I have an existing Docker Compose project that is currently used to orchestrate several services. However, I now want to integrate an additional service, in this case, Mayan EDMS, which has its own Docker Compose file.
---
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: ${AIRFLOW_IMAGE_NAME:-apache/airflow:2.3.3}
# build: .
environment:
&airflow-common-env
AIRFLOW__CORE__EXECUTOR: CeleryExecutor
AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:${POSTGRES_PASSWORD}@postgres/airflow
# For backward compatibility, with Airflow <2.3
AIRFLOW__CORE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:${POSTGRES_PASSWORD}@postgres/airflow
AIRFLOW__CELERY__RESULT_BACKEND: db+postgresql://airflow:${POSTGRES_PASSWORD}@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'
ENVIRONMENT: '${ENVIRONMENT}'
TENANT_ID: '${TENANT_ID}'
APPLICATION_ID: '${APPLICATION_ID}'
SECRET_VALUE: '${SECRET_VALUE}'
# Modificación
# Pip packages
_PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:- azure-storage-file-datalake openpyxl azure.keyvault azure.identity python-dotenv}
volumes:
- ./airflow_dags:/opt/airflow/dags
- ./airflow_logs:/opt/airflow/logs
- ./airflow_plugins:/opt/airflow/plugins
user: "${AIRFLOW_UID:-50000}:0"
depends_on:
&airflow-common-depends-on
redis:
condition: service_healthy
postgres:
condition: service_healthy
services:
postgres:
container_name: postgresql_airflow
image: postgres:13
environment:
POSTGRES_USER: airflow
POSTGRES_PASSWORD: ${POSTGRES_PASSWORD}
POSTGRES_DB: airflow
expose:
- "5432"
ports:
- "5433:5432"
volumes:
- airflow-db-volume:/var/lib/postgresql/data
healthcheck:
test: ["CMD", "pg_isready", "-U", "airflow"]
interval: 5s
retries: 5
restart: always
redis:
container_name: redis_airflow
image: redis:latest
expose:
- 6379
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 5s
timeout: 30s
retries: 50
restart: always
airflow-webserver:
container_name: 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
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
airflow-scheduler:
container_name: airflow_scheduler
<<: *airflow-common
command: scheduler
healthcheck:
test: ["CMD-SHELL", 'airflow jobs check --job-type SchedulerJob --hostname "$${HOSTNAME}"']
interval: 10s
timeout: 10s
retries: 5
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
airflow-worker:
container_name: airflow_worker
<<: *airflow-common
command: celery worker
healthcheck:
test:
- "CMD-SHELL"
- 'celery --app airflow.executors.celery_executor.app inspect ping -d "celery@$${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:
container_name: airflow_triggerer
<<: *airflow-common
command: triggerer
healthcheck:
test: ["CMD-SHELL", 'airflow jobs check --job-type TriggererJob --hostname "$${HOSTNAME}"']
interval: 10s
timeout: 10s
retries: 5
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
airflow-init:
container_name: airflow_init
<<: *airflow-common
entrypoint: /bin/bash
# yamllint disable rule:line-length
command:
- -c
- |
function ver() {
printf "%04d%04d%04d%04d" $${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:-belero-admin}
_AIRFLOW_WWW_USER_PASSWORD: ${_AIRFLOW_WWW_USER_PASSWORD:-${AIRFLOW_PASSWORD}}
_PIP_ADDITIONAL_REQUIREMENTS: ''
user: "0:0"
volumes:
- .:/sources
airflow-cli:
container_name: 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:
container_name: airflow_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
djangoappdev:
container_name: django_app_dev
build: .
environment:
ENVIRONMENT: '${ENVIRONMENT}'
TENANT_ID: '${TENANT_ID}'
APPLICATION_ID: '${APPLICATION_ID}'
SECRET_VALUE: '${SECRET_VALUE}'
ports:
# Where the django app runs
- "8001:8001"
volumes:
- ./beleroforms:/code/beleroforms
- ./beleroforms_app:/code/beleroforms_app
djangodb:
container_name: django_app_db_dev
# image: postgres:latest
image: postgres:14.7
volumes:
- postgres_data:/var/lib/postgresql/data/
environment:
- "POSTGRES_USER=django"
- "POSTGRES_PASSWORD=${POSTGRES_PASSWORD_DJANGO}"
- "POSTGRES_DB=django"
expose:
- "5432"
ports:
- "5434:5432"
volumes:
airflow-db-volume:
airflow_dags:
airflow_logs:
airflow_plugins:
postgres_data:
# beleroforms:
# beleroforms_app:
What is the best way to add Mayan's Docker Compose file to my existing project, how can I ensure that both files run consistently and communicate with each other if necessary?
I would very much appreciate any guidance or practical examples on how to achieve this integration without causing conflicts between existing and new services.
Thanks in advance for your help!
You can use the -f flag to combine multiple compose files
To use multiple override files, or an override file with a different name, you can use the -f option to specify the list of files. Compose merges files in the order they're specified on the command line. See the docker compose command reference for more information about using -f.
A practical example for your use-case:
docker-compose -f compose.yml -f mayan-compose.yml up -d
The documentation however lists a bunch of rules for merging, which you should be aware of. I recommend reading the full list but some key points:
For single-value options like image, command or mem_limit, the new value replaces the old value.
For the multi-value options ports, expose, external_links, dns, dns_search, and tmpfs, Compose concatenates both sets of values.
In the case of environment, labels, volumes, and devices, Compose "merges" entries together with locally defined values taking precedence. For environment and labels, the environment variable or label name determines which value is used.
Entries for volumes and devices are merged using the mount path in the container.