I'm new to Docker, and my previous experience is with deploying Java web applications (running in Tomcat containers) to Elastic Beanstalk. The pipeline I'm used to goes something like this: a commit is checked into git, which triggers a Jenkins job, which builds the application JAR (or WAR) file, publishes it to Artifactory, and then deploys that same JAR to an application in Elastic Beanstalk using eb deploy. (Apologies if "pipeline" is a reserved term; I'm using it conceptually.)
Incidentally, I'm also going to be using Gitlab for CI/CD instead of Jenkins (due to organizational reasons out of my control), but the jump from Jenkins to Gitlab seems straight-forward to me -- certainly moreso than the jump from deploying WARs directly to deploying Dockerized containers.
Moving over into the Docker world, I imagine the pipeline will go something like this: a commit is checked into git, which triggers the Gitlab CI, which will then build the JAR or WAR file, publish it to Artifactory, then use the Dockerfile to build the Docker image, publish that Docker image into Amazon ECR (maybe?)... and then I'm honestly not sure how the Elastic Beanstalk integration would proceed from there. I know it has something to do with the Dockerrun.aws.json file, and presumably needs to call the AWS CLI.
I just got done watching a webinar from Amazon called Running Microservices and Docker on AWS Elastic Beanstalk, which stated that in the root of my repo there should be a Dockerrun.aws.json file which essentially defines the integration to EB. However, it seems that JSON file contains a link to the individual Docker image in ECR, which is throwing me off. Wouldn't that link change every time a new image is built? I'm imagining that the CI would need to dynamically update the JSON file in the repo... which almost feels like an anti-pattern to me.
In the webinar I linked above, the host created his Docker image and pushed it ECR manually, with the CLI. Then he manually uploaded the Dockerrun.aws.json file to EB. He didn't need to upload the application however, since it was already contained within the Docker image. This all seems odd to me and I question whether I'm understanding things correctly. Will the Dockerrun.aws.json file need to change on every build? Or am I thinking about this the wrong way?
In the 8 months since I posted this question, I've learned a lot and we've already moved onto different and better technology. But I will post what I learned in answer to my original question.
The Dockerrun.aws.json file is almost exactly the same as an ECS task definition. It's important to use the Multi-Docker container deployment version of Beanstalk (as opposed to the single container), even if you're only deploying a single container. IMO they should just get rid of the single-container platform for Beanstalk as it's pretty useless. But assuming you have Beanstalk set to the Multi-Container Docker platform, then the Dockerrun.aws.json file looks something like this:
{
"AWSEBDockerrunVersion": 2,
"containerDefinitions": [
{
"name": "my-container-name-this-can-be-whatever-you-want",
"image": "my.artifactory.com/docker/my-image:latest",
"environment": [],
"essential": true,
"cpu": 10,
"memory": 2048,
"mountPoints": [],
"volumesFrom": [],
"portMappings": [
{
"hostPort": 80,
"containerPort": 80
}
],
"logConfiguration": {
"logDriver": "awslogs",
"options": {
"awslogs-group": "/aws/elasticbeanstalk/my-image/var/log/stdouterr.log",
"awslogs-region": "us-east-1",
"awslogs-datetime-format": "%Y-%m-%d %H:%M:%S.%L"
}
}
}
]
}
If you decide, down the road, to convert the whole thing to an ECS service instead of using Beanstalk, that becomes really easy, as the sample JSON above is converted directly to an ECS task definition by extracting the "containerDefinitions" part. So the equivalent ECS task definition might look something like this:
[
{
"name": "my-container-name-this-can-be-whatever-you-want",
"image": "my.artifactory.com/docker/my-image:latest",
"environment": [
{
"name": "VARIABLE1",
"value": "value1"
}
],
"essential": true,
"cpu": 10,
"memory": 2048,
"mountPoints": [],
"volumesFrom": [],
"portMappings": [
{
"hostPort": 0,
"containerPort": 80
}
],
"logConfiguration": {
"logDriver": "awslogs",
"options": {
"awslogs-group": "/aws/ecs/my-image/var/log/stdouterr.log",
"awslogs-region": "us-east-1",
"awslogs-datetime-format": "%Y-%m-%d %H:%M:%S.%L"
}
}
}
]
Key differences here are that with the Beanstalk version, you need to map port 80 to port 80 because a limitation of running Docker on Beanstalk is that you cannot replicate containers on the same instance, whereas in ECS you can. This means that in ECS you can map your container port to host port "zero," which really just tells ECS to pick a random port in the ephemeral range which allows you to stack multiple replicas of your container on a single instance. Secondly with ECS if you want to pass in environment variables, you need to inject them directly into the Task Definition JSON. In Beanstalk world, you don't need to put the environment variables in the Dockerrun.aws.json file, because Beanstalk has a separate facility for managing environment variables in the console.
In fact, the Dockerrun.aws.json file should really just be thought of as a template. Because Docker on Beanstalk uses ECS under-the-hood, it simply takes your Dockerrun.aws.json as a template and uses it to generate its own Task Definition JSON, which injects the managed environment variables into the "environment" property in the final JSON.
One of the big questions I had at the time when I first asked this question was whether you had to update this Dockerrun.aws.json file every time you deployed. What I discovered is that it comes down to a choice of how you want to deploy things. You can, but you don't have to. If you write your Dockerrun.aws.json file so that the "image" property references the :latest Docker image, then there's no need to ever update that file. All you need to do is bounce the Beanstalk instance (i.e. restart the environment), and it will pull whatever :latest Docker image is available from Artifactory (or ECR, or wherever else you publish your images). Thus, all a build pipeline would need to do is publish the :latest Docker image to your Docker repository, and then trigger a restart of the Beanstalk environment using the awscli, with a command like this:
$ aws elasticbeanstalk restart-app-server --region=us-east-1 --environment-name=myapp
However, there are a lot of drawbacks to that approach. If you have a dev/unstable branch that publishes a :latest image to the same repository, you become at risk of deploying that unstable branch if the environment happens to restart on its own. Thus, I would recommend versioning your Docker tags and only deploying the version tags. So instead of pointing to my-image:latest, you would point to something like my-image:1.2.3. This does mean that your build process would have to update the Dockerrun.aws.json file on each build. And then you also need to do more than just a simple restart-app-server.
In this case, I wrote some bash scripts that made use of the jq utility to programmatically update the "image" property in the JSON, replacing the string "latest" with whatever the current build version was. Then I would have to make a call to the awsebcli tool (note that this is a different package than the normal awscli tool) to update the environment, like this:
$ eb deploy myapp --label 1.2.3 --timeout 1 || true
Here I'm doing something hacky: the eb deploy command unfortunately takes FOREVER. (This was another reason we switched to pure ECS; Beanstalk is unbelievably slow.) That command hangs for the entire deployment time, which in our case could take up to 30 minutes or more. That's completely unreasonable for a build process, so I force the process to timeout after 1 minute (it actually continues the deployment; it just disconnects my CLI client and returns a failure code to me even though it may subsequently succeed). The || true is a hack that effectively tells Gitlab to ignore the failure exit code, and pretend that it succeeded. This is obviously problematic because there's no way to tell if the Elastic Beanstalk deployment really did fail; we're assuming it never does.
One more thing on using eb deploy: by default this tool will automatically try to ZIP up everything in your build directory and upload that entire ZIP to Beanstalk. You don't need that; all you need is to update the Dockerrun.aws.json. In order to do this, my build steps were something like this:
Use jq to update Dockerrun.aws.json file with the latest version tag
Use zip to create a new ZIP file called deploy.zip and put Dockerrun.aws.json inside it
Make sure a file called .elasticbeanstalk/config.yml is in place (described below)
Run the eb deploy ... command
Then you need a file in the build directory at .elasticbeanstalk/config.yml which looks like this:
deploy:
artifact: deploy.zip
global:
application_name: myapp
default_region: us-east-1
workspace_type: Application
The awsebcli knows to automatically look for this file when you call eb deploy. And what this particular file says is to look for a file called deploy.zip instead of trying to ZIP up the whole directory itself.
So the :latest method of deployment is problematic because you risk deploying something unstable; the versioned method of deployment is problematic because the deployment scripts are more complicated, and because unless you want your build pipelines to take 30+ minutes, there's a chance that the deployment won't be successful and there's really no way to tell (outside of monitoring each deployment yourself).
Anyways, it's a bit more work to set up, but I would recommend migrating to ECS whenever you can. (Better still to migrate to EKS, though that's a lot more work.) Beanstalk has a lot of problems.
I'm trying to use a large docker image (the image is on dockerhub here about 18GB) as a job definition for AWS batch. I'm getting the following error about running out of space:
CannotPullContainerError: write /var/lib/docker/tmp/GetImageBlob#######: no space left on device
The Cloudformation JSON section that defines the job is here
"JobDef3": {
"Type": "AWS::Batch::JobDefinition",
"Properties": {
"Type": "container",
"ContainerProperties": {
"Image": {
"Fn::Join": [
"",
[
"cornhundred/",
"dockerized-cellranger-nick:latest"
]
]
},
"Vcpus": 1,
"Command": ["some command"],
"Memory": 3000,
},
"RetryStrategy": {
"Attempts": 1
}
}
},
How can I get AWS to increase the amount of space available so that I can run this image?
I was able to run the docker container by moving the large files (~15GB reference genome files) out of the docker image and downloading them after running the container. I also needed to make a custom Amazon Machine Image (AMI, see AWS Batch Genomics for an example) and attach a volume to handle the large reference genome files since the default container was not large enough.
I had a similar issue. Clearing up unused docker images and volumes didn't work for me (ie docker container prune nor docker system prune
I saw another page saying that restarting docker fixed it for that user, but doing a service docker restart I got this error: /etc/init.docker: line 35: ulimit: open files: cannot modify limit: Operation not permitted
To try and fix that issue, I saw sites mentioning to update the ulimit values in some configuration files but when I tried to save the file with the updated parameters I got write error (file system full?)
At which point, I realized (as the initial error you showed) I needed to clean up and remove files.
I did a du -h from the root folder and saw that the /var/lib/docker/tmp/ folder (which is part of the error message I experienced and you posted above) used up way more disk space than other folders.
So I removed older files there and I no longer got that error message.
In the task definition on ECS, I have provided environment variable as following:
Key as HOST_NAME and the value as something.cloud.com
On my local I use this docker run command and I'm able to pass in my env variables, but through task definition the variables are not being passed to container.
The docker run command below works on local, but how do I set it up in the task definition in AWS ECS?
docker run -e HOST_NAME=something.cloud.com sid:latest
You should call it name and not key, see example below
{
"name": "nginx",
"image": "",
"portMappings": [
{
"containerPort": 80,
"hostPort": 80
}
],
"environment": [
{
"name": "HOST_NAME",
"value": "something.cloud.com"
}
]
}
If you used the new docker compose integration with ECS, then you will need to update the stack.
It is smart enough to update only the parts that changed. For my case, this was the task definition not picking new environment variables set on a .env file and mounted on the docker container
Run the same command you used to create the stack, only that this time round it'll update it(only parts that changed)
docker compose --context you-ecs-context up -f your.docker-compose.yml
For more: https://docs.docker.com/engine/context/ecs-integration/#rolling-update
You can set hostname var at task definition JSON file
hostname
Type: string
Required: no
The hostname to use for your container. This parameter maps to Hostname in the Create a container section of the Docker Remote API and the --hostname option to docker run.
Using application version label jenkins-mt-002.zip, which defines a Dockerfile as well as a Dockerrun.aws.json file. The JSON file only contains the volume mapping.
{
"AWSEBDockerrunVersion": "1",
"Volumes": [
{
"HostDirectory": "/efs_mount/master/live",
"ContainerDirectory": "/root/.jenkins"
}
]
}
I am trying to map an EFS mount located at /efs_mount on the host system to /root/.jenkins inside of the docker container. I thought I had set it up correctly, but apparently I'm doing something wrong. Could someone take a look and let me know what I'm doing wrong?
I created the following simple Dockerrun file per the instructions here using a public container and it's successfully running a single instance.
{
"AWSEBDockerrunVersion": "1",
"Image": {
"Name": "sbeam/influxdb",
"Update": "true"
},
"Ports": [
{
"ContainerPort": "8086"
}
],
"Volumes": [
{
"HostDirectory": "/data",
"ContainerDirectory": "/data"
}
]
}
However I want the /data directory to be mounted within the EC2 instance as a certain EBS volume. I've found answers (here and here) that indicate a .ebextensions is needed, but since I am not uploading a .zip image for the container, how is this possible? Is it necessary to download the Docker container, add the .ebextensions directory, zip and re-upload?
You will have to follow option 3: "Create a .zip file containing your application files, any application file dependencies, the Dockerfile, and the Dockerrun.aws.json file." as explained in your first link.
In your case the .zip file may only contain the Dockerrun.aws.json and the .ebextensions folder.
In order to attach the EBS volume to your instance, you can check this article: http://blogs.aws.amazon.com/application-management/post/Tx224DU59IG3OR9/Customize-Ephemeral-and-EBS-Volumes-in-Elastic-Beanstalk-Environments. It will give you indications concerning the content of the .config file that will be inside the .ebextensions folder