Kubernetes is open-source software that helps in the deployment and scaling of containerized applications. This is possible by grouping containers into logical units, which are easier to discover and manage. Primary Kubernetes features include storage orchestration, batch execution, load balancing, and automated rollouts and rollbacks.
Kubernetes performs all these roles using Kubernetes containers, Kubernetes Nodes, and Kubernetes Pods.
A Kubernetes container is software that contains all the dependencies, tools, settings, and system libraries required to run a particular application.
Kubernetes Pods, on the other hand, are groups of application containers with unique ports, image versions, and cluster IP addresses. A Pod can act as a logical host for a specific application.
Kubernetes Nodes are responsible for running Pods. A Kubernetes Node can be a virtual or physical machine that’s managed by a control plane. The Kubernetes control plane acts as a container orchestration layer and exposes interfaces and APIs.
This article explains the concept of Kubernetes Pods and Kubernetes Nodes. It defines how each entity works and the relationship between them.
- How Kubernetes Pods work
- How Kubernetes Nodes work
- The working relationship between Kubernetes Pods and Kubernetes Nodes
How Kubernetes Pods work
Applications usually run in containers where they can access required tools, libraries, and other vital settings. In Kubernetes, these containers are held in units known as Pods. Kubernetes Pods can consist of one or more containers.
Containers in the same Pod have access to a shared network and storage resources. This also means that the containers are co-scheduled since they work in a similar context or environment. The shared storage volumes provide persistent data, which helps Pods survive whenever containers are restarted.
Pods can contain init containers, which are initialized during startup. An init container is unique because it must be completed successfully before other containers are executed. If the init container fails, the kubelet will restart it repeatedly until it runs to completion.
Although Pods can accommodate multiple containers, one container per Pod is most often the case. Nevertheless, tight-coupled containers on the same Pod can still communicate quickly because they use a similar network port, IP address, and network namespace. This functionality supports an application’s lifecycle by ensuring access to the required resources.
Kubernetes Pods are designed to be short-lived and disposable. Whenever a user creates a Pod, it’s automatically scheduled to run on a Node. The Pod remains active until a specified process is completed. Kubernetes can increase the number of Pods and deploy them to accommodate increased user traffic.
The image below illustrates how multiple Pods can run on a single Node. Each Pod also contains several containers.
Workload resources like DaemonSet and StatefulSets allow developers to create and control multiple Pods. DaemonSet is a process for managing duplicated Pods or replicas, while StatefulSets are responsible for autoscaling Pods. The workload resource also creates new Pods to replace old ones in case of changes.
The key features of Kubernetes Pods are:
- Shared storage volumes
- Unique IP addresses, ports, and image versions
How Kubernetes Nodes work
Kubernetes Nodes are responsible for running Pods. These Pods can contain one or more containers. Depending on the Kubernetes cluster, a Node can be either a physical or a virtual machine. A Kubernetes cluster is composed of a group of worker Nodes for running containerized applications.
Kubernetes Nodes have the following components:
- The kubelet for managing containers and Pods running on a host machine
- A container runtime for downloading containers from the registry
- The kube-proxy for maintaining network rules
Users can create or update Node objects using kubectl, which is the command line interface (CLI) for managing a Kubernetes cluster. For instance, the kubectl cordon $Nodename command prevents a scheduler from running a Node.
All Nodes must be added to an API server that manages them. This is done in two major ways.
The first method is automatic. The kubelet component in a Node registers itself on the Kubernetes control manager.
The second technique involves adding a Node object to the master manually. Kubelet saves significant time by self-registering. This is why this method is more popular among developers.
Once the Node object is created, the control plane checks to ensure it’s healthy. For example, the Node object must have a valid DNS subdomain name. In case a Node is found to be unhealthy, the Kubernetes platform performs regular checks until it’s compliant. A controller or the developer can stop these safety checks.
Developers can then interact with Nodes using the master. This helps in determining when to create and destroy containers and for rerouting traffic based on demand. A cluster must have at least one master. However, it can also have more masters depending on its replication pattern.
Nodes enhance the deployment process by allowing developers to focus on productive areas rather than on the characteristics of a host machine. In a Kubernetes cluster, Nodes can substitute for one another depending on the availability of resources, such as RAM and CPU. This principle ensures that an application keeps running even when a specific Node fails.
The image below illustrates the relationship between the Kubernetes cluster, the master, and the Nodes. Note that the master or control plane controls the Nodes.
Kubernetes Nodes usually provide regular updates, also known as heartbeats. These updates allow the controller manager to take action whenever they detect failures or see that certain Nodes are available.
The working relationship between Kubernetes Pods and Kubernetes Nodes
The above sections discussed how Kubernetes Pods and Nodes work. Now, let’s review the relationship between these components.
Developers can create container images of their applications using popular software like Docker. (Discover the basics of Docker and how to use it) These containers are then pushed into Pods.
A Kubernetes Pod can have multiple containers. For instance, one container can have the backend while another hosts the frontend of an application. Since Pods are tightly coupled, data between these two containers can flow seamlessly.
The Kubernetes API then creates Node objects to start running the Pods. It also verifies the Node’s status by checking if a registered kubelet matches the Node’s metadata.name. If the Node is healthy, it’s cleared to run Pods. If the Node has errors, it’s suspended until it becomes healthy.
Kubernetes doesn’t manage container images individually. Instead, the containers are pushed into units known as Pods. Containers in the same Pods can share available resources, which is quite efficient. Kubernetes Nodes then run the Pods. A cloud provider, such as Amazon Web Services (AWS), can host the Kubernetes cluster.
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Pods and Nodes are essential elements when it comes to container orchestration using Kubernetes. These components make it easy to deploy and manage microservices.
Due to the critical role that Kubernetes plays, its popularity has soared. This is why the demand for Docker and Kubernetes skills is high.
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