Kubernetes, also known as K8s has changed how modern software applications are deployed, managed and scaled. As a leading open-source container orchestration platform, it allows organisations to run containerised applications reliably in diverse environments such as on-premises, in the cloud or hybrid. In our latest article, we discuss everything you need to know about Kubernetes Architecture.
The architecture of Kubernetes is built to handle the challenges of distributed systems, ensuring scalability, fault tolerance and high availability. Its design adopts the master-worker model, dividing responsibilities between the control plane and nodes (worker machines). This segregation enables Kubernetes to manage large-scale applications while maintaining operational simplicity.
The key concepts of Kubernetes Architecture are as mentioned below:
The control plane in Kubernetes oversees and coordinates every operation within the cluster. It maintains global states, enforces policies and manages resource scheduling and updates. These components ensure that Kubernetes clusters operate efficiently and that desired states are achieved. Let’s explore each control plane component.
The Kubernetes API Server acts as the front end for the control plane and serves as the primary interface for all cluster interactions.
etcd is the distributed key-value store integral to Kubernetes for maintaining the cluster's state.
This component is responsible for the operational logic of Kubernetes, managing the control loops that monitor and maintain cluster health.
The Kubernetes scheduler determines which node a newly created pod should run on based on factors like:
While the control plane orchestrates and monitors, worker nodes execute the actual workloads. Every worker node includes specific components that ensure proper container operation and cluster interaction:
The kubelet is the primary agent running on every worker node. It ensures the containers specified in the pod definitions are running as expected.
The kube-proxy is the networking component on worker nodes that maintains efficient communication within the cluster. The key features of Kube-proxy include:
This component is essential for running containers on Kubernetes nodes. The container runtime is responsible for managing container lifecycle events like creating, starting, and stopping containers.
The Kubernetes networking model ensures seamless communication for containerised applications with scalability and reliability. Each pod gets a unique IP address, enabling direct communication without NAT. Key abstractions like Services provide stable IPs, DNS names, and load-balancing, while kube-proxy handles routing. Ingress resources manage incoming HTTP/S traffic, enabling URL-based and domain-specific access. Network Policies enforce security with granular control over traffic, reducing risks. Kubernetes supports pluggable CNI drivers like Calico and Flannel for advanced networking features. Its flexible, robust model integrates with cloud-native and on-premises environments, simplifying deployment and fostering scalable, secure, and high-availability communication for modern workloads.
Kubernetes excels at managing both ephemeral and persistent storage, offering robust solutions for various application needs. While containers are inherently stateless, many applications require durable, reliable storage. Kubernetes meets these requirements by providing an abstracted, scalable framework for storage management, enabling workloads to seamlessly persist and access data.
Kubernetes supports two primary types of storage:
Ephemeral Storage: This is tied to the lifecycle of a pod or container. Storage types such as emptyDir or hostPath are deleted as soon as the pod is terminated. Ephemeral storage is ideal for temporary data like cache or session data.
The Key Components of Kubernetes Storage include:
Kubernetes provides several abstractions for deploying, scaling, and managing workloads. These abstractions help users define how applications should be deployed and interacted with across their clusters. The main workload abstractions are Deployments, StatefulSets, DaemonSets, Jobs, and CronJobs.
Deployments: Deployments manage stateless applications by creating and scaling Pods to maintain replicas, handling rolling updates without downtime, and re-creating failed Pods.
StatefulSets: StatefulSets manage stateful applications, ensuring Pods have stable identities, network names, and persistent storage, crucial for databases and similar applications.
DaemonSets: DaemonSets ensure one Pod runs on each cluster node, ideal for system-level applications like monitoring and logging, automatically scheduling Pods on new nodes.
Jobs and CronJobs: Jobs handle batch processing tasks, ensuring completion by a set number of Pods. CronJobs runs these tasks periodically, useful for backups and scheduled processing.
Kubernetes has multiple security layers to protect workloads, manage access, and defend against threats, ensuring both infrastructure and applications are secure.
Role-Based Access Control (RBAC): RBAC is a key security mechanism in Kubernetes, defining roles and permissions to control access to resources. It grants access based on the least privilege principle, ensuring only authorised actions. Roles set permissions, and role bindings link them to users or service accounts, managing access to sensitive data.
Network Policies: Kubernetes Network Policies secure Pod communications by controlling which Pods can interact with each other and external services. They define traffic rules, limiting unauthorised access and providing granular security.
Pod Security Standards (PSS): PSS offers guidelines for Pod security configurations at baseline, restricted, and privileged levels. It enforces security settings, limiting privileged mode usage to reduce risks.
Secrets Management: Kubernetes manages sensitive data like API keys and passwords with its Secrets resource, stored encrypted in etcd. Service accounts can access specific Secrets, ensuring secure data handling.
Audit Logging and Monitoring: Kubernetes audit logging tracks cluster operations for security and compliance, recording API server interactions. It supports tools like Prometheus for monitoring cluster activity and health.
Kubernetes excels at scaling and ensuring high availability for containerised workloads, which is crucial for production environments where uptime and performance affect user experience and business success. It achieves this through autoscaling, reliable monitoring, and fault-tolerant configurations.
Horizontal Pod Autoscaling (HPA): HPA automatically adjusts the number of Pods in a Deployment or ReplicaSet based on CPU usage or custom metrics, scaling up or down to meet demand.
Vertical Pod Autoscaling (VPA): VPA adjusts CPU and memory resources for individual Pods, increasing limits as needed, especially for workloads that can't scale horizontally.
Cluster Autoscaler: This tool manages node availability, adding nodes when demand increases and removing them when underutilised to save resources.
Replication and High Availability: Kubernetes uses replicas across nodes to ensure high availability, allowing for seamless recovery if a Pod or node fails.
Monitoring and logging are crucial for maintaining Kubernetes clusters' health and security. Kubernetes offers tools to track performance, troubleshoot, and ensure operational excellence, allowing teams to address issues proactively.
Kubernetes monitoring involves tracking the performance of clusters, nodes, Pods, and containers to ensure everything is running smoothly. There are several key components and best practices for Kubernetes monitoring:
Logging is crucial for troubleshooting and auditing, offering insights into applications and clusters. While Kubernetes lacks default centralised logging, it provides tools to simplify it.
Hyperstack offers on-demand provisioning of managed Kubernetes clusters, enabling you to deploy and manage containerised applications quickly and efficiently. Like other major cloud providers, all you need to do is specify the target Kubernetes version, node type, and a few basic parameters. The platform handles the rest, delivering a seamless and hassle-free experience.
Currently in Beta testing, Hyperstack's on-demand Kubernetes is accessible through our API guide. Ready to get started? Check out the API Guide below!
Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerised applications.
The control plane oversees cluster operations, managing resources, enforcing policies, and ensuring the desired state of applications.
Pods are the smallest deployable units in Kubernetes, containing one or more containers that share storage, networking, and runtime settings.
The API server is the central interface for all cluster interactions, processing requests and maintaining communication with backend systems like etcd.
A Persistent Volume (PV) is a storage resource in Kubernetes that provides reliable data persistence, independent of pod lifecycles.