What Is Kubernetes and How Does It Work?

What Is Kubernetes? An Introduction to the Wildly Popular Container Orchestration Platform

OK, but why all the buzz? Why is Kubernetes so popular?

Organizations search for solid, proven platforms as they shift to microservice and cloud-native designs that leverage containers. Kubernetes is gaining popularity with practitioners for four reasons:

1. Kubernetes allows you to move more quickly. Indeed, Kubernetes enables you to provide a self-service platform-as-a-service (PaaS) for development teams that builds a hardware abstraction layer. Your development teams will be able to request resources fast and efficiently. If they require extra help to manage increased load, they can receive them just as quickly because all of your teams’ resources originate from a shared infrastructure.

Filling out documents to request new machines to run your application is no longer necessary! Simply provision and go and take advantage of the Kubernetes-specific tooling for packaging, deployment, and testing. (We’ll go through Helm in greater detail in a later section.)

2. Kubernetes is inexpensive. Kubernetes and containers make considerably better use of resources than hypervisors and virtual machines. Containers require less CPU and memory resources to run because they are so small.

3. Kubernetes is cloud-independent. Kubernetes is available on Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) and locally. You can switch workloads without totally rethinking your infrastructure or rewrite your applications, allowing you to standardize on a platform and prevent vendor lock-in.

Companies like Kublr, Cloud Foundry, and Rancher, for example, provide the functionality to help you build and manage your Kubernetes cluster on-premises or on any cloud provider you want.

4. Cloud providers will manage Kubernetes. Kubernetes, as previously stated, is the current de facto standard for container orchestration technologies. It’s no surprise that big cloud providers have many Kubernetes-as-a-service products. Complete Kubernetes platform administration is provided by Amazon EKS, Google Cloud Kubernetes Engine, Azure Kubernetes Service (AKS), Red Hat OpenShift, and IBM Cloud Kubernetes Service, so you can focus on what matters most to you: shipping apps that satisfy your consumers.

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So, how does Kubernetes work?

The cluster is an essential part of Kubernetes. A group comprises several virtual or physical machines, each performing a specific function as a master or a node. The master notifies nodes when containers should produce and remove, and each node houses groups with one or more containers (which contain your apps). Simultaneously, it instructs nodes on rerouting traffic in response to new container alignments.

Kubernetes is the Kubernetes master.
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Administrators and other users can manage vessel scheduling and deployment via the Kubernetes master, which serves as the cluster’s access point (or control plane). A group will have at least one master, but it may have more depending on the cluster’s replication policy.

The master uses etc., a durable and distributed key-value data store to store the cluster’s status and configuration data. Each node has access to etcd, which teaches nodes how to keep the containers’ configurations up to date. Etcd can be run on the Kubernetes master and in standalone deployments.

The Kube-Episerver connects masters to the remainder of the cluster as the main access point to the control plane. The Kube-Episerver, for example, ensures that etcd configurations match the configurations of containers deployed in the group.

Control loops that govern the status of the cluster via the Kubernetes API server are handled by the Kube-controller-manager. Controls for deployments, replicas, and nodes are all driven by this service. The node controller, for example, is in charge of registering a node and monitoring its health during its lifespan.

The Kube-scheduler keeps track of and manages the cluster’s node workloads. This service maintains node capacity and resources and assigns work to them according to their availability.

The cloud-controller-manager is a Kubernetes service that helps keep the cluster cloud-agnostic. The cloud-controller-manager acts as an abstraction layer between cloud providers’ APIs and tools (such as storage volumes or load balancers) and their Kubernetes representations.

Nodes
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A container runtime, commonly Docker, must be installed on all nodes in a Kubernetes cluster. As Kubernetes delivers containers to cluster nodes, the container runtime begins and manages them. The containers are where your applications (web servers, databases, API servers, and so on) run.

Each Kubernetes node has an agent process called a kubelet that manages the node’s state, such as starting, stopping, and maintaining application containers in response to control plane commands. The kubelet monitors the performance and health of the nodes, pods, and containers it manages. It relays this information to the control plane to assist it in making scheduling decisions.

Kube-proxy is a cluster-wide network proxy that operates on the nodes. For node-based services, it also acts as a load balancer.

A pod is the most basic scheduling unit, consisting of one or more containers that guarantee to be co-located on the host computer and can share resources. Each pod gives its IP address within the cluster, allowing the application to use ports without conflict.

A Pod Spec is a YAML or JSON object that describes the expected state of the containers in a pod. Through the API server, these objects give to the kubelet.

A pod can define one or even more volumes, such as a local hard drive or a networked disk, and expose them to the containers in the pod, allowing them to share storage space. When one container downloads content and another upload it somewhere else, it can use volumes. Because containers inside pods are frequently temporary, Kubernetes provides a service load balancer to make delivering requests easier to return to a group of pods. A service is designed to target a logical group of pods that have been chosen based on their labels (explained below). You can only access services from within the cluster by default, but you can allow public access if you want them to receive requests outside the group.

Replicas and deployments
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A deployment is a YAML object that specifies the pods and the number of replicas (container instances) for each pod. A ReplicaSet, part of the deployment object, limits the number of images you want to operate in the cluster. If a node running a pod, for example, dies, the replica set ensures that another pod schedules on another available node.

A DaemonSet deploys and runs a specified daemon (in a pod) on the nodes you designate. DaemonSets are most commonly used to supply pods with services or maintenance. A DaemonSet, for example, is how New Relic Infrastructure deploys the Infrastructure agent to all nodes in a cluster.

Namespaces
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Namespaces allow you to establish virtual groups on top of a physical cluster. Namespaces are designed for situations with many users spread across several teams or projects. They logically segregate cluster resources and assign resource quotas.

Labels
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Labels are key/value pairs that you can assign to pods and other objects in Kubernetes. Kubernetes operators can use labels to categorize and pick a subset of items. Labels, for example, allow you to rapidly drill down to the information you’re most interested in when monitoring Kubernetes objects.

Persistent storage volumes with stateful sets
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StatefulSets allow you to assign unique IDs to pods if you need to relocate pods to different nodes, maintain pod networking, or persist data between them. Meanwhile, persistent storage volumes offer a cluster with storage resources to which pods can request access when they’re deployed.

Other useful components

The Kubernetes components listed below are helpful but not essential for regular Kubernetes operation.

DNS for Kubernetes
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Kubernetes provide this technique for pod-to-pod DNS-based service discovery. You can use this DNS server with other DNS servers in your architecture.

Logs at the cluster level
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If you have a logging tool, you can use it with Kubernetes to extract and store application and system logs written to standard output and standard error from within a cluster. If you want to use cluster-level records, you must offer your log storage solution because Kubernetes does not provide native log storage.

Helm is a command-line tool for administering Kubernetes applications.
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Helm is a Kubernetes application package management registry managed by the CNCF. Horizon charts pre-configure software application resources that you can employ in your Kubernetes cluster. In a 2020 CNCF study, 63 percent of respondents named Helm the best package management tool for Kubernetes applications. Helm charts can help DevOps teams learn to manage Kubernetes applications more quickly. It enables them to work with existing charts that they can share, version, and deploy in their development and production settings.

Istio and Kubernetes are a popular combo.
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In a microservices architecture like Kubernetes, a service mesh is an infrastructural layer that allows your service instances to communicate with one another. You may also customize how your service instances conduct critical tasks like service discovery, load balancing, data encryption, and authentication and authorization using the service mesh. Istio is one such service mesh, and current thinking from IT titans like Google and IBM implies they’re becoming increasingly inextricably linked.

The IBM Cloud team uses Istio to address control, visibility, and security challenges that it has encountered while running Kubernetes at scale. Istio assists IBM in the following ways:

• Secure connections between microservices with customizable permission and authentication settings Connect services and regulate traffic flow 
• IBM will be able to manage services in production if you provide a control point. 
• Observe what’s going on in their services using an adapter that provides Istio data, allowing it to monitor Kubernetes microservice performance data alongside its current application data.

Challenges to Kubernetes adoption

Kubernetes has undoubtedly progressed since its initial release. On the other hand, the rapid expansion comes with its share of growing pains. Here are some of the obstacles to Kubernetes adoption:

1. The Kubernetes technological landscape is complicated. One of the benefits of open-source technology like Kubernetes for developers is the opportunity for rapid innovation. However, too much innovation can lead to confusion, mainly when the central Kubernetes code base evolves faster than users can keep up. When a bevy of the platform and managed service providers threw into the mix, it’s easy for newbies to become lost in the shuffle.

2. Business priorities don’t always align with forward-thinking development and IT teams. It might be difficult for teams to secure funds to experiment with Kubernetes adoption projects when finances allocate to maintain the status quo. Such experiments often consume a significant amount of time and team resources. Furthermore, commercial IT teams are frequently risk-averse and hesitant to change.

3. Teams are still learning the skills they’ll need to use Kubernetes. It wasn’t until recently that developers and IT operations personnel had to alter their procedures to accommodate containers—and now they must also accommodate container orchestration. Enterprises interested in implementing Kubernetes should hire people who can code, manage operations, and understand application design, storage, and data pipelines.

4. Kubernetes can be challenging to work with. In reality, the Kubernetes Failure Stories GitHub repo contains many Kubernetes horror stories, ranging from DNS outages to “a cascade failure of distributed systems.”

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