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Dockerfile enhancements #703
Dockerfile enhancements #703
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Maintains all artifacts & volumes from previous version. * Move unzip to builder. * Clear apt-cache in runner.
This artifact is not needed to run the service.
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Looks good, although I would not change the config file
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Please let me know if there are any other changes you guys would like me to make to this MR. |
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looks good to me
Should I upgrade to the base images to Java 11? I was able to do that locally with no issues. Java version >11 had issues though. |
Additionally, tini is no longer required for Docker 1.13+: https://github.com/krallin/tini You can see in the screenshot below that docker-init (built-in tini) is forked to tini. @lfoppiano @kermitt2 Do you guys want me to continue pushing updates here? |
@superdude264 For backward compatibility maybe we can keep tiny for the time being and remove it later on. Regarding further improvements, is fine for me, indeed it depends on the changes. |
@lfoppiano The only other change I have to upgrade the runtime image to Java 11. |
@superdude264 you can include the update to java 11 in the current PR I think |
Here you go @lfoppiano. I left the builder image as-is and upgraded the runtime image to Java 11. The JVM now utilizes the memory assigned to the container, so there isn't a need to set the memory size in
I have not found a way to correct or silence these warning in our production setup, so I just left them. Final image size is ~950 MB. |
Thank you @superdude264 (and Luca!), it works fine for me too. I started to adapt the changes to |
@superdude264 I have a question, you removed the volume for the GROBID
I've read somewhere that writing in a volume is faster than in the container directly, but maybe this is not the case. Do you have any hints on this? |
@kermitt2 Re: I will look into the question regarding write speed to a container vs a volume. |
Thanks! see #721 |
RE: Removal of
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Aligned Deep Learning Dockerfile with PR #703
#697
Shrunk the container from 1.66 GB to 912.5 MB. Most of the change is achieved in the first commit, which maintains total parity of output with the previous version. Later commits are remove unused artifacts, volume, & disable logging into the container (which in production environments would cause it to fail over after running for long periods).