I'm trying to deploy a dockerized app on Azure's App Service. I enter all the fields correctly, my image gets pulled, put I keep getting this error until something times out.

我正在尝试在Azure的应用服务上部署停靠的应用。我正确地输入了所有字段，我的图像被拉出，我一直收到这个错误，直到有东西超时。

Waiting for response to warmup request for container -<container name > Elapsed time = 154.673506 sec

I did set WEBSITE_PORT 8080 (used by my app)

我确实设置了WebSite_Port 8080(由我的应用程序使用)

Here is the dockerfile

这是文档文件

FROM google/dart

WORKDIR /app
ADD pubspec.* /app/
RUN pub get --no-precompile
ADD . /app/
RUN pub get --offline --no-precompile

WORKDIR /app
EXPOSE 8080

ENTRYPOINT ["pub", "run", "aqueduct:aqueduct", "serve", "--port", "8080"]

It was working fine. I had it working last night. I wanted to refresh my image so I restarted. Nothing worked. After multiple hours I deleted my app and started again... no luck. Any ideas?

它运行得很好。我昨晚把它修好了。我想刷新我的形象，所以我重新开始了。什么都不管用。几个小时后，我删除了我的应用程序，并重新启动...运气不好。有什么主意吗？

EDIT 1:
Tried changing port to 80, no luck (This was the port I was using at first when it was working fine)

编辑1：尝试将端口更改为80，但没有成功(这是我最初使用的端口，当时它运行良好)

RESOLVED (Partially)*
I changed everything to port 8000. I realized that Linux and windows did not like having something non-system listening on 80. Therefore I changed everything on 8000 and set the system properties on Azure {WEBSITE_PORT, 8000}. IT now seems to work fine. I don't know if this is an official fix... But it does warmup after 30-ish seconds

已解决(部分)*我将所有内容都更改为端口8000。我意识到Linux和Windows不喜欢让非系统监听80。因此，我更改了8000上的所有内容，并在Azure{WebSite_Port，8000}上设置了系统属性。现在，它似乎运行得很好。我不知道这是不是官方的解决办法。但它确实会在30秒后预热

You can also try setting WEBSITES_CONTAINER_START_TIME_LIMIT to 1800

也可以尝试将WebSites_Container_Start_Time_Limit设置为1800

Depending which App Service plan you have, if there is an option ‘always on’, try to set ‘always on’ in the configuration of your app in Azure portal.

根据你拥有的应用服务计划，如果有选项“Always On”，请尝试在Azure门户中的应用配置中设置“Always On”。

If you are using a Premium App service plan, you can set pre-warm number of instances. Try to set that to 2-3 and see if it gets any better..here

如果您使用的是高级应用服务计划，您可以设置预热实例数。试着将其设置为2-3，看看是否会变得更好。

I had the same experience as you, but my container was really big since it contained ML model, so at the end I switched to AKS because it performed better..

我和你有同样的经历，但我的容器真的很大，因为它包含ML模型，所以最后我切换到AKS，因为它的性能更好。

App Service - Docker container deploy

In my case, this slowdown was caused by automatic port detection.
Setting the WEBSITES_PORT in the application setting solved the problem.

在我的例子中，这种减速是由自动端口检测引起的。在应用程序设置中设置WebSites_Port解决了问题。

WEBSITES_PORT=8000

Pay attention if you have more slots (production/staging?), you have to set this env variable in the other slots too.

如果您有更多插槽（生产/分段？），请注意，你必须在其他插槽中设置这个env变量。

From: Azure App Service on Linux FAQ - Custom Contaniers

来自：Azure App Service on Linux FAQ-Custom Contanier

We have automatic port detection. You can also specify an app setting called WEBSITES_PORT and give it the value of the expected port number. Previously, the platform used the PORT app setting. We are planning to deprecate this app setting and to use WEBSITES_PORT exclusively.

what actually worked for me was a combination of the answers above by Ethiene and kgalic, setting all ports to 8000 in the docker file

对我来说，实际有效的是Ethiene和kgalic上面的答案的组合，在docker文件中将所有端口设置为8000

EXPOSE 8000
CMD gunicorn -w 4 -b :8000 app:app

in the azure configuration application settings adding

在Azure配置应用程序设置中添加

"WEBSITES_PORT" : "8000" 

in the azure configuration general settings setting

在Azure配置常规设置设置中

"Always on" : "on"

In my case, I have changes the “start” command section in package.json (to a different port than the default one) for local testing purposes, and accidentally pushed these changes.

在我的例子中，出于本地测试的目的，我更改了Package.json中的“Start”命令部分(更改为与默认端口不同的端口)，并意外地推送了这些更改。

I had this same problem when I used the nodejs application, so I did build the dist folder by npm build on the creation of the docker image, so it is part of the docker image rather than the docker cmd creating the build image on the initial execution of the app. Maybe the RAM and CPU wasn't enough for the npm build to happen at the initial runtime

当我使用NodeJS应用程序时，我遇到了同样的问题，所以我在创建docker映像时通过NPM Build构建dist文件夹，因此它是docker映像的一部分，而不是在应用程序的初始执行时创建构建映像的docker cmd。也许RAM和CPU不足以在初始运行时进行NPM构建