Kubernetes, also known as K8s, is an open source Container orchestration platform. It is designed to automate deploying, scaling and operations of containerized applications. It groups containers that logically works as an application and further becomes easier to manage them together and to discover them. Kubernetes was originally designed by Google and is now maintained by the Cloud Native Computing Foundation. Kubernetes has become a standard in the world of software development and deployment. Here are some reasons why everyone should consider learning it:

  • Industry Adoption: Kubernetes is widely adopted by the industry. Many companies, from startups to tech giants, use Kubernetes for their production workloads. This means that knowing Kubernetes can open up a lot of job opportunities.
  • Portability and Flexibility: Kubernetes works with any type of container runtime and can run on any platform – be it public cloud, private cloud, or on-premise servers. This makes it a versatile tool that can fit into any infrastructure.
  • Scalability: Kubernetes can handle the automatic scaling of applications based on the workload. This is a crucial feature for applications that need to handle varying loads at different times.
  • Community and Ecosystem: Kubernetes has a vibrant community and ecosystem. There are numerous tools built around Kubernetes, and the community is always there to help.
  • Career Growth: As more and more companies adopt Kubernetes, the demand for professionals who understand Kubernetes is on the rise. Learning Kubernetes can give a significant boost to your career.
  • Future of Cloud Computing: Kubernetes is becoming a fundamental part of cloud computing. Understanding Kubernetes will help you stay relevant in the rapidly evolving cloud landscape.

Remember, while Kubernetes is powerful, it also comes with a steep learning curve. But don’t let that discourage you. The investment in learning Kubernetes can pay off significantly in your personal and professional development.

Happy learning! 

What problem does Kubernetes Solve?

In the era of cloud computing, applications are often deployed in a containerized environment for better resource utilization. However, managing these containers manually in a production environment is a complex task. This is where Kubernetes comes in. Imagine you are Slack, millions of active users every second and the no. of containers you have to manually manage to serve seemlessly.

Kubernetes solves the problem of orchestration. It automates the process of managing hundreds of containers in a production environment. Whether you are Facebook or Google, K8s can solve your infrastructure management issues, especially w.r.t containers management. It takes care of scheduling, deploying, and scaling of applications based on user-defined policies. It also ensures high availability of applications, regardless of the complexity of their setup.

Kubernetes basically abstracts the infrastructure as a code, so it becomes easier to manage. We will look into it in the later part of this tutorial.

Difference Between Kubernetes and Docker

While both Kubernetes and Docker are crucial to containerized applications, they serve different purposes and are not direct competitors.

Docker is a platform that enables developers to build, package, and distribute applications in containers. It provides an isolated environment for applications to run, which makes it easier to manage dependencies and deliver software reliably. Due to the sudden change in docker licensing and heavy footprints, it is advisable to look for alternatives to Docker like Podman, ContainerD, Rancher Desktop, Buildah, OrbStack and etc.

On the other hand, Kubernetes is a container orchestration platform. While Docker focuses on the lifecycle of individual containers, Kubernetes is concerned with clusters of containers. It helps manage services that are composed of multiple containers and run across multiple machines.

Key Features of Kubernetes

Kubernetes comes with a host of features that makes it a popular choice for container orchestration:

  1. Service Discovery and Load Balancing: Kubernetes can expose a container using the DNS name or their own IP address. If traffic to a container is high, Kubernetes can load balance and distribute the network traffic to stabilize the deployment.
  2. Storage Orchestration: Kubernetes allows you to automatically mount a storage system of your choice, such as local storage, public cloud providers, and more.
  3. Automated Rollouts and Rollbacks: You can describe the desired state for your deployed containers using Kubernetes, and it can change the actual state to the desired state at a controlled rate.
  4. Automatic Bin Packing: You provide Kubernetes with a cluster of nodes that it can use to run containerized tasks. You tell Kubernetes how much CPU and memory each container needs, and it fits containers onto your nodes to make the best use of your resources.
  5. Self-Healing: Kubernetes restarts containers that fail, replaces and reschedules containers when nodes die, kills containers that don’t respond to your user-defined health check, and doesn’t advertise them to clients until they are ready to serve.

Key Components of Kubernetes:

At the heart of Kubernetes lies a set of key components that work together to provide its robust functionality. In this article, we’ll explore the core components of Kubernetes, understanding their roles and interactions within the Kubernetes ecosystem. Below image just shows the same.

Kubernetes Architecture
Kubernetes Architecture

Kubernetes Key components can be groups into 4 parts:

  1. Master Components (Control Plane)
  2. Node Components (Worker Nodes)
  3. Networking Components (Addons Components)
  4. Storage Components (Cloud Infra specific)

1. Master Components:

  • API Server: The central management point of Kubernetes, the API server exposes the Kubernetes API, which is used by both users and other components to interact with the cluster.
  • Scheduler: Responsible for scheduling pods (the smallest deployable units in Kubernetes) onto nodes based on resource availability, constraints, and other policies.
  • Controller Manager: Manages various controller processes that regulate the state of the cluster, such as node controller, replication controller, and endpoint controller.
  • etcd: A distributed key-value store that serves as Kubernetes’ backing store for all cluster data, including configuration details, state, and metadata.
  • Cloud Controller Manager (CCM): The CCM interacts with the cloud provider’s APIs to manage resources such as virtual machines, load balancers, and storage volumes. It translates Kubernetes API calls into actions specific to the underlying cloud infrastructure. By separating cloud-specific logic into the Cloud Controller Manager, Kubernetes can remain cloud-agnostic at its core, making it easier to support multiple cloud providers.

2. Node Components:

  • Kubelet: The primary node agent responsible for managing pods, ensuring they are running and healthy. Kubelet communicates with the API server to receive instructions for pod deployment and management.
  • Kube-Proxy: Maintains network rules on nodes, enabling communication between different pods and external network resources. It also provides load balancing for services exposed to the cluster.
  • Container Runtime: The software responsible for running containers, such as Docker or containerd, installed on each node. Kubernetes supports various container runtimes, allowing flexibility in deployment.

3. Networking Components:

  • Pod Network: A network overlay that enables communication between pods across different nodes in the cluster. Popular pod network solutions include Flannel, Calico, and Weave.
  • Service: An abstraction that defines a logical set of pods and a policy by which to access them. Kubernetes services enable load balancing, service discovery, and internal communication within the cluster.

4. Storage Components:

  • Persistent Volumes: Abstractions that allow pods to access durable storage independent of the underlying storage infrastructure. Persistent volumes decouple storage from pod lifecycle, enabling data persistence across pod restarts.
  • Storage Classes: Defines the storage provisioner and parameters for dynamically provisioning persistent volumes. Storage classes enable dynamic provisioning and management of storage resources within the cluster.

Popular Cloud Offerings

There are several cloud providers that offer managed Kubernetes services, each with its own unique features and benefits. Here are some of them:

  • Google Kubernetes Engine (GKE): GKE closely follows the latest changes in the Kubernetes open-source project.
  • Azure Kubernetes Service (AKS): AKS is known for rich integration points to other Azure services.
  • Amazon Elastic Kubernetes Service (EKS): EKS is a strong option due to AWS’s robust infrastructure.
  • DigitalOcean Kubernetes (DOKS): DOKS is a newer Kubernetes service in the market.
  • IBM Cloud Kubernetes Service: IBM’s Kubernetes service is best for enterprise applications.
  • Oracle Container Engine for Kubernetes (OKE): OKE is Oracle’s managed Kubernetes service.
  • Alibaba Cloud Container Service for Kubernetes (ACK): ACK is Alibaba’s managed Kubernetes service.
  • Linode Kubernetes Engine (LKE): LKE is Linode’s managed Kubernetes service.

Each of these services provides its own set of features, pricing, and integrations, so the best choice depends on your specific needs and the nature of your projects. It’s always a good idea to understand the trade-offs and choose the right service for the job. Further reading: Battle of the 4 best Kubernetes Cloud

Exploring Advantages and Limitations of Kubernetes

Advantages of Kubernetes

  • Container Orchestration: Kubernetes excels in automating the deployment, scaling, and management of containerized applications. It abstracts away the underlying infrastructure complexities, allowing developers to focus on application logic rather than infrastructure management.
  • Scalability and Flexibility: Kubernetes enables seamless scaling of applications both horizontally and vertically. With features like auto-scaling, applications can dynamically adjust their resource consumption based on demand, ensuring optimal performance and cost efficiency.
  • High Availability: Kubernetes ensures high availability by automatically detecting and replacing failed containers or nodes. Through features like replication controllers and self-healing capabilities, it maintains desired application states even in the face of failures.
  • Declarative Configuration: Kubernetes embraces a declarative approach to infrastructure management, where desired state configurations are specified in YAML or JSON manifests. This simplifies deployment and promotes consistency across environments.
  • Service Discovery and Load Balancing: Kubernetes provides built-in mechanisms for service discovery and load balancing, making it easy to expose services internally or externally and distribute traffic across application instances.
  • Resource Utilization Optimization: Kubernetes optimizes resource utilization through features like bin-packing and resource quotas, ensuring efficient use of underlying infrastructure resources.

Limitations of Kubernetes

  1. Complexity: While Kubernetes abstracts away many infrastructure complexities, it introduces its own learning curve. Setting up, configuring, and managing Kubernetes clusters can be complex, requiring specialized knowledge and expertise.
  2. Resource Overhead: Kubernetes imposes additional resource overhead for cluster management, including etcd, kube-controller-manager, kube-scheduler, and other components. This overhead may impact the overall resource utilization efficiency of the cluster.
  3. Networking Challenges: Networking in Kubernetes can be challenging, especially in hybrid or multi-cloud environments. Configuring and managing network policies, ingress controllers, and service meshes require careful planning and expertise. We make use of Plugins like Flannel, Calico, Cilium etc to overcome the networking challenges.
  4. Monitoring and Debugging: Monitoring and debugging applications in Kubernetes can be complex due to the distributed nature of containerized workloads. Tools and practices for logging, monitoring, and tracing need to be carefully implemented to ensure visibility into application performance and health.
  5. Storage Orchestration: While Kubernetes provides support for persistent storage, storage orchestration can be challenging, especially in stateful applications. Integrating with various storage providers and managing data persistence requires careful consideration.
  6. Vendor Lock-In: Adopting Kubernetes often involves relying on specific cloud providers or distributions, potentially leading to vendor lock-in. Organizations need to carefully evaluate the trade-offs between flexibility and vendor-specific features when choosing Kubernetes solutions


In conclusion, Kubernetes is a powerful tool for container orchestration. It provides a robust platform for managing and scaling containerized applications in any environment. However, it’s not a silver bullet and should be used judiciously based on the specific requirements of the project. It’s always important to understand the trade-offs and choose the right tool for the job.

By |Last Updated: April 22nd, 2024|Categories: Kubernetes|