Understanding Containers

Due to Red Hat Enterprise Linux (RHEL) behavior, a container on a node with high CPU usage might seem to consume more memory than expected. The higher memory consumption could be caused by the kmem_cache in the RHEL kernel. The RHEL kernel creates a kmem_cache for each cgroup. For added performance, the kmem_cache contains a cpu_cache, and a node cache for any NUMA nodes. These caches all consume kernel memory.

The amount of memory stored in those caches is proportional to the number of CPUs that the system uses. As a result, a higher number of CPUs results in a greater amount of kernel memory being held in these caches. Higher amounts of kernel memory in these caches can cause Red Hat OpenShift Service on AWS containers to exceed the configured memory limits, resulting in the container being killed.

To avoid losing containers due to kernel memory issues, ensure that the containers request sufficient memory. You can use the following formula to estimate the amount of memory consumed by the kmem_cache, where nproc is the number of processing units available that are reported by the nproc command. The lower limit of container requests should be this value plus the container memory requirements:

A container engine is a piece of software that processes user requests, including command line options and image pulls. The container engine uses a container runtime, also called a lower-level container runtime, to run and manage the components required to deploy and operate containers. You likely will not need to interact with the container engine or container runtime.

Red Hat OpenShift Service on AWS uses CRI-O as the container engine and runC or crun as the container runtime. The default container runtime is runC.