Deploy Airflow DAGs and projects. Use when the user wants to deploy code, push DAGs, set up CI/CD, deploy to production, or asks about deployment strategies for Airflow.
84
77%
Does it follow best practices?
Impact
92%
1.14xAverage score across 3 eval scenarios
Risky
Do not use without reviewing
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/deploying-airflow/SKILL.mdAstro CI/CD deploy pipeline
DAG-only command
66%
100%
Full deploy command
100%
100%
DAG-only for fast iteration
66%
100%
Full deploy on main
100%
100%
Change-type distinction
100%
100%
Deploy queue awareness
37%
37%
Image-only deploy option
0%
0%
Separate staging and production
100%
100%
No manual deploy steps
100%
100%
GitHub Actions secret usage
100%
100%
Airflow 3 Docker Compose setup
API server service
100%
100%
Standalone DAG processor
0%
100%
LocalExecutor used
100%
100%
Airflow 3 image tag
100%
100%
No examples loaded
100%
100%
DAGs volume mount
100%
100%
Env-var configuration pattern
100%
100%
Python packages via requirements.txt rebuild
75%
100%
CLI command via exec
50%
100%
No webserver naming
0%
100%
Postgres healthcheck
100%
100%
Kubernetes Helm chart production deploy
Official Helm repo
100%
100%
Git-sync enabled
100%
100%
Git-sync repo configured
100%
100%
DAG processor enabled
100%
100%
API server key used
100%
100%
Log persistence enabled
100%
100%
Image version pinned
70%
0%
Git-sync rationale
100%
100%
No webserver key
0%
100%
Namespace specified
100%
100%
Official chart used
100%
100%
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Table of Contents
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