Docker compose - Start/Stop services dynamically - docker

I'm trying to set up a docker-compose structure that sort of mimics AWS Lambda, I have my main API, an AWS Lambda Service emulator, and several Lambda Function images.
The problem with the above is that each lambda_f_n is quite heavy, I can't have them all running at once.
The idea is that api talks to lambda_server, which spins up a lambda_f_x, which then returns an output back to lambda_server and stops executing. So each lambda_f_x is run dynamically and has an ephemeral lifecycle
My current solution actually just doesn't have any lambda_f_x in the compose definition, and they are run by lambda_server using Docker HTTP API, that works with one very annoying caveat: When you compose down, they keep running, making local development hell
Is there a way I can Start/Stop services inside a docker compose dynamically? Or dynamically add containers to a docker compose group so that they all stop together?

docker compose is just a simple language to run several predefined containers together, but not a fully featured container orchestration tool.
You may want to check out docker swarm or Kubernetes that are capable of starting/stopping containers dynamically, or in your current setup just add a shutdown hook to drop all related containers on shutdown.


Should I create a docker container or docker start a stopped container?

From the docker philosophy's point of view it is more advisable:
create a container every time we need to use a certain environment and then remove it after use (docker run <image> all the time); or
create a container for a specific environment (docker run <image>), stop it when it is not necessary and whenever it is initialized again (docker start <container>);
If you docker rm the old container and docker run a new one, you will always get a clean filesystem that starts from exactly what's in the original image (plus any volume mounts). You will also fairly routinely need to delete and recreate a container to change basic options: if you need to change a port mapping or an environment variable, or if you need to update the image to have a newer version of the software, you'll be forced to delete the container.
This is enough reason for me to make my standard process be to always delete and recreate the container.
# docker build -t the-image . # can be done first if needed
docker stop the-container # so it can cleanly shut down and be removed
docker rm the-container
docker run --name the-container ... the-image
Other orchestrators like Docker Compose and Kubernetes are also set up to automatically delete and recreate the container (or Kubernetes pod) if there's a change; their standard workflows do not generally involve restarting containers in-place.
I almost never use docker start. In a Compose-based workflow I generally use only docker-compose up -d, letting it restart things if needed; docker-compose down if I need the CPU/memory resources the container stack was using but not in routine work.
I'm talking with regards to my experience in the industry so take my answer with a grain of salt, because there might be no hard evidence or reference to the theory.
Here's the answer:
In short, you never need the docker stop and docker start because taking this approach is unreliable and you might lose the container and all the data inside if no proper action is applied beforehand.
Long answer:
You should only work with images and not the containers. Whenever you need some specific data or you need the image to have some customization, you better use docker save to have the image for future use.
If you're just testing out on your local machine, or in your dev virtual machine on a remote host, you're free to use either one you like. I personally take each of the approaches on different scenarios.
But if you're talking about a production environment, you'd better use some orchestration tool; it could be as simple and easy to work with as docker-compose or docker swarm or even Kubernetes on more complex environments.
You better not take the second approach (docker run, docker stop & docker start) in those environments because at any moment in time you might lose that container and if you are solely dependent on that specific container or it's data, then you're gonna have a bad weekend.

Ansible commands on docker containers?

Upto now i had setup my ansible-playbook commands running on AWS EC2 instances.
can i run regular ansible commands like (linefile, apt, pip, etc) on container?
can i add my container-ip to hosts file in container-group and then does the same code works, here if i chanage my main.yml file that has
hosts: ec2-group
does all commands work?
i am bit beginner into this..please do confirm me i am actually thinking of making docker-compose files from scratch, and run docker-compose commands using ansible.
You can, but it's not really how Docker is designed to be used.
A Docker container is usually a wrapper around a single process. In the standard setup you create an image that has that application built and packaged, and you can just run it without any further setup. It's not usually interesting to run a bare Linux distribution container (which won't have an application installed) or to run an interactive shell as the main container process. Tutorials like Docker's Build and run your image walk through this sequence.
A corollary to this is that containers don't usually have any local state. In the best case any state a container needs is in an external database; if you can't do that then you store local state in a volume that outlives the container.
Finally, it's extremely routine to delete and recreate containers. You need to do this to change some common options; in a cluster environment like Kubernetes this can happen outside your control. When this happens the new container will restart running its default setup, and it won't know about any manual changes the previous container might have had.
So you don't usually want to try to install software directly in a running container, since that will get lost as soon as the container exits. You can, in principle, get a shell in a container (via docker exec) but this is more of a debugging tool than an administration tool. You could make the only process a container runs be an ssh daemon, but anything you start this way will get lost as soon as the container exits (and I've never seen a recipe that correctly and securely sets up credentials to access it).
I'd recommend learning the standard Dockerfile system and running self-contained Docker images over trying to adapt Ansible to this rather different environment.

Any reasons to not use Docker Swarm (instead of Docker-Compose) on a single node?

There's Docker Swarm (now built into Docker) and Docker-Compose. People seem to use Docker-Compose when running containers on a single node only. However, Docker-Compose doesn't support any of the deploy config values, see, which include mem_limit and cpus, which seems like nice/important to be able to set.
So therefore maybe I should use Docker Swarm? although I'm deploying on a single node only. Also, then the installation instructions will be simpler for other people to follow (they won't need to install Docker-Compose).
But maybe there are reasons why I should not use Swarm on a single node?
I'm posting an answer below, but I'm not sure if it's correct.
Edit: Please note that this is not an opinion based question. If you have a look at the answer below, you'll see that there are "have-to" and "cannot-do" facts about this.
For development, use Docker-Compose. Because only Docker-Compose is able to read your Dockerfiles and build images for you. Docker Stack instead needs pre-built images. Also, with Docker-Compose, you can easily start and stop single containers, with docker-compose kill ... and ... start .... This is useful, during development (in my experience). For example, to see how the app server reacts if you kill the database. Then you don't want Swarm to auto-restart the database directly.
In production, use Docker Swarm (unless: see below), so you can configure mem limits. Docker-Compose has less functionality that Docker Swarm (no mem or cpu limits for example) and doesn't have anything that Swarm does not have (right?). So no reason to use Compose in production. (Except maybe if you know how Compose works already and don't want to spend time reading about the new Swarm commands.)
Docker Swarm doesn't, however, support .env files like Docker-Compose does. So you cannot have e.g. IMAGE_VERSION=1.2.3 in an .env file and then in the docker-compose.yml file have: image: name:${IMAGE_VERSION}. See — instead you'll need to set env vars "manually": IMAGE_VERSION=SOMETHING docker stack up ... (this actually made me stick with Docker-Compose. + that I didn't reasonably quickly find out how to view a container's log, via Swarm; Swarm seemed more complicated.)
In addition to #KajMagnus answer I should note that Docker Swarm still don't support Linux Capabilities as Docker [Compose] do. You can learn about this issue and dive into Docker community discussions here.

Docker and jenkins

I am working with docker and jenkins, and I'm trying to do two main tasks :
Control and manage docker images and containers (run/start/stop) with jenkins.
Set up a development environment in a docker image then build and test my application which is in the container using jenkins.
While I was surfing the net I found many solutions :
Run jenkins as container and link it with other containers.
Run jenkins as service and use the jenkins plugins provided to support docker.
Run jenkins inside the container which contain the development environment.
So my question is what is the best solution or you can suggest an other approach.
One more question I heard about running a container inside a container. Is it a good practice or better avoid it ?
To run Jenkins as a containerized service is not a difficult task. There are many images out there that allow you to do just that. It took me just a couple minutes to make Jenkins 2.0-beta-1 run in a container, compiling from source (image can be found here). Particularity I like this approach, you just have to make sure to use a data volume or a data container as jenkins_home to make your data persist.
Things become a little bit trickier when you want to use this Jenkins - in a container - to build and manage containers itself. To achieve that, you need to implement something called docker-in-docker, because you'll need a docker daemon and client available inside the Jenkins container.
There is a very good tutorial explaining how to do it: Docker in Docker with Jenkins and Supervisord.
Basically, you will need to make the two processes (Jenkins and Docker) run in the container, using something like supervisord. It's doable and proclaims to have good isolation, etc... But can be really tricky, because the docker daemon itself has some dependencies, that need to be present inside the container as well. So, only using supervisord and running both processes is not enough, you'll need to make use of the DIND project itself to make it work... AND you'll need to run the container in privileged mode... AND you'll need to deal with some strange DNS problems...
For my personal taste, it sounded too much workarounds to make something simple work and having two services running inside one container seems to break docker good practices and the principle of separation of concerns, something I'd like to avoid.
My opinion got even stronger when I read this: Using Docker-in-Docker for your CI or testing environment? Think twice. It's worth to mention that this last post is from the DIND author himself, so he deserves some attention.
My final solution is: run Jenkins as a containerized service, yes, but consider the docker daemon as part of the provisioning of the underlying server, even because your docker cache and images are data that you'll probably want to persist and they are fully owned and controlled by the daemon.
With this setup, all you need to do is mount the docker daemon socket in your Jenkins image (which also needs the docker client, but not the service):
$ docker run -p 8080:8080 -v /var/run/docker.sock:/var/run/docker.sock -v local/folder/with/jenkins_home:/var/jenkins_home namespace/my-jenkins-image
Or with a docker-compose volumes directive:
version: '2'
image: namespace/my-jenkins-image
- '8080:8080'
- /var/run/docker.sock:/var/run/docker.sock
- local/folder/with/jenkins_home:/var/jenkins_home
# other services ...

Strategies for deciding when to use 'docker run' vs 'docker start' and using the latest version of a given image

I'm dockerizing some of our services. For our dev environment, I'd like to make things as easy as possible for our developers and so I'm writing some scripts to manage the dockerized components. I want developers to be able to start and stop these services just as if they were non-dockerized. I don't want them to have to worry about creating and running the container vs stopping and starting and already-created container. I was thinking that this could be handled using Fig. To create the container (if it doesn't already exist) and start the service, I'd use fig up --no-recreate. To stop the service, I'd use fig stop.
I'd also like to ensure that developers are running containers built using the latest images. In other words, something would check to see if there was a later version of the image in our Docker registry. If so, this image would be downloaded and run to create a new container from that image. At the moment it seems like I'd have to use docker commands to list the contents of the registry (docker search) and compare that to existing local containers (docker ps -a) with the addition of some greping and awking or use the Docker API to achieve the same thing.
Any persistent data will be written to mounted volumes so the data should survive the creation of a new container.
This seems like it might be a common pattern so I'm wondering whether anyone else has given these sorts of scenarios any thought.
This is what I've decided to do for now for our Neo4j Docker image:
I've written a shell script around docker run that accepts command-line arguments for the port, database persistence directory on the host, log file persistence directory on the host. It executes a docker run command that looks like:
docker run --rm -it -p ${port}:7474 -v ${graphdir}:/var/lib/neo4j/data/graph.db -v ${logdir}:/var/log/neo4j my/neo4j
By default port is 7474, graphdir is $PWD/graph.db and logdir is $PWD/log.
--rm removes the container on exit, however the database and logs are maintained on the host's file system. So no containers are left around.
-it allows the container and the Neo4j service running within it to receive signals so that the service can be gracefully shut down (the Neo4j server gracefully shuts down on SIGINT) and the container exited by hitting ^C or sending it a SIGINT if the developer puts this in the background. No need for separate start/stop commands.
Although I certainly wouldn't do this in production, I think this fine for a dev environment.
I am not familiar with fig but your scenario seems good.
Usually, I prefer to kill/delete + run my container instead of playing with start/stop though. That way, if there is a new image available, Docker will use it. This work only for stateless services. As you are using Volumes for persistent data, you could do something like this.
Regarding the image update, what about running docker pull <image> every N minutes and checking the "Status" that the command returns? If it is up to date, then do nothing, otherwise, kill/rerun the container.