> ## Documentation Index
> Fetch the complete documentation index at: https://docs.coreweave.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction to CoreWeave Kubernetes Service (CKS)

> High-performance managed Kubernetes on bare metal with DPU isolation and per-cluster VPCs

**CoreWeave Kubernetes Service (CKS)** offers a managed Kubernetes service that lets you run clusters on [bare metal servers](/products/cks/clusters/introduction) in CoreWeave Cloud. CKS is built to offer granular control, high performance, enhanced security, and high reliability, as well as high visibility into cluster metrics. CKS is designed to serve as a managed workload orchestration solution for High-Performance Computing (HPC) workloads, taking advantage of bare-metal performance and HPC networking.

On CKS, clusters use <Tooltip tip="A Data Processing Unit (DPU) is a 'computer-in-front-of-a-computer', fully isolated from the host's CPU, that provides network and other functions." cta="Learn more" href="/glossary#data-processing-unit-dpu">Data Processing Unit (DPU)</Tooltip> technology to provide enhanced isolation and performance. Each CKS cluster operates within its own private Virtual Private Cloud (VPC). This offers a level of security and acceleration among managed Kubernetes solutions that is unique among major cloud providers.

## How CKS is different

The following sections describe how CKS differs from other managed Kubernetes services.

### High-performance Kubernetes on high-performance compute

CKS is engineered to orchestrate and serve highly computationally intensive workloads, designed for model training, inference, and HPC tasks.

* CKS harnesses CoreWeave's extensive fleet of high-performance [GPU](/platform/instances/gpu-instances) and [CPU](/platform/instances/cpu-instances) servers and [advanced HPC networking infrastructure](/products/networking/hpc-interconnect/about-hpc-interconnect) to maximize throughput and minimize latency.
* CKS runs Kubernetes directly on bare metal Nodes, without a hypervisor. Customer clusters don't run Virtual Machines.
* CKS clusters use NVIDIA® BlueField® [Data Processing Units](/platform/fleet-management/nimbus) (<Tooltip tip="A Data Processing Unit (DPU) is a 'computer-in-front-of-a-computer', fully isolated from the host's CPU, that provides network and other functions." cta="Learn more" href="/glossary#data-processing-unit-dpu">DPUs</Tooltip>) attached to each Node to offload processing tasks. This allows the Node to focus primarily on executing application workloads.
* CKS Nodes are stateless. At each boot, they load a clean Operating System image. This allows Nodes to be rapidly scaled and re-provisioned, and ensures that all Nodes use the correct software versions.
* Clusters integrate with an InfiniBand fabric that features a non-blocking, Fat-Tree architecture with [NVIDIA® Scalable Hierarchical Aggregation and Reduction Protocol (SHARP)™](https://docs.nvidia.com/networking/software/accelerator-software/index.html#nvidia-sharp) optimizations. These optimizations are capable of supporting the demand of tasks like training Large Language Models (LLMs) across clusters comprised of thousands of GPU instances.

#### Do not install the NVIDIA GPU Operator on CKS clusters

<Warning>
  CoreWeave manages the [NVIDIA GPU Operator](https://docs.nvidia.com/datacenter/cloud-native/gpu-operator/latest/getting-started.html) on your behalf. Do not install the NVIDIA GPU Operator on CKS clusters. Doing so conflicts with the platform-managed deployment and is not supported.
</Warning>

### Hyper-secure infrastructure

CKS is engineered with a strong emphasis on security.

* The [DPU-based architecture](/platform/fleet-management/nimbus) used by CKS enables advanced security features including custom network and security policies, dedicated [Virtual Private Clouds (VPCs)](/products/networking/vpc/about-vpcs), and privileged network access controls.
* CoreWeave houses physical infrastructure in high-surveillance data centers, providing comprehensive security. Within the CKS platform, your data is operationally isolated, ensuring complete separation and confidentiality.

### Data Plane flexibility

CKS provides a managed Control Plane alongside configurable Data Plane elements. This strikes a balance between operational simplicity and the flexibility to tailor the environment to specific workload requirements.

* CKS clusters include a pre-installed [Container Storage Interface (CSI) and Container Network Interface (CNI)](/products/cks/reference/cluster-components) to standardize storage and networking across container environments.
* Unlike other managed Kubernetes services, CKS extends your control beyond the Control Plane by allowing direct management of [Data Plane components](/products/cks/reference/cluster-components). This approach minimizes your infrastructure management burden while still offering extensive customization possibilities.

## Additional advantages

The following sections describe additional advantages that CKS offers.

### Privilege and access management

CKS offers comprehensive privilege management, balancing managed solutions with the flexibility of self-managed ones. This gives you the freedom to choose the most suitable option for your security needs.

[CKS Managed Auth](/security/authn-authz/managed-auth/introduction) provides a managed solution backed by role-based access control (RBAC) for cluster-wide access control and organization management. CKS supports third-party RBAC providers for granular in-cluster permissions.

### Metrics and observability

CKS provides comprehensive support for auditing and compliance requirements. You can also integrate performance and data metrics with your existing infrastructure, enabling a flexible observability solution.

* For enhanced monitoring, CKS grants access to the CKS cluster API server, enabling Control Plane audit logs.
* This extensive access also lets you deploy your own metrics stacks with custom collection tools, including DaemonSet or Loki logging.
* You can also monitor Node logs, GPU utilization, and other Node-level metrics through [CoreWeave Grafana](/observability/managed-grafana).