When it comes to container orchestration, K8s (Kubernetes) has become a de facto standard for managing applications and infrastructure at scale across on-premise data centers and public clouds. But as organizations look to deploy containerized workloads to devices at the edge of their network or for Internet of Things (IoT) applications, the full Kubernetes distribution can be overkill.
This is where K3s comes in. Developed by Rancher Labs, K3s is a lightweight Kubernetes distribution designed specifically for resource-constrained edge and IoT environments.
In this article, we'll walk you through the key differences between K3s and the upstream Kubernetes project to help you understand when each makes the most sense for your application architecture and deployment needs.
What is K8s?
Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. It allows you to define your application's desired state and ensures that it runs consistently in a cluster of machines.
Kubernetes automates tasks such as load balancing, self-healing, and scaling, making it easier to manage and maintain container-based applications. It has become the industry standard for container orchestration, simplifying the management of complex, distributed applications. To learn more about how it works, check out this blog: Kubernetes Architecture Explained: Overview for DevOps Enthusiasts.
Why Use K8s
- Scalability and Resource Efficiency - Kubernetes enables easy scaling of your applications up or down based on demand. It optimizes resource allocation, ensuring efficient use of your infrastructure. This scalability and resource efficiency helps you save on cloud or hardware costs while providing a responsive user experience.
- High Availability and Reliability - Kubernetes offers built-in features for load balancing, self-healing, and automated failover. It ensures that your applications are highly available and reliable, even in the face of hardware or software failures. This results in reduced downtime and improved application stability.
- Rich Ecosystem - Kubernetes has a mature and extensive ecosystem with a variety of tools, plugins, and third-party solutions that can help with tasks like monitoring, logging, and continuous integration and deployment (CI/CD). This ecosystem provides more options for customization and integration, which is crucial for enterprise-level applications.
What is K3s?
At its core, K3s shares the same API and fundamental concepts as Kubernetes - it allows you to deploy and manage containerized applications across a cluster of machines using concepts like pods, services, deployments, and more. However, rather than being a monolithic distribution, K3s is built using a modular design that strips out unnecessary components for edge scenarios.
Modular design is a design approach that emphasizes the use of separate, interchangeable modules that can be combined in various ways to create a larger system. Monolithic distribution is a distribution approach that involves building a system as a single, self-contained unit.
K3s is built using a modular design that strips out unnecessary components for edge scenarios. This means that K3s does not include some of the features and integrations that are available in stock Kubernetes, such as cloud provider-specific services, storage drivers, and alpha resources. This makes K3s more lightweight, efficient, and easy to use than a monolithic distribution of Kubernetes. It also allows K3s to run on resource-constrained environments, such as edge computing and IoT devices.
Why Use K3s?
- Lightweight Design - By removing components like etcd, API server authentication plugins, and other security features that are less important at the edge, K3s has a much smaller overall footprint using around 70% less disk space and memory resources than a full K8s install. This makes it suitable for microservice devices and IoT gateways with limited hardware.
- Embedded Database - Rather than requiring an external etcd cluster for hosting cluster state, K3s embeds an etcd database right inside the K3s server process. This simplifies deployment without separate etcd servers or management.
- Self-Hosted Agents - Agent nodes in K3s run lightweight kubelet and kube-proxy services without requiring Docker or container runtimes. This reduces resource usage on edge nodes.
- Simple Deployment - K3s is designed to be installed via a single binary package and can be deployed on clusters of any size with simple commands. There's no need to build Kubernetes from the source or install complex Helm charts.
- Security Defaults - Common security features like RBAC, TLS between components, and secure service exposure are built-in and don't require additional configuration compared to Kubernetes.
So in summary, K3s retains the core Kubernetes API while stripping out unnecessary fat, integration points, and dependencies - making it suitable for running production workloads on resource-constrained edge devices in a similar fashion to full Kubernetes.
When To Use K3s vs Kubernetes
Now that we understand the key differences at an architectural level, let's dive into some specific use cases and scenarios to help determine when K3s or Kubernetes may be a better fit:
- IoT Devices: IoT applications involve connecting various devices and sensors to the internet and collecting data from them. These devices can range from smart home appliances to industrial machines to wearable gadgets. IoT applications often require real-time processing, analytics, and communication capabilities. K3s can enable these applications by running on the devices themselves or on nearby edge nodes and orchestrating the containers that power them. Small, low-power embedded or IoT gateways with limited RAM/CPU are the ideal targets for K3s due to its lightweight modular design. K8s would be overkill.
- Edge computing: Edge computing refers to running applications closer to the source of data or users, rather than in centralized servers or clouds. This can improve performance, latency, bandwidth, security, and privacy. Edge computing use cases include smart cities, autonomous vehicles, drones, video streaming, gaming, etc. K3s can run on these devices with minimal resources and provide a consistent Kubernetes experience across different environments.
- Small clusters: If you want to deploy containerized applications on 2-5 nodes, K3s can simplify the process and reduce the operational complexity of full Kubernetes without compromising the functionality. K3s can run on any Linux machine, even on low-powered devices, and provide a consistent and secure Kubernetes experience.
- Development/testing: K3s can help you quickly set up local test environments for your applications in seconds without taxing your laptop. K3s can run on your local machine or in a virtual machine and allow you to test your applications in a realistic Kubernetes environment. You can also use tools like k3d or k3sup to create and manage multiple K3s clusters with ease.
- Limited infrastructure: If you have limited networking, storage, or automation capabilities in your organization, K3s can make it easier for you to operate Kubernetes than managing a full K8s environment. K3s does not require any external dependencies or services to run and can work with local storage or network-attached storage. It also has built-in automation features, such as automatic certificate management, cluster registration, and backup/restore.
- Embedded platforms: K3s can fit your needs with its packaged, self-contained design on systems like single-board computers, network appliances, or other embedded devices. It does not require Docker or any other container runtime to run and can use containerd or cri-o instead. It also supports ARM architectures and can run on devices like Raspberry Pi or Jetson Nano.
- Existing Kubernetes skills: If you already have a team that understands Kubernetes concepts and tools, K3s can be a low-effort migration option for you. K3s uses the same APIs, primitives, and tools as Kubernetes and works seamlessly with other Kubernetes distributions and platforms. You can also use Helm charts, kubectl commands, and custom resource definitions with K3s as you would with Kubernetes
In contrast, full Kubernetes distribution makes more sense for:
- Large Production Clusters: Once you exceed 5 nodes, the extra features in Kubernetes like upgrade handling, Federation, Kubernetes Dashboard, etc. become more compelling vs K3s limited capabilities.
- Cloud Native Applications: For stateful, complex microservices and cloud-native apps, Kubernetes APIs, operational functions, and support for features like Istio/Prometheus are better aligned. This means that Kubernetes offers more capabilities and integrations that can help you develop, deploy, and manage your cloud-native applications more effectively and efficiently.
- Significant GPU/Hardware Resources: When nodes have substantial RAM, multiple CPUs, SSDs, etc., Kubernetes does a great job of optimizing resource scheduling.
- Demanding Workloads: Critical production apps with stringent high availability requirements may prefer Kubernetes battle-hardened resilience over K3s targeted simplicity.
Ease of Operations of K8s vs. K3s
Beyond initial deployment, another key advantage of K3s over K8s is its focus on simplifying day-to-day management and operations of the Kubernetes cluster compared to the upstream project.
Some highlights include:
- Single Binary Updates - K3s upgrades between versions use a simple binary package. On the other hand, Kubernetes requires complex in-place upgrades of multiple components.
- Integrated Configuration - All cluster configuration is stored locally in an SQLite database rather than needing distributed config maps and secrets stored across Master/Agent nodes.
- Self-Healing Cluster - The control plane (master) is self-hosted rather than having a dedicated control-plane node. This means that if a node goes down, the control plane can start right back up on another node without losing any data or configuration. This makes K3s more resilient and fault-tolerant than Kubernetes, which relies on having a backup or a replica of the control plane node.
- No External Dependencies - K3s does not require any external dependencies or services to run, such as etcd or Docker. K3s has fewer external services to monitor and maintain than K8s, which relies on etcd as the backend datastore and Docker or other container runtimes as the execution engine.
- TLS Certificates as a Service - K3s simplifies the security and encryption of your applications and resources than K8s, which requires you to generate and manage your certificates or use third-party tools.
- Embedded Provisioning - K3s makes it easier for you to add or remove nodes from your cluster. K8s, on the other hand, requires you to install and configure the Kubernetes components on each node manually or use external provisioning tools.
- Easy Backups - K3s can efficiently create full database backups using straightforward snapshots because it relies on SQLite or MySQL as its backend data store. In contrast, K8s necessitates the backup of multiple components and crucial data, including etcd, config maps, secrets, and other elements, which can be a more intricate and time-consuming process.
The simplified operational model was a core design philosophy for K3s and dramatically reduced the day-to-day toil of managing Kubernetes in edge/IoT scenarios compared to a full upstream installation. The tradeoff is reduced scale and more advanced features - but for many edge workloads, these compromises are worth it for superior usability.
Check out our K3s playground at Kubernetes 1.24(K3s) Playground. A great place to learn and practice creating and managing deployments.
Disadvantages of K3s
K3s is not without its drawbacks, such as:
- Less feature-rich: K3s does not include some of the features and integrations that are available in stock Kubernetes, such as cloud provider-specific services, storage drivers, and alpha resources. This limits some of the functionalities and customizations that you can achieve with K8s, such as leveraging the benefits of cloud computing, using different types of storage volumes, or testing new functionalities or innovations.
- Less mature: K3s is relatively new compared to K8s, which has been around since 2014. This means that K3s may have less community support, documentation, and stability than K8s.
- Cloud providers: K3s does not support any cloud provider-specific services, which means that you cannot use them to enhance the capabilities of Kubernetes. This makes it harder for you to migrate your applications to the cloud or use the cloud services that you need with K3s.
- Security: K3s has some security challenges and risks that are different from K8s. For example, K3s uses a different backend datastore, hosts the master components on any node, and does not include some of the security tools and frameworks that are available for K8s. This makes K3s more vulnerable to threats and attacks than K8s.
The key differences between K3s and K8s are;
In summary, while K3s and Kubernetes share the core Kubernetes API and concepts, K3s was purpose-built from the ground up with a modular, lightweight design optimized specifically for edge, IoT, and containerized microservice applications running on resource-constrained devices.
For organizations already comfortable with Kubernetes - K3s allows you to leverage existing skills and tooling for edge scenarios without compromise. And for those newer to containers, K3s streamlined deployment and operations paradigm lowers the barrier significantly compared to starting off with full Kubernetes.
So in short - K3s is prefered for edge/IoT installations under 5 nodes, embedded/constrained infrastructure, or where simplicity trumps scale. Kubernetes prevails once your cluster and applications grow beyond those parameters.
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