ZackingIt opened a new issue #18025:
URL: https://github.com/apache/airflow/issues/18025
### Apache Airflow version
2.1.3 (latest released)
### Operating System
Ubuntu VERSION="16.04.6 LTS (Xenial Xerus)"
### Versions of Apache Airflow Providers
2.1.3
### Deployment
Docker-Compose
### Deployment details
My docker-compose.yaml is identical to the default dev box example except I
mount a few additional volumes:
```
volumes:
- ./dags:/opt/airflow/dags
- ./logs:/opt/airflow/logs
- ./plugins:/opt/airflow/plugins
- ./kubernetes_configs:/opt/airflow/kubernetes_configs
- ./airflow.cfg:/opt/airflow/airflow.cfg
```
### What happened
KubernetesPodOperator seems to be *opening* the config file at the location,
and then providing the opened file contents as the "file path", rather than
simply providing the generated string which is the composition of the
template_path and the additional config_file path.
```
AIRFLOW_CTX_DAG_RUN_ID=manual__2021-09-03T20:22:20.691296+00:00
[2021-09-03 20:22:23,803] {taskinstance.py:1462} ERROR - Task failed with
exception
Traceback (most recent call last):
File
"/home/airflow/.local/lib/python3.6/site-packages/airflow/models/taskinstance.py",
line 1164, in _run_raw_task
self._prepare_and_execute_task_with_callbacks(context, task)
File
"/home/airflow/.local/lib/python3.6/site-packages/airflow/models/taskinstance.py",
line 1282, in _prepare_and_execute_task_with_callbacks
result = self._execute_task(context, task_copy)
File
"/home/airflow/.local/lib/python3.6/site-packages/airflow/models/taskinstance.py",
line 1312, in _execute_task
result = task_copy.execute(context=context)
File
"/home/airflow/.local/lib/python3.6/site-packages/airflow/providers/cncf/kubernetes/operators/kubernetes_pod.py",
line 336, in execute
config_file=self.config_file,
File
"/home/airflow/.local/lib/python3.6/site-packages/airflow/kubernetes/kube_client.py",
line 145, in get_kube_client
client_conf = _get_kube_config(in_cluster, cluster_context, config_file)
File
"/home/airflow/.local/lib/python3.6/site-packages/airflow/kubernetes/kube_client.py",
line 46, in _get_kube_config
load_kube_config(client_configuration=cfg, config_file=config_file,
context=cluster_context)
File
"/home/airflow/.local/lib/python3.6/site-packages/airflow/kubernetes/refresh_config.py",
line 123, in load_kube_config
loader = _get_kube_config_loader_for_yaml_file(config_file,
active_context=context, config_persister=None)
File
"/home/airflow/.local/lib/python3.6/site-packages/airflow/kubernetes/refresh_config.py",
line 105, in _get_kube_config_loader_for_yaml_file
with open(filename) as f:
FileNotFoundError: [Errno 2] No such file or directory: 'apiVersion:
batch/v1beta1\nkind: CronJob\nmetadata:\n name: zek-01\nspec:\n schedule: "0
*/1 * * *"\n concurrencyPolicy: Forbid\n jobTemplate:\n spec:\n
template:\n metadata:\n labels:\n
networkpolicy.xandr.com/unrestrictedEgress: "true"\n spec:\n
containers:\n - name: zek-01\n image:
docker.artifactory.prod.adnxs.net/ssp-object-sync:0.87\n env:\n
- name: GROUP\n value: "1"\n - name: ENV\n
value: "TEST"\n - name: SCRIPT\n value:
"ADX-CREATIVE-REGISTER"\n - name: "PARAM_api_user"\n
valueFrom:\n secretKeyRef:\n name:
ssp-object-sync-secrets-production\n key: "PARAM_api_user"\n
- name: "PARAM_api_passwd"\n valueFrom:\n
secretKeyRef:\n name: ssp-o
bject-sync-secrets-production\n key: "PARAM_api_passwd"\n
- name: "PARAM_cron_db_user"\n valueFrom:\n
secretKeyRef:\n name: ssp-object-sync-secrets-production\n
key: "PARAM_cron_db_user"\n - name:
"PARAM_cron_db_passwd"\n valueFrom:\n
secretKeyRef:\n name: ssp-object-sync-secrets-production\n
key: "PARAM_cron_db_passwd"\n - name:
"PARAM_int_db_user"\n valueFrom:\n secretKeyRef:\n
name: ssp-object-sync-secrets-production\n
key: "PARAM_int_db_user"\n - name: "PARAM_int_db_passwd"\n
valueFrom:\n secretKeyRef:\n name:
ssp-object-sync-secrets-production\n key:
"PARAM_int_db_passwd"\n resources:\n limits:\n
cpu: "1"\n memory: "2.5Gi
"\n requests:\n cpu: "0.1"\n
memory: "1Gi"\n volumeMounts:\n - mountPath:
/var/log/adnexus\n name: log-volume\n volumes:\n
- name: log-volume\n emptyDir: {}\n restartPolicy: Never'
[2021-09-03 20:22:23,804] {taskinstance.py:1512} INFO - Marking task as
FAILED. dag_id=aaa_sample_dag_2, task_id=noop_zek_1,
execution_date=20210903T202220, start_date=20210903T202223,
end_date=20210903T202223
[2021-09-03 20:22:23,854] {local_task_job.py:151} INFO - Task exited with
return code 1
[2021-09-03 20:22:23,875] {local_task_job.py:261} INFO - 0 downstream tasks
scheduled from follow-on schedule check
```
### What you expected to happen
This is the code that's running: -- I would expect
`config_file='kubernetes_configs/foo.yaml'` to
generate the correct filepath and for the KubePodOperator to consume the
generated *filepath*, not the generated *filepath contents*.
```
args = {
'owner': 'sup_team',
'start_date': days_ago(1)
}
dag = DAG(dag_id = 'aaa_sample_dag_2', default_args=args,
schedule_interval=None, template_searchpath="/opt/airflow/")
with dag:
kube_operator_1 = KubernetesPodOperator(
task_id= 'noop_zek_1',
name='zekk',
namespace='default',
cmds=['echo'],
in_cluster=False,
do_xcom_push=False,
config_file='kubernetes_configs/foo.yaml'
)
kube_operator_1
```
### How to reproduce
You can reproduce with simple docker-compose up with following
docker-compose.yaml file -- just make sure the final result has a
`kubernetes_config` folder with a `foo.yaml` file inside:
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
#
# Basic Airflow cluster configuration for CeleryExecutor with Redis and
PostgreSQL.
#
# WARNING: This configuration is for local development. Do not use it in a
production deployment.
#
# This configuration supports basic configuration using environment
variables or an .env file
# The following variables are supported:
#
# AIRFLOW_IMAGE_NAME - Docker image name used to run Airflow.
# Default: apache/airflow:master-python3.8
# AIRFLOW_UID - User ID in Airflow containers
# Default: 50000
# AIRFLOW_GID - Group ID in Airflow containers
# Default: 0
#
# Those configurations are useful mostly in case of standalone
testing/running Airflow in test/try-out mode
#
# _AIRFLOW_WWW_USER_USERNAME - Username for the administrator account (if
requested).
# Default: airflow
# _AIRFLOW_WWW_USER_PASSWORD - Password for the administrator account (if
requested).
# Default: airflow
# _PIP_ADDITIONAL_REQUIREMENTS - Additional PIP requirements to add when
starting all containers.
# Default: ''
#
# Feel free to modify this file to suit your needs.
---
version: '3'
x-airflow-common:
&airflow-common
# In order to add custom dependencies or upgrade provider packages you can
use your extended image.
# Comment the image line, place your Dockerfile in the directory where you
placed the docker-compose.yaml
# and uncomment the "build" line below, Then run `docker-compose build` to
build the images.
image: ${AIRFLOW_IMAGE_NAME:-apache/airflow:2.1.3}
# build: .
environment:
&airflow-common-env
AIRFLOW__CORE__EXECUTOR: CeleryExecutor
AIRFLOW__CORE__SQL_ALCHEMY_CONN:
postgresql+psycopg2://airflow:airflow@postgres/airflow
AIRFLOW__CELERY__RESULT_BACKEND:
db+postgresql://airflow:airflow@postgres/airflow
AIRFLOW__CELERY__BROKER_URL: redis://:@redis:6379/0
AIRFLOW__CORE__FERNET_KEY: ''
AIRFLOW__CORE__DAGS_ARE_PAUSED_AT_CREATION: 'true'
AIRFLOW__CORE__LOAD_EXAMPLES: 'true'
AIRFLOW__API__AUTH_BACKEND: 'airflow.api.auth.backend.basic_auth'
_PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:-}
volumes:
- ./dags:/opt/airflow/dags
- ./logs:/opt/airflow/logs
- ./plugins:/opt/airflow/plugins
- ./kubernetes_configs:/opt/airflow/kubernetes_configs
- ./airflow.cfg:/opt/airflow/airflow.cfg
user: "${AIRFLOW_UID:-50000}:${AIRFLOW_GID:-0}"
depends_on:
redis:
condition: service_healthy
postgres:
condition: service_healthy
services:
postgres:
image: postgres:13
deploy:
resources:
limits:
cpus: 2
memory: 2096M
reservations:
cpus: 1
memory: 1048M
environment:
POSTGRES_USER: airflow
POSTGRES_PASSWORD: airflow
POSTGRES_DB: airflow
volumes:
- postgres-db-volume:/var/lib/postgresql/data
healthcheck:
test: ["CMD", "pg_isready", "-U", "airflow"]
interval: 5s
retries: 5
restart: always
redis:
image: redis:latest
deploy:
resources:
limits:
cpus: 2
memory: 2096M
reservations:
cpus: 1
memory: 1048M
ports:
- 6379:6379
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 5s
timeout: 30s
retries: 50
restart: always
airflow-webserver:
<<: *airflow-common
command: webserver
deploy:
resources:
limits:
cpus: 2
memory: 2096M
reservations:
cpus: 1
memory: 1048M
ports:
- 8080:8080
healthcheck:
test: ["CMD", "curl", "--fail", "http://localhost:8080/health";]
interval: 10s
timeout: 10s
retries: 5
restart: always
airflow-scheduler:
<<: *airflow-common
command: scheduler
healthcheck:
test: ["CMD-SHELL", 'airflow jobs check --job-type SchedulerJob
--hostname "$${HOSTNAME}"']
interval: 10s
timeout: 10s
retries: 5
restart: always
airflow-worker:
<<: *airflow-common
command: celery worker
healthcheck:
test:
- "CMD-SHELL"
- 'celery --app airflow.executors.celery_executor.app inspect ping
-d "celery@$${HOSTNAME}"'
interval: 10s
timeout: 10s
retries: 5
restart: always
airflow-init:
<<: *airflow-common
entrypoint: /bin/bash
command:
- -c
- |
function ver() {
printf "%04d%04d%04d%04d" $${1//./ }
}
airflow_version=$$(gosu airflow airflow version)
airflow_version_comparable=$$(ver $${airflow_version})
min_airflow_version=2.1.0
min_airlfow_version_comparable=$$(ver $${min_airflow_version})
if (( airflow_version_comparable < min_airlfow_version_comparable
)); then
echo -e "\033[1;31mERROR!!!: Too old Airflow version
$${airflow_version}!\e[0m"
echo "The minimum Airflow version supported:
$${min_airflow_version}. Only use this or higher!"
exit 1
fi
if [[ -z "${AIRFLOW_UID}" ]]; then
echo -e "\033[1;31mERROR!!!: AIRFLOW_UID not set!\e[0m"
echo "Please follow these instructions to set AIRFLOW_UID and
AIRFLOW_GID environment variables:
https://airflow.apache.org/docs/apache-airflow/stable/start/docker.html#initializing-environment";
exit 1
fi
one_meg=1048576
mem_available=$$(($$(getconf _PHYS_PAGES) * $$(getconf PAGE_SIZE) /
one_meg))
cpus_available=$$(grep -cE 'cpu[0-9]+' /proc/stat)
disk_available=$$(df / | tail -1 | awk '{print $$4}')
warning_resources="false"
if (( mem_available < 4000 )) ; then
echo -e "\033[1;33mWARNING!!!: Not enough memory available for
Docker.\e[0m"
echo "At least 4GB of memory required. You have $$(numfmt --to iec
$$((mem_available * one_meg)))"
warning_resources="true"
fi
if (( cpus_available < 2 )); then
echo -e "\033[1;33mWARNING!!!: Not enough CPUS available for
Docker.\e[0m"
echo "At least 2 CPUs recommended. You have $${cpus_available}"
warning_resources="true"
fi
if (( disk_available < one_meg * 10 )); then
echo -e "\033[1;33mWARNING!!!: Not enough Disk space available for
Docker.\e[0m"
echo "At least 10 GBs recommended. You have $$(numfmt --to iec
$$((disk_available * 1024 )))"
warning_resources="true"
fi
if [[ $${warning_resources} == "true" ]]; then
echo
echo -e "\033[1;33mWARNING!!!: You have not enough resources to
run Airflow (see above)!\e[0m"
echo "Please follow the instructions to increase amount of
resources available:"
echo "
https://airflow.apache.org/docs/apache-airflow/stable/start/docker.html#before-you-begin";
fi
mkdir -p /sources/logs /sources/dags /sources/plugins
chown -R "${AIRFLOW_UID}:${AIRFLOW_GID}" /sources/{logs,dags,plugins}
exec /entrypoint airflow version
environment:
<<: *airflow-common-env
_AIRFLOW_DB_UPGRADE: 'true'
_AIRFLOW_WWW_USER_CREATE: 'true'
_AIRFLOW_WWW_USER_USERNAME: ${_AIRFLOW_WWW_USER_USERNAME:-airflow}
_AIRFLOW_WWW_USER_PASSWORD: ${_AIRFLOW_WWW_USER_PASSWORD:-airflow}
user: "0:${AIRFLOW_GID:-0}"
volumes:
- .:/sources
flower:
<<: *airflow-common
command: celery flower
ports:
- 5555:5555
healthcheck:
test: ["CMD", "curl", "--fail", "http://localhost:5555/";]
interval: 10s
timeout: 10s
retries: 5
restart: always
volumes:
postgres-db-volume:
### Anything else
Problem occurs every time.
### Are you willing to submit PR?
- [ ] Yes I am willing to submit a PR!
### Code of Conduct
- [X] I agree to follow this project's [Code of
Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)
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