A Pod can use as much compute resources as represented by the sum of requests and limits of all containers in that Pod. This means that a single Pod can end up hogging the resources of the node! To avoid this, administrators can control the amount of CPU and memory resources each container in a Pod can use by setting resource requests and limits in the Pod configuration file. By default, a Pod in Kubernetes will run with no limits on CPU and memory. Typically, when Pods run containers, they use the CPU and memory resources on the node to which they are scheduled. This way, administrators can detect and resolve issues in containerized applications before end-users notice. Alongside status of Pods, an administrator also needs to keep track of the status of containers at all times, as container failures impact the availability and performance of the containerized applications. Once a Pod is assigned to a node by scheduler, kubelet starts creating containers using container runtime.

This is necessary because, if a Pod fails, then the cluster's actual state may go out of sync with its desired state. At any given point in time, an administrator needs to know at which phase a Pod is in its life cycle, so they can promptly detect Pod failures or undue slowness in Pod creation and rapidly initiate investigations into the same. If a Node dies, the Pods scheduled to that node are scheduled for deletion, after a timeout period. Pods are created, assigned a unique ID (UID), and scheduled to nodes where they remain until termination (according to restart policy) or deletion. A Pod’s contents are always co-located and co-scheduled, and run in a shared context. A Pod (as in a pod of whales or pea pod) is a group of one or more containers (such as Docker containers), with shared storage/network, and a specification for how to run the containers. Pods are the smallest deployable units of computing that can be created and managed in Kubernetes.

Ios pod class namespace