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Definition: What Is Kubernetes?

Kubernetes, initially developed by Google engineers, is an open-source platform that makes it easy to deploy, maintain, scale and run containers automatically. Kubernetes is known for its scalability and flexibility and allows on-premises, hybrid, or public cloud infrastructure to migrate workloads quickly.

Also referred to as “k8s”, it has a Greek origin meaning “helmsman”, where 8 refers to the number of letters between “K” and “s.” Google later donated the Kubernetes project to the newly formed Cloud Native Computing Foundation (CNCF) in 2015.

Need some help getting started with Kubernetes? Check out the short video below.


Why Use Kubernetes: Key Benefits

Containerization can make an application platform-independent and allow faster and more secure deployment. Container orchestrators such as Kubernetes can automatically deploy the desired application version. And ensure that the service is ready to be used and that multiple containers‘ operations go smoothly. It also provides container updates with no downtime during production.

In addition, it can make it easier to manage things like scaling containerized apps, releasing new app versions, managing canary deployment, or providing framework support. More specifically, here are some of the benefits and advantages of Kubernetes:

  • Fast and easy deployment: Kubernetes dramatically simplifies the development, release, and deployment processes. It supports multiple deployment options for application development and deployment needs. The open API of Kubernetes makes it easy to integrate with CI/CD procedures. For example, when running a stateless web server such as nginx, the deployment controller in Kubernetes will consistently maintain the desired state of the app (e.g., number of instantiated Kubernetes pod replicas).
  • Cost efficient: It can assist enterprises in cutting ecosystem maintenance costs by making the best use of hardware to optimize infrastructural resources. Kubernetes can also automatically change a service’s cluster size, letting you scale apps on demand flexibly. This utilization-based scaling of microservices/applications makes it cost-effective.
  • Easy migration: Being open-source and compatible with many popular platforms, Kubernetes gives freedom to run on any premises and readily move application workloads from on-premises to public or private clouds.
  • Autoscaling: Kubernetes supports autoscaling, which enables businesses to scale up and down the number of resources they use in real time.
  • Open-source community: Kubernetes has a large and active community, constantly releasing open-source solutions that extend its capabilities. This makes it easy to integrate with other tools you’re probably working with like logging, monitoring and alerting software.
  • API-based: Kubernetes API lets you query and manipulate the state of objects in Kubernetes. (for example, Pods, Namespaces, ConfigMaps, and Events). The API continuously evolves and changes the system to maintain compatibility with existing clients. It also allows you to add new API resources and resource fields or remove API resources per API deprecation policy and do much more.
  • Improved DevOps practices: Enterprises use Kubernetes to simplify their CI/CD pipeline to quickly scale at the load changes. Kubernetes lessens the engineers’ workload and allows them to focus on customer requirements while relying on the cloud for a load of functioning apps.
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What Is Kubernetes Used For: Main Features & Applications

Kubernetes automates most tedious and time-consuming tasks that would otherwise have to be completed manually. Here are the features provided by Kubernetes that make container management easier:

  • Automated rollouts/rollbacks: Kubernetes’ automatic rollout/rollback feature ensures that all instances of a given application are not killed simultaneously. If something goes wrong, Kubernetes will go back and undo the changes.
  • Service discovery and load balancing: Without specifying IP addresses or configuring endpoints in advance, services can automatically learn about one another through a process called “service discovery.” Kubernetes can expose a container using the DNS name or their own IP address. If container traffic is heavy, Kubernetes can load balance and disperse network traffic to stabilize the deployment.
  • Coordinating data storage: Kubernetes can integrate with all popular cloud providers and storage systems. It can automatically mount local storage, public cloud providers, and more. For example, NFS, iSCSI, Gluster, Ceph, Cinder, and Flocker are all supported as network storage systems that can be automatically mounted.
  • Configuration and secret management: Using a Secret; you can avoid writing sensitive information into your application code. You can deploy and update secrets and application configuration without rebuilding your container images or exposing secrets in your stack configuration.
  • Automatic bin packing: Kubernetes can make the best use of container resources (RAM, CPU, etc.) by automatically placing containers on your nodes based on your requirements. Furthermore, workloads are balanced between urgent and best-effort tasks so that all available resources can be used effectively.
  • Batch execution: Kubernetes can manage batch and CI workloads and replace failed containers. It provides two workload resources: a Job object that creates and reruns on__e or more Pods until a certain number terminates successfully; and a CronJob object that allows you to set up repeating processes like backups and emails or schedule individual activities for a specific time.
  • IPv4/IPv6 dual-stack: Kubernetes supports Dual-stack Pod networking (a single IPv4 and IPv6 address per Pod), IPv4 and IPv6 enabled Services, and Pod off-cluster egress routing through IPv4 and IPv6 interfaces.
  • Self-healing: Kubernetes is an excellent way to track how containers, pods, and nodes are doing. If a container fails, Kubernetes will either restart it, replace it, or terminate it based on a user-defined health check, and it will keep it hidden until it is ready to serve.
  • Horizontal scalability: Kubernetes lets users horizontally scale containers based on application needs, which may change. With horizontal scalability, when demand rises, more Pods are added to handle the extra workload. The Horizontal Pod Autoscaler can be used to accomplish it.
  • Dynamic Volume Provisioning: The dynamic volume provisioning feature creates storage on-demand. Without dynamic provisioning, cluster admins must manually create new storage volumes and then represent them in Kubernetes using PersistentVolume Object. It eliminates pre-provisioning for cluster admins. Instead, it automatically provides storage as requested.
  • DevSecOps & Security: Kubernetes makes it easier for DevOps to transition towards DevSecOps as users can configure and administer Kubernetes’ native security controls directly rather than depending on security operators’ security tools. These include network policies (used to restrict pod-to-pod traffic), role-based access control (used to establish user and service account responsibilities and privileges), and more.

Who Uses Kubernetes

Kubernetes is an excellent pick among emerging container architectures for adding cutting-edge features to the development of hardware and software design. Kubernetes’s flexible application support, which can lower hardware costs and lead to more efficient architecture, made businesses switch to it since its release. And many others will continue to do so. Here’s how some companies successfully used Kubernetes to solve their problems:

  • Babylon: Built a self-service AI training platform on top of Kubernetes for their Medical AI Innovations.
  • Adidas: Within a year, Adidas saw a 40% reduction in the time it needed to get a project up and running and integrated into its infrastructure.
  • Squarespace: By implementing Kubernetes and updating its networking stack, Squarespace has cut the time it takes to deliver new features by approximately 85%.
  • Nokia: Using Kubernetes in a Telecom Company to Enable 5G and DevOps Moving to cloud-native technologies making products infrastructure-agnostic.
  • Spotify: An early container user, Spotify is migrating to Kubernetes, which provides greater agility, lower costs, and alignment with the rest of the industry on best practices.

K8s Architecture and Basic Terminology Explained

Before you know how Kubernetes work, it’s essential to understand some of the basic terms used in its ecosystem.

Pod: These are the smallest and simplest Kubernetes objects. Most of the time, a Pod is set up to run a single container. Read more about Kubernetes pods.

Node/Worker Node: A node is a worker machine that performs the requested tasks assigned by the control plane/master node.

The worker node consists of Kubelet, an agent necessary to run the pod, Kube-proxy maintaining the network rules and allowing communication, and the Container runtime software to run containers.

Main Node / Control plane: Control plane components make decisions about the cluster, like scheduling, detecting, and responding to cluster events, such as starting a new pod when a deployment’s replicas field is not the same as mentioned in the desired state. It includes Kube-apiserver to expose Kubernetes API, etcd, a key-value data storage, Kube-scheduler to watch over unassigned pods and assign them to a node based on the desired state, and Kube-controller-manager containing all the controller functions of the control plane.

Cluster: A group of worker nodes that run containerized applications. Every cluster has at least one worker node.

Kubectl: Command line tool for communicating with a Kubernetes cluster’s control plane via the Kubernetes API.

Kubelet: An agent that runs on each node in the cluster, ensuring containers run in a Pod.

Kubeproxy: A network proxy that runs on each node in your cluster and implements the Kubernetes Service concept.

CoreDNS: DNS server that can be used as the Kubernetes cluster DNS.

API server (Kube-API server): The Kubernetes API is accessible through the API server, which is a part of the Kubernetes control plane. The API server is the Kubernetes control plane’s front end.

Secrets: Kubernetes object with sensitive data stored such as a password, a token, or a key. By using a Secret, you can avoid writing sensitive information into your application code.

Controller: Controllers are control loops that keep watch on the state of your cluster and make or ask for changes as needed. Each controller tries to bring the current state of the cluster closer to the desired state.

Operator: This allows you to encapsulate domain-specific knowledge for an application. By automating tasks specific to an application, Operators make it easier to deploy and manage apps on K8s.

How Does Kubernetes Work

On a high level, the Kubernetes cluster infrastructure consists of the main node/control plane and worker node. Each of these worker nodes contains pods, the smallest Kubernetes unit with a minimum of one container each. The main node/control plane takes up the developer’s instructions and decides tasks for the worker nodes automatically.


For example, when the developer sends the instructions to the control plane, the API server, the only way to interact with the cluster, takes in the instructions (desired state) in YAML or JSON format and performs authentication before moving it onto the stack.

The control-manager takes it up and sees that the actual state equals the desired state. So, for example, if the desired state has 5 running pods and the actual state has only 3 pods running. Then, it plans to start 2 pods and tells the scheduler to do that.

The scheduler tries to optimize and pack things into the servers utilizing every last piece of resource you have without any waste and assigning new pods to the nodes.

Meanwhile, the etcd stores all the cluster states as a key-value store. Distributing the state to all the other control planes is a distributed data store.

The kubelet then takes it up and runs the cluster. It updates information with the cluster with the state of the node it’s on. It also starts and stops the container as directed by the scheduler.

The Kube-proxy exposes services for the outside world to interact with the cluster and routes network traffic to the proper resource on the node.

Kubernetes vs. Docker

Docker is a platform for containerization, while Kubernetes is a platform for executing and managing containers from various container applications. It’s not a matter of “either,” “or,” but instead, they complement each other.

For example, when you design a containerized application using Docker, as your application grows and develops layered architecture, it may be challenging to keep up with each layer’s resource needs. However, Kubernetes can take care of these containers and automate system health and failure management.

Docker can run without Kubernetes; however, using it with Kubernetes improves your app’s availability and infrastructure. In addition, it increases app scalability; for example, if your app gets a lot of traffic and you need to scale out to improve user experience, you can add extra containers or nodes to your Kubernetes cluster.

Running and Managing Kubernetes Containers in Production

Including Kubernetes in your tech stack has many benefits. However, there are risks, potential problems, and challenges that must be taken into account. If your company is using Kubernetes, you’ve probably run into some of these common issues.

Security Risks

Kubernetes’ complexity and accessibility make security a major concern. Multiple container deployments make vulnerability assessment more challenging, this, making hacking systems easier.

Some of the common security risks include misconfigured container images and exposed secrets, exploits on containers such as malware installation, crypto mining, host access, etc., runtime threats, compliance and audit failures.

Scalability Issues

Despite Kubernetes’ potential to enhance scalability and availability, it’s difficult to scale. This is because Kubernetes’ advanced microservices deployment creates a vast volume of data, making it tough to analyze and resolve issues.

While keeping tabs on all relevant services and data is essential for spotting issues and fixing them, many can struggle to do so. This makes scaling without automation hard. Other reasons include, integration errors such as compatibility issues between Kubernetes and other scaling tools, large application size with dynamic computing environment such as managing multiple clouds, cluster, user experiences and difficult installation processes.

Storage Issues

Larger enterprises, especially those with on-premises servers, have Kubernetes storage issues. One explanation is that they don’t use cloud storage which can cause memory problems. The availability and resilience needs for your application are another factor relating to this issue.

It’s important to have a solution that provides data replication, either at the storage level or the application level, if you want the application to continue running in the event of an availability zone failure.

Networking Issues

Networking is another challenge as distinct portions of an application may have different communication requirements that must be considered when defining how your containers will communicate. Plus, Kubernetes isn’t compatible with traditional networking. So, as the size of your deployment grows, so do the problems.

This includes complexity and multi-tenancy problems, for example, when deployed to several clouds or with mixed workloads from VMs and Kubernetes.

Monitor Kubernetes Performance with Sematext

Sematext Cloud is a cloud monitoring tool that handles Kubernetes monitoring and logging without requiring you to host any storage or monitoring infrastructure. It allows you to monitor pod, container, and host metrics while also collecting Kubernetes events. Sematext gives you insight into container-specific metrics like CPU, memory, disk I/O, and network usage that you can group in either pre-built or customized dashboards, making it easier and faster to point out problematic pods.

You can set up anomaly detection and alerts to get notified on both Kubernetes metrics and Kubernetes logs through various notification hooks, including email, Slack, or PagerDuty.

Sematext’s service auto-discovery feature automatically spots new containerized applications and instantly enables performance monitoring and log monitoring without any additional configuration. You can rest assured that as your containerized environment changes, any new service will be monitored.

Start the 14 free days trial and see how Sematext Cloud can help monitor your Kubernetes environment!

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