i'm quite new to GCP and been using mostly AWS. I am currently trying to play around with GCP and want to deploy a container using docker-compose
.
I set up a very basic docker-compose.yml file as follows:
# docker-compose.yml
version: '3.3'
services:
git:
image: alpine/git
volumes:
- ${PWD}:/git
command: "clone https://github.com/PHP-DI/demo.git"
composer:
image: composer
volumes:
- ${PWD}/demo:/app
command: "composer install"
depends_on:
- git
web:
image: php:7.4-apache
ports:
- "8080:${PORT:-80}"
- "8000:${PORT:-8000}"
volumes:
- ${PWD}/demo:/var/www/html
command: php -S 0.0.0.0:8000 -t /var/www/html
depends_on:
- composer
So the container will get the code from git, then install the dependencies using composer and finally be available on port 8000.
On my machine, running docker-compose up
does everything. However how can push this docker-compose to google cloud.
I have tried building a container using the docker/compose
image and a Dockerfile as follows:
FROM docker/compose
WORKDIR /opt
COPY docker-compose.yml .
WORKDIR /app
CMD docker-compose -f /opt/docker-compose.yml up web
Then push the container to the registry. And from there i tried deploying to:
/var/run/docker.sock
docker.sock
but i keep getting an error in the logs that /app
from the git service is read onlyI don't want to make a container by copying all local files into it then upload, as the dependencies could be really big thus making a heavy container to push.
I have a working docker-compose and just want to use it on GCP. What's the easiest way?
Take a look at Kompose. It can help you convert the docker compose instructions into Kuberenetes specific deployment and services. You can then apply the Kubernetes files against your GKE Clusters. Note that you will have to build the containers and store in Container Registry first and update the image tag in service definitions accordingly.
Compute engine is basically a virtual machine so just log in via ssh and install docker and docker-compose. After that docker-compose up
will run with no problem just like on your local machine.