Related
Let's say I have pulled the official mysql:5.6.21 image.
I have deployed this image by creating several docker containers.
These containers have been running for some time until MySQL 5.6.22 is released. The official image of mysql:5.6 gets updated with the new release, but my containers still run 5.6.21.
How do I propagate the changes in the image (i.e. upgrade MySQL distro) to all my existing containers? What is the proper Docker way of doing this?
After evaluating the answers and studying the topic I'd like to summarize.
The Docker way to upgrade containers seems to be the following:
Application containers should not store application data. This way you can replace app container with its newer version at any time by executing something like this:
docker pull mysql
docker stop my-mysql-container
docker rm my-mysql-container
docker run --name=my-mysql-container --restart=always \
-e MYSQL_ROOT_PASSWORD=mypwd -v /my/data/dir:/var/lib/mysql -d mysql
You can store data either on host (in directory mounted as volume) or in special data-only container(s). Read more about it
About volumes (Docker docs)
Tiny Docker Pieces, Loosely Joined (by Tom Offermann)
How to deal with persistent storage (e.g. databases) in Docker (Stack Overflow question)
Upgrading applications (eg. with yum/apt-get upgrade) within containers is considered to be an anti-pattern. Application containers are supposed to be immutable, which shall guarantee reproducible behavior. Some official application images (mysql:5.6 in particular) are not even designed to self-update (apt-get upgrade won't work).
I'd like to thank everybody who gave their answers, so we could see all different approaches.
I don't like mounting volumes as a link to a host directory, so I came up with a pattern for upgrading docker containers with entirely docker managed containers. Creating a new docker container with --volumes-from <container> will give the new container with the updated images shared ownership of docker managed volumes.
docker pull mysql
docker create --volumes-from my_mysql_container [...] --name my_mysql_container_tmp mysql
By not immediately removing the original my_mysql_container yet, you have the ability to revert back to the known working container if the upgraded container doesn't have the right data, or fails a sanity test.
At this point, I'll usually run whatever backup scripts I have for the container to give myself a safety net in case something goes wrong
docker stop my_mysql_container
docker start my_mysql_container_tmp
Now you have the opportunity to make sure the data you expect to be in the new container is there and run a sanity check.
docker rm my_mysql_container
docker rename my_mysql_container_tmp my_mysql_container
The docker volumes will stick around so long as any container is using them, so you can delete the original container safely. Once the original container is removed, the new container can assume the namesake of the original to make everything as pretty as it was to begin.
There are two major advantages to using this pattern for upgrading docker containers. Firstly, it eliminates the need to mount volumes to host directories by allowing volumes to be directly transferred to an upgraded containers. Secondly, you are never in a position where there isn't a working docker container; so if the upgrade fails, you can easily revert to how it was working before by spinning up the original docker container again.
Just for providing a more general (not mysql specific) answer...
In short
Synchronize with service image registry (https://docs.docker.com/compose/compose-file/#image):
docker-compose pull
Recreate container if docker-compose file or image have changed:
docker-compose up -d
Background
Container image management is one of the reason for using docker-compose
(see https://docs.docker.com/compose/reference/up/)
If there are existing containers for a service, and the service’s configuration or image was changed after the container’s creation, docker-compose up picks up the changes by stopping and recreating the containers (preserving mounted volumes). To prevent Compose from picking up changes, use the --no-recreate flag.
Data management aspect being also covered by docker-compose through mounted external "volumes" (See https://docs.docker.com/compose/compose-file/#volumes) or data container.
This leaves potential backward compatibility and data migration issues untouched, but these are "applicative" issues, not Docker specific, which have to be checked against release notes and tests...
I would like to add that if you want to do this process automatically (download, stop and restart a new container with the same settings as described by #Yaroslav) you can use WatchTower. A program that auto updates your containers when they are changed https://github.com/v2tec/watchtower
Consider for this answers:
The database name is app_schema
The container name is app_db
The root password is root123
How to update MySQL when storing application data inside the container
This is considered a bad practice, because if you lose the container, you will lose the data. Although it is a bad practice, here is a possible way to do it:
1) Do a database dump as SQL:
docker exec app_db sh -c 'exec mysqldump app_schema -uroot -proot123' > database_dump.sql
2) Update the image:
docker pull mysql:5.6
3) Update the container:
docker rm -f app_db
docker run --name app_db --restart unless-stopped \
-e MYSQL_ROOT_PASSWORD=root123 \
-d mysql:5.6
4) Restore the database dump:
docker exec app_db sh -c 'exec mysql -uroot -proot123' < database_dump.sql
How to update MySQL container using an external volume
Using an external volume is a better way of managing data, and it makes easier to update MySQL. Loosing the container will not lose any data. You can use docker-compose to facilitate managing multi-container Docker applications in a single host:
1) Create the docker-compose.yml file in order to manage your applications:
version: '2'
services:
app_db:
image: mysql:5.6
restart: unless-stopped
volumes_from: app_db_data
app_db_data:
volumes: /my/data/dir:/var/lib/mysql
2) Update MySQL (from the same folder as the docker-compose.yml file):
docker-compose pull
docker-compose up -d
Note: the last command above will update the MySQL image, recreate and start the container with the new image.
Similar answer to above
docker images | awk '{print $1}' | grep -v 'none' | grep -iv 'repo' | xargs -n1 docker pull
Here's what it looks like using docker-compose when building a custom Dockerfile.
Build your custom Dockerfile first, appending a next version number to differentiate. Ex: docker build -t imagename:version . This will store your new version locally.
Run docker-compose down
Edit your docker-compose.yml file to reflect the new image name you set at step 1.
Run docker-compose up -d. It will look locally for the image and use your upgraded one.
-EDIT-
My steps above are more verbose than they need to be. I've optimized my workflow by including the build: . parameter to my docker-compose file. The steps looks this now:
Verify that my Dockerfile is what I want it to look like.
Set the version number of my image name in my docker-compose file.
If my image isn't built yet: run docker-compose build
Run docker-compose up -d
I didn't realize at the time, but docker-compose is smart enough to simply update my container to the new image with the one command, instead of having to bring it down first.
If you do not want to use Docker Compose, I can recommend portainer. It has a recreate function that lets you recreate a container while pulling the latest image.
You need to either rebuild all the images and restart all the containers, or somehow yum update the software and restart the database. There is no upgrade path but that you design yourself.
Taking from http://blog.stefanxo.com/2014/08/update-all-docker-images-at-once/
You can update all your existing images using the following command pipeline:
docker images | awk '/^REPOSITORY|\<none\>/ {next} {print $1}' | xargs -n 1 docker pull
Make sure you are using volumes for all the persistent data (configuration, logs, or application data) which you store on the containers related to the state of the processes inside that container. Update your Dockerfile and rebuild the image with the changes you wanted, and restart the containers with your volumes mounted at their appropriate place.
Tried a bunch of things from here, but this worked out for me eventually.
IF you have AutoRemove: On on the Containers you can't STOP and EDIT the contianers, or a Service is running that can't be stopped even momentarily,
You must:
PULL latest image --> docker pull [image:latest]
Verify if the correct image is pulled, you can see the UNUSED tag in the Portainer Images section
UPDATE the service using Portainer or CLI and make sure you use LATEST VERSION of the image, Portainer will give you the option to do same.
THis would not only UPDATE the Container with Latest Image, but also keep the Service Running.
This is something I've also been struggling with for my own images. I have a server environment from which I create a Docker image. When I update the server, I'd like all users who are running containers based on my Docker image to be able to upgrade to the latest server.
Ideally, I'd prefer to generate a new version of the Docker image and have all containers based on a previous version of that image automagically update to the new image "in place." But this mechanism doesn't seem to exist.
So the next best design I've been able to come up with so far is to provide a way to have the container update itself--similar to how a desktop application checks for updates and then upgrades itself. In my case, this will probably mean crafting a script that involves Git pulls from a well-known tag.
The image/container doesn't actually change, but the "internals" of that container change. You could imagine doing the same with apt-get, yum, or whatever is appropriate for you environment. Along with this, I'd update the myserver:latest image in the registry so any new containers would be based on the latest image.
I'd be interested in hearing whether there is any prior art that addresses this scenario.
Update
This is mainly to query the container not to update as building images is the way to be done
I had the same issue so I created docker-run, a very simple command-line tool that runs inside a docker container to update packages in other running containers.
It uses docker-py to communicate with running docker containers and update packages or run any arbitrary single command
Examples:
docker run --rm -v /var/run/docker.sock:/tmp/docker.sock itech/docker-run exec
by default this will run date command in all running containers and return results but you can issue any command e.g. docker-run exec "uname -a"
To update packages (currently only using apt-get):
docker run --rm -v /var/run/docker.sock:/tmp/docker.sock itech/docker-run update
You can create and alias and use it as a regular command line
e.g.
alias docker-run='docker run --rm -v /var/run/docker.sock:/tmp/docker.sock itech/docker-run'
I have a lot of standard runtime docker images like python3 with tensorflow 1.7 installed and I want to use these standard images to run some customers code out side of them. The scenario seems quite similar with the serverless. So what is the best way to put the code into runtime dockers?
Right now I am trying to use a persistent volume to mount the code into runtime. But it has a lot of work. Is there some solution easier for this?
UPDATE
What is the workflow for google machine learning engine or floydhub. I think what I want is similar. They have a command line tool to make the local code combine with a standard env.
Following cloud native practices, code should be immutable, and releases and their dependencies uniquely identifiable for repeat-ability, replic-ability, etc - in short: you should really create images with your src code.
In your case, that would mean basing your Dockerfile on upstream python3 or TF images, there are a couple projects that may help with the workflow for above (code+build-release-run):
https://github.com/Azure/draft -- looks like better suited for your case
https://github.com/GoogleContainerTools/skaffold -- more golang friendly afaics
Hope it helps --jjo
One of the best practices is NOT to mount the code from a volume into it, but create a client-specific image that uses your TensorFlow image as a base image:
# Your base image comes in here.
FROM aisensiy/tensorflow:1
# Copy the client into your image.
COPY src /
# As Kubernetes will run your containers with an
# arbitrary UID, we set the user to nobody.
USER nobody
# ... and they will run with GID 0, so we
# need to change the group to 0 and make
# your stuff accessible to GID 0.
RUN \
chgrp -R 0 /src && \
chmod -R g=u && \
true
CMD ["/usr/bin/python", ...]
Some more best practices:
Always log to stdout instead of log files.
One process per container. If you need multiple local
processes, co-locate them into a single pod.
Even more best practices are provided in the OpenShift documentation: https://docs.openshift.org/latest/creating_images/guidelines.html
https://docs.openshift.org/latest/creating_images/guidelines.html
The code file can be passed from stdin when the container is being started. This way you can run arbitrary code when starting the container.
Please see below for example:
root#node-1:~# cat hello.py
print("This line will be printed.")
root#node-1:~#
root#node-1:~# docker run --rm -i python python < hello.py
This line will be printed.
root#node-1:~#
If this is your case,
You have a docker image with code in it.
Aim: To update the code inside docker image.
Solution:
Run a bash session with the docker image with a directory in your file system mounted as volume.
Place the updated code in the volume directory.
From the docker bash session replace the real code with updated code from the volume.
Save the current state of container as new docker image.
Sample Commands
Assume ~/my-dir in your file system has the new code updated-code.py
$ docker run -it --volume ~/my-dir:/workspace --workdir /workspace my-docker-image bash
Now a new bash session will start inside docker container.
Assuming you have the code in '/code/code.py' inside docker container,
You can simply update the code by
$ cp /workspace/updated-code.py /code/code.py
Or you can create new directory and place the code.
$ cp /workspace/updated-code.py /my-new-dir/code.py
Now the docker container contains updated code. But changes will be reset if you close the container and again run the image. To create a docker image with latest code, save this state of container using docker commit.
Open a new tab in the terminal.
$ docker ps
Will list all running docker containers.
Find CONTAINER ID of your docker container and save it.
$ docker commit id-of-your-container new-docker-image-name
Now run the docker image with latest code
$ docker run -it new-docker-image-name
Note: It is recommended to remove the old docker image using docker rmi command as docker images are heavy.
We're dealing with a similar challenge also. Our approach is to build a static docker image where Tensorflow, Python, etc are built once and maintained.
Each user has a PVC (persistent volume claim) where large files that may change such as datasets and workspaces live.
Then we have a bash shell that launches the cluster resources and syncs the workspace using ksync (like rsync for a kubernetes cluster).
We are about to "dockerize" our not-so-big infrastructure. One crucial question here is the whole backup / restore workflow, which is I think crucial for most enterprise but even private users.
I know about the export and save features of docker which will generate a tarball of a running container, which is neat because it can be done without shutting down the container.
So let's say we are running a container X and we have mounted some volumes:
-v /home/user/dockerapp-X/data:/var/www/html
-v /home/user/dockerapp-X/logs:/var/logs/app-x
-v /home/user/dockerapp-X/config:/etc/app-x
The biggest benefit of this is, if we update app-X we just have to pull the new image and restart the container.
But:
This way those directories wouldn't get backupped if we do docker-export or save.
So either we can just backup those directories extra, with rsync, backula or whatever. I guess this would be the "standart" way of backupping. But there is no guarantee and also no connection between the current version of the image and the data.
On a VM we would just make a snapshot to have the data and the app connected.
So the question is:
Is it a best practice to just make a Dockerfile with the current app-x version and copy the volumes in the image and build/push the whole image to our private repo?
so it would look like this:
FROM repo/app-x
COPY /home/user/dockerapp-X/data:/var/www/html
COPY /home/user/dockerapp-X/logs:/var/logs/app-x
COPY /home/user/dockerapp-X/config:/etc/app-x
then
docker build -t repo/infra/app-x:backup-v1-22.10.2016 .
docker push repo/infra/app-x:backup-v1-22.10.2016
This would mean that in our repo there is a snapshot for the current version of the app and the image contains all current data of the volumes.
So restoring would be:
docker run --name=backup-restored repo/infra/app-x:backup-v1-22.10.2016
And we could even mount the data folders locally on the host again:
docker run --name=backup-restored \
-v /home/user/dockerapp-X/data:/var/www/html
-v /home/user/dockerapp-X/logs:/var/logs/app-x
-v /home/user/dockerapp-X/config:/etc/app-x
repo/infra/app-x:backup-v1-22.10.2016
Will my data and my app have the correct data and app version?
So, I'm trying to package my WordPress image in a way that all files except the uploads are persisted. In order to do so, I have created my Dockerfile which uses the official WordPress image as its base, and adds the files from an archive (containing all the WordPress files, themes, plugins, etc.), like so:
FROM wordpress
ADD archive.tar.gz /var/www/html/
Since I want the uploads to be persisted, I have created a separate data volume container, e.g. test2.com-wp-data:
docker create -v /var/www/html/wp-content/uploads —name test2.com-wp-data wordpress
Then I simply mount it via —-volumes-from flag:
docker run —name test2.com --volumes-from test2.com-wp-data -d --link test2.com-mysql:mysql myimage
However, when I inspect my newly created container, I cannot find /var/www/html/wp-content/uploads:
# docker inspect -f '{{.HostConfig.VolumesFrom}}' test2.com
[test2.com-wp-data]
# docker inspect -f '{{.Volumes}}' test2.com
map[/var/www/html:/var/lib/docker/vfs/dir/4fff1d36d5aacd0b2c73977acf8fe680bda6fd891f2c4410a90f6c2dca4aaedf]
I can see that both /var/www/html and /var/www/html/wp-content/uploads are set up as volumes in my test2.com-wp-data data container:
# docker inspect -f '{{.Config.Volumes}}' test2.com-wp-data
map[/var/www/html:map[] /var/www/html/wp-content/uploads:map[]]
I know that the wordpress image by default creates a /var/www/html volume, for which I don't really mind, but does that mean that anything that is below that folder is ignored if mounted separately? Will I need to build my own WordPress image in order to have /var/www/html/wp-content/uploads set as a volume in my WordPress container?
Thank you very much for your time!
EDIT: I've tested a different setup with a folder that has nothing to do with /var/www/html, and the result is the same: —-volumes-from is ignored.
Version 1.4 + of docker should be what you need to get this working. Older versions of docker don't seem to play nicely with data-only containers instantiated with "create" rather than "run".
Well, after some further testing I've realised that despite what the documentation indicates, docker create alone is not enough to get a working data volume working. I've only managed to get working data volumes by instantiating them with the docker run command, as follows:
docker run —-name data -v /var/www/html/wp-content/uploads mysql true
This way the container exits immediately, but if I use it to attach the data volume to another container it works as expected.
If anyone knows any specific reason behind this behaviour, I'd be glad to learn more, especially since the documentation seems to be misleading.
Thanks!
EDIT: It turns out I was using Docker 1.3.x, which hadn't implemented this feature yet, hence why the documentation was misleading for me!
Let's say I have pulled the official mysql:5.6.21 image.
I have deployed this image by creating several docker containers.
These containers have been running for some time until MySQL 5.6.22 is released. The official image of mysql:5.6 gets updated with the new release, but my containers still run 5.6.21.
How do I propagate the changes in the image (i.e. upgrade MySQL distro) to all my existing containers? What is the proper Docker way of doing this?
After evaluating the answers and studying the topic I'd like to summarize.
The Docker way to upgrade containers seems to be the following:
Application containers should not store application data. This way you can replace app container with its newer version at any time by executing something like this:
docker pull mysql
docker stop my-mysql-container
docker rm my-mysql-container
docker run --name=my-mysql-container --restart=always \
-e MYSQL_ROOT_PASSWORD=mypwd -v /my/data/dir:/var/lib/mysql -d mysql
You can store data either on host (in directory mounted as volume) or in special data-only container(s). Read more about it
About volumes (Docker docs)
Tiny Docker Pieces, Loosely Joined (by Tom Offermann)
How to deal with persistent storage (e.g. databases) in Docker (Stack Overflow question)
Upgrading applications (eg. with yum/apt-get upgrade) within containers is considered to be an anti-pattern. Application containers are supposed to be immutable, which shall guarantee reproducible behavior. Some official application images (mysql:5.6 in particular) are not even designed to self-update (apt-get upgrade won't work).
I'd like to thank everybody who gave their answers, so we could see all different approaches.
I don't like mounting volumes as a link to a host directory, so I came up with a pattern for upgrading docker containers with entirely docker managed containers. Creating a new docker container with --volumes-from <container> will give the new container with the updated images shared ownership of docker managed volumes.
docker pull mysql
docker create --volumes-from my_mysql_container [...] --name my_mysql_container_tmp mysql
By not immediately removing the original my_mysql_container yet, you have the ability to revert back to the known working container if the upgraded container doesn't have the right data, or fails a sanity test.
At this point, I'll usually run whatever backup scripts I have for the container to give myself a safety net in case something goes wrong
docker stop my_mysql_container
docker start my_mysql_container_tmp
Now you have the opportunity to make sure the data you expect to be in the new container is there and run a sanity check.
docker rm my_mysql_container
docker rename my_mysql_container_tmp my_mysql_container
The docker volumes will stick around so long as any container is using them, so you can delete the original container safely. Once the original container is removed, the new container can assume the namesake of the original to make everything as pretty as it was to begin.
There are two major advantages to using this pattern for upgrading docker containers. Firstly, it eliminates the need to mount volumes to host directories by allowing volumes to be directly transferred to an upgraded containers. Secondly, you are never in a position where there isn't a working docker container; so if the upgrade fails, you can easily revert to how it was working before by spinning up the original docker container again.
Just for providing a more general (not mysql specific) answer...
In short
Synchronize with service image registry (https://docs.docker.com/compose/compose-file/#image):
docker-compose pull
Recreate container if docker-compose file or image have changed:
docker-compose up -d
Background
Container image management is one of the reason for using docker-compose
(see https://docs.docker.com/compose/reference/up/)
If there are existing containers for a service, and the service’s configuration or image was changed after the container’s creation, docker-compose up picks up the changes by stopping and recreating the containers (preserving mounted volumes). To prevent Compose from picking up changes, use the --no-recreate flag.
Data management aspect being also covered by docker-compose through mounted external "volumes" (See https://docs.docker.com/compose/compose-file/#volumes) or data container.
This leaves potential backward compatibility and data migration issues untouched, but these are "applicative" issues, not Docker specific, which have to be checked against release notes and tests...
I would like to add that if you want to do this process automatically (download, stop and restart a new container with the same settings as described by #Yaroslav) you can use WatchTower. A program that auto updates your containers when they are changed https://github.com/v2tec/watchtower
Consider for this answers:
The database name is app_schema
The container name is app_db
The root password is root123
How to update MySQL when storing application data inside the container
This is considered a bad practice, because if you lose the container, you will lose the data. Although it is a bad practice, here is a possible way to do it:
1) Do a database dump as SQL:
docker exec app_db sh -c 'exec mysqldump app_schema -uroot -proot123' > database_dump.sql
2) Update the image:
docker pull mysql:5.6
3) Update the container:
docker rm -f app_db
docker run --name app_db --restart unless-stopped \
-e MYSQL_ROOT_PASSWORD=root123 \
-d mysql:5.6
4) Restore the database dump:
docker exec app_db sh -c 'exec mysql -uroot -proot123' < database_dump.sql
How to update MySQL container using an external volume
Using an external volume is a better way of managing data, and it makes easier to update MySQL. Loosing the container will not lose any data. You can use docker-compose to facilitate managing multi-container Docker applications in a single host:
1) Create the docker-compose.yml file in order to manage your applications:
version: '2'
services:
app_db:
image: mysql:5.6
restart: unless-stopped
volumes_from: app_db_data
app_db_data:
volumes: /my/data/dir:/var/lib/mysql
2) Update MySQL (from the same folder as the docker-compose.yml file):
docker-compose pull
docker-compose up -d
Note: the last command above will update the MySQL image, recreate and start the container with the new image.
Similar answer to above
docker images | awk '{print $1}' | grep -v 'none' | grep -iv 'repo' | xargs -n1 docker pull
Here's what it looks like using docker-compose when building a custom Dockerfile.
Build your custom Dockerfile first, appending a next version number to differentiate. Ex: docker build -t imagename:version . This will store your new version locally.
Run docker-compose down
Edit your docker-compose.yml file to reflect the new image name you set at step 1.
Run docker-compose up -d. It will look locally for the image and use your upgraded one.
-EDIT-
My steps above are more verbose than they need to be. I've optimized my workflow by including the build: . parameter to my docker-compose file. The steps looks this now:
Verify that my Dockerfile is what I want it to look like.
Set the version number of my image name in my docker-compose file.
If my image isn't built yet: run docker-compose build
Run docker-compose up -d
I didn't realize at the time, but docker-compose is smart enough to simply update my container to the new image with the one command, instead of having to bring it down first.
If you do not want to use Docker Compose, I can recommend portainer. It has a recreate function that lets you recreate a container while pulling the latest image.
You need to either rebuild all the images and restart all the containers, or somehow yum update the software and restart the database. There is no upgrade path but that you design yourself.
Taking from http://blog.stefanxo.com/2014/08/update-all-docker-images-at-once/
You can update all your existing images using the following command pipeline:
docker images | awk '/^REPOSITORY|\<none\>/ {next} {print $1}' | xargs -n 1 docker pull
Make sure you are using volumes for all the persistent data (configuration, logs, or application data) which you store on the containers related to the state of the processes inside that container. Update your Dockerfile and rebuild the image with the changes you wanted, and restart the containers with your volumes mounted at their appropriate place.
Tried a bunch of things from here, but this worked out for me eventually.
IF you have AutoRemove: On on the Containers you can't STOP and EDIT the contianers, or a Service is running that can't be stopped even momentarily,
You must:
PULL latest image --> docker pull [image:latest]
Verify if the correct image is pulled, you can see the UNUSED tag in the Portainer Images section
UPDATE the service using Portainer or CLI and make sure you use LATEST VERSION of the image, Portainer will give you the option to do same.
THis would not only UPDATE the Container with Latest Image, but also keep the Service Running.
This is something I've also been struggling with for my own images. I have a server environment from which I create a Docker image. When I update the server, I'd like all users who are running containers based on my Docker image to be able to upgrade to the latest server.
Ideally, I'd prefer to generate a new version of the Docker image and have all containers based on a previous version of that image automagically update to the new image "in place." But this mechanism doesn't seem to exist.
So the next best design I've been able to come up with so far is to provide a way to have the container update itself--similar to how a desktop application checks for updates and then upgrades itself. In my case, this will probably mean crafting a script that involves Git pulls from a well-known tag.
The image/container doesn't actually change, but the "internals" of that container change. You could imagine doing the same with apt-get, yum, or whatever is appropriate for you environment. Along with this, I'd update the myserver:latest image in the registry so any new containers would be based on the latest image.
I'd be interested in hearing whether there is any prior art that addresses this scenario.
Update
This is mainly to query the container not to update as building images is the way to be done
I had the same issue so I created docker-run, a very simple command-line tool that runs inside a docker container to update packages in other running containers.
It uses docker-py to communicate with running docker containers and update packages or run any arbitrary single command
Examples:
docker run --rm -v /var/run/docker.sock:/tmp/docker.sock itech/docker-run exec
by default this will run date command in all running containers and return results but you can issue any command e.g. docker-run exec "uname -a"
To update packages (currently only using apt-get):
docker run --rm -v /var/run/docker.sock:/tmp/docker.sock itech/docker-run update
You can create and alias and use it as a regular command line
e.g.
alias docker-run='docker run --rm -v /var/run/docker.sock:/tmp/docker.sock itech/docker-run'