Docker:通过Gunicorn运行Flask应用-工人超时吗?表现不佳?

问题描述

我正在尝试创建一个用Python Flask编写，由gunicorn运行，然后被docker化的新应用.

I am trying to create a new app that is written in Python Flask, run by gunicorn and then dockerised.

我遇到的问题是docker容器内的性能非常差，不一致，最终我得到了响应，但我不明白为什么性能会下降.有时我在日志[CRITICAL] WORKER TIMEOUT (pid:9)中看到.

The problem I have is the performance inside the docker container is very poor, inconsistent and I do eventually get a response but I can't understand why the performance is decreasing. Sometimes I see in the logs [CRITICAL] WORKER TIMEOUT (pid:9).

这是我的应用程序:

server.py

from flask import Flask
app = Flask(__name__)

@app.route('/')
def index():
    return "The server is running!"

if __name__ == '__main__':
    app.run()

Dockerfile

FROM python:3.6.9-slim

# Copy all the files to the src folder
COPY build/ /usr/src/
# Create the virtual environment
RUN python3 -m venv /usr/src/myapp_venv
# Install the requirements
RUN /usr/src/myapp_venv/bin/pip3 install -r /usr/src/requirements.txt
# Runs gunicorn
# --chdir sets the directory where gunicorn should look for the server files
# server:app means run the "server.py" file and look for the "app" constructor within that
ENTRYPOINT ["/usr/src/myapp/bin/gunicorn", "--bind", "0.0.0.0:5000", "--workers", "1", "--chdir", "/usr/src/", "server:app"]
# Expose the gunicorn port
EXPOSE 5000

requirements.txt

Click==7.0
Flask==1.1.1
gunicorn==20.0.0
itsdangerous==1.1.0
Jinja2==2.10.3
MarkupSafe==1.1.1
Werkzeug==0.16.0

我这样运行docker容器:

I run the docker container like this:

docker build -t killerkode/myapp .
docker run --name myapp -p 5000:5000 killerkode/myapp

推荐答案

我设法找到了这篇有用的文章，该文章解释了Gunicorn为何挂起. https://pythonspeed.com/articles/gunicorn-in-docker/

I managed to find this helpful article which explains why Gunicorn hangs.https://pythonspeed.com/articles/gunicorn-in-docker/

对我来说，解决方案是更改worker临时目录，并将最小worker增加到2.我仍然看到worker被杀死了，但是不再有任何延迟/缓慢.我怀疑添加gthread会进一步改善效果.

The solution for me was to change the worker temp directory and increase the minimum workers to 2. I still see workers being killed off but there is no longer any delays / slowness. I suspect adding in the gthread will improve things further.

这是我更新的Dockerfile:

Here is my updated Dockerfile:

FROM python:3.6.9-slim

# Copy all the files to the src folder
COPY build/ /usr/src/
# Create the virtual environment
RUN python3 -m venv /usr/src/myapp_venv
# Install the requirements
RUN /usr/src/myapp_venv/bin/pip3 install -r /usr/src/requirements.txt
# Runs gunicorn
# --chdir sets the directory where gunicorn should look for the server files
# server:app means run the "server.py" file and look for the "app" constructor within that
ENTRYPOINT ["/usr/src/myapp/bin/gunicorn", "--bind", "0.0.0.0:5000", "--worker-tmp-dir", "/dev/shm", "--workers", "2", "--chdir", "/usr/src/", "server:app"]
# Expose the gunicorn port
EXPOSE 5000

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