![]() Let's assume that you set the limits above for your pod, since you've also set the same limits in your Docker image via -Xms and -Xmx flags. If your application uses more than this, the pod will be OOM killed spec: containers: - image: yourorg/yourimage:tag name: your-service resources: requests: memory: 128Mi # This is the minimum memory that is requested and allocated every time a pod has been created limits: memory: 256Mi # This is the memory limit for your pod. When it comes to memory limits, you can set the following parameters in your deplyoment: apiVersion: apps/v1 kind: Deployment metadata: #. If you are not aware of the things described above, you could easily end up with a configuration that will cause regular restarts to your pods due to OOMKilled. ENTRYPOINT Īlternatively, if you're using Jib, you can make it work like this in your adle: // adleĮnvironment = ![]() You can pass these flags to your JAR in a Docker image like that: # Dockerfile #. Setting Xms and Xmx inside a Docker image The NOT so happy path with resource limitsĪs your resources are limited inside a Kubernetes cluster, you have to be careful when it comes to the allocation of them, since you want to avoid the situation where one pod eats up all your resources, and the others will "starve". The reason behind this is that JVM uses memory outside the heap for other purposes as well (metaspace, code cache, etc.), while Xmx affects only the heap. Let's check the overall memory usage of the same Java process (see the highlighted row): It seems totally fine, your application requests a minimum of 128MiB of memory, which means that it will be allocated to the heap right after the application starts, and will be limited to 256MiB afterwards. For example, if you set -Xms128M and -Xmx256M and you start monitoring your application with VisualVM, you'll see something like this: Xms, -Xmx and the problem with themĪs you probably already know, you can set the initial ( Xms) and the maximum ( Xmx) memory pool allocation for a JVM application with these flags. If you would like to get familiar with the core concepts of memory handling, heap and GC inside JVM, you should take a look on this comprehensive video first. In addition, memory management/usage of a JVM application is also an interesting topic, but this article is not about that. That's especially true for setting the right resource limits for your pod that is running a JVM application. microservices) could be a challenging task. In Kubernetes, scaling applications vertically, that are primarily designed to scale horizontally (i.e.
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