Why Auto-Scaling and Deployment of Applications is Easier Using Kubernetes

Speed and ease of use are two key requirements of customers today. Modern businesses leverage cloud-native technologies to meet these needs by facilitating the development of scalable applications in dynamic environments leveraging cloud architecture such as microservices, containers, declarative APIs, service meshes, and immutable infrastructure. As they can be loosely coupled, they provide resilience and are easy to manage. Automation further allows high-impact changes to be made as and when needed with minimum disruption.

One of the key factors driving the success of the cloud application is the use of containers, which are light, fast, and portable, unlike virtual machines. They improve the testability of the applications, are more secure, and allow workloads to be isolated inside cost-effective clusters. This helps with faster development and deployment to meet the ever-changing needs of the customers.

To leverage containers successfully, developers need a managed container platform such as Kubernetes from Google. Kubernetes enables the building of customized platforms that align with the organization’s governance needs regarding project creation, nodes being used, and the libraries and repositories that can be tapped by providing a governed and secure framework.

Kubernetes refers to an open-source model that helps create and scale reliable apps and services in a secure environment and adds value through innovation using standardized plugins and extensions. This is expected to help the global Kubernetes solutions market grow from USD 1747.20 million in 2021 at a CAGR of 17.70% to reach USD 5467.40 million by 2028.

Automating Scaling and Deployment

Kubernetes or K8s automate the deployment and management of cloud-native applications on public cloud platforms or on-premises infrastructure and orchestrate containerized applications to run on a cluster of hosts. Some of the functions of Kubernetes include:

• Distributing application workloads across a Kubernetes cluster
• Automating dynamic container networking needs
• Allocating storage and persistent volumes to running containers
• Enabling automatic scaling
• Maintaining the desired state of applications
• Providing resiliency

Kubernetes Architecture

The applications are encapsulated in the containers in a portable form, which makes it easy to deploy. The Kubernetes architecture is made up of clusters that include a minimum of one control plane and one worker node and are designed to run containerized applications.

The control plane’s responsibilities include exposing the Kubernetes API through the API server and managing the nodes contained in the cluster. It manages the cluster and identifies and responds to cluster events.

Kubernetes Pod is the smallest unit of execution for an application in Kubernetes, has one or more containers, and runs on worker nodes.

Kubernetes allows two kinds of scaling:

Horizontal Scaling: Horizontal Pod Autoscaler allows the adding of new nodes or increasing the replicated count of pods to the existing cluster of computing resources. The number of pods needed is calculated based on the metrics specified at the outset such as CPU and RAM consumption or other custom metrics.

Vertical Scaling: In this, attributed resources are modified for each node in the cluster, and the resource requests and limits are adjusted as per current application requirements using Vertical Pod Autoscaler.

Container Orchestration: Kubernetes container lifecycle management encompassing provisioning, deployment, scaling, networking, and load balancing is enabled through orchestration. This automates the tasks essential for running containerized workloads and services.

Kubernetes Features

Some of the key features of K8 that enable orchestrating containers across multiple hosts, automating cluster management, and optimizing resource utilization include:

Auto-scaling: It enables the automated scaling up and down of containerized applications and their resources based on need.

Lifecycle Management. It enables automated deployments and updates, rollback to earlier versions, pausing or continuing a deployment, and so on.

Declarative Model: When the desired state is declared, K8s maintain that state and recover in case of failures by working in the background.

Self-healing and Resilience: Application self-healing is made possible by automated placement, restart, replication, and scaling.

Persistent Storage: Storage can be mounted and added dynamically.

Load Balancing: Several types of internal and external load balancing is supported for diverse needs.

DevSecOps Support: Kubernetes facilitates DevSecOps to improve developer productivity, simplify and automate container operations across clouds, and integrate security through the container life cycle.

Some of the key benefits of Kubernetes include:

• Faster time to release by simplifying the development lifecycle
• Cost-effectiveness through automatic modulation of resource allocation
• Making applications scalable and available

Advantage Indium

Indium Software is a cutting-edge cloud engineering company with a team of experts that can help with the migration and modernization of applications. Developing microservices and containerizing applications is one of our strengths. We are a Kubernetes solution provider, working closely with our customers and developing cloud-native applications and modernizing apps using the Kubernetes platform.

Our DevSecOps expertise further helps us to leverage Kubernetes for faster development and deployment of applications with security integrated into the process. Our experts analyze and understand the business needs and facilitate smooth management of clusters for scaling up and down based on the need for greater availability at lower costs.