase test coverage from 87% to over 90% by adding tests for various error handling scenarios across `app/main.py`, `app/model.py`, and `app/security.py`. The focus is on ensuring production reliability by covering edge cases like missing files, invalid inputs, and startup failures, and verifying appropriate error responses.
Complexity:
3/5
good first issue priority: p2-medium effort: m type: enhancement area: testing
End-to-end ML platform implementation: EKS-based pipelines, model registry, CI/CD, feature store, and observability — with reflections on platform design.
Python