Why is it faster to start a jar in a Docker-Container than on local machine? Code Answer

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Currently I’m testing with Microservices and Docker-Container. And during my last try with a Micronaut-Server I saw differences between the start-up-time for starting local (cmd) and starting with Docker. But what made me curios, is the fact that the Container was much faster.

I’m creating a runnable jar (more precisely a shadowjar – not sure what the exact difference is) with Gradle. Then I build a Docker-Image with that jar file. The start command for both is the same (see the Dockerfile below): java -jar micronaut.jar

During my search for a reason for that I found this question which is also about performance of Docker-Container, but the conclusion was more, that the Container should be slightly slower, not faster.

My Dockerfile:

FROM adoptopenjdk/openjdk11-openj9:jdk-
COPY build/libs/*.jar micronaut.jar
CMD java -jar micronaut.jar

and the docker command: docker run -p 9999:9999 -it --name dokuserver pge/dokuserver:0.1

I expected that the start-up-time would be the same oder a bit slower for the container but actually the time is.

  • Local: 4000-5000ms
  • Docker: ~2500ms

I tried several times but the outcome ist always nearly the same.

I’m working on a Win10 PC with DockerDesktop (Docker 19.03.1), IntelliJ and Gradle (5.5.1) and used the IntelliJ-Terminal and the windows-cmd for the local start.

I’m no an expert in Docker or the things which happens closer to the hardware so I couldn’t find an answer for this speed difference. So I’m asking you:

What could cause that?


AdoptOpenJDK has builds with two different JVMs: HotSpot and OpenJ9

HotSpot and OpenJ9 are totally different implementations of JVM with different JIT compilers, GC algorithms and internal architecture.

As your docker file suggests, you are using adoptopenjdk/openjdk11-openj9:jdk- which is a name suggests OpenJ9 based.

On Windows your are likely to use HotSpot based JVM (java -version to know for sure).

OpenJ9 has less aggressive compiler optimizations so difference in start up time is not surprising.

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