In Docker Hub website Is it possible to build an automated build for an Arm Image ?
I have modified my existing DockerFile to use an Arm base image, but it fails on the next line when it tries to run the apk command with exec format error. So it looks like Docker Hub is trying to build as Intel despite base image being built for Arm.
Is it possible to build Arm image with Docker Hub website or not ?
If not can anyone provide succint instructions on how to build Arm Image from my Dockerfile either by
Using my (Intel PC) from the docker command line
Using my (Intel Mac) from the docker command line
Using QNAP TS131P Container station, (since this is natively Arm maybe this is simpler)
Turned out to be relatively easy using the QNAP, alot simpler than it seemed from the posts I had read, I think my confusion was these posts were about building Arm version on an Intel machine, which i didnt need to do. And all the Arm specific instructions were for Raspberry Pi which had its own problems.
Created new empty repository in DockerHub
Uploaded my DockerFile to my webserver
ssh qnapserver
docker build DockerFileUrl
docker login DockerHubUsername DockerHubPassword
docker images (to get imageId of built image)
docker tag imageId DockerHubNameSpace/DockerHubRepository:latest
docker push DockerHubNameSpace/DockerHubRepository:latest
The push worked, and I was then able to use ContainerStation to get the image from Docker Hub and run in a container.
I have followed this guide from Google documentation in order to be able to push a custom Docker image to Google Container Registry and then be able to start a new GCE instance with this image. At first I wanted to try using an anaconda3 public image from docker hub without any modification (in order to test).
So here is the steps I have done so far after installing gcloud and docker:
gcloud auth configure-docker -> configured docker with my gcloud crendentials
docker pull continuumio/anaconda3 -> pulled the public image
docker tag continuumio/anaconda3 eu.gcr.io/my-project-id/anaconda3 -> tagged the local image with the registry name as specified in the doc
docker push eu.gcr.io/my-project-id/anaconda3 -> pushed the image to GCR
Good ! I am now able to see my image trough GCR interface, and also able to deploy it with GCE. I choose to deploy it with a f1-micro instance, Container-Optimized OS 67-10575.62.0 stable, 10 Go boot disk, Allow HTTP traffic, etc.
But when I connect with ssh to the freshly new created VM instance, I can't find anaconda3 librairies (which are supposed to be created in /opt/conda). Instead, I can see a /opt/google directory which makes me think that the image has not been deployed correctly and GCE is using a default image...
So I tried to check if the image was pushed correctly in GCR, so I decided to delete my local image and pull it once again from GCR:
docker rmi -f eu.gcr.io/my-project-id/anaconda3
docker pull eu.gcr.io/my-project-id/anaconda3:latest
I run the image
docker run -t -i eu.gcr.io/my-project-id/anaconda3
and I can see that everything is fine, I have anaconda3 installed correctly inside /opt/conda with all the toolts needed (Pandas, Numpy, Jupyter notebook, etc.)
I tried to find people with the same problem as me without any success... maybe I have done something wrong in my proccess ?
Thanks !
TL;DR My problem is that I have pushed an anaconda3 image on Google GCR, but when I launch a virtual instance with this image, I do not have anaconda on it
It's normal that you can't find anaconda libraries installed directly on the GCE instance.
Actually, when you choose to deploy a container image on a GCE VM instance, a Docker container is started from the image you provide (in your example, eu.gcr.io/my-project-id/anaconda3). The libraries are not installed on the host, but rather inside that container (run docker ps to see it, but normally it has the same name as your VM instance). If you run something like :
docker exec -it <docker_container_name> ls /opt/conda
Then you should see the anaconda libraries, only existing inside the container.
When you run docker run -t -i eu.gcr.io/my-project-id/anaconda3, you're actually starting the container and running an interactive bash session inside that container (see the CMD here). That's why you can find anaconda libraries : you are inside the container!
Containerization software (docker here) provides isolation between your host and your containers. I'll suggest you to read documentation about containerization, Docker and how to run containers on Container-Optimized OS.
I have a private registry with a set of images. It can be visualized as a store of applications.
My app can take these applications and run them on other machines.
To achieve this, my app first pull the image from the private registry and then copies it to a local registry for later use.
Step as are follow:
docker pull privateregistry:5000/company/app:tag
docker tag privateregistry:5000/company/app:tag localregistry:5000/company/app:tag
docker push localregistry:5000/company/app:tag
Then later on a different machine in my network:
docker pull localregistry:5000/company/app:tag
Is there a way to efficiently copy an image from a repository to another without using a docker client in between ?
you can use docker save to save the images to tar archive and then copy the tar to new host and use docker load to untar it.
read below links for more
https://docs.docker.com/engine/reference/commandline/save/
Is there a way to efficiently copy an image from a repository to another without using a docker client in between?
Yes, there's a variety of tools that implement this today. RedHat has been pushing their skopeo, Google has crane, and I've been working on my own with regclient. Each of these tools talks directly to the registry server without needing a docker engine. And at least with regclient (I haven't tested the others), these will only copy the layers that are not already in the target registry, avoiding the need to pull layers again. Additionally, you can move a multi-platform image, retaining all of the available platforms, which you would lose with a docker pull since that dereferences the image to a single platform.
A colleague find out Docker and want to use it for our project. I start to use Docker for test. After reading an article about Docker swarm I want to test it.
I have installed 3 VM (ubuntu server 14.04) with docker and swarm. I followed some How To ( http://blog.remmelt.com/2014/12/07/docker-swarm-setup/ and http://devopscube.com/docker-tutorial-getting-started-with-docker-swarm/). My cluster work. I can launch for exemple a basic apache container (the image was pull in the Docker hub) but I want to use my own image (an apache server with my web site).
I tested to load an image (after save it in a .tar) but this option isn't supported by the clustering mode, same thing with the import option.
So my question is : Can I use my own image without to push it in the Docker hub and how I do this ?
If your own image is based on a Dockerfile that you build you can execute the build command on your project while targeting the swarm.
However if the image wasn't built, but created manually you need to have a registry in between that you can push to, either docker hub or some other registry solution like https://github.com/docker/docker-registry
What's the procedure for installing and running Docker on Google Compute Engine?
Until the recent GA release of Compute Engine, running Docker was not supported on GCE (due to kernel restrictions) but with the newly announced ability to deploy and use custom kernels, that restriction is no longer intact and Docker now works great on GCE.
Thanks to proppy, the instructions for running Docker on Google Compute Engine are now documented for you here: http://docs.docker.io/en/master/installation/google/. Enjoy!
They now have a VM which has docker pre-installed now.
$ gcloud compute instances create instance-name
--image projects/google-containers/global/images/container-vm-v20140522
--zone us-central1-a
--machine-type f1-micro
https://developers.google.com/compute/docs/containers/container_vms
A little late, but I wanted to add an answer with a more detailed workflow and links, since answers are still rather scattered:
Create a Docker image
a. Locally
b. Using Google Container Builder
Push local Docker image to Google Container Repository
docker tag <current name>:<current tag> gcr.io/<project name>/<new name>
gcloud docker -- push gcr.io/<project name>/<new name>
UPDATE
If you have upgraded to Docker client versions above 18.03, gcloud docker commands are no longer supported. Instead of the above push, use:
docker push gcr.io/<project name>/<new name>
If you have issues after upgrading, see more here.
Create a compute instance.
This process actually obfuscates a number of steps. It creates a virtual machine (VM) instance using Google Compute Engine, which uses a Google-provided, container-optimized OS image. The image includes Docker and additional software responsible for starting our docker container. Our container image is then pulled from the Container Repository, and run using docker run when the VM starts. Note: you still need to use docker attach even though the container is running. It's worth pointing out only one container can be run per VM instance. Use Kubernetes to deploy multiple containers per VM (the steps are similar). Find more details on all the options in the links at the bottom of this post.
gcloud beta compute instances create-with-container <desired instance name> \
--zone <google zone> \
--container-stdin \
--container-tty \
--container-image <google repository path>:<tag> \
--container-command <command (in quotes)> \
--service-account <e-mail>
Tip You can view available gcloud projects with gcloud projects list
SSH into the compute instance.
gcloud beta compute ssh <instance name> \
--zone <zone>
Stop or Delete the instance. If an instance is stopped, you will still be billed for resources such as static IPs and persistent disks. To avoid being billed at all, use delete the instance.
a. Stop
gcloud compute instances stop <instance name>
b. Delete
gcloud compute instances delete <instance name>
Related Links:
More on deploying containers on VMs
More on zones
More create-with-container options
As of now, for just Docker, the Container-optimized OS is certainly the way to go:
gcloud compute images list --project=cos-cloud --no-standard-images
It comes with Docker and Kubernetes preinstalled. The only thing it lacks is the Cloud SDK command-line tools. (It also lacks python3, despite Google's announce of Python 2 sunset on 2020-01-01. Well, it's still 27 days to go...)
As an additional piece of information I wanted to share, I was searching for a standard image that would offer both docker and gcloud/gsutil preinstalled (and found none, oops). I do not think I'm alone in this boat, as gcloud is the thing you could hardly go by without on GCE¹.
My best find so far was the Ubuntu 18.04 image that came with their own (non-Debian) package manager, snap. The image comes with the Cloud SDK preinstalled, and Docker installs literally in a snap, 11 seconds on an F1 instance initial test, about 6s on an n1-standard-1. The only snag I hit was the error message that the docker authorization helper was not available; an attempt to add it with gcloud components install failed because the SDK was installed as a snap, too. However, the helper is actually there, only not in the PATH. The following was what got me the both tools available in a single transient builder VM in the least amount of setup script runtime, starting off the supported Ubuntu 18.04 LTS image²:
snap install docker
ln -s /snap/google-cloud-sdk/current/bin/docker-credential-gcloud /usr/bin
gcloud -q auth configure-docker
¹ I needed both for a Daisy workflow imaging a disk with both artifacts from GS buckets and a couple huge, 2GB+ library images from the local gcr.io registry that were shared between the build (as cloud builder layers) and the runtime (where I had to create and extract containers to the newly built image). But that's besides the point; one may needs both tools for a multitude of possible reasons.
² Use gcloud compute images list --uri | grep ubuntu-1804 to get the most current one.
Google's GitHub site offers now a gce image including docker. https://github.com/GoogleCloudPlatform/cloud-sdk-docker-image
It's as easy as:
creating a Compute Engine instance
curl https://get.docker.io | bash
Using docker-machine is another way to host your google compute instance with docker.
docker-machine create \
--driver google \
--google-project $PROJECT \
--google-zone asia-east1-c \
--google-machine-type f1-micro $YOUR_INSTANCE
If you want to login this machine on google cloud compute instance, just use docker-machine ssh $YOUR_INSTANCE
Refer to docker machine driver gce
There is now improved support for containers on GCE:
Google Compute Engine is extending its support for Docker containers. This release is an Open Preview of a container-optimized OS image that includes Docker and an open source agent to manage containers. Below, you'll find links to interact with the community interested in Docker on Google, open source repositories, and examples to get started. We look forward to hearing your feedback and seeing what you build.
Note that this is currently (as of 27 May 2014) in Open Preview:
This is an Open Preview release of containers on Virtual Machines. As a result, we may make backward-incompatible changes and it is not covered by any SLA or deprecation policy. Customers should take this into account when using this Open Preview release.
Running Docker on GCE instance is not supported. The instance goes down and not able to login again.
We can use the Docker image given by the GCE, to create a instance.
If your google cloud virtual machine is based on ubuntu use the following command to install docker
sudo apt install docker.io
You may use this link: https://cloud.google.com/cloud-build/docs/quickstart-docker#top_of_page.
The said link explains how to use Cloud Build to build a Docker image and push the image to Container Registry. You will first build the image using a Dockerfile and then build the same image using the Cloud Build's build configuration file.
Its better to get it while creating compute instance
Go to the VM instances page.
Click the Create instance button to create a new instance.
Under the Container section, check Deploy container image.
Specify a container image name under Container image and configure options to run the container if desired. For example, you can specify gcr.io/cloud-marketplace/google/nginx1:1.12 for the container image.
Click Create.
Installing Docker on GCP Compute Engine VMs:
This is the link to GCP documentation on the topic:
https://cloud.google.com/compute/docs/containers#installing
In it it links to the Docker install guide, you should follow the instructions depending on what type of Linux you have running in the vm.