CPU and memory are each a resource type. A resource type has a base unit. CPU represents compute processing and is specified in units of Kubernetes CPUs. Memory is specified in units of bytes.
requests and limits can only be specified on individual Containers.
Each Container of a Pod can specify one or more of the following:
spec.containers[].resources.limits.cpu
spec.containers[].resources.limits.memory
spec.containers[].resources.limits.hugepages-
spec.containers[].resources.requests.cpu
spec.containers[].resources.requests.memory
spec.containers[].resources.requests.hugepages-
resource request
When you specify the resource request for Containers in a Pod, the scheduler uses this information to decide which node to place the Pod on.
resource limit
When you specify a resource limit for a Container, the kubelet enforces those limits so that the running container is not allowed to use more of that resource than the limit you set.
The kubelet also reserves at least the request amount of that system resource specifically for that container to use. If the node where a Pod is running has enough of a resource available, it’s possible (and allowed) for a container to use more resource than its request for that resource specifies. However, a container is not allowed to use more than its resource limit.
CPU and memory are each a resource type. A resource type has a base unit. CPU represents compute processing and is specified in units of Kubernetes CPUs. Memory is specified in units of bytes.
When you create a Pod, the Kubernetes scheduler selects a node for the Pod to run on. Each node has a maximum capacity for each of the resource types: the amount of CPU and memory it can provide for Pods. The scheduler ensures that, for each resource type, the sum of the resource requests of the scheduled Containers is less than the capacity of the node.
If a Container exceeds its memory limit, it might be terminated. If it is restartable, the kubelet will restart it, as with any other type of runtime failure.
If a Container exceeds its memory request, it is likely that its Pod will be evicted whenever the node runs out of memory.
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