Gunicorn worker terminated with signal 9

Question

I am running a Flask application and hosting it on Kubernetes from a Docker container. Gunicorn is managing workers that reply to API requests.

The following warning message is a regular occurrence, and it seems like requests are being canceled for some reason. On Kubernetes, the pod is showing no odd behavior or restarts and stays within 80% of its memory and CPU limits.

[2021-03-31 16:30:31 +0200] [1] [WARNING] Worker with pid 26 was terminated due to signal 9

How can we find out why these workers are killed?

Solution 1

I encountered the same warning message.

[WARNING] Worker with pid 71 was terminated due to signal 9

I came across this faq, which says that "A common cause of SIGKILL is when OOM killer terminates a process due to low memory condition."

I used dmesg realized that indeed it was killed because it was running out of memory.

Out of memory: Killed process 776660 (gunicorn)

Solution 2

In our case application was taking around 5-7 minutes to load ML models and dictionaries into memory. So adding timeout period of 600 seconds solved the problem for us.

gunicorn main:app --workers 1 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:8443 --timeout 600

Solution 3

I encountered the same warning message when I limit the docker's memory, use like -m 3000m.

see docker-memory

and

gunicorn-Why are Workers Silently Killed?

The simple way to avoid this is set a high memory for docker or not set.

Solution 4

I was using AWS Beanstalk to deploy my flask application and I had a similar error.

• In the log I saw:
• web: MemoryError
• [CRITICAL] WORKER TIMEOUT
• [WARNING] Worker with pid XXXXX was terminated due to signal 9

I was using the t2.micro instance and when I changed it to t2.medium my app worked fine. In addition to this I changed to the timeout in my nginx config file.

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Comments

[lionbigcat]

Did you manage to find out why? Having the same issue, and tried specifying the --shm-size - but no avail.

[Jodiug]

Our problems seem to have gone away since we started using --worker-class gevent. I suspect Simon is right and this was either an out of memory error, or a background process running for too long and the main process (1) decided to kill it.

[Jodiug]

Meta: I'm not sure why this question is being downvoted. Please drop a comment if you feel it needs further clarification.

[Blop]

I have the same problem, and gevent did not solve it. does anyone knows why this started all of a sudden? was there a change in gunicorn or in kube?

[Blop]

also related to a non answered question: stackoverflow.com/questions/57745100/…

[lionbigcat]

@Blop - my issue was OOM-related. I had to use a larger instance with more RAM, and gave the docker container access to that RAM.

[Blop]

@lionbigcat ye, eventually that's exactly what I did as well. just adding another 1GB fixed the problem. no need to change to gevent.

[Vincent Agnes]

I faced the same issue and solved it by switching from python 3.8 to python 3.7

[Jodiug]

Our problems seem to have gone away since we started using --worker-class gevent. I can't verify this answer, but it seems that dmesg is a good way to get more information and diagnose the problem. Thanks for your answer!

[Areza]

how did you fix it ?

[EgurnovD]

Got rid of warm-up. Looking for ways to do it right after app start now.

[Martin Bucher]

that was it in my case as well. many thanks for the pointer.

[Snehangsu]

Mind sharing the timeout variable name?

[Vkey]

Below is the contents on my timeout.conf file under the nginx>conf.d folder keepalive_timeout 600s; proxy_connect_timeout 600s; proxy_send_timeout 600s; proxy_read_timeout 600s; fastcgi_send_timeout 600s; fastcgi_read_timeout 600s; client_max_body_size 20M;