This is an automated email from the ASF dual-hosted git repository.
potiuk pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/airflow.git
The following commit(s) were added to refs/heads/main by this push:
new 57dc7a20077 Fix k8s tests doc formatting (#71913)
57dc7a20077 is described below
commit 57dc7a20077669e838a2195b44d939719bc533d1
Author: Przemysław Mirowski <[email protected]>
AuthorDate: Tue Sep 22 01:58:51 2026 +0200
Fix k8s tests doc formatting (#71913)
---
contributing-docs/testing/k8s_tests.rst | 671 ++++++++++++++++----------------
1 file changed, 333 insertions(+), 338 deletions(-)
diff --git a/contributing-docs/testing/k8s_tests.rst
b/contributing-docs/testing/k8s_tests.rst
index 807ce24e213..f21774e999a 100644
--- a/contributing-docs/testing/k8s_tests.rst
+++ b/contributing-docs/testing/k8s_tests.rst
@@ -80,8 +80,8 @@ For your testing, you manage Kind cluster with ``k8s`` breeze
command group. Tho
created:
.. image:: ../../dev/breeze/doc/images/output_k8s.svg
- :width: 100%
- :alt: Breeze k8s
+ :width: 100%
+ :alt: Breeze k8s
The command group allows you to setup environment, start/stop/recreate/status
Kind Kubernetes cluster,
configure cluster (via ``create-cluster``, ``configure-cluster`` command).
Those commands can be run with
@@ -118,21 +118,20 @@ You can interact with the cluster (via ``shell`` and
``k9s`` commands).
You can run set of k8s tests via ``tests`` command. You can also run tests in
parallel on all/selected
clusters by ``--run-in-parallel`` flag.
+.. note::
-**Note**:
-
-If you want to run tests with a non-``LocalExecutor``, you need to deploy
Airflow with the corresponding ``executor`` flags.
-For example, if you want to run tests with ``KubernetesExecutor``
+ If you want to run tests with a non-``LocalExecutor``, you need to deploy
Airflow with the corresponding ``executor`` flags.
+ For example, if you want to run tests with ``KubernetesExecutor``
.. code-block:: bash
- breeze k8s tests --executor KubernetesExecutor
+ breeze k8s tests --executor KubernetesExecutor
you need to deploy Airflow with the ``--executor KubernetesExecutor`` flag.
.. code-block:: bash
- breeze k8s deploy-airflow --executor KubernetesExecutor
+ breeze k8s deploy-airflow --executor KubernetesExecutor
Hot-reloading Dags and core sources
@@ -145,14 +144,14 @@ hot-reload mode; the API server and webserver UI are not
hot-reloaded by default
.. code-block:: bash
- breeze k8s dev
+ breeze k8s dev
If skaffold cannot find the running pods (for example if the release was
deployed outside skaffold),
rerun with ``--deploy`` so it upgrades the Helm release and manages the
resources:
.. code-block:: bash
- breeze k8s dev --deploy
+ breeze k8s dev --deploy
Running tests with Kubernetes Cluster
@@ -166,15 +165,15 @@ Running Kubernetes tests via breeze:
.. code-block:: bash
- breeze k8s tests
- breeze k8s tests TEST TEST [TEST ...]
+ breeze k8s tests
+ breeze k8s tests TEST TEST [TEST ...]
Optionally add ``--executor``:
.. code-block:: bash
- breeze k8s tests --executor CeleryExecutor
- breeze k8s tests --executor CeleryExecutor TEST TEST [TEST ...]
+ breeze k8s tests --executor CeleryExecutor
+ breeze k8s tests --executor CeleryExecutor TEST TEST [TEST ...]
Entering shell with Kubernetes Cluster
--------------------------------------
@@ -187,13 +186,13 @@ The binaries are available in
``kubernetes-tests/.venv/bin`` path.
.. code-block:: bash
- breeze k8s shell
+ breeze k8s shell
Optionally add ``--executor``:
.. code-block:: bash
- breeze k8s shell --executor CeleryExecutor
+ breeze k8s shell --executor CeleryExecutor
K9s CLI - debug Kubernetes in style!
@@ -212,15 +211,15 @@ You can read more about k9s at `https://k9scli.io/
<https://k9scli.io/>`_
Here is the screenshot of k9s tools in operation:
.. image:: images/k9s.png
- :align: center
- :alt: K9S tool
+ :align: center
+ :alt: K9S tool
You can enter the k9s tool via breeze (after you deployed Airflow):
.. code-block:: bash
- breeze k8s k9s
+ breeze k8s k9s
You can exit k9s by pressing Ctrl-C.
@@ -234,169 +233,168 @@ Typical testing pattern for Kubernetes tests
The typical session for tests with Kubernetes looks like follows:
-1. Prepare the environment:
+#. Prepare the environment:
-.. code-block:: bash
+ .. code-block:: bash
- breeze k8s setup-env
+ breeze k8s setup-env
-The first time you run it, it should result in creating the virtualenv and
installing good versions
-of kind, kubectl and helm. All of them are installed in ``./build/k8s-env``
(binaries available in ``bin``
-sub-folder of it).
+ The first time you run it, it should result in creating the virtualenv and
installing good versions
+ of kind, kubectl and helm. All of them are installed in ``./build/k8s-env``
(binaries available in ``bin``
+ sub-folder of it).
-.. code-block:: text
+ .. code-block:: text
- Initializing K8S virtualenv in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv
- Reinstalling PIP version in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv
- Installing necessary packages in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv
- The ``kind`` tool is not downloaded yet. Downloading 0.14.0 version.
- Downloading from:
https://github.com/kubernetes-sigs/kind/releases/download/v0.14.0/kind-darwin-arm64
- The ``kubectl`` tool is not downloaded yet. Downloading 1.24.3 version.
- Downloading from:
https://storage.googleapis.com/kubernetes-release/release/v1.24.3/bin/darwin/arm64/kubectl
- The ``helm`` tool is not downloaded yet. Downloading 3.9.2 version.
- Downloading from: https://get.helm.sh/helm-v3.9.2-darwin-arm64.tar.gz
- Extracting the darwin-arm64/helm to
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin
- Moving the helm to
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin/helm
+ Initializing K8S virtualenv in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv
+ Reinstalling PIP version in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv
+ Installing necessary packages in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv
+ The ``kind`` tool is not downloaded yet. Downloading 0.14.0 version.
+ Downloading from:
https://github.com/kubernetes-sigs/kind/releases/download/v0.14.0/kind-darwin-arm64
+ The ``kubectl`` tool is not downloaded yet. Downloading 1.24.3 version.
+ Downloading from:
https://storage.googleapis.com/kubernetes-release/release/v1.24.3/bin/darwin/arm64/kubectl
+ The ``helm`` tool is not downloaded yet. Downloading 3.9.2 version.
+ Downloading from: https://get.helm.sh/helm-v3.9.2-darwin-arm64.tar.gz
+ Extracting the darwin-arm64/helm to
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin
+ Moving the helm to
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin/helm
-This prepares the virtual environment for tests and downloads the right
versions of the tools
-to ``./build/k8s-env``
+ This prepares the virtual environment for tests and downloads the right
versions of the tools
+ to ``./build/k8s-env``
-2. Create the KinD cluster:
+#. Create the KinD cluster:
-.. code-block:: bash
+ .. code-block:: bash
- breeze k8s create-cluster
+ breeze k8s create-cluster
-Should result in KinD creating the K8S cluster.
+ Should result in KinD creating the K8S cluster.
-.. code-block:: text
+ .. code-block:: text
- Config created in
/Users/jarek/IdeaProjects/airflow/.build/.k8s-clusters/airflow-python-3.10-v1.24.2/.kindconfig.yaml:
+ Config created in
/Users/jarek/IdeaProjects/airflow/.build/.k8s-clusters/airflow-python-3.10-v1.24.2/.kindconfig.yaml:
- kind: Cluster
- apiVersion: kind.x-k8s.io/v1alpha4
- networking:
- ipFamily: ipv4
- apiServerAddress: "127.0.0.1"
- apiServerPort: 48366
- nodes:
- - role: control-plane
- - role: worker
- extraPortMappings:
- - containerPort: 30007
- hostPort: 18150
- listenAddress: "127.0.0.1"
- protocol: TCP
+ kind: Cluster
+ apiVersion: kind.x-k8s.io/v1alpha4
+ networking:
+ ipFamily: ipv4
+ apiServerAddress: "127.0.0.1"
+ apiServerPort: 48366
+ nodes:
+ - role: control-plane
+ - role: worker
+ extraPortMappings:
+ - containerPort: 30007
+ hostPort: 18150
+ listenAddress: "127.0.0.1"
+ protocol: TCP
- Creating cluster "airflow-python-3.10-v1.24.2" ...
- ✓ Ensuring node image (kindest/node:v1.24.2) 🖼
- ✓ Preparing nodes 📦 📦
- ✓ Writing configuration 📜
- ✓ Starting control-plane 🕹️
- ✓ Installing CNI 🔌
- ✓ Installing StorageClass 💾
- ✓ Joining worker nodes 🚜
- Set kubectl context to "kind-airflow-python-3.10-v1.24.2"
- You can now use your cluster with:
+ Creating cluster "airflow-python-3.10-v1.24.2" ...
+ ✓ Ensuring node image (kindest/node:v1.24.2) 🖼
+ ✓ Preparing nodes 📦 📦
+ ✓ Writing configuration 📜
+ ✓ Starting control-plane 🕹️
+ ✓ Installing CNI 🔌
+ ✓ Installing StorageClass 💾
+ ✓ Joining worker nodes 🚜
+ Set kubectl context to "kind-airflow-python-3.10-v1.24.2"
+ You can now use your cluster with:
- kubectl cluster-info --context kind-airflow-python-3.10-v1.24.2
+ kubectl cluster-info --context kind-airflow-python-3.10-v1.24.2
- Not sure what to do next? 😅 Check out
https://kind.sigs.k8s.io/docs/user/quick-start/
+ Not sure what to do next? 😅 Check out
https://kind.sigs.k8s.io/docs/user/quick-start/
- KinD Cluster API server URL: http://localhost:48366
- Connecting to localhost:18150. Num try: 1
- Error when connecting to localhost:18150 : ('Connection aborted.',
RemoteDisconnected('Remote end closed connection without response'))
+ KinD Cluster API server URL: http://localhost:48366
+ Connecting to localhost:18150. Num try: 1
+ Error when connecting to localhost:18150 : ('Connection aborted.',
RemoteDisconnected('Remote end closed connection without response'))
- Airflow webserver is not available at port 18150. Run `breeze k8s
deploy-airflow --python 3.10 --kubernetes-version v1.24.2` to (re)deploy airflow
+ Airflow webserver is not available at port 18150. Run `breeze k8s
deploy-airflow --python 3.10 --kubernetes-version v1.24.2` to (re)deploy airflow
- KinD cluster airflow-python-3.10-v1.24.2 created!
+ KinD cluster airflow-python-3.10-v1.24.2 created!
- NEXT STEP: You might now configure your cluster by:
+ NEXT STEP: You might now configure your cluster by:
- breeze k8s configure-cluster
+ breeze k8s configure-cluster
+#. Configure cluster for Airflow - this will recreate namespace and upload
test resources for Airflow.
-3. Configure cluster for Airflow - this will recreate namespace and upload
test resources for Airflow.
+ .. code-block:: bash
-.. code-block:: bash
+ breeze k8s configure-cluster
- breeze k8s configure-cluster
+ .. code-block:: text
-.. code-block:: text
+ Configuring airflow-python-3.10-v1.24.2 to be ready for Airflow
deployment
+ Deleting K8S namespaces for kind-airflow-python-3.10-v1.24.2
+ Error from server (NotFound): namespaces "airflow" not found
+ Error from server (NotFound): namespaces "test-namespace" not found
+ Creating namespaces
+ namespace/airflow created
+ namespace/test-namespace created
+ Created K8S namespaces for cluster kind-airflow-python-3.10-v1.24.2
- Configuring airflow-python-3.10-v1.24.2 to be ready for Airflow deployment
- Deleting K8S namespaces for kind-airflow-python-3.10-v1.24.2
- Error from server (NotFound): namespaces "airflow" not found
- Error from server (NotFound): namespaces "test-namespace" not found
- Creating namespaces
- namespace/airflow created
- namespace/test-namespace created
- Created K8S namespaces for cluster kind-airflow-python-3.10-v1.24.2
+ Deploying test resources for cluster kind-airflow-python-3.10-v1.24.2
+ persistentvolume/test-volume created
+ persistentvolumeclaim/test-volume created
+ service/airflow-webserver-node-port created
+ Deployed test resources for cluster kind-airflow-python-3.10-v1.24.2
- Deploying test resources for cluster kind-airflow-python-3.10-v1.24.2
- persistentvolume/test-volume created
- persistentvolumeclaim/test-volume created
- service/airflow-webserver-node-port created
- Deployed test resources for cluster kind-airflow-python-3.10-v1.24.2
+ NEXT STEP: You might now build your k8s image by:
- NEXT STEP: You might now build your k8s image by:
+ breeze k8s build-k8s-image
- breeze k8s build-k8s-image
+#. Check the status of the cluster
-4. Check the status of the cluster
+ .. code-block:: bash
-.. code-block:: bash
-
- breeze k8s status
+ breeze k8s status
-Should show the status of current KinD cluster.
+ Should show the status of current KinD cluster.
-.. code-block:: text
+ .. code-block:: text
-
========================================================================================================================
- Cluster: airflow-python-3.10-v1.24.2
+
========================================================================================================================
+ Cluster: airflow-python-3.10-v1.24.2
- *
KUBECONFIG=/Users/jarek/IdeaProjects/airflow/.build/.k8s-clusters/airflow-python-3.10-v1.24.2/.kubeconfig
- *
KINDCONFIG=/Users/jarek/IdeaProjects/airflow/.build/.k8s-clusters/airflow-python-3.10-v1.24.2/.kindconfig.yaml
+ *
KUBECONFIG=/Users/jarek/IdeaProjects/airflow/.build/.k8s-clusters/airflow-python-3.10-v1.24.2/.kubeconfig
+ *
KINDCONFIG=/Users/jarek/IdeaProjects/airflow/.build/.k8s-clusters/airflow-python-3.10-v1.24.2/.kindconfig.yaml
- Cluster info: airflow-python-3.10-v1.24.2
+ Cluster info: airflow-python-3.10-v1.24.2
- Kubernetes control plane is running at https://127.0.0.1:48366
- CoreDNS is running at
https://127.0.0.1:48366/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy
+ Kubernetes control plane is running at https://127.0.0.1:48366
+ CoreDNS is running at
https://127.0.0.1:48366/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy
- To further debug and diagnose cluster problems, use 'kubectl cluster-info
dump'.
+ To further debug and diagnose cluster problems, use 'kubectl
cluster-info dump'.
- Storage class for airflow-python-3.10-v1.24.2
+ Storage class for airflow-python-3.10-v1.24.2
- NAME PROVISIONER RECLAIMPOLICY
VOLUMEBINDINGMODE ALLOWVOLUMEEXPANSION AGE
- standard (default) rancher.io/local-path Delete
WaitForFirstConsumer false 83s
+ NAME PROVISIONER RECLAIMPOLICY
VOLUMEBINDINGMODE ALLOWVOLUMEEXPANSION AGE
+ standard (default) rancher.io/local-path Delete
WaitForFirstConsumer false 83s
- Running pods for airflow-python-3.10-v1.24.2
+ Running pods for airflow-python-3.10-v1.24.2
- NAME READY
STATUS RESTARTS AGE
- coredns-6d4b75cb6d-rwp9d 1/1
Running 0 71s
- coredns-6d4b75cb6d-vqnrc 1/1
Running 0 71s
- etcd-airflow-python-3.10-v1.24.2-control-plane 1/1
Running 0 84s
- kindnet-ckc8l 1/1
Running 0 69s
- kindnet-qqt8k 1/1
Running 0 71s
- kube-apiserver-airflow-python-3.10-v1.24.2-control-plane 1/1
Running 0 84s
- kube-controller-manager-airflow-python-3.10-v1.24.2-control-plane 1/1
Running 0 84s
- kube-proxy-6g7hn 1/1
Running 0 69s
- kube-proxy-dwfvp 1/1
Running 0 71s
- kube-scheduler-airflow-python-3.10-v1.24.2-control-plane 1/1
Running 0 84s
+ NAME READY
STATUS RESTARTS AGE
+ coredns-6d4b75cb6d-rwp9d 1/1
Running 0 71s
+ coredns-6d4b75cb6d-vqnrc 1/1
Running 0 71s
+ etcd-airflow-python-3.10-v1.24.2-control-plane 1/1
Running 0 84s
+ kindnet-ckc8l 1/1
Running 0 69s
+ kindnet-qqt8k 1/1
Running 0 71s
+ kube-apiserver-airflow-python-3.10-v1.24.2-control-plane 1/1
Running 0 84s
+ kube-controller-manager-airflow-python-3.10-v1.24.2-control-plane 1/1
Running 0 84s
+ kube-proxy-6g7hn 1/1
Running 0 69s
+ kube-proxy-dwfvp 1/1
Running 0 71s
+ kube-scheduler-airflow-python-3.10-v1.24.2-control-plane 1/1
Running 0 84s
- KinD Cluster API server URL: http://localhost:48366
- Connecting to localhost:18150. Num try: 1
- Error when connecting to localhost:18150 : ('Connection aborted.',
RemoteDisconnected('Remote end closed connection without response'))
+ KinD Cluster API server URL: http://localhost:48366
+ Connecting to localhost:18150. Num try: 1
+ Error when connecting to localhost:18150 : ('Connection aborted.',
RemoteDisconnected('Remote end closed connection without response'))
- Airflow webserver is not available at port 18150. Run `breeze k8s
deploy-airflow --python 3.10 --kubernetes-version v1.24.2` to (re)deploy airflow
+ Airflow webserver is not available at port 18150. Run `breeze k8s
deploy-airflow --python 3.10 --kubernetes-version v1.24.2` to (re)deploy airflow
- Cluster healthy: airflow-python-3.10-v1.24.2
+ Cluster healthy: airflow-python-3.10-v1.24.2
-5. Build the image base on PROD Airflow image. You need to build the PROD
image first (the command will
+#. Build the image base on PROD Airflow image. You need to build the PROD
image first (the command will
guide you if you did not) either by running the build separately or passing
``--rebuild-base-image``
flag. Generally speaking you should not need to rebuild the base image
unless you changed some
dependencies in ``pyproject.toml``.
@@ -406,312 +404,309 @@ Should show the status of current KinD cluster.
built your PROD image without ``--use-uv`` flag the first build might be a
bit longer. You can also switch
to using a ``pip`` based image by specifying ``--no-use-uv`` flag together
with ``--rebuild-base-image``.
-.. code-block:: bash
+ .. code-block:: bash
- breeze k8s build-k8s-image
+ breeze k8s build-k8s-image
-.. code-block:: text
+ .. code-block:: text
- Building the K8S image for Python 3.10 using Airflow base image:
ghcr.io/apache/airflow/main/prod/python3.10:latest
+ Building the K8S image for Python 3.10 using Airflow base image:
ghcr.io/apache/airflow/main/prod/python3.10:latest
- [+] Building 0.1s (8/8) FINISHED
- => [internal] load build definition from Dockerfile
0.0s
- => => transferring dockerfile: 301B
0.0s
- => [internal] load .dockerignore
0.0s
- => => transferring context: 35B
0.0s
- => [internal] load metadata for
ghcr.io/apache/airflow/main/prod/python3.10:latest
0.0s
- => [1/3] FROM ghcr.io/apache/airflow/main/prod/python3.10:latest
0.0s
- => [internal] load build context
0.0s
- => => transferring context: 3.00kB
0.0s
- => CACHED [2/3] COPY airflow/example_dags/ /opt/airflow/dags/
0.0s
- => CACHED [3/3] COPY airflow/kubernetes_executor_templates/
/opt/airflow/pod_templates/
0.0s
- => exporting to image
0.0s
- => => exporting layers
0.0s
- => => writing image
sha256:c0bdd363c549c3b0731b8e8ce34153d081f239ee2b582355b7b3ffd5394c40bb
0.0s
- => => naming to
ghcr.io/apache/airflow/main/prod/python3.10-kubernetes:latest
+ [+] Building 0.1s (8/8) FINISHED
+ => [internal] load build definition from Dockerfile
0.0s
+ => => transferring dockerfile: 301B
0.0s
+ => [internal] load .dockerignore
0.0s
+ => => transferring context: 35B
0.0s
+ => [internal] load metadata for
ghcr.io/apache/airflow/main/prod/python3.10:latest
0.0s
+ => [1/3] FROM ghcr.io/apache/airflow/main/prod/python3.10:latest
0.0s
+ => [internal] load build context
0.0s
+ => => transferring context: 3.00kB
0.0s
+ => CACHED [2/3] COPY airflow/example_dags/ /opt/airflow/dags/
0.0s
+ => CACHED [3/3] COPY airflow/kubernetes_executor_templates/
/opt/airflow/pod_templates/
0.0s
+ => exporting to image
0.0s
+ => => exporting layers
0.0s
+ => => writing image
sha256:c0bdd363c549c3b0731b8e8ce34153d081f239ee2b582355b7b3ffd5394c40bb
0.0s
+ => => naming to
ghcr.io/apache/airflow/main/prod/python3.10-kubernetes:latest
- NEXT STEP: You might now upload your k8s image by:
+ NEXT STEP: You might now upload your k8s image by:
- breeze k8s upload-k8s-image
+ breeze k8s upload-k8s-image
+#. Upload the image to KinD cluster - this uploads your image to make it
available for the KinD cluster.
-6. Upload the image to KinD cluster - this uploads your image to make it
available for the KinD cluster.
+ .. code-block:: bash
-.. code-block:: bash
+ breeze k8s upload-k8s-image
- breeze k8s upload-k8s-image
+ .. code-block:: text
-.. code-block:: text
+ K8S Virtualenv is initialized in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv
+ Good version of kind installed: 0.14.0 in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin
+ Good version of kubectl installed: 1.25.0 in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin
+ Good version of helm installed: 3.9.2 in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin
+ Stable repo is already added
+ Uploading Airflow image
ghcr.io/apache/airflow/main/prod/python3.10-kubernetes to cluster
airflow-python-3.10-v1.24.2
+ Image: "ghcr.io/apache/airflow/main/prod/python3.10-kubernetes" with ID
"sha256:fb6195f7c2c2ad97788a563a3fe9420bf3576c85575378d642cd7985aff97412" not
yet present on node "airflow-python-3.10-v1.24.2-worker", loading...
+ Image: "ghcr.io/apache/airflow/main/prod/python3.10-kubernetes" with ID
"sha256:fb6195f7c2c2ad97788a563a3fe9420bf3576c85575378d642cd7985aff97412" not
yet present on node "airflow-python-3.10-v1.24.2-control-plane", loading...
- K8S Virtualenv is initialized in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv
- Good version of kind installed: 0.14.0 in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin
- Good version of kubectl installed: 1.25.0 in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin
- Good version of helm installed: 3.9.2 in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin
- Stable repo is already added
- Uploading Airflow image
ghcr.io/apache/airflow/main/prod/python3.10-kubernetes to cluster
airflow-python-3.10-v1.24.2
- Image: "ghcr.io/apache/airflow/main/prod/python3.10-kubernetes" with ID
"sha256:fb6195f7c2c2ad97788a563a3fe9420bf3576c85575378d642cd7985aff97412" not
yet present on node "airflow-python-3.10-v1.24.2-worker", loading...
- Image: "ghcr.io/apache/airflow/main/prod/python3.10-kubernetes" with ID
"sha256:fb6195f7c2c2ad97788a563a3fe9420bf3576c85575378d642cd7985aff97412" not
yet present on node "airflow-python-3.10-v1.24.2-control-plane", loading...
+ NEXT STEP: You might now deploy Airflow by:
- NEXT STEP: You might now deploy Airflow by:
+ breeze k8s deploy-airflow
- breeze k8s deploy-airflow
+#. Deploy Airflow to the cluster - this will use Airflow Helm Chart to deploy
Airflow to the cluster.
+ .. code-block:: bash
-7. Deploy Airflow to the cluster - this will use Airflow Helm Chart to deploy
Airflow to the cluster.
-
-.. code-block:: bash
-
- breeze k8s deploy-airflow
+ breeze k8s deploy-airflow
-.. code-block:: text
+ .. code-block:: text
- Deploying Airflow for cluster airflow-python-3.10-v1.24.2
- Deploying kind-airflow-python-3.10-v1.24.2 with Airflow Helm Chart.
- Copied chart sources to
/private/var/folders/v3/gvj4_mw152q556w2rrh7m46w0000gn/T/chart_edu__kir/chart
- Deploying Airflow from
/private/var/folders/v3/gvj4_mw152q556w2rrh7m46w0000gn/T/chart_edu__kir/chart
- NAME: airflow
- LAST DEPLOYED: Tue Aug 30 22:57:54 2022
- NAMESPACE: airflow
- STATUS: deployed
- REVISION: 1
- TEST SUITE: None
- NOTES:
- Thank you for installing Apache Airflow 2.3.4!
+ Deploying Airflow for cluster airflow-python-3.10-v1.24.2
+ Deploying kind-airflow-python-3.10-v1.24.2 with Airflow Helm Chart.
+ Copied chart sources to
/private/var/folders/v3/gvj4_mw152q556w2rrh7m46w0000gn/T/chart_edu__kir/chart
+ Deploying Airflow from
/private/var/folders/v3/gvj4_mw152q556w2rrh7m46w0000gn/T/chart_edu__kir/chart
+ NAME: airflow
+ LAST DEPLOYED: Tue Aug 30 22:57:54 2022
+ NAMESPACE: airflow
+ STATUS: deployed
+ REVISION: 1
+ TEST SUITE: None
+ NOTES:
+ Thank you for installing Apache Airflow 2.3.4!
- Your release is named airflow.
- You can now access your dashboard(s) by executing the following command(s)
and visiting the corresponding port at localhost in your browser:
+ Your release is named airflow.
+ You can now access your dashboard(s) by executing the following
command(s) and visiting the corresponding port at localhost in your browser:
- Airflow API server: kubectl port-forward svc/airflow-api-server
8080:8080 --namespace airflow
- Default Webserver (Airflow UI) Login credentials:
- username: admin
- password: admin
- Default Postgres connection credentials:
- username: postgres
- password: postgres
- port: 5432
+ Airflow API server: kubectl port-forward svc/airflow-api-server
8080:8080 --namespace airflow
+ Default Webserver (Airflow UI) Login credentials:
+ username: admin
+ password: admin
+ Default Postgres connection credentials:
+ username: postgres
+ password: postgres
+ port: 5432
- You can get Fernet Key value by running the following:
+ You can get Fernet Key value by running the following:
- echo Fernet Key: $(kubectl get secret --namespace airflow
airflow-fernet-key -o jsonpath="{.data.fernet-key}" | base64 --decode)
+ echo Fernet Key: $(kubectl get secret --namespace airflow
airflow-fernet-key -o jsonpath="{.data.fernet-key}" | base64 --decode)
- WARNING:
- Kubernetes workers task logs may not persist unless you configure log
persistence or remote logging!
- Logging options can be found at:
https://airflow.apache.org/docs/helm-chart/stable/manage-logs.html
- (This warning can be ignored if logging is configured with environment
variables or secrets backend)
+ WARNING:
+ Kubernetes workers task logs may not persist unless you configure
log persistence or remote logging!
+ Logging options can be found at:
https://airflow.apache.org/docs/helm-chart/stable/manage-logs.html
+ (This warning can be ignored if logging is configured with
environment variables or secrets backend)
- ###########################################################
- # WARNING: You should set a static webserver secret key #
- ###########################################################
+ ###########################################################
+ # WARNING: You should set a static webserver secret key #
+ ###########################################################
- You are using a dynamically generated webserver secret key, which can lead
to
- unnecessary restarts of your Airflow components.
+ You are using a dynamically generated webserver secret key, which can
lead to
+ unnecessary restarts of your Airflow components.
- Information on how to set a static webserver secret key can be found here:
-
https://airflow.apache.org/docs/helm-chart/stable/production-guide.html#api-secret-key
- Deployed kind-airflow-python-3.10-v1.24.2 with Airflow Helm Chart.
+ Information on how to set a static webserver secret key can be found
here:
+
https://airflow.apache.org/docs/helm-chart/stable/production-guide.html#api-secret-key
+ Deployed kind-airflow-python-3.10-v1.24.2 with Airflow Helm Chart.
- Airflow for Python 3.10 and K8S version v1.24.2 has been successfully
deployed.
+ Airflow for Python 3.10 and K8S version v1.24.2 has been successfully
deployed.
- The KinD cluster name: airflow-python-3.10-v1.24.2
- The kubectl cluster name: kind-airflow-python-3.10-v1.24.2.
+ The KinD cluster name: airflow-python-3.10-v1.24.2
+ The kubectl cluster name: kind-airflow-python-3.10-v1.24.2.
- KinD Cluster API server URL: http://localhost:48366
- Connecting to localhost:18150. Num try: 1
- Established connection to webserver at http://localhost:18150/health and
it is healthy.
- Airflow Web server URL: http://localhost:18150 (admin/admin)
+ KinD Cluster API server URL: http://localhost:48366
+ Connecting to localhost:18150. Num try: 1
+ Established connection to webserver at http://localhost:18150/health and
it is healthy.
+ Airflow Web server URL: http://localhost:18150 (admin/admin)
- NEXT STEP: You might now run tests or interact with Airflow via shell
(kubectl, pytest etc.) or k9s commands:
+ NEXT STEP: You might now run tests or interact with Airflow via shell
(kubectl, pytest etc.) or k9s commands:
- breeze k8s tests
+ breeze k8s tests
- breeze k8s shell
+ breeze k8s shell
- breeze k8s k9s
+ breeze k8s k9s
+#. Run Kubernetes tests
-8. Run Kubernetes tests
+ Note that the tests are executed in production container not in the CI
container.
+ There is no need for the tests to run inside the Airflow CI container image
as they only
+ communicate with the Kubernetes-run Airflow deployed via the production
image.
+ Those Kubernetes tests require virtualenv to be created locally with
Airflow installed.
+ The virtualenv required will be created automatically when the scripts are
run.
-Note that the tests are executed in production container not in the CI
container.
-There is no need for the tests to run inside the Airflow CI container image as
they only
-communicate with the Kubernetes-run Airflow deployed via the production image.
-Those Kubernetes tests require virtualenv to be created locally with Airflow
installed.
-The virtualenv required will be created automatically when the scripts are run.
+ #. You can run all the tests
-8a) You can run all the tests
+ .. code-block:: bash
-.. code-block:: bash
+ breeze k8s tests
- breeze k8s tests
+ .. code-block:: text
-.. code-block:: text
+ Using CPython 3.12.7
+ Creating virtual environment at: .venv
+ Activate with: source .venv/bin/activate
+ Resolved 775 packages in 84ms
+ Audited 190 packages in 1ms
+ Good version of kind installed: 0.26.0 in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin
+ Good version of kubectl installed: 1.31.0 in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin
+ Good version of helm installed: 3.16.4 in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin
+ Stable repo is already added
- Using CPython 3.12.7
- Creating virtual environment at: .venv
- Activate with: source .venv/bin/activate
- Resolved 775 packages in 84ms
- Audited 190 packages in 1ms
- Good version of kind installed: 0.26.0 in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin
- Good version of kubectl installed: 1.31.0 in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin
- Good version of helm installed: 3.16.4 in
/Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv/bin
- Stable repo is already added
+ Running tests with kind-airflow-python-3.10-v1.29.12 cluster.
+ Command to run: uv run pytest kubernetes-tests/tests/
+ Installed 74 packages in 179ms
+
/Users/jarek/IdeaProjects/airflow/.venv/lib/python3.12/site-packages/pytest_asyncio/plugin.py:208:
PytestDeprecationWarning: The configuration option
"asyncio_default_fixture_loop_scope" is unset.
+ The event loop scope for asynchronous fixtures will default to the
fixture caching scope. Future versions of pytest-asyncio will default the loop
scope for asynchronous fixtures to function scope. Set the default fixture loop
scope explicitly in order to avoid unexpected behavior in the future. Valid
fixture loop scopes are: "function", "class", "module", "package", "session"
- Running tests with kind-airflow-python-3.10-v1.29.12 cluster.
- Command to run: uv run pytest kubernetes-tests/tests/
- Installed 74 packages in 179ms
-
/Users/jarek/IdeaProjects/airflow/.venv/lib/python3.12/site-packages/pytest_asyncio/plugin.py:208:
PytestDeprecationWarning: The configuration option
"asyncio_default_fixture_loop_scope" is unset.
- The event loop scope for asynchronous fixtures will default to the fixture
caching scope. Future versions of pytest-asyncio will default the loop scope
for asynchronous fixtures to function scope. Set the default fixture loop scope
explicitly in order to avoid unexpected behavior in the future. Valid fixture
loop scopes are: "function", "class", "module", "package", "session"
+
warnings.warn(PytestDeprecationWarning(_DEFAULT_FIXTURE_LOOP_SCOPE_UNSET))
+
=======================================================================================================================================
test session starts
========================================================================================================================================
+ platform darwin -- Python 3.12.7, pytest-8.3.3, pluggy-1.5.0 --
/Users/jarek/IdeaProjects/airflow/.venv/bin/python3
+ cachedir: .pytest_cache
+ rootdir: /Users/jarek/IdeaProjects/airflow/kubernetes-tests
+ configfile: pyproject.toml
+ plugins: asyncio-0.24.0, cov-6.0.0, instafail-0.5.0, timeouts-1.2.1,
time-machine-2.16.0, custom-exit-code-0.3.0, icdiff-0.9, kgb-7.2,
rerunfailures-15.0, mock-3.14.0, unordered-0.6.1, anyio-4.6.2.post1,
xdist-3.6.1, requests-mock-1.12.1
+ asyncio: mode=Mode.STRICT, default_loop_scope=None
+ setup timeout: 0.0s, execution timeout: 0.0s, teardown timeout: 0.0s
+ collected 52 items
-
warnings.warn(PytestDeprecationWarning(_DEFAULT_FIXTURE_LOOP_SCOPE_UNSET))
-
=======================================================================================================================================
test session starts
========================================================================================================================================
- platform darwin -- Python 3.12.7, pytest-8.3.3, pluggy-1.5.0 --
/Users/jarek/IdeaProjects/airflow/.venv/bin/python3
- cachedir: .pytest_cache
- rootdir: /Users/jarek/IdeaProjects/airflow/kubernetes-tests
- configfile: pyproject.toml
- plugins: asyncio-0.24.0, cov-6.0.0, instafail-0.5.0, timeouts-1.2.1,
time-machine-2.16.0, custom-exit-code-0.3.0, icdiff-0.9, kgb-7.2,
rerunfailures-15.0, mock-3.14.0, unordered-0.6.1, anyio-4.6.2.post1,
xdist-3.6.1, requests-mock-1.12.1
- asyncio: mode=Mode.STRICT, default_loop_scope=None
- setup timeout: 0.0s, execution timeout: 0.0s, teardown timeout: 0.0s
- collected 52 items
+
kubernetes-tests/tests/kubernetes_tests/test_kubernetes_executor.py::TestKubernetesExecutor::test_integration_run_dag
PASSED
+ ...
[ 1%]
-
kubernetes-tests/tests/kubernetes_tests/test_kubernetes_executor.py::TestKubernetesExecutor::test_integration_run_dag
PASSED
- ...
[
1%]
+ #. You can enter an interactive shell to run tests one-by-one
-8b) You can enter an interactive shell to run tests one-by-one
+ This enters the virtualenv in ``kubernetes-tests/.venv`` folder:
-This enters the virtualenv in ``kubernetes-tests/.venv`` folder:
+ .. code-block:: bash
-.. code-block:: bash
-
- breeze k8s shell
+ breeze k8s shell
-Once you enter the environment, you receive this information:
+ Once you enter the environment, you receive this information:
-.. code-block:: text
+ .. code-block:: text
- Entering interactive k8s shell.
+ Entering interactive k8s shell.
- (kind-airflow-python-3.10-v1.24.2:KubernetesExecutor)>
+ (kind-airflow-python-3.10-v1.24.2:KubernetesExecutor)>
-In a separate terminal you can open the k9s CLI:
+ In a separate terminal you can open the k9s CLI:
-.. code-block:: bash
+ .. code-block:: bash
- breeze k8s k9s
+ breeze k8s k9s
-Use it to observe what's going on in your cluster.
+ Use it to observe what's going on in your cluster.
-9. Debugging in IntelliJ/PyCharm
+#. Debugging in IntelliJ/PyCharm
-It is very easy to running/debug Kubernetes tests with IntelliJ/PyCharm.
Unlike the regular tests they are
-in ``kubernetes_tests`` folder and if you followed the previous steps and
entered the shell using
-``breeze k8s shell`` command, you can setup your IDE very easy to run (and
debug) your
-tests using the standard IntelliJ Run/Debug feature. You just need a few steps:
+ It is very easy to running/debug Kubernetes tests with IntelliJ/PyCharm.
Unlike the regular tests they are
+ in ``kubernetes_tests`` folder and if you followed the previous steps and
entered the shell using
+ ``breeze k8s shell`` command, you can setup your IDE very easy to run (and
debug) your
+ tests using the standard IntelliJ Run/Debug feature. You just need a few
steps:
-9a) Add the virtualenv as interpreter for the project:
+ #. Add the virtualenv as interpreter for the project:
-.. image:: images/kubernetes-virtualenv.png
- :align: center
- :alt: Kubernetes testing virtualenv
+ .. image:: images/kubernetes-virtualenv.png
+ :align: center
+ :alt: Kubernetes testing virtualenv
-The virtualenv is created in your "Airflow" source directory in the
-``kubernetes-tests/.venv`` folder and you have to find ``python`` binary and
choose
-it when selecting interpreter.
+ The virtualenv is created in your "Airflow" source directory in the
+ ``kubernetes-tests/.venv`` folder and you have to find ``python`` binary
and choose
+ it when selecting interpreter.
-9b) Choose pytest as test runner:
+ #. Choose pytest as test runner:
-.. image:: images/pytest-runner.png
- :align: center
- :alt: Pytest runner
+ .. image:: images/pytest-runner.png
+ :align: center
+ :alt: Pytest runner
-9c) Run/Debug tests using standard "Run/Debug" feature of IntelliJ
+ #. Run/Debug tests using standard "Run/Debug" feature of IntelliJ
-.. image:: images/run-test.png
- :align: center
- :alt: Run/Debug tests
+ .. image:: images/run-test.png
+ :align: center
+ :alt: Run/Debug tests
-Make sure to select the ``kubernetes-tests/.venv`` as venv for your project.
+ Make sure to select the ``kubernetes-tests/.venv`` as venv for your
project.
-NOTE! The first time you run it, it will likely fail with
-``kubernetes.config.config_exception.ConfigException``:
-``Invalid kube-config file. Expected key current-context in kube-config``. You
need to add KUBECONFIG
-environment variable copying it from the result of "breeze k8s tests":
+ NOTE! The first time you run it, it will likely fail with
+ ``kubernetes.config.config_exception.ConfigException``:
+ ``Invalid kube-config file. Expected key current-context in
kube-config``. You need to add KUBECONFIG
+ environment variable copying it from the result of "breeze k8s tests":
-.. code-block:: bash
+ .. code-block:: bash
- echo ${KUBECONFIG}
+ echo ${KUBECONFIG}
-
/home/jarek/code/airflow/.build/.k8s-clusters/airflow-python-3.10-v1.28.13/.kube/config
+
/home/jarek/code/airflow/.build/.k8s-clusters/airflow-python-3.10-v1.28.13/.kube/config
-.. image:: images/kubeconfig-env.png
- :align: center
- :alt: Run/Debug tests
+ .. image:: images/kubeconfig-env.png
+ :align: center
+ :alt: Run/Debug tests
-The .env file with the KUBECONFIG variable is also set in
``kubernetes-tests/.env`` file - pointing
-to the file above - so you can also use it to set the KUBECONFIG variable in
your IDE by settings the
-``kubernetes-tests/`` folder as the folder where your IDE should look for the
.env file (if the IDE supports it)
+ The .env file with the KUBECONFIG variable is also set in
``kubernetes-tests/.env`` file - pointing
+ to the file above - so you can also use it to set the KUBECONFIG
variable in your IDE by settings the
+ ``kubernetes-tests/`` folder as the folder where your IDE should look
for the .env file (if the IDE supports it)
-You can iterate with tests while you are in the virtualenv. All the tests
requiring Kubernetes cluster
-are in "kubernetes_tests" folder. You can add extra ``pytest`` parameters then
(for example ``-s`` will
-print output generated test logs and print statements to the terminal
immediately. You should have
-kubernetes_tests as your working directory.
+ You can iterate with tests while you are in the virtualenv. All the
tests requiring Kubernetes cluster
+ are in "kubernetes_tests" folder. You can add extra ``pytest``
parameters then (for example ``-s`` will
+ print output generated test logs and print statements to the terminal
immediately. You should have
+ kubernetes_tests as your working directory.
-.. code-block:: bash
+ .. code-block:: bash
- pytest
tests/kubernetes_tests/test_kubernetes_executor.py::TestKubernetesExecutor::test_integration_run_dag_with_scheduler_failure
-s
+ pytest
tests/kubernetes_tests/test_kubernetes_executor.py::TestKubernetesExecutor::test_integration_run_dag_with_scheduler_failure
-s
-You can also run the tests with ``uv``
+ You can also run the tests with ``uv``
-.. code-block:: bash
+ .. code-block:: bash
- uv run --env .env pytest
tests/kubernetes_tests/test_kubernetes_executor.py::TestKubernetesExecutor::test_integration_run_dag_with_scheduler_failure
-s
+ uv run --env .env pytest
tests/kubernetes_tests/test_kubernetes_executor.py::TestKubernetesExecutor::test_integration_run_dag_with_scheduler_failure
-s
-You can modify the tests or KubernetesPodOperator and re-run them without
re-deploying
-Airflow to KinD cluster.
+ You can modify the tests or KubernetesPodOperator and re-run them
without re-deploying
+ Airflow to KinD cluster.
-10. Dumping logs
+#. Dumping logs
-Sometimes You want to see the logs of the cluster. This can be done with
``breeze k8s logs``.
+ Sometimes You want to see the logs of the clister. This can be done with
``breeze k8s logs``.
-.. code-block:: bash
+ .. code-block:: bash
- breeze k8s logs
+ breeze k8s logs
-11. Redeploying airflow
+#. Redeploying airflow
-Sometimes there are side effects from running tests. You can run ``breeze k8s
deploy-airflow --upgrade``
-without recreating the whole cluster.
+ Sometimes there are side effects from running tests. You can run ``breeze
k8s deploy-airflow --upgrade``
+ without recreating the whole cluster.
-.. code-block:: bash
+ .. code-block:: bash
- breeze k8s deploy-airflow --upgrade
+ breeze k8s deploy-airflow --upgrade
-If needed you can also delete the cluster manually (within the virtualenv
activated by
-``breeze k8s shell``:
+ If needed you can also delete the cluster manually (within the virtualenv
activated by
+ ``breeze k8s shell``:
-.. code-block:: bash
+ .. code-block:: bash
- kind get clusters
- kind delete clusters <NAME_OF_THE_CLUSTER>
+ kind get clusters
+ kind delete clusters <NAME_OF_THE_CLUSTER>
-Kind has also useful commands to inspect your running cluster:
+ Kind has also useful commands to inspect your running cluster:
-.. code-block:: text
+ .. code-block:: text
- kind --help
+ kind --help
-12. Stop KinD cluster when you are done
+#. Stop KinD cluster when you are done
-.. code-block:: bash
+ .. code-block:: bash
- breeze k8s delete-cluster
+ breeze k8s delete-cluster
-.. code-block:: text
+ .. code-block:: text
- Deleting KinD cluster airflow-python-3.10-v1.24.2!
- Deleting cluster "airflow-python-3.10-v1.24.2" ...
- KinD cluster airflow-python-3.10-v1.24.2 deleted!
+ Deleting KinD cluster airflow-python-3.10-v1.24.2!
+ Deleting cluster "airflow-python-3.10-v1.24.2" ...
+ KinD cluster airflow-python-3.10-v1.24.2 deleted!
Running complete k8s tests
