I have created a Docker containers using docker-compose. In my local environment, i am able to bring up my application without any issues.
Now i wanted to deploy all my docker containers to the AWS EC2 (ECS). After going over the ECS documentation, i found out that we can make use of the same docker-compose to deploy in ECS using ECS-CLI. But ECS-CLI is not available for windows instances as of now. So now i am not sure how to use my docker-compose to build all my images using a single command and deploy it to the ECS from an windows instance.
It seems like i have to deploy my docker containers one by one to ECS as like below steps,
From the ECS Control Panel, create a Docker Image Repository.
Connect your local Docker client with your Docker credentials in ECS:
Copy and paste the Docker login command from the previous step. This will log you in for 24 hours
Tag your image locally ready to push to your ECS repository – use the repo URI from the first step
Push the image to your ECS repoository\
create tasks with the web UI, or manually as a JSON file
create a cluster, using the web UI.
Run your task specifying the EC2 cluster to run on
Is there any other way of running the docker containers in ECS ?
Docker-Compose is wrong at this place, when you're using ECS.
You can configure multiple containers within a task definition, as seen here in the CloudFormation docs:
ContainerDefinitions is a property of the AWS::ECS::TaskDefinition resource that describes the configuration of an Amazon EC2 Container Service (Amazon ECS) container
Type: "AWS::ECS::TaskDefinition"
Properties:
Volumes:
- Volume Definition
Family: String
NetworkMode: String
PlacementConstraints:
- TaskDefinitionPlacementConstraint
TaskRoleArn: String
ContainerDefinitions:
- Container Definition
Just list multiple containers there and all will be launched together on the same machine.
I got the same situation as you. One way to resolve this was using the Terraform to deploy our containers as a Task Definitions on AWS ECS.
So, we using the docker-compose.yml to run locally and the terraform is a kind of mirror of our docker-compose on AWS.
Also another option is Kubernetes that you can translate from docker-compose to Kubernetes resources.
Related
I have an application which consists of 2 docker containers. Both are small and need to interact with each other quite often through rest api.
How can I deploy both of them to a single Virtial Machine in Google Cloud?
Usually, when creating virtual machine, I get to chose a container image to deploy: Deploy a container image to this VM instance.
I can specify one of my images and get it running in the VM. Can I set multiple images?
You can not deploy multiple containers per VM.
Please consider this limitation when deploying containers on VMs:
1.You can only deploy one container for each VM instance. Consider Google Kubernetes Engine if you need to deploy multiple containers per
VM instance.
2.You can only deploy containers from a public repository or from a private repository at Container Registry. Other private repositories
are currently not supported.
3.You can't map a VM instance's ports to the container's ports (Docker's -p option).
4.You can only use Container-Optimized OS images with this deployment method. You can only use this feature through the Google Cloud
Platform Console or the gcloud command-line tool, not the API.
You can use docker-compose to deploy multi-container applications.
To achieve this on Google Cloud, you'll need:
ssh access to VM
docker and docker compose installed on the VM
We are developing spring boot application which is currently deploying in AWS manually. For that, first we build docker image through Dockerfile and then connect to AWS EC2 instance from laptop & then pull the image and then we use docker run to start it. But we want to automate the process using gitlab CI/CD.
We created .gitlab-ci.yml, build stage builds spring-boot application and generates jar file. Package stage then build docker images using Dockerfile from source code and then push the image to registry.
Now i don't know how to finish deploy stage. Most of the tutorials explains only about deploying into Google cloud provider. I use below steps to deploy the docker image...
ssh -i "spring-boot.pem" ubuntu#ec2-IP_address.compute-2.amazonaws.com
sudo docker pull username/spring-boot:v1
sudo docker run -d -p 80:8080 username/spring-boot:v1
Can anybody help me to add above steps into deploy stage. Do I need to add pem file into source to connect to ec2 instance.
Or is there any easy way to deploy docker in ec2 from gitlab ci/cd.
First thing, If there is ssh then it's mean you must provide the key or password by default unless you allow access to everyone.
Do I need to add pem file into source to connect to ec2 instance?
Yes, you should provide the key for ssh.
Or is there any easy way to deploy Docker in ec2 from gitlab ci/cd?
Yes, there is the easiest way to do that but for that, you need to use ECS, the specially designed for Docker container and you can manage your deployment through API instead of doing ssh to the ec2 server.
ECS is designed for running Docker container, Some of the big Advantage of ECS over ec2 is you do not need to worry about container management, scalability and availability, ECS will take care of it. provide ECR which is like docker registry but it's private and with in-network.
deploy-docker-containers
I'm trying to run my custom Jenkins on Openshift. I'm trying to run dockerized pipelines using privileged containers and scc to be able to run docker using my Jenkins. So far, I managed to run the job and it is creating a new Docker container successfully. But, since my new docker is created by Jenkins it doesn't have access to Nexus service on my project. How can I fix this? I was thinking the solution should be for the Jenkins to run docker in the same namespace as my Jenkins.
I'm assuming that you want to run your container in Kubernetes.
On your Deployment I would advise using either a ConfigMap or if you want to keep in encrypted in the cluster you can use a Secret to store your Nexus credentials.
Then you can mount your ConfigMap or Secret under ~/.ivy2/.credentials for example.
With the Kubernetes orchestrator now available in the stable version of Docker Desktop for Win/Mac, I've been playing around with running an existing compose stack on Kubernetes locally.
This works fine, e.g., docker stack deploy -c .\docker-compose.yml myapp.
Now I want to go to the next step of running this same application in a production environment using the likes of Amazon EKS or Azure AKS. These services expect proper Kubernetes YAML files.
My question(s) is what's the best way to get these files, or more specifically:
Presumably, docker stack is performing some conversion from Compose YAML to Kubernetes YAML 'under the hood'. Is there documentation/source code links as to what is going on here and can that converted YAML be exported?
Or should I just be using Kompose?
It seems that running the above docker stack deploy command against a remote context (e.g., AKS/EKS) is not possible and that one must do a kubectl deploy. Can anyone confirm?
docker stack deploy with a Compose file to Kube only works on Docker's Kubernetes distributions - Docker Desktop and Docker Enterprise.
With the recent federation announcement you'll be able to manage AKS and EKS with Docker Enterprise, but using them direct means you'll have to use Kubernetes manifest files and kubectl.
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.