Configuration of the Xmx flag
Running a Java microservice in an environment you have to make/decide some configuration.
The configuration that I refer now is how to set the Xmx flag.
I consider that any type of instance you choose, you have to leave some RAM for the system and other programs.
I have a t2.medium (4 GB) AWS EB and I configured the Xmx flag for Java microservice to 3 GB.
After the load, the committed memory reaches a bit above 3.0 GB, around 3.1 GB. There are a lot of free memory. The problem is that AWS EB reports 97% RAM, this means that left memory is used for CloudWatch Agent, NGINX, Linux and maybe for other things.
If the values reaches or goes beyond 100%, something can be killed by Linux Kernel due to high usage of the RAM.
Question: Do you have any idea, the best practices in choosing the value for Xmx flag based on total available RAM of the machine? Do you decide it by doing experiments?
Thank you
java linux microservices ram amazon-elastic-beanstalk
add a comment |
Running a Java microservice in an environment you have to make/decide some configuration.
The configuration that I refer now is how to set the Xmx flag.
I consider that any type of instance you choose, you have to leave some RAM for the system and other programs.
I have a t2.medium (4 GB) AWS EB and I configured the Xmx flag for Java microservice to 3 GB.
After the load, the committed memory reaches a bit above 3.0 GB, around 3.1 GB. There are a lot of free memory. The problem is that AWS EB reports 97% RAM, this means that left memory is used for CloudWatch Agent, NGINX, Linux and maybe for other things.
If the values reaches or goes beyond 100%, something can be killed by Linux Kernel due to high usage of the RAM.
Question: Do you have any idea, the best practices in choosing the value for Xmx flag based on total available RAM of the machine? Do you decide it by doing experiments?
Thank you
java linux microservices ram amazon-elastic-beanstalk
add a comment |
Running a Java microservice in an environment you have to make/decide some configuration.
The configuration that I refer now is how to set the Xmx flag.
I consider that any type of instance you choose, you have to leave some RAM for the system and other programs.
I have a t2.medium (4 GB) AWS EB and I configured the Xmx flag for Java microservice to 3 GB.
After the load, the committed memory reaches a bit above 3.0 GB, around 3.1 GB. There are a lot of free memory. The problem is that AWS EB reports 97% RAM, this means that left memory is used for CloudWatch Agent, NGINX, Linux and maybe for other things.
If the values reaches or goes beyond 100%, something can be killed by Linux Kernel due to high usage of the RAM.
Question: Do you have any idea, the best practices in choosing the value for Xmx flag based on total available RAM of the machine? Do you decide it by doing experiments?
Thank you
java linux microservices ram amazon-elastic-beanstalk
Running a Java microservice in an environment you have to make/decide some configuration.
The configuration that I refer now is how to set the Xmx flag.
I consider that any type of instance you choose, you have to leave some RAM for the system and other programs.
I have a t2.medium (4 GB) AWS EB and I configured the Xmx flag for Java microservice to 3 GB.
After the load, the committed memory reaches a bit above 3.0 GB, around 3.1 GB. There are a lot of free memory. The problem is that AWS EB reports 97% RAM, this means that left memory is used for CloudWatch Agent, NGINX, Linux and maybe for other things.
If the values reaches or goes beyond 100%, something can be killed by Linux Kernel due to high usage of the RAM.
Question: Do you have any idea, the best practices in choosing the value for Xmx flag based on total available RAM of the machine? Do you decide it by doing experiments?
Thank you
java linux microservices ram amazon-elastic-beanstalk
java linux microservices ram amazon-elastic-beanstalk
edited Nov 12 '18 at 15:29
Adrian
asked Nov 12 '18 at 15:22
AdrianAdrian
125110
125110
add a comment |
add a comment |
1 Answer
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There is no formula for tuning JVM. It is highly dependent on each specific machine, the application, application server, and usage pattern by end users. It is recommended that you set the same value for Xmx and Xms. You should try different values and profile JVM using JProfiler or Visual VM. This is an article for Liferay JVM tuning. Hopefully, it is useful and brings you some ideas.
Thank you for your answer. I know I can do it very well using JProfiler with a deployed agent inside the env. I am interested in some best practices. The ultimate solution is by doing experiments.
– Adrian
Nov 13 '18 at 7:23
I am going to read your link.
– Adrian
Nov 13 '18 at 7:24
add a comment |
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1 Answer
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
There is no formula for tuning JVM. It is highly dependent on each specific machine, the application, application server, and usage pattern by end users. It is recommended that you set the same value for Xmx and Xms. You should try different values and profile JVM using JProfiler or Visual VM. This is an article for Liferay JVM tuning. Hopefully, it is useful and brings you some ideas.
Thank you for your answer. I know I can do it very well using JProfiler with a deployed agent inside the env. I am interested in some best practices. The ultimate solution is by doing experiments.
– Adrian
Nov 13 '18 at 7:23
I am going to read your link.
– Adrian
Nov 13 '18 at 7:24
add a comment |
There is no formula for tuning JVM. It is highly dependent on each specific machine, the application, application server, and usage pattern by end users. It is recommended that you set the same value for Xmx and Xms. You should try different values and profile JVM using JProfiler or Visual VM. This is an article for Liferay JVM tuning. Hopefully, it is useful and brings you some ideas.
Thank you for your answer. I know I can do it very well using JProfiler with a deployed agent inside the env. I am interested in some best practices. The ultimate solution is by doing experiments.
– Adrian
Nov 13 '18 at 7:23
I am going to read your link.
– Adrian
Nov 13 '18 at 7:24
add a comment |
There is no formula for tuning JVM. It is highly dependent on each specific machine, the application, application server, and usage pattern by end users. It is recommended that you set the same value for Xmx and Xms. You should try different values and profile JVM using JProfiler or Visual VM. This is an article for Liferay JVM tuning. Hopefully, it is useful and brings you some ideas.
There is no formula for tuning JVM. It is highly dependent on each specific machine, the application, application server, and usage pattern by end users. It is recommended that you set the same value for Xmx and Xms. You should try different values and profile JVM using JProfiler or Visual VM. This is an article for Liferay JVM tuning. Hopefully, it is useful and brings you some ideas.
answered Nov 12 '18 at 15:53
AbdollahAbdollah
10011
10011
Thank you for your answer. I know I can do it very well using JProfiler with a deployed agent inside the env. I am interested in some best practices. The ultimate solution is by doing experiments.
– Adrian
Nov 13 '18 at 7:23
I am going to read your link.
– Adrian
Nov 13 '18 at 7:24
add a comment |
Thank you for your answer. I know I can do it very well using JProfiler with a deployed agent inside the env. I am interested in some best practices. The ultimate solution is by doing experiments.
– Adrian
Nov 13 '18 at 7:23
I am going to read your link.
– Adrian
Nov 13 '18 at 7:24
Thank you for your answer. I know I can do it very well using JProfiler with a deployed agent inside the env. I am interested in some best practices. The ultimate solution is by doing experiments.
– Adrian
Nov 13 '18 at 7:23
Thank you for your answer. I know I can do it very well using JProfiler with a deployed agent inside the env. I am interested in some best practices. The ultimate solution is by doing experiments.
– Adrian
Nov 13 '18 at 7:23
I am going to read your link.
– Adrian
Nov 13 '18 at 7:24
I am going to read your link.
– Adrian
Nov 13 '18 at 7:24
add a comment |
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