Deployment & CI/CD setups
Data vs Model Deployment for Deployment & CI/CD
Comparing two Claude Code plugins for deployment & ci/cd. Below: side-by-side facts, then a verdict you can disagree with.
Side by side
Data engineering for Apache Airflow and Astronomer. Author DAGs with best practices, debug pipeline failures, trace data lineage, profile tables, migrate Airflow 2 to 3, and manage local and cloud deployments.
Tags
developmentdeploymentai
- Author
- anthropics
- Stars
- 18,951
- Updated
- May 2026
- Source
- GitHub
Install
/plugin install data@claude-plugins-officialDeploy ML models with FastAPI, Docker, Kubernetes. Use for serving predictions, containerization, monitoring, drift detection, or encountering latency issues, health check failures, version conflicts.
Tags
aikubernetesdockerdeploymentmonitoringapi
Install
/plugin marketplace add secondsky/claude-skills && /plugin install model-deployment@claude-skillsVerdict
Model Deployment edges out Data for deployment & ci/cd on this site's signals (tag fit, popularity, recency).
- Pick Data if your project leans on development.
- Pick Model Deployment if you need stronger kubernetes support.
Auto-generated from tag fit, popularity, recency, and featured status. Not a hand review.