Saketkr21 opened a new pull request, #73259:
URL: https://github.com/apache/airflow/pull/73259
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Add a new `apache-airflow-providers-dbt-core` provider package that ships a
single
operator, `DbtKubernetesRunOperator`, which runs a dbt Core job inside a
single
Kubernetes pod — mirroring a dbt Cloud job run without requiring dbt Cloud.
The operator subclasses `KubernetesPodOperator` and orchestrates the full dbt
lifecycle in one pod:
1. **Clone** the dbt project from git (optional; repo may be baked into the
image).
A git-repo cache on S3/GCS lets runs recover if git is temporarily
unreachable.
2. **Run `dbt deps`** (optional).
3. **Execute `steps`** — ordered shell commands (typically dbt CLI calls)
sequentially;
the first non-zero exit stops the run and fails the task.
4. **Upload `target/`** to S3 or GCS on **both success and failure**, so
`run_results.json` and compiled SQL are always available for inspection.
Because the operator is a thin subclass, all `KubernetesPodOperator`
arguments
(`namespace`, `container_resources`, `deferrable`, `secrets`,
`init_containers`, …)
pass straight through.
### Files added / changed
| Path | What |
|---|---|
| `providers/dbt/core/pyproject.toml` | New provider package |
| `providers/dbt/core/provider.yaml` | Provider metadata |
| `providers/dbt/core/src/.../operators/dbt.py` | `DbtKubernetesRunOperator`
|
| `providers/dbt/core/src/.../operators/run.sh` | Pod entrypoint script |
| `providers/dbt/core/docs/` | Operator how-to, connections, security,
changelog |
| `providers/dbt/core/README.rst` | Package README |
| `providers/dbt/core/tests/unit/.../test_dbt.py` | 26 unit tests (no pod
created) |
| `providers/dbt/core/tests/system/.../example_dbt_kubernetes.py` | System
test / example Dag |
### Design choices
- **One entrypoint script (`run.sh`)**: the Python operator constructs a set
of
environment variables and delegates to a bundled bash script. This keeps
the
operator thin and makes the lifecycle trivially inspectable via pod logs.
- **`steps` not just dbt commands**: the parameter accepts any shell
command, so
users can include setup steps (`uv sync`, `pip install …`) without needing
a
separate operator or custom image.
- **`artifact_conn_id` required with `artifact_dest`**: credentials are
resolved
on the worker and injected as env vars; the pod never touches Airflow
connections
directly. This is documented in `docs/security.rst`.
- **git repo caching**: slug-based S3/GCS key per DAG + repo + branch; the
operator
updates the cache on every successful clone and falls back to it on clone
failure.
- **Optional cloud providers**: `amazon` and `google` extras are guarded with
`AirflowOptionalProviderFeatureException`; the base package only requires
`apache-airflow-providers-cncf-kubernetes`.
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* Read the **[Pull Request
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for more information. Note: commit author/co-author name and email in commits
become permanently public when merged.
* For fundamental code changes, an Airflow Improvement Proposal
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is needed.
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`{pr_number}.significant.rst`, in
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You can add this file in a follow-up commit after the PR is created so you
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