Docker compose fails. Why is my docker compose using docker.io? - docker

Question

I am having problems running docker compose (the yaml file later). It should build three containers: Jupyter, mlflow and postgres but for some reason it only builds postgress.
The error message is
Building mlflow
[+] Building 0.7s (5/9)
=> [internal] load build definition from Dockerfile 0.0s
=> => transferring dockerfile: 38B 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 34B 0.0s
=> ERROR [internal] load metadata for docker.io/library/python:3.7 0.6s
=> ERROR [1/5] FROM docker.io/library/python:3.7 0.1s
=> => resolve docker.io/library/python:3.7 0.1s
=> [internal] load build context 0.0s
------
> [internal] load metadata for docker.io/library/python:3.7:
------
------
> [1/5] FROM docker.io/library/python:3.7:
------
failed to solve with frontend dockerfile.v0: failed to build LLB: failed to load cache key: unexpected status code https://dockerhub.azk8s.cn/v2/library/python/manifests/3.7: 403 Forbidden
ERROR: Service 'mlflow' failed to build : Build failed
Looking at the error message I notices that it says
=> ERROR [internal] load metadata for docker.io/library/python:3.7 0.6s
=> ERROR [1/5] FROM docker.io/library/python:3.7
So I looked it up and I found this article in which it says that
Docker.Io is the enterprise edition of Docker, and is only available
to paying customers
So why is my Docker image using a pay only repository(?)
So far I have used docker multiple time without problem, and I never knew about this "docker.io" what is this exactly?
And why progres could build even though it used also this pay only version?
How can I use the community edition? Or should I?
It this the root of the problem?
For reference here is the yaml file
version: '3.7'
services:
jupyter:
user: root
build:
context: .
dockerfile: ./docker/jupyter/Dockerfile
target: ${JUPYTER_TARGET}
args:
- MLFLOW_ARTIFACT_STORE=/${MLFLOW_ARTIFACT_STORE}
- MLFLOW_VERSION=${MLFLOW_VERSION}
- JUPYTER_BASE_IMAGE=${JUPYTER_BASE_IMAGE}
- JUPYTER_BASE_VERSION=${JUPYTER_BASE_VERSION}
- JUPYTER_USERNAME=${JUPYTER_USERNAME}
image: ${IMAGE_OWNER}/${REPO_SLUG}/${JUPYTER_TARGET}:${VERSION}
ports:
- "${JUPYTER_PORT}:${JUPYTER_PORT}"
depends_on:
- mlflow
environment:
MLFLOW_TRACKING_URI: ${MLFLOW_TRACKING_URI}
JUPYTER_ENABLE_LAB: ${JUPYTER_ENABLE_LAB}
NB_USER: ${JUPYTER_USERNAME}
NB_UID: ${JUPYTER_UID}
CHOWN_HOME: "yes"
CHOWN_HOME_OPTS: '-R'
CHOWN_EXTRA: ${JUPYTER_CHOWN_EXTRA}
CHOWN_EXTRA_OPTS: '-R'
volumes:
- ./:/home/${JUPYTER_USERNAME}/work
- ./${MLFLOW_ARTIFACT_STORE}:/${MLFLOW_ARTIFACT_STORE}
mlflow:
build:
context: ./docker/mlflow
args:
- MLFLOW_VERSION=${MLFLOW_VERSION}
image: ${IMAGE_OWNER}/${REPO_SLUG}/${MLFLOW_IMAGE_NAME}:${VERSION}
expose:
- "${MLFLOW_TRACKING_SERVER_PORT}"
ports:
- "${MLFLOW_TRACKING_SERVER_PORT}:${MLFLOW_TRACKING_SERVER_PORT}"
depends_on:
- postgres
environment:
MLFLOW_TRACKING_SERVER_HOST: ${MLFLOW_TRACKING_SERVER_HOST}
MLFLOW_TRACKING_SERVER_PORT: ${MLFLOW_TRACKING_SERVER_PORT}
MLFLOW_ARTIFACT_STORE: ${MLFLOW_ARTIFACT_STORE}
MLFLOW_BACKEND_STORE: ${MLFLOW_BACKEND_STORE}
POSTGRES_USER: ${POSTGRES_USER}
POSTGRES_PASSWORD: ${POSTGRES_PASSWORD}
POSTGRES_DATABASE: ${POSTGRES_DATABASE}
POSTGRES_PORT: ${POSTGRES_PORT}
WAIT_FOR_IT_TIMEOUT: ${WAIT_FOR_IT_TIMEOUT}
volumes:
- ./${MLFLOW_ARTIFACT_STORE}:/${MLFLOW_ARTIFACT_STORE}
postgres:
user: "${POSTGRES_UID}:${POSTGRES_GID}"
build:
context: ./docker/postgres
image: ${IMAGE_OWNER}/${REPO_SLUG}/${POSTGRES_IMAGE_NAME}:${VERSION}
restart: always
environment:
POSTGRES_PASSWORD: ${POSTGRES_PASSWORD}
POSTGRES_USER: ${POSTGRES_USER}
ports:
- "${POSTGRES_PORT}:${POSTGRES_PORT}"
volumes:
- ./${POSTGRES_STORE}:/var/lib/postgresql/data