Kubernetes

 What is Kubernetes (k8s)?

Kubernetes is an open-source Container Management tool that automates container deployment, container scaling, descaling, and container load balancing (also called a container orchestration tool). It is written in Golang and has a vast community because it was first developed by Google and later donated to CNCF (Cloud Native Computing Foundation). Kubernetes can group ‘n’ number of containers into one logical unit for managing and deploying them easily. It works brilliantly with all cloud vendors i.e. public, hybrid, and on-premises. 

Benefits of Using Kubernetes

1. Automated deployment and management

2. Scalability

3. High availability

4. Cost-effectiveness

5. Improved developer productivity

 

Features of Kubernetes

1. Automated Scheduling– Kubernetes provides an advanced scheduler to launch containers on cluster nodes. It performs resource optimization.

2. Self-Healing Capabilities– It provides rescheduling, replacing, and restarting the containers that are dead.

3. Automated Rollouts and Rollbacks– It supports rollouts and rollbacks for the desired state of the containerized application.

4. Horizontal Scaling and Load Balancing– Kubernetes can scale up and scale down the application as per the requirements.

5. Resource Utilization– Kubernetes provides resource utilization monitoring and optimization, ensuring containers are using their resources efficiently.

6. Support for multiple clouds and hybrid clouds– Kubernetes can be deployed on different cloud platforms and run containerized applications across multiple clouds.

7. Extensibility– Kubernetes is very extensible and can be extended with custom plugins and controllers.

8. Community Support- Kubernetes has a large and active community with frequent updates, bug fixes, and new features being added.

 

Use cases of Kubernetes in real-world scenarios

Following are the some of the use cases of kubernetes in real-world scenarios

• E-commerce: You deploy and manage the e-commerce websites by auto scaling and load balancing you can manage the millions of users and transactions.

• Media and entertainment: You can store the static and dynamic data can deliver it to the across the world without any latency to the end users.

• Financial services: kubernetes is well suited for the financial application because of the level of security it is offering.

• Healthcare: You can store the data of patient and take care the outcomes of the health of patient.

 

Kubernetes Architecture Overview

Kubernetes follows a master-slave architecture. Here’s a simple explanation:

• Master Node: The master node is the control plane of Kubernetes. It makes global decisions about the cluster (like scheduling), and it detects and responds to cluster events (like starting up a new pod when a deployment’s replicas field is unsatisfied).
• Worker Nodes: Worker nodes are the machines where your applications run. Each worker node runs at least:
  - Kubelet is a process responsible for communication between the Kubernetes Master and the node; it manages the pods and the containers running on a machine.
  - A container runtime (like Docker, rkt), is responsible for pulling the container image from a registry, unpacking the container, and running the application.

 

Master Node (Control Plane) Components

The master node, also known as the control plane, is responsible for managing the Kubernetes cluster. It contains several key components:

API Server: The API server (kube-apiserver) is the entry point for all API requests. It processes REST operations, validates and configures data for API objects, and serves as the hub for all communication between the components.

Controller Manager: The controller manager (kube-controller-manager) runs controllers that regulate the state of the cluster. Controllers ensure that the current state matches the desired state (e.g., managing replicas of a pod, handling node failures).

Scheduler: The scheduler (kube-scheduler) is responsible for assigning newly created pods to nodes based on resource requirements, constraints, and policies.

etcd: etcd is a distributed key-value store used to store all the cluster data. It holds the configuration data, state, and metadata of the cluster.

Cloud Controller Manager: If the cluster is running in a cloud environment, the cloud controller manager interacts with the cloud provider's API to manage resources and services.

Worker Nodes

Worker nodes are the machines where containerized applications run. Each worker node contains several critical components:

• Kubelet: The kubelet is an agent that runs on each worker node. It ensures that containers are running as specified in the pod specifications and reports the status of the node back to the master.
• Kube-Proxy: The kube-proxy maintains network rules on each node to allow communication between pods and services. It manages network routing and load balancing.
• Container Runtime: The container runtime is the software responsible for running containers. Kubernetes supports several runtimes, including Docker, containerd, and CRI-O. 

Cluster Components

• Pods: The smallest and simplest Kubernetes object, a pod represents a single instance of a running process in the cluster. Pods can contain one or more containers.
• Services: Services provide a stable IP address and DNS name to access a set of pods. They abstract away the complexity of networking and load balancing.
• Deployments: Deployments manage the creation and updating of pods and ensure the desired number of replicas are running.
• ReplicaSets: ReplicaSets ensure that a specified number of pod replicas are running at any given time.
• Namespaces: Namespaces provide a way to divide cluster resources between multiple users or teams.

 Add-ons

Kubernetes supports various add-ons to enhance functionality and provide additional services:

·       DNS: Kubernetes provides a built-in DNS service for service discovery within the cluster, allowing applications to find each other by name.

·       Dashboard: The Kubernetes Dashboard is a web-based UI for managing and visualizing the cluster.

·       Logging and Monitoring: Tools like Prometheus for monitoring and Fluentd for logging can be integrated to provide observability and metrics

Network and Storage

·       Network: Kubernetes provides a flat network model where all pods can communicate with each other directly. Networking in Kubernetes involves concepts like CNI (Container Network Interface) plugins, network policies, and service discovery.

·       Storage: Kubernetes supports various storage options including Persistent Volumes (PVs) and Persistent Volume Claims (PVCs) to manage storage resources.

Kubernetes CLI Tools

1. kubectl: The primary CLI tool for Kubernetes; it allows managing applications and clusters. With Kubectl, you can inspect cluster resources, create, update, delete components, and much more.
2. Helm: A Kubernetes package manager streamlining Kubernetes applications’ installation and management. It manages Kubernetes applications through Helm Charts, which define, install, and upgrade complex Kubernetes applications.
3. Skaffold: A command-line tool that facilitates continuous development for Kubernetes applications. It automates the workflow for building, pushing, and deploying applications.
4. Customize: A Kubernetes native configuration management tool allows customized Kubernetes deployments without needing templating engines. It supports multiple build strategies like strategic merge patches, JSON 7001 patches, and more.
5. Kubeval: A tool to validate your Kubernetes configuration files, ensuring they are valid and in the correct format. It can be run locally and in your CI/CD, ensuring configurations are correct before deployment.

Kubernetes monitoring tools

1.      Sematext Monitoring: A real-time monitoring solution for traditional and microservice-based applications deployed on Kubernetes, featuring customizable alerts, analytics reports, and dashboards. It also provides Kubernetes Audit integration and infrastructure mapping.

2.      Kubernetes Dashboard: A simple web-based UI addon for Kubernetes clusters that provides basic metrics related to memory and CPU usage statistics across nodes and the ability to monitor the health of workloads.

3.      Prometheus: A popular open-source tool used to monitor Kubernetes, Prometheus utilizes a powerful multidimensional data model, a flexible query language (PromQL), and a built-in real-time alerting mechanism. It follows a pull model for metrics.

4.      Grafana: It is commonly used with Prometheus for monitoring and visualizing metrics. It offers powerful visualization options for your Kubernetes cluster data.

5.      Jaeger: You can trace and monitor complex microservices–oriented architecture. It helps to troubleshoot and find bottlenecks in the system.

Kubernetes deployment tools

1. Jenkins: Although not explicitly cited in the search result, Jenkins is an open-source automation tool that provides plugins for building, deploying, and automating projects. It enables the implementation of a continuous integration or continuous delivery (CI/CD) pipeline for Kubernetes.
2. Spinnaker: It is a multi-cloud continuous delivery platform that supports deploying to Kubernetes, AWS, GCP, and more. It supports advanced deployment strategies like canary and blue/green deployments for higher availability.
3. io: A competent Kubernetes CD tool that automates the deployment of services to Kubernetes. It detects new images, observes image repositories, updates configurations, and ensures every update gets correctly deployed to your cluster.