Memory Footprint Of Java EE Servers On Docker -- And What Is The Difference To "Hello World"?

What is the memory (RAM) consumption of Java EE application servers: WebLogic, WildFly, WebSphere Liberty Profile, TomEE and Payara Server comparing it to a "Hello World" Java SE application running in a Docker container?

In this screencast I started the application servers and measured the RAM consumption of the entire docker image, the OS, JVM and application server included. The application servers were used with various JVM heap settings, so the results are not directly comparable, but are good enough for an estimation.

See docklands for the docker images used in the workshop. Each application server was started with deployed ping app and nano -- the Java 8 / Nashorn HTTP Server was used as "Hello World" reference.

See you at Java EE Workshops at Munich Airport, Terminal 2 and particularly at Java EE 7 Microservices.

Comments:

Really nice comparison. I think video about optimization would be great also:)

Best regards
TJ

Posted by TJ on April 05, 2016 at 11:13 AM CEST #

Adam, what are the benefits of using Swarm (or any embedded container) on Docker ? I don't see any advantage of running a fat jar instead setting a proper Wildfly for example.
Also, are SDKs reasonable on microservices for internal rest requests ? (coupling, maintenance etc). Thanks a lot and keep the good work !

Posted by Josh on April 08, 2016 at 08:23 PM CEST #

Did you use full Liberty server or web profile?

Posted by Paul on June 22, 2016 at 02:33 PM CEST #

Adam, if you do not mind I put here the link to the article how to enable elasticity of memory usage for Java applications. It can help to fight the "heaviness" in terms of memory consumption and works perfectly for variable workloads. So being configured smartly, Java can be cost-effective for all ranges of projects – from cloud-native to the legacy enterprise.

https://www.javacodegeeks.com/2017/11/minimize-java-memory-usage-right-garbage-collector.html

Posted by Ruslan on November 21, 2017 at 10:17 PM CET #

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