I run a dockerized Django-celery app which takes some user input/data from a webpage and (is supposed to) run a unix binary on the host system for subsequent data analysis. The data analysis takes a bit of time, so I use celery to run it asynchronously. The data analysis software is dockerized as well, so my django-celery worker should do os.system('docker run ...'). However, celery says docker: command not found, obviously because docker is not installed within my Django docker image. What is the best solution to this problem? I don't want to run docker within docker, because my analysis software should be allowed to use all system resources and not just the resources assigned to the Django image.
I don't want to run docker within docker, because my analysis software should be allowed to use all system resources and not just the resources assigned to the Django image.
I didn't catch the causal relationship here. In fact, we just need to add 2 steps to your Django image:
Follow Install client binaries on Linux to download the docker client binary from prebuilt, then your Django image will have the command docker.
When starting the Django container, add /var/run/docker.sock bind mount, this allows the Django container to directly talk to the docker daemon on the host machine and start the data-analysis tool container on the host. As the analysis container does not start in Django container, they can have separate system resources. In other words, the analysis container's resources do not depend on the resource of the Django image container.
Samples with one docker image which already has the docker client in it:
root#pie:~# ls /dev/fuse
/dev/fuse
root#pie:~# docker run --rm -it -v /var/run/docker.sock:/var/run/docker.sock docker /bin/sh
/ # ls /dev/fuse
ls: /dev/fuse: No such file or directory
/ # docker run --rm -it -v /dev:/dev alpine ls /dev/fuse
/dev/fuse
You can see, although the initial container does not have access to the host's /dev folder, the docker container whose command initialized from the initial container could really have separate resources.
If the above is what you need, then it's the right solution for you. Otherwise, you will have to install the analysis tool in your Django image
So I am following the official documentation django with postgres in docker
https://docs.docker.com/compose/django/
I created another database, ( not using the default postgres db ). but when shutdown the server and re run it, It doesn't show the database. How can i create database so that it doesn't vanish when i shut down my docker server.
All data in a container deleted when a container is destroyed or deleted. To save the data, you should save it in some mounted volume in docker. That volume will be on your machine. So all data which will be created during running of any process in that docker container will be stored in your machine. For this, you will have to understand Volume Api of docker.
Create a volume like this
docker volume create hello
And use that volume in your container like this
docker run -d -v hello:/world busybox ls /world
You can get further help from here.
I'm new to Gitlab (and I only know the basic features of git : pull, push, merge, branch...).
I'm using a local DynamoDB database launched with docker run -p 8000:8000 amazon/dynamodb-local to do unit testing on my Python project. So I have to launch this docker container in the Gitlab CI/CD so that my unit tests work.
I already read the documentation on this subject on the site of gitlab without finding an answer to my problem and I know that I have to modify my gitlab-ci.yml file in order to launch the docker container.
When using Gitlab you can use Docker-in-Docker.
At the top of your .gitlab-ci.yml file
image: docker:stable
services:
- docker:dind
Then in your stage for tests, you can start up the database and use it.
unit_tests:
stage: tests
script:
- export CONTAINER_ID=$(docker run -p 8000:8000 amazon/dynamodb-local)
## You might need to wait a few seconds with `sleep X` for the container to start up.
## Your database is now here docker:8000
## Run your tests here. Database host=docker and port=8000
This is the best way I have found to achieve it and the easiest to understand
As i am working on docker, i need help to take a container or image from existing AWS box. In my AWS box our application is installed and initiated.
For our application initialization, it takes more time. So i want to deploy this container(application installed) while the box launching time itself. When i am taking docker container it will have my application initiated, as per my understanding. So i can save the application initialization time.
I am launching the machine through ansible in AWS VPC. So i can call the docker container there.
Can anyone help on this how to do this activity.
With Thanks,
Ezhilmurugan M I
If you docker commit your changes into an image with a tag, you can then push to a registry, and then pull down the images on another server.
$ docker commit <hash or name> yourusername/red_panda
$ docker push yourusername/red_panda
On other host
$ docker pull yourusername/red_panda
You could also export the image, transfer however you want, and then import the image on the new server.
$ docker export red_panda > latest.tar
$ cat latest.tgz | docker import - exampleimagelocal:new
I am running docker-container on Amazon EC2. Currently I have added AWS Credentials to Dockerfile. Could you please let me know the best way to do this?
A lot has changed in Docker since this question was asked, so here's an attempt at an updated answer.
First, specifically with AWS credentials on containers already running inside of the cloud, using IAM roles as Vor suggests is a really good option. If you can do that, then add one more plus one to his answer and skip the rest of this.
Once you start running things outside of the cloud, or have a different type of secret, there are two key places that I recommend against storing secrets:
Environment variables: when these are defined on a container, every process inside the container has access to them, they are visible via /proc, apps may dump their environment to stdout where it gets stored in the logs, and most importantly, they appear in clear text when you inspect the container.
In the image itself: images often get pushed to registries where many users have pull access, sometimes without any credentials required to pull the image. Even if you delete the secret from one layer, the image can be disassembled with common Linux utilities like tar and the secret can be found from the step where it was first added to the image.
So what other options are there for secrets in Docker containers?
Option A: If you need this secret only during the build of your image, cannot use the secret before the build starts, and do not have access to BuildKit yet, then a multi-stage build is a best of the bad options. You would add the secret to the initial stages of the build, use it there, and then copy the output of that stage without the secret to your release stage, and only push that release stage to the registry servers. This secret is still in the image cache on the build server, so I tend to use this only as a last resort.
Option B: Also during build time, if you can use BuildKit which was released in 18.09, there are currently experimental features to allow the injection of secrets as a volume mount for a single RUN line. That mount does not get written to the image layers, so you can access the secret during build without worrying it will be pushed to a public registry server. The resulting Dockerfile looks like:
# syntax = docker/dockerfile:experimental
FROM python:3
RUN pip install awscli
RUN --mount=type=secret,id=aws,target=/root/.aws/credentials aws s3 cp s3://... ...
And you build it with a command in 18.09 or newer like:
DOCKER_BUILDKIT=1 docker build -t your_image --secret id=aws,src=$HOME/.aws/credentials .
Option C: At runtime on a single node, without Swarm Mode or other orchestration, you can mount the credentials as a read only volume. Access to this credential requires the same access that you would have outside of docker to the same credentials file, so it's no better or worse than the scenario without docker. Most importantly, the contents of this file should not be visible when you inspect the container, view the logs, or push the image to a registry server, since the volume is outside of that in every scenario. This does require that you copy your credentials on the docker host, separate from the deploy of the container. (Note, anyone with the ability to run containers on that host can view your credential since access to the docker API is root on the host and root can view the files of any user. If you don't trust users with root on the host, then don't give them docker API access.)
For a docker run, this looks like:
docker run -v $HOME/.aws/credentials:/home/app/.aws/credentials:ro your_image
Or for a compose file, you'd have:
version: '3'
services:
app:
image: your_image
volumes:
- $HOME/.aws/credentials:/home/app/.aws/credentials:ro
Option D: With orchestration tools like Swarm Mode and Kubernetes, we now have secrets support that's better than a volume. With Swarm Mode, the file is encrypted on the manager filesystem (though the decryption key is often there too, allowing the manager to be restarted without an admin entering a decrypt key). More importantly, the secret is only sent to the workers that need the secret (running a container with that secret), it is only stored in memory on the worker, never disk, and it is injected as a file into the container with a tmpfs mount. Users on the host outside of swarm cannot mount that secret directly into their own container, however, with open access to the docker API, they could extract the secret from a running container on the node, so again, limit who has this access to the API. From compose, this secret injection looks like:
version: '3.7'
secrets:
aws_creds:
external: true
services:
app:
image: your_image
secrets:
- source: aws_creds
target: /home/user/.aws/credentials
uid: '1000'
gid: '1000'
mode: 0700
You turn on swarm mode with docker swarm init for a single node, then follow the directions for adding additional nodes. You can create the secret externally with docker secret create aws_creds $HOME/.aws/credentials. And you deploy the compose file with docker stack deploy -c docker-compose.yml stack_name.
I often version my secrets using a script from: https://github.com/sudo-bmitch/docker-config-update
Option E: Other tools exist to manage secrets, and my favorite is Vault because it gives the ability to create time limited secrets that automatically expire. Every application then gets its own set of tokens to request secrets, and those tokens give them the ability to request those time limited secrets for as long as they can reach the vault server. That reduces the risk if a secret is ever taken out of your network since it will either not work or be quick to expire. The functionality specific to AWS for Vault is documented at https://www.vaultproject.io/docs/secrets/aws/index.html
The best way is to use IAM Role and do not deal with credentials at all. (see http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/iam-roles-for-amazon-ec2.html )
Credentials could be retrieved from http://169.254.169.254..... Since this is a private ip address, it could be accessible only from EC2 instances.
All modern AWS client libraries "know" how to fetch, refresh and use credentials from there. So in most cases you don't even need to know about it. Just run ec2 with correct IAM role and you good to go.
As an option you can pass them at the runtime as environment variables ( i.e docker run -e AWS_ACCESS_KEY_ID=xyz -e AWS_SECRET_ACCESS_KEY=aaa myimage)
You can access these environment variables by running printenv at the terminal.
Yet another approach is to create temporary read-only volume in docker-compose.yaml. AWS CLI and SDK (like boto3 or AWS SDK for Java etc.) are looking for default profile in ~/.aws/credentials file.
If you want to use other profiles, you just need also to export AWS_PROFILE variable before running docker-compose command.
export AWS_PROFILE=some_other_profile_name
version: '3'
services:
service-name:
image: docker-image-name:latest
environment:
- AWS_PROFILE=${AWS_PROFILE}
volumes:
- ~/.aws/:/root/.aws:ro
In this example, I used root user on docker. If you are using other user, just change /root/.aws to user home directory.
:ro - stands for read-only docker volume
It is very helpful when you have multiple profiles in ~/.aws/credentials file and you are also using MFA. Also helpful when you want to locally test docker-container before deploying it on ECS on which you have IAM Roles, but locally you don't.
Another approach is to pass the keys from the host machine to the docker container. You may add the following lines to the docker-compose file.
services:
web:
build: .
environment:
- AWS_ACCESS_KEY_ID=${AWS_ACCESS_KEY_ID}
- AWS_SECRET_ACCESS_KEY=${AWS_SECRET_ACCESS_KEY}
- AWS_DEFAULT_REGION=${AWS_DEFAULT_REGION}
The following one-liner works for me even when my credentials are set up by aws-okta or saml2aws:
$ docker run -v$HOME/.aws:/root/.aws:ro \
-e AWS_ACCESS_KEY_ID \
-e AWS_CA_BUNDLE \
-e AWS_CLI_FILE_ENCODING \
-e AWS_CONFIG_FILE \
-e AWS_DEFAULT_OUTPUT \
-e AWS_DEFAULT_REGION \
-e AWS_PAGER \
-e AWS_PROFILE \
-e AWS_ROLE_SESSION_NAME \
-e AWS_SECRET_ACCESS_KEY \
-e AWS_SESSION_TOKEN \
-e AWS_SHARED_CREDENTIALS_FILE \
-e AWS_STS_REGIONAL_ENDPOINTS \
amazon/aws-cli s3 ls
Please note that for advanced use cases you might need to allow rw (read-write) permissions, so omit the ro (read-only) limitation when mounting the .aws volume in -v$HOME/.aws:/root/.aws:ro
Volume mounting is noted in this thread but as of docker-compose v3.2 + you can Bind Mount.
For example, if you have a file named .aws_creds in the root of your project:
In your service for the compose file do this for volumes:
volumes:
# normal volume mount, already shown in thread
- ./.aws_creds:/root/.aws/credentials
# way 2, note this requires docker-compose v 3.2+
- type: bind
source: .aws_creds # from local
target: /root/.aws/credentials # to the container location
Using this idea, you can publicly store your docker images on docker-hub because your aws credentials will not physically be in the image...to have them associated, you must have the correct directory structure locally where the container is started (i.e. pulling from Git)
You could create ~/aws_env_creds containing:
touch ~/aws_env_creds
chmod 777 ~/aws_env_creds
vi ~/aws_env_creds
Add these value (replace the key of yours):
AWS_ACCESS_KEY_ID=AK_FAKE_KEY_88RD3PNY
AWS_SECRET_ACCESS_KEY=BividQsWW_FAKE_KEY_MuB5VAAsQNJtSxQQyDY2C
Press "esc" to save the file.
Run and test the container:
my_service:
build: .
image: my_image
env_file:
- ~/aws_env_creds
If someone still face the same issue after following the instructions mentioned in accepted answer then make sure that you are not passing environment variables from two different sources. In my case I was passing environment variables to docker run via a file and as parameters which was causing the variables passed as parameters show no effect.
So the following command did not work for me:
docker run --env-file ./env.list -e AWS_ACCESS_KEY_ID=ABCD -e AWS_SECRET_ACCESS_KEY=PQRST IMAGE_NAME:v1.0.1
Moving the aws credentials into the mentioned env.list file helped.
for php apache docker the following command works
docker run --rm -d -p 80:80 --name my-apache-php-app -v "$PWD":/var/www/html -v ~/.aws:/.aws --env AWS_PROFILE=mfa php:7.2-apache
Based on some of previous answers, I built my own as follows.
My project structure:
├── Dockerfile
├── code
│ └── main.py
├── credentials
├── docker-compose.yml
└── requirements.txt
My docker-compose.yml file:
version: "3"
services:
app:
build:
context: .
volumes:
- ./credentials:/root/.aws/credentials
- ./code:/home/app
My Docker file:
FROM python:3.8-alpine
RUN pip3 --no-cache-dir install --upgrade awscli
RUN mkdir /app
WORKDIR /home/app
CMD python main.py