CI/CD ML Pipeline
by AaaS · open-source · Last verified 2026-03-01
CI/CD pipeline for machine learning models with automated testing, evaluation, registry management, and staged deployment. Runs benchmark suites, compares against baseline metrics, and promotes models through staging environments with approval gates.
https://aaas.blog/script/ci-cd-ml-pipeline ↗C
C—Below Average
Adoption: C+Quality: AFreshness: ACitations: CEngagement: F
Specifications
- License
- MIT
- Pricing
- open-source
- Capabilities
- automated-testing, benchmark-evaluation, model-registry, staged-deployment, approval-gates
- Integrations
- pytest, datasets, mlflow, docker
- Use Cases
- ml-deployment-automation, model-lifecycle-management, regression-prevention, production-promotion
- API Available
- No
- Language
- python
- Dependencies
- pytest, datasets, mlflow, docker, boto3
- Environment
- Python 3.11+ with Docker and CI runner (GitHub Actions/GitLab CI)
- Est. Runtime
- 10-45 minutes for full pipeline run
- Tags
- script, automation, ci-cd, ml-pipeline, deployment
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
47.8Adoption
52
Quality
80
Freshness
82
Citations
44
Engagement
0