A pod is used as a wrapper around a single container, eliminating the need for Kubernetes to manage the containers directly. Kubernetes would manage the pods in this case. These are pods operating several containers clustered together as one. These containers are co-related, and they do share resources like storage. The whole system works in unison such that one container may approach a certain task as data storage, while the other updates the files.
Every pod in this model is built only to run one application at a time, thus being more efficient. Scaling up is possible, although one has to scale up the number of nodes used to match the load balance. This is called replication in the Kubernetes architecture. The replicated pods are modeled and run as a unit by workload resources through replication controllers. Multi-container pods are used in adapters, bridges, and proxies to connect the main container to the external world.
For example, they are used as helper containers to reroute requests from the primary container to the external world. Thus, allowing the main container to connect to a localhost without a service discovery. The first notable benefit of using pods is an increase in productivity within the system. The very simplistic node-to-node communication in the delegation and completion of tasks makes operations run smoothly and in the shortest time possible. It is possible to scale up your system using pods, and that is by simply adding nodes into the cluster to scale up your operations.
This scaling-up must, however, be done properly for the best outcome. Efficiency is also improved in the replication process, which duplicates a failing pod and delegates that duty to another pod. The replication process focuses on enhancing efficiency by reducing failure probability and increasing productivity. Pods are a product of controllers that are responsible for managing operations within the Kubernetes system. Controllers facilitate the rollout, replication, and the overall state of the pods in a cluster.
The controller is the delegator of replication of pods if one pod fails. There are three main kinds of controllers, namely, jobs , deployments , and statefulSets. When a Pod gets created directly by you, or indirectly by a controller , the new Pod is scheduled to run on a Node in your cluster.
The Pod remains on that node until the Pod finishes execution, the Pod object is deleted, the Pod is evicted for lack of resources, or the node fails. When you create the manifest for a Pod object, make sure the name specified is a valid DNS subdomain name. You can use workload resources to create and manage multiple Pods for you. A controller for the resource handles replication and rollout and automatic healing in case of Pod failure.
For example, if a Node fails, a controller notices that Pods on that Node have stopped working and creates a replacement Pod. The scheduler places the replacement Pod onto a healthy Node. Controllers for workload resources create Pods from a pod template and manage those Pods on your behalf.
PodTemplates are specifications for creating Pods, and are included in workload resources such as Deployments , Jobs , and DaemonSets.
Each controller for a workload resource uses the PodTemplate inside the workload object to make actual Pods. The PodTemplate is part of the desired state of whatever workload resource you used to run your app. The sample below is a manifest for a simple Job with a template that starts one container. The container in that Pod prints a message then pauses.
Modifying the pod template or switching to a new pod template has no direct effect on the Pods that already exist. If you change the pod template for a workload resource, that resource needs to create replacement Pods that use the updated template. For example, the StatefulSet controller ensures that the running Pods match the current pod template for each StatefulSet object. If you edit the StatefulSet to change its pod template, the StatefulSet starts to create new Pods based on the updated template.
Eventually, all of the old Pods are replaced with new Pods, and the update is complete. Each workload resource implements its own rules for handling changes to the Pod template. On Nodes, the kubelet does not directly observe or manage any of the details around pod templates and updates; those details are abstracted away. That abstraction and separation of concerns simplifies system semantics, and makes it feasible to extend the cluster's behavior without changing existing code.
As mentioned in the previous section, when the Pod template for a workload resource is changed, the controller creates new Pods based on the updated template instead of updating or patching the existing Pods. Kubernetes doesn't prevent you from managing Pods directly. It is possible to update some fields of a running Pod, in place. However, Pod update operations like patch , and replace have some limitations:. Most of the metadata about a Pod is immutable. For example, you cannot change the namespace , name , uid , or creationTimestamp fields; the generation field is unique.
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