EC2, 16.04, Systemd, Supervisord, & Python - python-2.7

I have a service written in python 2.7 and managed by supervisord on an Ubuntu 16.04 EC2 spot instance.
On system startup I have a number of systemd tasks that need to take place and finish prior to supervisord starting the service.
When the instance is about to shutdown, I need supervisord to capture the event and tell the service to gracefully halt. The service will need to stop processing and return any workloads to the queue prior to exiting gracefully.
What would be the optimal way to manage system startup in this scenario?
What would be the optimal way to manage system shutdown in this scenario?
How do I best handle the interaction between supervisord and the service?

First, we need to install a systemd task that we want to run prior to supervisor starting up. Let's create a script, /usr/bin/pre-supervisor.sh, that will handle performing that work for us and create the /lib/systemd/system/pre-supervisor.service for systemd.
[Unit]
Description=Task to run prior to supervisor Starting up
After=cloud-init.service
Before=supervisor.service
Requires=cloud-init.service
[Service]
Type=oneshot
WorkingDirectory=/usr/bin
ExecStart=/usr/bin/pre-supervisor.sh
RemainAfterExit=no
TimeoutSec=90
User=ubuntu
# Output needs to appear in instance console output
StandardOutput=journal+console
[Install]
WantedBy=multi-user.target
As you can see, this will run after the ec2 cloud-init.service completes, and prior to the supervisor.service.
Next, let us modify the /lib/systemd/system/supervisor.service to run After the pres-supervisor.service completes, instead of after network.target.
[Unit]
Description=Supervisor process control system for UNIX
Documentation=http://supervisord.org
After=pre-supervisor.service
[Service]
ExecStart=/usr/bin/supervisord -n -c /etc/supervisor/supervisord.conf
ExecStop=/usr/bin/supervisorctl $OPTIONS shutdown
ExecReload=/usr/bin/supervisorctl -c /etc/supervisor/supervisord.conf $OPTIONS reload
KillMode=process
Restart=on-failure
RestartSec=50s
[Install]
WantedBy=multi-user.target
That will ensure that our pre-supervisor tasks run prior to supervisor starting up.
Because these are spot instances, AWS has exposed the termination notice in the meta-data url, I simply need to inject something like:
if requests.get("http://169.254.169.254/latest/meta-data/spot/termination-time").status_code == 200
into my python service, have it check every five seconds or so, and gracefully shutdown as soon as the termination notice appears.

Related

Symfony Messenger not shutting down gracefully when using APP_ENV=prod

We are using Symfony Messenger in combination with supervisor running in a Docker container on AWS ECS. We noticed the worker is not shut down gracefully. After debugging it appears it does work as expected when using APP_ENV=dev, but not when APP_ENV=prod.
I made a simple sleepMessage, which sleeps for 1 second and then prints a message for 60 seconds. This is when running with APP_ENV=dev
As you can see it's clearly waiting for the program to stop running.
Now with APP_ENV=prod:
It stops immediately without waiting.
In the Dockerfile we have configured the following to start supervisor. It's based on php:8.1-apache, so that's why STOPSIGNAL has been configured
RUN apt-get update && apt-get install -y --no-install-recommends \
# for supervisor
python \
supervisor
The start-worker.sh script contains this
#!/usr/bin/env bash
cp config/worker/messenger-worker.conf ../../../etc/supervisor/supervisord.conf
exec /usr/bin/supervisord
We do this because certain env variables are only available when starting up.
For debugging purposes the config has been hardcoded to test.
Below is the messenger-worker.conf
[unix_http_server]
file=/tmp/supervisor.sock
[supervisord]
nodaemon=true ; start in foreground if true; default false
[rpcinterface:supervisor]
supervisor.rpcinterface_factory = supervisor.rpcinterface:make_main_rpcinterface
[program:messenger-consume]
stderr_logfile_maxbytes=0
stdout_logfile=/dev/stdout
stdout_logfile_maxbytes=0
command=bin/console messenger:consume async -vv --env=prod --time-limit=129600
process_name=%(program_name)s_%(process_num)02d
autostart=true
autorestart=true
numprocs=1
environment=
MESSENGER_TRANSPORT_DSN="https://sqs.eu-central-1.amazonaws.com/{id}/dev-
symfony-messenger-queue"
So in short, when using --env=prod in the config above it doesn't wait for the worker to stop, while with --env=dev it does. Does anybody know how to solve this?
I don't know why there would be a difference between dev & prod environment but it seems you have no grace period set (at least for Supervisor). As I added in the docs:
the workers will be able to handle the SIGTERM signal if you have the PCNTL PHP extension
you need to add stopwaitsecs to your Supervisor program configuration
As you use Docker too, you can also set the graceful period at the service level which defaults to 10s:
services:
my_app:
stop_grace_period: 20s
# ...
With this configuration, running docker-compose down (just an example):
Docker sends a SIGTERM signal to the service entrypoint (Supervisor) and waits 20s for it to exit
Supervisor sends a SIGTERM signal to its programs (messenger:consume commands) and waits 20s for them to exit
the messenger:consume processes will "catch" the signal, finish handling the current message and stop
every program stopped, Supervisor can stop, then the Docker Compose stack
Turns out it was related to the wait_time option related to SQS transports. It probably caused a request that was started just before the container exited and was sent back when the container did not exist anymore. So, wait_time to 0 fixed that problem.
Then there was this which could lead to the same issue

System has not been booted with systemd as init system (PID 1). Can't operate. Failed to connect to bus: Host is down

I am trying to activate service after creating a systemd service using the following commands in google cloud terminal:
vim /etc/systemd/system/app.service
Pasted the contents below to this file:
#vim /etc/systemd/system/app.service
[Unit]
# specifies metadata and dependencies
Description=Gunicorn instance to serve myproject
After=network.target
# tells the init system to only start this after the networking target has been reached
# We will give our regular user account ownership of the process since it owns all of the relevant files
[Service]
# Service specify the user and group under which our process will run.
User=clashgamers2021
# give group ownership to the www-data group so that Nginx can communicate easily with the Gunicorn processes.
Group=www-data
# We'll then map out the working directory and set the PATH environmental variable so that the init system knows where our the executables for the process are located (wi$
WorkingDirectory=/home/clashgamers2021/clashgamers/
Environment="PATH=/home/clashgamers2021/clashgamers/env/bin"
# We'll then specify the commanded to start the service
ExecStart=/home/clashgamers2021/clashgamers/env/bin/gunicorn --workers 3 --bind unix:app.sock -m 007 wsgi:app
# This will tell systemd what to link this service to if we enable it to start at boot. We want this service to start when the regular multi-user system is up and running:
[Install]
WantedBy=multi-user.target
For activating this service, I typed:
sudo systemctl start app
sudo systemctl enable app
However I got this error:
clashgamers2021#cloudshell:~/clashgamers (clash-gamers-318206)$ sudo systemctl start app
System has not been booted with systemd as init system (PID 1). Can't operate.
Failed to connect to bus: Host is down
You're trying to run the commands in the Cloud Shell:
Cloud Shell is an interactive shell environment for Google Cloud that makes it easy for you to learn and experiment with Google Cloud and manage your projects and resources from your web browser.
Create a new VM (specify hardware & OS) and connect to it using SSH button in the Cloud Console or use other methods described in the documentation.
Then run your commands and if they don't work update your question with more details.

docker-compose and graceful Celery shutdown

I've been wondering about and searching for solutions for this and I didn't find any.
I'm running Celery in a container built with docker-compose. My container is configured like this:
celery:
build: .
container_name: cl01
env_file: ./config/variables.env
entrypoint:
- /celery-entrypoint.sh
volumes:
- ./django:/django
depends_on:
- web
- db
- redis
stop_grace_period: 1m
And my entrypoint script looks like this:
#!/bin/sh
# Wait for django
sleep 10
su -m dockeruser -c "celery -A myapp worker -l INFO"
Now, if I run docker-compose stop, I would like to have a warm (graceful) shutdown, giving Celery the provided 1 minute (stop_grace_period) to finish already started tasks. However docker-compose stop seems to kill Celery straight away. Celery should also log that it is asked to shut down gracefully, but I don't see anything but an abrupt stop to my task logs.
What am I doing wrong or what do I need to change to make Celery shut down gracefully?
edit:
Suggested answer below about providing the --timeout parameter to docker-compose stop does not solve my issue.
You need to mark celery process with exec, this way celery process will have the same ID as docker command and docker will be able to send a SIGTERM signal to it and gracefully close celery process.
# should be the last command in script
exec celery -A myapp worker -l INFO
Via docs
Usage: stop [options] [SERVICE...]
Options:
-t, --timeout TIMEOUT Specify a shutdown timeout in seconds (default: 10).
Try with timeout set to 60 seconds at least.
My experience implementing graceful shutdown for celery workers spawned by supervisord inside a docker container.
Supervisord part
supervisord.conf
...
[supervisord]
...
nodaemon=true # run supervisord in the foreground
[include]
files=celery.conf # path to the celery config file
Set nodaemon=true so that we can start it as a background process from the entrypoint script later.
celery.conf
[group:celery_workers]
programs=one, two
[program:one]
...
command=celery -A backend --config=celery.py worker -n worker_one --pidfile=/var/log/celery/worker_one.pid --pool=gevent --concurrency=10 --loglevel=INFO
killasgroup=true
stopasgroup=true
stopsignal=TERM
stopwaitsecs=600
[program:two]
...
# similar to the previous one
The configuration file above is responsible for starting a group of workers each running in a separate process within a group. I'd like to stop on a stopwaitsecs section value. Let's see what the documentation tells us about it:
This parameter sets the number of seconds to wait for the OS to return
a SIGCHLD to supervisord after the program has been sent a
stopsignal. If this number of seconds elapses before supervisord
receives a SIGCHLD from the process, supervisord will attempt to kill
it with a final SIGKILL.
If stopwaitsecs>stop_grace_period specified for your service in a docker-compose file then you'll be getting SIGKILL from your docker. Make sure
stopwaitsecs<stop_grace_period, otherwise all running tasks get interrupted by docker.
Entrypoint script part
entrypoint.sh
#!/bin/bash
# safety switch, exit script if there's error.
set -e
on_close(){
echo "Signal caught..."
echo "Supervisor is stopping processes gracefully..."
# cleanup all pid files
rm worker_one.pid
rm worker_two.pid
supervisorctl stop celery_workers:
echo "All processes have been stopped. Exiting..."
exit 1
}
start_supervisord(){
supervisord -c /etc/supervisor/supervisord.conf
}
# start trapping signals (docker sends `SIGTERM` for shutdown)
trap on_close SIGINT SIGTERM SIGKILL
start_supervisord & # start supervisord in a background
SUPERVISORD_PID=$! # PID of the last background process started
wait $SUPERVISORD_PID
EXIT_STATUS=$? # the exit status of the last command executed
The script above consists of:
registering a cleanup function on_close
starting supervisord's process group in a background
registering the last background process's PID and waiting for it to finish
Docker part
docker-compose.yml
...
services:
celery:
...
stop_grace_period: 15m30s
entrypoint: [/entrypoints/entrypoint.sh]
The only setting worth mentioning here is entrypoint form declaration. In our case better to use exec form. It starts an executable script in a process with PID 1 and doesn't create any subprocesses as shell form does. SIGTERM from docker stop <container> gets propagated to an executable which traps it and performs all cleaning and closing logic.
Try using this:
docker-compose down

How do I restart airflow webserver?

I am using airflow for my data pipeline project. I have configured my project in airflow and start the airflow server as a backend process using following command
airflow webserver -p 8080 -D True
Server running successfully in backend. Now I want to enable authentication in airflow and done configuration changes in airflow.cfg, but authentication functionality is not reflected in server. when I stop and start airflow server in my local machine it works.
So How can I restart my daemon airflow webserver process in my server??
I advice running airflow in a robust way, with auto-recovery with systemd
so you can do:
- to start systemctl start airflow
- to stop systemctl stop airflow
- to restart systemctl restart airflow
For this you'll need a systemd 'unit' file.
As a (working) example you can use the following:
put it in /lib/systemd/system/airflow.service
[Unit]
Description=Airflow webserver daemon
After=network.target postgresql.service mysql.service redis.service rabbitmq-server.service
Wants=postgresql.service mysql.service redis.service rabbitmq-server.service
[Service]
PIDFile=/run/airflow/webserver.pid
EnvironmentFile=/home/airflow/airflow.env
User=airflow
Group=airflow
Type=simple
ExecStart=/bin/bash -c 'export AIRFLOW_HOME=/home/airflow ; airflow webserver --pid /run/airflow/webserver.pid'
ExecReload=/bin/kill -s HUP $MAINPID
ExecStop=/bin/kill -s TERM $MAINPID
Restart=on-failure
RestartSec=42s
PrivateTmp=true
[Install]
WantedBy=multi-user.target
P.S: change AIRFLOW_HOME to where your airflow folder with the config
Can you check $AIRFLOW_HOME/airflow-webserver.pid for the process id of your webserver daemon?
Then pass it a kill signal to kill it
cat $AIRFLOW_HOME/airflow-webserver.pid | xargs kill -9
Then clear the pid file
cat /dev/null > $AIRFLOW_HOME/airflow-webserver.pid
Then just run
airflow webserver -p 8080 -D True
to restart the daemon.
This worked for me (multiple times! :D )
find the process id: (assuming 8080 is the port)
lsof -i tcp:8080
kill it
kill <pid>
Use Airflow webserver's (gunicorn) signal handling
Airflow uses gunicorn as it's HTTP server, so you can send it standard POSIX-style signals. A signal commonly used by daemons to restart is HUP.
You'll need to locate the pid file for the airflow webserver daemon in order to get the right process id to send the signal to. This file could be in $AIRFLOW_HOME or also /var/run, which is where you'll find a lot of pids.
Assuming the pid file is in /var/run, you could run the command:
cat /var/run/airflow-webserver.pid | xargs kill -HUP
gunicorn uses a preforking model, so it has master and worker processes. The HUP signal is sent to the master process, which performs these actions:
HUP: Reload the configuration, start the new worker processes with a new configuration and gracefully shutdown older workers. If the application is not preloaded (using the preload_app option), Gunicorn will also load the new version of it.
More information in the gunicorn signal handling docs.
This is mostly an expanded version of captaincapsaicin's answer, but using HUP (SIGHUP) instead of KILL (SIGKILL) to reload the process instead of actually killing it and restarting it.
In my case i want to kill previous airflow process and start.
for that following command did the magic
killall -9 airflow
As the question was related to webserver, this is something that worked in my case:
systemctl restart airflow-webserver
Just run:
airflow webserver -p 8080 -D
Find pid with:
airflow webserver
will give: "The webserver is already running under PID 21250."
Than kill web server process with:
kill 21250
None of these worked for me. I had to delete the $AIRFLOW_HOME/airflow-webserver.pid file and then running airflow webserver worked.
Create a init script and use the command "daemon" to run this as service.
daemon --user="${USER}" --pidfile="${PID_FILE}" airflow webserver -p 8090 >> "${LOG_FILE}" 2>&1 &
The recommended approach is to create and enable the airflow webserver as a service. If you named the webserver as 'airflow-webserver', run the following command to restart the service:
systemctl restart airflow-webserver
You can use a ready-made AMI (namely, LightningFLow) from AWS Marketplace which provides Airflow services (webserver, scheduler, worker) which are enabled at startup.
Note: LightningFlow comes pre-integrated with all required libraries, Livy, custom operators, and local Spark cluster.
Link for AWS Marketplace: https://aws.amazon.com/marketplace/pp/Lightning-Analytics-Inc-LightningFlow-Integrated-o/B084BSD66V
Just by killing processes!!
Assuming the default airflow home directory is ~/airflow/
List the 3 parent processes running the airflow (PID):
cat ~/airflow/airflow-scheduler.pid
cat ~/airflow/airflow-webserver.pid
cat ~/airflow/airflow-webserver-monitor.pid
Get their PGID using:
ps -xjf
And finally run loop to kill all tree of each parent (PID):
for child in $(ps x -o "%P %p %r"| awk '{ if ( $1 == $your_first_PID || $3 == $your_first_PGID) { print $2 }}'); do kill $child; done
To restart Airflow you need to restart Airflow webserver and Airflow scheduler.
Check if Airflow servers are running:
ps -aux | grep airflow
if you see in list of running processes entries like:
ubuntu 49601 0.1 1.6 266668 135520 ? S 12:19 0:00 [ready] gunicorn: worker [airflow-webserver]
This means that Airflow webserver is running.
If you see entries like this:
ubuntu 49653 0.6 2.3 308912 187596 ? S 12:19 0:00 airflow scheduler -- DagFileProcessorManager
That means that Airflow scheduler is running.
Stop Airflow servers (webserver and scheduler):
pkill -f "airflow scheduler"
pkill -f "airflow webserver"
Now use again ps -aux | grep airflow to check if they are really shut down.
Start Airflow servers in background (daemon):
airflow webserver -D
airflow scheduler -D

Gunicorn sync workers spawning processes

We're using Django + Gunicorn + Nginx in our server. The problem is that after a while we see lot's of gunicorn worker processes that have became orphan, and a lot other ones that have became zombie. Also we can see that some of Gunicorn worker processes spawn some other Gunicorn workers. Our best guess is that these workers become orphans after their parent workers have died.
Why Gunicorn workers spawn child workers? Why do they die?! And how can we prevent this?
I should also mention that we've set Gunicorn log level to debug and still we don't see any thing significant, other than periodical log of workers number, which reports count of workers we wanted from it.
UPDATE
This is the line we used to run gunicorn:
gunicorn --env DJANGO_SETTINGS_MODULE=proj.settings proj.wsgi --name proj --workers 10 --user proj --group proj --bind 127.0.0.1:7003 --log-level=debug --pid gunicorn.pid --timeout 600 --access-logfile /home/proj/access.log --error-logfile /home/proj/error.log
In my case I deploy in Ubuntu servers (LTS releases, now almost are 14.04 LTS servers) and I never did have problems with gunicorn daemons, I create a gunicorn.conf.py and launch gunicorn with this config from upstart with an script like this in /etc/init/djangoapp.conf
description "djangoapp website"
start on startup
stop on shutdown
respawn
respawn limit 10 5
script
cd /home/web/djangoapp
exec /home/web/djangoapp/bin/gunicorn -c gunicorn.conf.py -u web -g web djangoapp.wsgi
end script
I configure gunicorn with a .py file config and i setup some options (details below) and deploy my app (with virtualenv) in /home/web/djangoapp and no problems with zombie and orphans gunicorn processes.
i verified your options, timeout can be a problem but another one is that you don't setup max-requests in your config, by default is 0, so, no automatic worker restart in your daemon and can generate memory leaks (http://gunicorn-docs.readthedocs.org/en/latest/settings.html#max-requests)
We will use a .sh file to start the gunicorn process. Later you will use a supervisord configuration file. what is supervisord? some external know how information link about how to install supervisord with Django,Nginx,Gunicorn Here
gunicorn_start.sh remember to give chmod +x to the file.
#!/bin/sh
NAME="myDjango"
DJANGODIR="/var/www/html/myDjango"
NUM_WORKERS=3
echo "Starting myDjango -- Django Application"
cd $DJANGODIR
exec gunicorn -w $NUM_WORKERS $NAME.wsgi:application --bind 127.0.0.1:8001
mydjango_django.conf : Remember to install supervisord on your OS. and
Copy this on the configuration folder.
[program:myDjango]
command=/var/www/html/myDjango/gunicorn_start.sh
user=root
autorestart=true
redirect_sderr=true
Later on use the command:
Reload the daemon’s configuration files, without add/remove (no restarts)
supervisordctl reread
Restart all processes Note: restart does not reread config files. For that, see reread and update.
supervisordctl start all
Get all process status info.
supervisordctl status
This sounds like a timeout issue.
You have multiple timeouts going on and they all need to be in a descending order. It seems they may not be.
For example:
Nginx has a default timeout of 60 seconds
Gunicorn has a default timeout of 30 seconds
Django has a default timeout of 300 seconds
Postgres default timeout is complicated but let's pose 60 seconds for this example.
In this example, when 30 seconds has passed and Django is still waiting for Postgres to respond. Gunicorn tells Django to stop, which in turn should tell Postgres to stop. Gunicorn will wait a certain amount of time for this to happen before it kills django, leaving the postgres process as an orphan query. The user will re-initiate their query and this time the query will take longer because the old one is still running.
I see that you have set your Gunicorn tiemeout to 300 seconds.
This would probably mean that Nginx tells Gunicorn to stop after 60 seconds, Gunicorn may wait for Django who waits for Postgres or any other underlying processes, and when Nginx gets tired of waiting, it kills Gunicorn, leaving Django hanging.
This is still just a theory, but it is a very common problem and hopefully leads you and any others experiencing similar problems, to the right place.