Running applications in containers solves consistency issues, but it introduces a new challenge: how to operate and coordinate those containers reliably across multiple servers. This includes handling deployments, restarting failed instances, distributing traffic, and scaling services based on demand. Doing this manually becomes impractical as systems grow.

Kubernetes is designed to handle these operational tasks. It provides a structured way to manage containerized applications across a cluster without relying on manual processes.

This article explains, in practical terms, what Kubernetes is used for and how it works under the hood. It covers its role in managing containerized workloads, outlines its architecture, and breaks down the core components that allow it to automate deployment, scaling, and recovery.

Understanding Kubernetes 

Kubernetes is a container orchestration platform that manages how containerized applications run across a cluster of nodes. These nodes can be physical servers, virtual machines, or cloud-based instances, all of which provide the CPU, memory, and storage needed to run your containers. Kubernetes lets teams define the desired state of their applications and continuously ensures the system matches that state without manual intervention.

What Kubernetes Is Used For in Practice

Kubernetes is used to handle several core operational tasks required to run modern applications:

• Application deployment and updates: Kubernetes manages application rollouts and updates across multiple containers. It supports controlled deployments, such as rolling updates, which replace containers gradually to avoid downtime.
• Running microservices architectures: It enables applications to be split into smaller, independent services. Kubernetes provides service discovery and internal networking, enabling these services to communicate reliably without fixed IP addresses or manual configuration.
• Service exposure and traffic routing: Kubernetes routes traffic to the correct containers using built-in load balancing. It ensures requests are distributed across healthy instances and can expose services internally or to external users.
• Automatic scaling: It adjusts the number of running containers based on metrics like CPU usage or traffic. This allows applications to handle spikes in demand without manual scaling.
• Self-healing and failure recovery: If a container fails or becomes unresponsive, Kubernetes automatically restarts or replaces it. If a node goes down, workloads are rescheduled to other available nodes.
• Resource management and scheduling: Kubernetes decides where containers should run based on available resources. It ensures efficient use of CPU and memory while preventing workloads from interfering with each other.

For teams looking to implement Kubernetes without managing the infrastructure themselves, at Delta, we provide a managed Kubernetes service with full support across deployment, configuration, scaling, and monitoring. Our experts handle cluster setup, automation, and ongoing maintenance, letting your team focus on building applications rather than managing infrastructure.

Stateful vs. Stateless Applications in Kubernetes

Kubernetes can run both stateless and stateful applications, but they’re managed differently. Stateless workloads (such as web frontends or API services) don’t store persistent data locally, so Kubernetes can scale them up or down, restart containers, and reschedule pods freely without losing important state. 

Stateful workloads (such as databases, queues, and systems that require stable identity or persistent storage) need additional guarantees, including durable volumes, controlled rollouts, and stable network identifiers, so data remains consistent even when pods are restarted or moved to other nodes.

Persistent Storage in Kubernetes: PVs and PVCs

To support stateful workloads, Kubernetes uses persistent storage abstractions that separate application configuration from the underlying storage system. A PersistentVolume (PV) is a cluster resource that represents real storage (for example, a cloud disk, SAN, or NFS share) provisioned by an administrator or dynamically by a storage class. A PersistentVolumeClaim (PVC) is a request for storage made by an application, specifying requirements like size and access mode. Kubernetes binds a PVC to a suitable PV and mounts it into pods, so data can persist even if containers restart or pods are rescheduled to different nodes.

Kubernetes Architecture Explained

A Kubernetes cluster consists of two main parts: the control plane and the worker nodes. The control plane manages the cluster, while worker nodes run the application workloads.

Control Plane

The control plane coordinates the cluster and ensures the system matches the desired state defined by users. Its key components include:

• API Server: the main entry point for commands and configuration changes.
• etcd: a distributed key-value store that keeps the cluster’s state.
• Scheduler: assigns workloads to specific worker nodes based on resource availability.
• Controller Manager: monitors cluster state and makes adjustments to maintain consistency.

Worker Nodes

Worker nodes provide the compute resources for running containers. Each node includes:

• Kubelet: ensures containers are running as specified.
• Kube-proxy: manages network routing for communication between containers.
• Container runtime: software like CRI-O or containerd that runs the containers themselves.

This separation of control and execution allows Kubernetes to scale applications reliably. If a node fails, the control plane detects the issue and reschedules workloads to healthy nodes, maintaining availability. Centralized management combined with distributed execution ensures both reliability and efficient resource utilization.

Core Kubernetes Components

Kubernetes uses a set of core objects to define, run, and expose applications. These components work together to manage how workloads are deployed, updated, and accessed within a cluster.

Pods

Pods are the smallest deployable units in Kubernetes. A pod represents a single instance of an application and can contain one or more containers that share the same network and storage. Containers within a pod communicate over localhost and are managed as a single unit. Pods are not permanent; they can be created, replaced, or terminated as the system adjusts to changes.

Nodes

Nodes are the machines where pods run. Each node provides the CPU, memory, and storage required for workloads. Kubernetes schedules pods onto nodes based on resource availability and constraints, ensuring efficient distribution across the cluster.

Deployments

Deployments define how applications should run and be updated. They manage pod creation and ensure that a specified number of instances are always running. Deployments also handle updates through controlled rollout strategies, allowing new versions to be introduced gradually without downtime.

Services

Services provide stable access to applications running in pods. Since pods can change over time, services act as a consistent endpoint that routes traffic to the correct pods. They also handle load balancing, distributing requests across multiple instances to maintain reliability and performance.

How Kubernetes Works in Practice

Kubernetes operates by continuously ensuring that the actual state of applications matches the desired state defined by developers. Here’s how this process works in practice:

1. Define the Desired State: Developers submit configurations through the API server, specifying details such as container images, number of replicas, and resource requirements. This becomes the desired state that Kubernetes works to maintain.
2. Schedule Workloads: The scheduler evaluates available nodes and assigns pods to the most suitable ones based on resource availability and constraints, ensuring efficient distribution across the cluster.
3. Deploy and Run Containers: Kubelets on each node start the containers and monitor their health. They report status back to the control plane, ensuring containers run as expected.
4. Maintain System State: Controllers continuously compare the actual state with the desired state. If a pod fails or a container crashes, new instances are created automatically to maintain the intended configuration.
5. Scale and Manage Traffic: Kubernetes distributes traffic across pods using Services to prevent overload and maintain consistent performance. For scaling, it can use the Horizontal Pod Autoscaler (HPA) to automatically increase or decrease the number of pod replicas based on metrics such as CPU, memory, or other application signals, helping the system respond to demand without manual intervention.
6. Self-Healing and Recovery: When nodes fail, or containers terminate unexpectedly, Kubernetes reschedules workloads to healthy nodes, ensuring applications remain available without manual intervention. 

Benefits of Using Kubernetes

• Efficiency: Automates routine tasks such as deployment, scaling, and monitoring, letting development teams focus on building features instead of managing infrastructure.
• Scalability: Dynamically adjusts workloads to handle traffic changes without manual intervention, maintaining performance and optimizing resource use.
• Portability: Runs applications consistently across different environments, making it easier to migrate workloads between cloud providers or on-premises systems. This reduces vendor lock-in and increases flexibility.
• Self-Healing: Automatically replaces failed containers or reschedules workloads from unavailable nodes, reducing downtime and improving system reliability.
• Extensibility and Ecosystem Support: Kubernetes integrates with a wide range of tools for logging, monitoring, networking, and security. Its extensible architecture allows teams to add custom controllers, operators, and automation to meet specific operational needs.

Conclusion

Kubernetes has transformed how modern applications are deployed and managed, providing automation, scalability, and reliability for containerized workloads. Understanding how it works and its key benefits is essential for teams building cloud-native applications and microservices.

At delta.bg, we offer a managed Kubernetes service that handles cluster deployment, configuration, and ongoing monitoring, allowing your team to focus on application development instead of infrastructure management. Our service ensures high availability, automatic scaling, and secure operations across public cloud, dedicated servers, or on-premise environments. For support or inquiries, contact us at sales@delta.bg or call 02 448 416 5, and our team will assist you.