I’m new to working on Linux. I apologize if this is a dumb question. Despite searching for more than a week, I was not able to derive a clear answer to my question.
I’m running a very long Python program on Nvidia CPUs. The output is several csv files. It takes long to compute the output, so I use nohup to be able to exit the process.
Let’s say main.py file is this
import numpy as p
import pandas as pd
if __name__ == ‘__main__’:
a = np.arange(1,1000)
data = a*2
filename = ‘results.csv’
output = pd.DataFrame(data, columns = [“Output”])
output.to_csv(filename)
The calculations for data is more complicated, of course. I build a docker container, and run this program inside this container. When I use python main.py for a smaller-sized example, there is no problem. It writes the csv files.
My question is this:
When I do nohup python main.py &, I check what’s going on with tail -f nohup.out in the docker container, I get what it is doing at that time but I cannot exit it and let the execution run its course. It just stops there. How can I exit safely from the screen that comes with tail -f nohup.out?
I tried not checking the condition of the code and letting the code continue for two days, then I returned. The output of tail -f nohup.out indicated that the execution finished but csv files were nowhere to be seen. It is somehow bundled up inside nohup.out or does it indicate something else is wrong?
If you're going to run this setup in a Docker container:
A Docker container runs only one process, as a foreground process; when that process exits the container completes. That process is almost always the script or server you're trying to run and not an interactive shell. But;
It's possible to use Docker constructs to run the container itself in the background, and collect its logs while it's running or after it completes.
A typical Dockerfile for a Python program like this might look like:
FROM python:3.10
# Create and use some directory; it can be anything, but do
# create _some_ directory.
WORKDIR /app
# Install Python dependencies as a separate step. Doing this first
# saves time if you repeat `docker build` without changing the
# requirements list.
COPY requirements.txt .
RUN pip install -r requirements.txt
# Copy in the rest of the application.
COPY . .
# Set the main container command to be the script.
CMD ["./main.py"]
The script should be executable (chmod +x main.py on your host) and begin with a "shebang" line (#!/usr/bin/env python3) so the system knows where to find the interpreter.
You will hear recommendations to use both CMD and ENTRYPOINT for the final line. It doesn't matter much to your immediate question. I prefer CMD for two reasons: it's easier to launch an alternate command to debug your container (docker run --rm your-image ls -l vs. docker run --rm --entrypoint ls your-image -l), and there's a very useful pattern of using ENTRYPOINT to do some initial setup (creating environment variables dynamically, running database migrations, ...) and then launching CMD.
Having built the image, you can use the docker run -d option to launch it in the background, and then run docker logs to see what comes out of it.
# Build the image.
docker build -t long-python-program .
# Run it, in the background.
docker run -d --name run1 long-python-program
# Review its logs.
docker logs run1
If you're running this to produce files that need to be read back from the host, you need to mount a host directory into your container at the time you start it. You need to make a couple of changes to do this successfully.
In your code, you need to write the results somewhere different than your application code. You can't mount a host directory over the /app directory since it will hide the code you're actually trying to run.
data_dir = os.getenv('DATA_DIR', 'data')
filename = os.path.join(data_dir, 'results.csv')
Optionally, in your Dockerfile, create this directory and set a pointer to it. Since my sample code gets its location from an environment variable you can again use any path you want.
# Create the data directory.
RUN mkdir /data
ENV DATA_DIR=/data
When you launch the container, the docker run -v option mounts filesystems into the container. For this sort of output file you're looking for a bind mount that directly attaches a host directory to the container.
docker run -d --name run2 \
-v "$PWD/results:/data" \
long-python-program
In this example so far we haven't set the USER of the program, and it will run as root. You can change the Dockerfile to set up an alternate USER (which is good practice); you do not need to chown anything except the data directory to be owned by that user (leaving your code owned by root and not world-writeable is also good practice). If you do this, when you launch the container (on native Linux) you need to provide the host numeric user ID that can write to the host directory; you do not need to make other changes in the Dockerfile.
docker run -d --name run2 \
-u $(id -u) \
-v "$PWD/results:/data" \
long-python-program
1- Container is a foreground process. Use CMD or Entrypoint in Dockerfile.
2- Map volume in docker to linux directory's.
How to control host from docker container?
For example, how to execute copied to host bash script?
This answer is just a more detailed version of Bradford Medeiros's solution, which for me as well turned out to be the best answer, so credit goes to him.
In his answer, he explains WHAT to do (named pipes) but not exactly HOW to do it.
I have to admit I didn't know what named pipes were when I read his solution. So I struggled to implement it (while it's actually very simple), but I did succeed.
So the point of my answer is just detailing the commands you need to run in order to get it working, but again, credit goes to him.
PART 1 - Testing the named pipe concept without docker
On the main host, chose the folder where you want to put your named pipe file, for instance /path/to/pipe/ and a pipe name, for instance mypipe, and then run:
mkfifo /path/to/pipe/mypipe
The pipe is created.
Type
ls -l /path/to/pipe/mypipe
And check the access rights start with "p", such as
prw-r--r-- 1 root root 0 mypipe
Now run:
tail -f /path/to/pipe/mypipe
The terminal is now waiting for data to be sent into this pipe
Now open another terminal window.
And then run:
echo "hello world" > /path/to/pipe/mypipe
Check the first terminal (the one with tail -f), it should display "hello world"
PART 2 - Run commands through the pipe
On the host container, instead of running tail -f which just outputs whatever is sent as input, run this command that will execute it as commands:
eval "$(cat /path/to/pipe/mypipe)"
Then, from the other terminal, try running:
echo "ls -l" > /path/to/pipe/mypipe
Go back to the first terminal and you should see the result of the ls -l command.
PART 3 - Make it listen forever
You may have noticed that in the previous part, right after ls -l output is displayed, it stops listening for commands.
Instead of eval "$(cat /path/to/pipe/mypipe)", run:
while true; do eval "$(cat /path/to/pipe/mypipe)"; done
(you can nohup that)
Now you can send unlimited number of commands one after the other, they will all be executed, not just the first one.
PART 4 - Make it work even when reboot happens
The only caveat is if the host has to reboot, the "while" loop will stop working.
To handle reboot, here what I've done:
Put the while true; do eval "$(cat /path/to/pipe/mypipe)"; done in a file called execpipe.sh with #!/bin/bash header
Don't forget to chmod +x it
Add it to crontab by running
crontab -e
And then adding
#reboot /path/to/execpipe.sh
At this point, test it: reboot your server, and when it's back up, echo some commands into the pipe and check if they are executed.
Of course, you aren't able to see the output of commands, so ls -l won't help, but touch somefile will help.
Another option is to modify the script to put the output in a file, such as:
while true; do eval "$(cat /path/to/pipe/mypipe)" &> /somepath/output.txt; done
Now you can run ls -l and the output (both stdout and stderr using &> in bash) should be in output.txt.
PART 5 - Make it work with docker
If you are using both docker compose and dockerfile like I do, here is what I've done:
Let's assume you want to mount the mypipe's parent folder as /hostpipe in your container
Add this:
VOLUME /hostpipe
in your dockerfile in order to create a mount point
Then add this:
volumes:
- /path/to/pipe:/hostpipe
in your docker compose file in order to mount /path/to/pipe as /hostpipe
Restart your docker containers.
PART 6 - Testing
Exec into your docker container:
docker exec -it <container> bash
Go into the mount folder and check you can see the pipe:
cd /hostpipe && ls -l
Now try running a command from within the container:
echo "touch this_file_was_created_on_main_host_from_a_container.txt" > /hostpipe/mypipe
And it should work!
WARNING: If you have an OSX (Mac OS) host and a Linux container, it won't work (explanation here https://stackoverflow.com/a/43474708/10018801 and issue here https://github.com/docker/for-mac/issues/483 ) because the pipe implementation is not the same, so what you write into the pipe from Linux can be read only by a Linux and what you write into the pipe from Mac OS can be read only by a Mac OS (this sentence might not be very accurate, but just be aware that a cross-platform issue exists).
For instance, when I run my docker setup in DEV from my Mac OS computer, the named pipe as explained above does not work. But in staging and production, I have Linux host and Linux containers, and it works perfectly.
PART 7 - Example from Node.JS container
Here is how I send a command from my Node.JS container to the main host and retrieve the output:
const pipePath = "/hostpipe/mypipe"
const outputPath = "/hostpipe/output.txt"
const commandToRun = "pwd && ls-l"
console.log("delete previous output")
if (fs.existsSync(outputPath)) fs.unlinkSync(outputPath)
console.log("writing to pipe...")
const wstream = fs.createWriteStream(pipePath)
wstream.write(commandToRun)
wstream.close()
console.log("waiting for output.txt...") //there are better ways to do that than setInterval
let timeout = 10000 //stop waiting after 10 seconds (something might be wrong)
const timeoutStart = Date.now()
const myLoop = setInterval(function () {
if (Date.now() - timeoutStart > timeout) {
clearInterval(myLoop);
console.log("timed out")
} else {
//if output.txt exists, read it
if (fs.existsSync(outputPath)) {
clearInterval(myLoop);
const data = fs.readFileSync(outputPath).toString()
if (fs.existsSync(outputPath)) fs.unlinkSync(outputPath) //delete the output file
console.log(data) //log the output of the command
}
}
}, 300);
Use a named pipe.
On the host OS, create a script to loop and read commands, and then you call eval on that.
Have the docker container read to that named pipe.
To be able to access the pipe, you need to mount it via a volume.
This is similar to the SSH mechanism (or a similar socket-based method), but restricts you properly to the host device, which is probably better. Plus you don't have to be passing around authentication information.
My only warning is to be cautious about why you are doing this. It's totally something to do if you want to create a method to self-upgrade with user input or whatever, but you probably don't want to call a command to get some config data, as the proper way would be to pass that in as args/volume into docker. Also, be cautious about the fact that you are evaling, so just give the permission model a thought.
Some of the other answers such as running a script. Under a volume won't work generically since they won't have access to the full system resources, but it might be more appropriate depending on your usage.
The solution I use is to connect to the host over SSH and execute the command like this:
ssh -l ${USERNAME} ${HOSTNAME} "${SCRIPT}"
UPDATE
As this answer keeps getting up votes, I would like to remind (and highly recommend), that the account which is being used to invoke the script should be an account with no permissions at all, but only executing that script as sudo (that can be done from sudoers file).
UPDATE: Named Pipes
The solution I suggested above was only the one I used while I was relatively new to Docker. Now in 2021 take a look on the answers that talk about Named Pipes. This seems to be a better solution.
However, nobody there mentioned anything about security. The script that will evaluate the commands sent through the pipe (the script that calls eval) must actually not use eval for the whole pipe output, but to handle specific cases and call the required commands according to the text sent, otherwise any command that can do anything can be sent through the pipe.
That REALLY depends on what you need that bash script to do!
For example, if the bash script just echoes some output, you could just do
docker run --rm -v $(pwd)/mybashscript.sh:/mybashscript.sh ubuntu bash /mybashscript.sh
Another possibility is that you want the bash script to install some software- say the script to install docker-compose. you could do something like
docker run --rm -v /usr/bin:/usr/bin --privileged -v $(pwd)/mybashscript.sh:/mybashscript.sh ubuntu bash /mybashscript.sh
But at this point you're really getting into having to know intimately what the script is doing to allow the specific permissions it needs on your host from inside the container.
My laziness led me to find the easiest solution that wasn't published as an answer here.
It is based on the great article by luc juggery.
All you need to do in order to gain a full shell to your linux host from within your docker container is:
docker run --privileged --pid=host -it alpine:3.8 \
nsenter -t 1 -m -u -n -i sh
Explanation:
--privileged : grants additional permissions to the container, it allows the container to gain access to the devices of the host (/dev)
--pid=host : allows the containers to use the processes tree of the Docker host (the VM in which the Docker daemon is running)
nsenter utility: allows to run a process in existing namespaces (the building blocks that provide isolation to containers)
nsenter (-t 1 -m -u -n -i sh) allows to run the process sh in the same isolation context as the process with PID 1.
The whole command will then provide an interactive sh shell in the VM
This setup has major security implications and should be used with cautions (if any).
Write a simple server python server listening on a port (say 8080), bind the port -p 8080:8080 with the container, make a HTTP request to localhost:8080 to ask the python server running shell scripts with popen, run a curl or writing code to make a HTTP request curl -d '{"foo":"bar"}' localhost:8080
#!/usr/bin/python
from BaseHTTPServer import BaseHTTPRequestHandler,HTTPServer
import subprocess
import json
PORT_NUMBER = 8080
# This class will handles any incoming request from
# the browser
class myHandler(BaseHTTPRequestHandler):
def do_POST(self):
content_len = int(self.headers.getheader('content-length'))
post_body = self.rfile.read(content_len)
self.send_response(200)
self.end_headers()
data = json.loads(post_body)
# Use the post data
cmd = "your shell cmd"
p = subprocess.Popen(cmd, stdout=subprocess.PIPE, shell=True)
p_status = p.wait()
(output, err) = p.communicate()
print "Command output : ", output
print "Command exit status/return code : ", p_status
self.wfile.write(cmd + "\n")
return
try:
# Create a web server and define the handler to manage the
# incoming request
server = HTTPServer(('', PORT_NUMBER), myHandler)
print 'Started httpserver on port ' , PORT_NUMBER
# Wait forever for incoming http requests
server.serve_forever()
except KeyboardInterrupt:
print '^C received, shutting down the web server'
server.socket.close()
If you are not worried about security and you're simply looking to start a docker container on the host from within another docker container like the OP, you can share the docker server running on the host with the docker container by sharing it's listen socket.
Please see https://docs.docker.com/engine/security/security/#docker-daemon-attack-surface and see if your personal risk tolerance allows this for this particular application.
You can do this by adding the following volume args to your start command
docker run -v /var/run/docker.sock:/var/run/docker.sock ...
or by sharing /var/run/docker.sock within your docker compose file like this:
version: '3'
services:
ci:
command: ...
image: ...
volumes:
- /var/run/docker.sock:/var/run/docker.sock
When you run the docker start command within your docker container,
the docker server running on your host will see the request and provision the sibling container.
credit: http://jpetazzo.github.io/2015/09/03/do-not-use-docker-in-docker-for-ci/
As Marcus reminds, docker is basically process isolation. Starting with docker 1.8, you can copy files both ways between the host and the container, see the doc of docker cp
https://docs.docker.com/reference/commandline/cp/
Once a file is copied, you can run it locally
docker run --detach-keys="ctrl-p" -it -v /:/mnt/rootdir --name testing busybox
# chroot /mnt/rootdir
#
I have a simple approach.
Step 1: Mount /var/run/docker.sock:/var/run/docker.sock (So you will be able to execute docker commands inside your container)
Step 2: Execute this below inside your container. The key part here is (--network host as this will execute from host context)
docker run -i --rm --network host -v /opt/test.sh:/test.sh alpine:3.7
sh /test.sh
test.sh should contain the some commands (ifconfig, netstat etc...) whatever you need.
Now you will be able to get host context output.
You can use the pipe concept, but use a file on the host and fswatch to accomplish the goal to execute a script on the host machine from a docker container. Like so (Use at your own risk):
#! /bin/bash
touch .command_pipe
chmod +x .command_pipe
# Use fswatch to execute a command on the host machine and log result
fswatch -o --event Updated .command_pipe | \
xargs -n1 -I "{}" .command_pipe >> .command_pipe_log &
docker run -it --rm \
--name alpine \
-w /home/test \
-v $PWD/.command_pipe:/dev/command_pipe \
alpine:3.7 sh
rm -rf .command_pipe
kill %1
In this example, inside the container send commands to /dev/command_pipe, like so:
/home/test # echo 'docker network create test2.network.com' > /dev/command_pipe
On the host, you can check if the network was created:
$ docker network ls | grep test2
8e029ec83afe test2.network.com bridge local
In my scenario I just ssh login the host (via host ip) within a container and then I can do anything I want to the host machine
I found answers using named pipes awesome. But I was wondering if there is a way to get the output of the executed command.
The solution is to create two named pipes:
mkfifo /path/to/pipe/exec_in
mkfifo /path/to/pipe/exec_out
Then, the solution using a loop, as suggested by #Vincent, would become:
# on the host
while true; do eval "$(cat exec_in)" > exec_out; done
And then on the docker container, we can execute the command and get the output using:
# on the container
echo "ls -l" > /path/to/pipe/exec_in
cat /path/to/pipe/exec_out
If anyone interested, my need was to use a failover IP on the host from the container, I created this simple ruby method:
def fifo_exec(cmd)
exec_in = '/path/to/pipe/exec_in'
exec_out = '/path/to/pipe/exec_out'
%x[ echo #{cmd} > #{exec_in} ]
%x[ cat #{exec_out} ]
end
# example
fifo_exec "curl https://ip4.seeip.org"
Depending on the situation, this could be a helpful resource.
This uses a job queue (Celery) that can be run on the host, commands/data could be passed to this through Redis (or rabbitmq). In the example below, this is occurring in a django application (which is commonly dockerized).
https://www.codingforentrepreneurs.com/blog/celery-redis-django/
To expand on user2915097's response:
The idea of isolation is to be able to restrict what an application/process/container (whatever your angle at this is) can do to the host system very clearly. Hence, being able to copy and execute a file would really break the whole concept.
Yes. But it's sometimes necessary.
No. That's not the case, or Docker is not the right thing to use. What you should do is declare a clear interface for what you want to do (e.g. updating a host config), and write a minimal client/server to do exactly that and nothing more. Generally, however, this doesn't seem to be very desirable. In many cases, you should simply rethink your approach and eradicate that need. Docker came into an existence when basically everything was a service that was reachable using some protocol. I can't think of any proper usecase of a Docker container getting the rights to execute arbitrary stuff on the host.
I am new to Docker. I have a python script which does :
starts a docker container through:
call(["sudo docker run -i -t -d test /bin/sh"],shell=True)
removes a soft link that exists inside the container through the command:
call("sudo docker exec -i "+ tag1 +" rm /usr/local/lib/boost_logger",shell=True)
where tag1 is my docker container id
I copy new files from my centos folders to the docker instance through:
call("sudo tar -cv * | sudo docker exec -i "+ tag1 +" tar x -C /usr/local/lib/", shell=True)
I re-create 2 soft links using:
call("sudo docker exec -i "+ tag1 +" ln -s /usr/local/lib/libboost_logger.so /usr/local/lib/boost_logger",shell=True)
call("sudo docker exec -i "+ tag1 +" ln -s /usr/local/lib/libredis_client.so /usr/local/lib/redis_client",shell=True)
Now, I commit the docker image through:
dockercommit = ["sudo","docker","commit","-m",'"Building docker instance"',"-a",'"Tejas"',tag1,dockerfilename]
call(dockercommit)
The same commands work fine through bash.
The problem I face is after step 2. My script stops execution. It resumes after I manually hit Ctrl+D and the rest of the script is executed!
I am running the docker instances on centos running on virtualbox. I have allocated 3 cores and around 10GB base memory.
Also, if there are no docker instances currently running and only the base image present, hitting Ctrl+D releases the script immediately.
But in case I have more instances or probably during the second or third iteration of the same script, it takes a longer time for the control to get released.
Adding user input with shell=True is strongly discouraged as
mentioned in the documentation:
Warning: Executing shell commands that incorporate unsanitized input from an untrusted source makes a program vulnerable to shell injection, a serious security flaw which can result in arbitrary command execution. For this reason, the use of shell=True is strongly discouraged in cases where the command string is constructed from external input:
You should instead use subprocess.popen as mentioned in the note.
I have to setup "dockerized" environments (integration, qa and production) on the same server (client's requirement). Each environment will be composed as follow:
rabbitmq
celery
flower
python 3 based application called "A" (specific branch per
environment)
Over them, jenkins will handle the deployment based on CI.
Using set of containers per environment sounds like the best approach.
But now I need, process manager to run and supervise all of them:
3 rabbit containers,
3 celery/flower containers,
3 "A" containers,
1 jenkins containers.
Supervisord seem to be the best choice, but during my tests, i'm not able to "properly" restart a container. Here a snippet of the supervisord.conf
[program:docker-rabbit]
command=/usr/bin/docker run -p 5672:5672 -p 15672:15672 tutum/rabbitmq
startsecs=20
autorestart=unexpected
exitcodes=0,1
stopsignal=KILL
So I wonder what is the best way to separate each environment and be able to manage and supervise each service (a container).
[EDIT My solution inspired by Thomas response]
each container is run by a .sh script that looking like
rabbit-integration.py
#!/bin/bash
#set -x
SERVICE="rabbitmq"
SH_S = "/path/to_shs"
export MY_ENV="integration"
. $SH_S/env_.sh
. $SH_S/utils.sh
SERVICE_ENV=$SERVICE-$MY_ENV
ID_FILE=/tmp/$SERVICE_ENV.name # pid file
trap stop SIGHUP SIGINT SIGTERM # trap signal for calling the stop function
run_rabbitmq
$SH_S/env_.sh is looking like:
# set env variable
...
case $MONARCH_ENV in
$INTEGRATION)
AMQP_PORT="5672"
AMQP_IP="172.17.42.1"
...
;;
$PREPRODUCTION)
AMQP_PORT="5673"
AMQP_IP="172.17.42.1"
...
;;
$PRODUCTION)
AMQP_PORT="5674"
REDIS_IP="172.17.42.1"
...
esac
$SH_S/utils.sh is looking like:
#!/bin/bash
function random_name(){
echo "$SERVICE_ENV-$(cat /proc/sys/kernel/random/uuid)"
}
function stop (){
echo "stopping docker container..."
/usr/bin/docker stop `cat $ID_FILE`
}
function run_rabbitmq (){
# do no daemonize and use stdout
NAME="$(random_name)"
echo $NAME > $ID_FILE
/usr/bin/docker run -i --name "$NAME" -p $AMQP_IP:$AMQP_PORT:5672 -p $AMQP_ADMIN_PORT:15672 -e RABBITMQ_PASS="$AMQP_PASSWORD" myimage-rabbitmq &
PID=$!
wait $PID
}
At least myconfig.intergration.conf is looking like:
[program:rabbit-integration]
command=/path/sh_s/rabbit-integration.sh
startsecs=20
priority=90
autorestart=unexpected
exitcodes=0,1
stopsignal=TERM
In the case i want use the same container the startup function is looking like:
function _run_my_container () {
NAME="my_container"
/usr/bin/docker start -i $NAME &
PID=$!
wait $PID
rc=$?
if [[ $rc != 0 ]]; then
_run_my_container
fi
}
where
function _run_my_container (){
/usr/bin/docker run -p{} -v{} --name "$NAME" myimage &
PID=$!
wait $PID
}
Supervisor requires that the processes it manages do not daemonize, as per its documentation:
Programs meant to be run under supervisor should not daemonize
themselves. Instead, they should run in the foreground. They should
not detach from the terminal from which they are started.
This is largely incompatible with Docker, where the containers are subprocesses of the Docker process itself (i.e. and hence are not subprocesses of Supervisor).
To be able to use Docker with Supervisor, you could write an equivalent of the pidproxy program that works with Docker.
But really, the two tools aren't really architected to work together, so you should consider changing one or the other:
Consider replacing Supervisor with Docker Compose (which is designed to work with Docker)
Consider replacing Docker with Rocket (which doesn't have a "master" process)
You need to make sure you use stopsignal=INT in your supervisor config, then exec docker run normally.
[program:foo]
stopsignal=INT
command=docker -rm run whatever
At least this seems to work for me with docker version 1.9.1.
If you run docker from inside a shell script, it is very important that you have exec in front of the docker run command, so that docker run replaces the shell process and thus receives the SIGINT directly from supervisord.
You can have Docker just not detach and then things work fine. We manage our Docker containers in this way through supervisor. Docker compose is great, but if you're already using Supervisor to manage non-docker things as well, it's nice to keep using it to have all your management in one place. We'll wrap our docker run in a bash script like the following and have supervisor track that, and everything works fine:
#!/bin/bash¬
TO_STOP=docker ps | grep $SERVICE_NAME | awk '{ print $1 }'¬
if [$TO_STOP != '']; then¬
docker stop $SERVICE_NAME¬
fi¬
TO_REMOVE=docker ps -a | grep $SERVICE_NAME | awk '{ print $1 }'¬
if [$TO_REMOVE != '']; then¬
docker rm $SERVICE_NAME¬
fi¬
¬
docker run -a stdout -a stderr --name="$SERVICE_NAME" \
--rm $DOCKER_IMAGE:$DOCKER_TAG
I found that executing docker run via supervisor actually works just fine, with a few precautions. The main thing one needs to avoid is allowing supervisord to send a SIGKILL to the docker run process, which will kill off that process but not the container itself.
For the most part, this can be handled by following the instructions in Why Your Dockerized Application Isn’t Receiving Signals. In short, one needs to:
Use the CMD ["/path/to/myapp"] form (same for ENTRYPOINT) instead of the shell form (CMD /path/to/myapp).
Pass --init to docker run.
If using an ENTRYPOINT, ensure its last line calls exec, so as to avoid spawning a new process.
If the above still isn't working, add a STOPSIGNAL to your Dockerfile.
Additionally, you'll want to make sure that your stopwaitsecs setting in supervisor is greater than the time your process might take to shutdown gracefully when it receives a SIGTERM (e.g., graceful_timeout if using gunicorn).
Here's a sample config to run a gunicorn container:
[program:gunicorn]
command=/usr/bin/docker run --init --rm -i -p 8000:8000 gunicorn
redirect_stderr=true
stopwaitsecs=31