aws-solutions / mlops-workload-orchestrator
The MLOps Workload Orchestrator solution helps you streamline and enforce architecture best practices for machine learning (ML) model productionization. This solution is an extendable framework that provides a standard interface for managing ML pipelines for AWS ML services and third-party services.
Summary
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| Main Code: 5,686 LOC (57 files) = PY (99%) + JS (<1%) Secondary code: Test: 2,713 LOC (19); Generated: 13 LOC (1); Build & Deploy: 322 LOC (2); Other: 398 LOC (9); |
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| Duplication: 6% | |||
| File Size: 0% long (>1000 LOC), 33% short (<= 200 LOC) | |||
| Unit Size: 21% long (>100 LOC), 47% short (<= 10 LOC) | |||
| Conditional Complexity: 0% complex (McCabe index > 50), 78% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (11 components) | ||
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1 year, 2 months old
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0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
Latest commit date: 2022-01-24
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3
commits
(30 days)
2
contributors
(30 days) |
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