SERVICES YOU CAN LAUNCH WITH THE RAFAY PLATFORM

Kubernetes as a Service

Rafay-Powered Managed Kubernetes (K8S)

Rafay's Managed Kubernetes as a Service (MKS) delivers fully managed, GPU-ready Kubernetes clusters as a governed, self-service offering. The service is built on Rafay MKS, an upstream Kubernetes distribution for bare metal and virtual machines. It streamlines every stage of your operations, including provisioning, securing, and managing the full cluster lifecycle across public, private, air-gapped, and sovereign environments.

  • Automated Lifecycle: Run multiple Kubernetes versions with automated, non-disruptive upgrades and rollbacks fleet-wide from one control plane.
  • Governance by Default: Enterprise-grade multi-tenancy, RBAC, and Zero Trust Kubectl, with secure access without VPNs or bastions.
  • AI/ML Conformant: Rafay MKS holds CNCF Kubernetes AI Conformance for v1.35, with integrated GPU scheduling for training and inference.
Hero image on an article featuring Rafay-powered managed Kubernetes as a service

Simplify Kubernetes Cluster Management and Lifecycle Automation

One control plane provisions, governs, and scales clusters across every environment

Automated Cluster Lifecycle

On-demand provisioning, upgrades, scaling, and Day-2 operations fleet-wide, with multi-version support

AI/ML Ready

Integrated GPU operator and GPU scheduling for training and inference out of the box

Network Automation & CNI

Cilium, Calico, Flannel, or your own CNI, plus load balancer and ingress integration

Zero-Trust Access

Per-tenant isolation, RBAC, and zero-trust kubectl access on every tenant

Deliver Secure, Compliant, and Efficient Kubernetes Services

Deliver a governed service in weeks, not months


Building a managed Kubernetes offering from scratch can require significant engineering effort before it is ready for customers. Rafay provides the operational framework needed to deploy governed Kubernetes managed services without building every component in-house. This shortens the path from infrastructure to a production-ready service while providing the consistency and reliability enterprise customers expect.

Operate Growing Kubernetes Fleets Without Growing Operational Overhead


As the number of customer clusters grows, the operational workload does not have to grow at the same rate. Lifecycle automation reduces repetitive configuration work and helps prevent configuration drift across the fleet. This allows platform teams to manage more clusters and multi-cloud environments from a single control plane without continually increasing administrative overhead.

Support Secure and Sovereign Kubernetes Deployments


Enterprise and regulated customers can have strict requirements around how workloads, infrastructure, and data are accessed and controlled. Zero-trust access, RBAC, and network policies help providers enforce those requirements consistently, while support for private, air-gapped, and sovereign environments extends Kubernetes services to customers with more stringent security and compliance needs.

Run AI and ML Workloads on an AI-Conformant Kubernetes Foundation


Kubernetes services increasingly need to support AI and ML alongside traditional microservices and applications. Rafay MKS provides a CNCF AI-conformant foundation with integrated GPU scheduling, helping providers allocate expensive compute resources efficiently across AI workloads. This enables them to expand their Kubernetes offering to support AI training and inference while helping optimize GPU utilization.

Frequently Asked Questions About Kubernetes as a Service

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What Is Kubernetes as a Service?

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Kubernetes as a Service is a managed model for providing Kubernetes clusters and the supporting capabilities required to operate them. Normally, organizations must build and maintain the entire Kubernetes infrastructure themselves. A managed service, on the other hand, allows them to provision clusters, apply governance, and handle ongoing operational tasks.

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The exact division of responsibility depends on the service. A comprehensive managed Kubernetes solution can cover areas such as cluster lifecycle management, security policies, upgrades, monitoring, and access controls. This reduces the operational burden of installing, configuring, and maintaining Kubernetes. At the same time, it gives end users a more consistent way to access the resources they need.

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How Does Managed Kubernetes Differ From Self-Managed Kubernetes?

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The primary difference is who is responsible for operating the Kubernetes environment. With self-managed Kubernetes, internal teams typically configure, upgrade, secure, monitor, and troubleshoot the clusters themselves. Managed Kubernetes shifts some or all of those responsibilities to a platform or service provider.

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This can be particularly valuable as the number and size of Kubernetes environments grow. Instead of maintaining separate operational processes for individual clusters, organizations can standardize how they deploy and manage workloads and establish centralized visibility across their Kubernetes estate.

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Can Kubernetes as a Service Run Across Hybrid and Multi-Cloud Environments?

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Yes. Kubernetes can run across public cloud, private cloud, virtualized, bare-metal, and other infrastructure. However, the environments supported depend on the Kubernetes service or platform being used.

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A consistent management layer can help organizations operate clusters across multiple cloud providers and infrastructure types without creating an entirely separate operational workflow for each environment. This is particularly useful when applications need to remain in particular locations for performance, security, sovereignty, or regulatory reasons.

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How Does Kubernetes as a Service Support Application Development?

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Kubernetes as a Service gives development teams a standardized environment for deploying and running containerized applications without requiring them to manage the underlying clusters themselves. Developers can concentrate on application development, while platform teams establish the infrastructure, policies, and operational controls that applications run within.

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Standardized environments can also make it easier to move modern applications through development, testing, and production. Teams can use familiar Kubernetes tooling, including APIs and Helm, while the service handles much of the underlying container orchestration and cluster administration.

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Can Managed Kubernetes Support Stateful Applications and Databases?

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Yes. Kubernetes can run both stateless and stateful workloads, including applications that depend on persistent storage and database services. However, these workloads have different requirements from applications that can simply be restarted elsewhere without retaining local state.

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Organizations therefore need to consider persistent storage, backup and recovery, availability, and how workloads are rescheduled when a node becomes unavailable. The Kubernetes platform only provides the orchestration layer. It's the underlying storage and infrastructure architecture that determine many of the resilience and performance characteristics of the application.

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How Does Kubernetes as a Service Improve Reliability and Scalability?

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Kubernetes provides mechanisms for maintaining application availability and responding to changes in workload demand. It can reschedule workloads when infrastructure fails and increase or decrease application capacity according to configured requirements.

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However, high availability and scalability depend on more than Kubernetes itself. Organizations also need appropriately designed compute, networking, storage, load balancing, monitoring, and recovery processes. A managed service helps bring these operational components together so teams can build more resilient environments without individually managing every part of the Kubernetes stack.

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What Security Capabilities Should a Managed Kubernetes Service Provide?

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A managed Kubernetes service should provide controls for managing who can access clusters, what actions they can perform, and how workloads communicate. Depending on the environment, these can include role-based access controls, identity integration, network policies, secrets management, audit capabilities, and policy enforcement.

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Security also needs to extend beyond individual clusters. Organizations operating distributed environments need a consistent way to apply controls and understand activity across the fleet. Observability and centralized governance can help teams identify issues and operate Kubernetes securely as the number of clusters, workloads, and users increases.

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What Should Organizations Look for in a Kubernetes as a Service Platform?

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Organizations should look for a platform that can support the complete operational lifecycle rather than focusing only on cluster provisioning. Important considerations include lifecycle automation, governance, security, deployment flexibility, multi-tenancy, observability, developer access, and support for the infrastructure and workloads the organization intends to run.

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The platform should also fit existing operational processes and tooling. Support for Kubernetes APIs, automation, policy controls, and established deployment tools can reduce the need to create bespoke processes as the environment grows. For service providers in particular, it is also important to consider how easily the platform can provide governed services to multiple customers or business units.

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“We are able to deliver new, innovative products and services to the global market faster and manage them cost-effectively with Rafay.”

Joe Vaughan
Joe Vaughan
Chief Technology Officer
,
MoneyGram

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