I have built a docker image that when run, it registers itself as a GitHub Runner. This runner will, amongst other things, be used to build and push images to GitHub Container Registry. I don't want to deploy the containers to GKE or Compute, as I don't want the overhead of managing those resources. I would prefer to deploy the containers to Google Cloud Run. I've scoured the docs for help but I can't seem to find the answers to the following question:
Can I run 'docker in docker' when the container is deployed to GCP Cloud Run?
How do I specify the volume mount required when deploying the container to Google Cloud Run, i.e. the usual mapping with docker run would be:
-v /var/run/docker.sock:/var/run/docker.sock
I never tested but it's possible that the current Cloud Run sandbox prevent this king of use. And I don't really know the use case for this!
You can't mount volume in Cloud Run, it's stateless. You only have a in-memory file system in the /tmp directory (and it's in memory, size correctly your Cloud Run instance memory to take this into account). You can connect your instance to 3rd party product, such as Google Cloud Storage or databases, but no volume mountable on Cloud Run (for now)
If you have these requirement you can maybe have a look to autopilot and deploy directly your container on fully managed K8S.
Related
I am trying to deploy this app. https://github.com/taigaio/taiga-docker . This container is a collection of various images. It uses docker-compose to create the container. It is my understanding that this cannot be run as an image from a GCP Artifact Repo as a docker Image. This needs a VM perhaps?
My question is if there is a way to deploy this container as an Image in a serverless fashion in GCP or any other cloud platform. Any pointers/help is much appreciated.
You can either use Cloud Run (the most Serverless way) or on a VM.
On Cloud Run you can deploy a single image as a Service (Cloud Run Terminology), if you have more than one image you can deploy multiple Services and make them talk to each other
Or on VM, that would be as if you are deploying on your personal laptop
I've built an app that uses two home made micro services, each of the micro service having its own Dockerfile.
When I build it locally I use docker-compose for practical reasons.
Currently, when I deploy to Cloud Run I use commands like
docker tag xxx
docker push xxx
Then I select the image I want to deploy on Cloud run
As I understand, docker-compose build just builds two images (one for each Dockerfile) and the places them within the same network which allows some practical connections between these two API.
Is it possible to do something similar one Cloud Run without having to deploy each image on a different service ?
PS: For business reasons I can't host my code directly on Cloud Source Repositories, it has to be on Azure
It is not possible to deploy 2 different Docker images to Cloud Run.
The Cloud Run works in the following way:
You build a container image and upload to Google Container Registry
Deploy to Cloud Run with the container image.
Your service is automatically scaled up and down to a specific number of container instances depending on your incoming requests. Each container will run the container image.
Summary = Cloud Run takes a user's container and executes it on Google infrastructure, and handles the instantiation of instances (scaling) of that container.
Please Note, Cloud Run is designed to run Websites,REST APIs backend, Back‐office administration etc and it does not support microservices architecture (different servers running in a different container).
For you scenario, you can deploy multiple services in Cloud Run or use other Google Products such as Cloud SQL, Datastore, Spanner or BigTable.
Note: You can'd deploy 2 containers in the same service however you can deploy a container that contains multiple processes as explained in this article written by a Googler
I run Rstudio server mostly from an EC2 instance. However, I´d also like to run it from a cluster at work. They tell me that I can setup docker with rstudio and make it run. Now, I´d also like the Rstudios both on EC2 and work to have the same packages and the same versions available. Any idea how I can do this? Can I have both version point to a dropbox folder? In that case, how can I mount a dropbox folder?
You should setup a docker repository on dockerhub or aws ec2 container service (ecs). ECS is a managed service that allows you to easily deploy docker containers onto a cluster of 1 or more ec2 instances that are running the ecs agent (an aws program that helps that cluster work with the ecs). The Dockerfile should install all packages that you need at build time of the image. I suggest referencing the aws ecs documentation, which includes a walkthrough to get you going very quickly (assuming you have an idea of how docker works): https://aws.amazon.com/documentation/ecs/
You should then always run from that docker image, whether you are running on a local or remote machine. One key advantage of docker is that it keeps your application's environments the same (assuming you use the same build of the image) regardless of the host environment.
I am not sure why would not always run on ECS (we have multiple analysts using RStudio, and ECS lets us provision cpu/memory resources to each one, as well as autoscale as needed). You could install docker on EC2 and manage it that way, but probably easier to just install the ecs agent (or use the ecs optimized ec2 ami which has it preinstalled - the docs above walk through configuring it), and use ECS to launch rstudio services.
My application is comprised of two separate docker containers. One being a Grails based web application and second being a RESTful Python Flask application. Both docker containers are sitting on my local computer. They are not hosted on docker hub. They are proprietary and I don't want to host them publicly.
I would like to try Cloud Foundry to deploy these docker containers and see how it works. However, from the documentation I get a sense that Cloud Foundry doesn't support deploying docker containers sitting on a local machine.
Question
Is there a way to deploy docker containers sitting on a local computer to CloudFoundry? If not, what is a way to securely host the containers somewhere from CF can fetch them?
Is CloudFoundry capable of running a docker container that is a Python Flask application?
One option you have is to not use Docker images, and just push your code directly, one of the nice features of CF. PCF comes with a python buildpack which should automatically detect your Flask app.
Another option would be run your own trusted docker registry, push your images there, and then when you push your app, tell it to grab the images from your registry. If you google "cloud foundry docker registry" you get the following useful results you should check out:
https://github.com/cloudfoundry-community/docker-registry-boshrelease
http://docs.pivotal.io/pivotalcf/1-8/adminguide/docker.html#caveats
https://docs.pivotal.io/pivotalcf/1-7/opsguide/docker-registry.html
Is it possible to create a docker container in a Google Container Engine cluster, using a dockerfile, which builds an image on-the-fly and deploy in cluster,
rather than creating an image first and uploading it to a Google Container Registry, and then using it from there?
I feel like that is cumbersome, and there should be a way to create containers in cluster directly using a dockerfile.
It is not possible to do this in Google Container Engine. Google Container Engine is designed to help orchestrate container deployment and does not itself provide a source -> deployment workflow.
You may want to look at Google App Engine or Openshift 3 (which is built on Kubernetes) as a more fully featured platform-as-a-service offering.
You can also build this type of tooling on top of a Google Container Engine cluster yourself as all of the building blocks are available.
One service to take a look at when constructing a workflow is Google Container Builder, which can simplify the process of building a container from source and pushing it to Google Container Registry.
It is currently a fairly low level service, but offers some advantages for environments where it may be impractical to run docker build locally.