Issue 1:
Apache Airflow version

2.4.0

What happened

ISSUE

I have run other dag files previously they all give this message even if they pass or fail.

Goal

Get this error fixed

Log that contains the error

I got this after running simple dag

241adsgf1108
*** Log file does not exist: /opt/airflow/logs/dag_id=numpy_pandas/run_id=manual__2022-09-27T16:31:22.968544+00:00/task_id=print_the_context/attempt=1.log
*** Fetching from: http://241adsgf1108:8793/dag_id=numpy_pandas/run_id=manual__2022-09-27T16:31:22.968544+00:00/task_id=print_the_context/attempt=1.log
*** !!!! Please make sure that all your Airflow components (e.g. schedulers, webservers and workers) have the same 'secret_key' configured in 'webserver' section and time is synchronized on all your machines (for example with ntpd) !!!!!
****** See more at https://airflow.apache.org/docs/apache-airflow/stable/configurations-ref.html#secret-key
****** Failed to fetch log file from worker. Client error '403 FORBIDDEN' for url 'http://241adsgf1108:8793/dag_id=numpy_pandas/run_id=manual__2022-09-27T16:31:22.968544+00:00/task_id=print_the_context/attempt=1.log'
For more information check: https://httpstatuses.com/403

Commands

docker build -t my-image-apache/airflow:latest-python3.8 .

docker-compose up

Environment

AWS EC2

Ubuntu 20.04

What you think should happen instead

Folder Structure

airflow /

docker-compose.yml

Dockerfile

dags [FOLDER]/

all_python_dag_files.py

How to reproduce

Files

my dag file

import pendulum

from airflow import DAG
#from airflow.decorators import task
from airflow.operators.python import PythonOperator

with DAG(
dag_id="numpy_pandas",
schedule=None,
start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
catchup=False,
tags=["example"],) as dag:

def numpy_something():
"""Print Numpy array."""
import numpy as np # <- THIS IS HOW NUMPY SHOULD BE IMPORTED IN THIS CASE
import pandas as pd

d = {'col1': [1, 2], 'col2': [3, 4]}
df = pd.DataFrame(data=d)
print(df)
a = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
print(a)
#a= 10
return a

run_this = PythonOperator(
task_id="print_the_context",
python_callable=numpy_something,
)

Operating System

Ubuntu 20.04.4 LTS

Versions of Apache Airflow Providers

dockerfile

FROM apache/airflow:latest-python3.8
COPY requirements.txt .
COPY personal_python_file.py /usr/local/airflow/dags/personal_python_file.py
RUN pip install -r requirements.txt

Deployment

Docker-Compose

Deployment details

docker-compose.yml

---
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:-my-image-apache/airflow:latest-python3.8}
### SAME AS IN MY DOCKERFILE "FROM apache/airflow:latest-python3.8" BUT I CAN MODIFY IT AS THE IAMGE THAT I GNERATE IS THE IMPORTANT ONE
# my-image-apache/airflow:latest-python3.8}
# build: .
environment:
&airflow-common-env
AIRFLOW__CORE__EXECUTOR: CeleryExecutor
AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:airflow@postgres/airflow
# For backward compatibility, with Airflow <2.3
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: 'false'
AIRFLOW__API__AUTH_BACKENDS: 'airflow.api.auth.backend.basic_auth'
_PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:-}

# I have added these
AIRFLOW__CORE__ENABLE_XCOM_PICKLING: 'true'
#AIRFLOW__CORE__DAGS_FOLDER: /opt/airflow/dags
#connect local and docker conatiner DAGS folers
#AIRFLOW__CORE__DAGS_FOLDER: ./dags

# AIRFLOW__CORE__PLUGINS_FOLDER: /opt/airflow/plugins
# AIRFLOW__CORE__LOGGING_CONFIG_CLASS: airflow.utils.log.logging_config.DEFAULT_LOGGING_CONFIG
# AIRFLOW__CORE__LOGGING_LEVEL: INFO

volumes:
- ./dags/:/opt/airflow/dags
- ./logs/:/opt/airflow/logs
- ./plugins/:/opt/airflow/plugins
user: "${AIRFLOW_UID:-50000}:0"
depends_on:
&airflow-common-depends-on
redis:
condition: service_healthy
postgres:
condition: service_healthy

services:
postgres:
image: postgres:13
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
expose:
- 6379
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 5s
timeout: 30s
retries: 50
restart: always

airflow-webserver:
<<: *airflow-common
command: webserver
ports:
- 8080:8080
healthcheck:
test: ["CMD", "curl", "--fail", "http://localhost:8080/health"]
interval: 10s
timeout: 10s
retries: 5
restart: always
stdin_open: true
tty: true
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
volumes:
- ./airflow:/usr/local/airflow

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
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully

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
environment:
<<: *airflow-common-env
# Required to handle warm shutdown of the celery workers properly
# See https://airflow.apache.org/docs/docker-stack/entrypoint.html#signal-propagation
DUMB_INIT_SETSID: "0"
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully

airflow-triggerer:
<<: *airflow-common
command: triggerer
healthcheck:
test: ["CMD-SHELL", 'airflow jobs check --job-type TriggererJob --hostname "$${HOSTNAME}"']
interval: 10s
timeout: 10s
retries: 5
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully

airflow-init:
<<: *airflow-common
entrypoint: /bin/bash
# yamllint disable rule:line-length
command:
- -c
- |
function ver() {
printf "%04d%04d%04d%04d" $${1//./ }
}
airflow_version=$$(AIRFLOW__LOGGING__LOGGING_LEVEL=INFO && gosu airflow airflow version)
airflow_version_comparable=$$(ver $${airflow_version})
min_airflow_version=2.2.0
min_airflow_version_comparable=$$(ver $${min_airflow_version})
if (( airflow_version_comparable < min_airflow_version_comparable )); then
echo
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!"
echo
exit 1
fi
if [[ -z "${AIRFLOW_UID}" ]]; then
echo
echo -e "\033[1;33mWARNING!!!: AIRFLOW_UID not set!\e[0m"
echo "If you are on Linux, you SHOULD follow the instructions below to set "
echo "AIRFLOW_UID environment variable, otherwise files will be owned by root."
echo "For other operating systems you can get rid of the warning with manually created .env file:"
echo " See: https://airflow.apache.org/docs/apache-airflow/stable/start/docker.html#setting-the-right-airflow-user"
echo
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
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)))"
echo
warning_resources="true"
fi
if (( cpus_available < 2 )); then
echo
echo -e "\033[1;33mWARNING!!!: Not enough CPUS available for Docker.\e[0m"
echo "At least 2 CPUs recommended. You have $${cpus_available}"
echo
warning_resources="true"
fi
if (( disk_available < one_meg * 10 )); then
echo
echo -e "\033[1;33mWARNING!!!: Not enough Disk space available for Docker.\e[0m"
echo "At least 10 GBs recommended. You have $$(numfmt --to iec $$((disk_available * 1024 )))"
echo
warning_resources="true"
fi
if [[ $${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"
echo
fi
mkdir -p /sources/logs /sources/dags /sources/plugins
chown -R "${AIRFLOW_UID}:0" /sources/{logs,dags,plugins}
exec /entrypoint airflow version
# yamllint enable rule:line-length
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}
_PIP_ADDITIONAL_REQUIREMENTS: ''
user: "0:0"
volumes:
- .:/sources

airflow-cli:
<<: *airflow-common
profiles:
- debug
environment:
<<: *airflow-common-env
CONNECTION_CHECK_MAX_COUNT: "0"
# Workaround for entrypoint issue. See: https://github.com/apache/airflow/issues/16252
command:
- bash
- -c
- airflow

# You can enable flower by adding "--profile flower" option e.g. docker-compose --profile flower up
# or by explicitly targeted on the command line e.g. docker-compose up flower.
# See: https://docs.docker.com/compose/profiles/
flower:
<<: *airflow-common
command: celery flower
profiles:
- flower
ports:
- 5555:5555
healthcheck:
test: ["CMD", "curl", "--fail", "http://localhost:5555/"]
interval: 10s
timeout: 10s
retries: 5
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully

volumes:
postgres-db-volume:

Anything else

Tried Already:

https://stackoverflow.com/questions/59591008/airflow-giving-log-file-does-not-exist-error-while-running-on-docker

https://forum.astronomer.io/t/log-file-does-not-exist/277 (can not access jira link)

Are you willing to submit PR?

Yes I am willing to submit a PR!

Code of Conduct

I agree to follow this project's Code of Conduct

Issue 2:
Discussed in #26490

Originally posted by emredjan September 19, 2022

Apache Airflow version

2.4.0

What happened

When running tasks on a remote celery worker, webserver fails to fetch logs from the machine, giving a '403 - Forbidden' error on version 2.4.0. This behavior does not happen on 2.3.3, where the remote logs are retrieved and displayed successfully.

The webserver / secret_key configuration is the same in all nodes (the config files are synced), and their time is synchronized using a central NTP server, making the solution in the warning message not applicable.

My limited analysis pointed to the serve_logs.py file, and the flask request object that's passed to it, but couldn't find the root cause.

What you think should happen instead

It should fetch and show remote celery worker logs on the webserver UI correctly, as it did in previous versions.

How to reproduce

Use airflow version 2.4.0

Use CeleryExecutor with RabbitMQ

Use a separate Celery worker machine

Run a dag/task on the remote worker

Try to display task log on the web UI

Operating System

Red Hat Enterprise Linux 8.6 (Ootpa)

Versions of Apache Airflow Providers

apache-airflow-providers-celery==3.0.0
apache-airflow-providers-common-sql==1.1.0
apache-airflow-providers-ftp==3.0.0
apache-airflow-providers-hashicorp==3.0.0
apache-airflow-providers-http==3.0.0
apache-airflow-providers-imap==3.0.0
apache-airflow-providers-microsoft-mssql==3.0.0
apache-airflow-providers-mysql==3.0.0
apache-airflow-providers-odbc==3.0.0
apache-airflow-providers-sftp==3.0.0
apache-airflow-providers-sqlite==3.0.0
apache-airflow-providers-ssh==3.0.0

Deployment

Virtualenv installation

Deployment details

Using CeleryExecutor / rabbitmq with 2 servers

Anything else

All remote task executions has the same problem.

Are you willing to submit PR?

Yes I am willing to submit a PR!

Code of Conduct

I agree to follow this project's Code of Conduct