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OpenStack and Kubernetes are not competing products at the same layer. OpenStack is an infrastructure cloud platform for providing virtual machines, networks, storage and tenancy. Kubernetes schedules and operates containerized applications. A managed Kubernetes service such as Amazon EKS, Microsoft AKS or Google GKE provides Kubernetes with the provider operating much of the control plane. In a private or regional cloud, OpenStack can supply the infrastructure on which Kubernetes runs.
The practical choice is therefore about which operational responsibility you want to own. Choose OpenStack when control of infrastructure, locality, hardware or private-cloud tenancy matters most; choose Kubernetes when portable container operations are the main problem; choose managed Kubernetes when reducing control-plane maintenance is worth recurring provider charges and less control over the underlying platform.
What each platform actually does
OpenStack: an infrastructure cloud operating system
OpenStack presents pools of datacenter compute, storage and networking as an on-demand cloud. The Open Infrastructure Foundation describes it as a “cloud operating system” that lets administrators control those resources while users provision them through a web interface. In practical terms, OpenStack is an infrastructure-as-a-service (IaaS) layer.
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An OpenStack deployment normally exposes APIs and dashboards for creating virtual machines, attaching block or object storage, defining networks and security rules, and separating tenants with projects, quotas and identity policies. The organization operating OpenStack chooses the physical servers, hypervisors, storage systems, network design and upgrade process. That control is valuable when workloads must remain in a particular facility, use specialized hardware, or follow internal tenancy and governance rules.
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Kubernetes: a container orchestration platform
Kubernetes manages containerized workloads rather than raw datacenter capacity. You describe the desired state of applications—such as which container images should run, how many replicas are required, how traffic reaches them and which configuration or secrets they need. Kubernetes schedules those workloads onto worker nodes and continually reconciles the running state with the declaration.
Kubernetes supplies the orchestration API, scheduler, controllers and extensibility model. Infrastructure services such as virtual machines, load balancers, persistent disks and identity are supplied by a cloud or by another infrastructure platform. The Kubernetes project’s cloud-provider migration moved built-in integrations for providers including Google Cloud, AWS, Azure, OpenStack and vSphere out of the core project into external implementations. A cluster therefore needs cloud-controller-manager (CCM), Container Storage Interface (CSI) and related components that match the Kubernetes and infrastructure versions you operate.
Managed Kubernetes: Kubernetes with a provider-operated control plane
Amazon EKS, Microsoft AKS and Google GKE package Kubernetes as a cloud service. The provider installs and operates the control-plane components and typically handles much of their availability engineering, patching and upgrade workflow. Microsoft characterizes AKS as a fully managed Kubernetes platform for deploying, scaling and managing containerized applications. Google also documents managing clusters across AWS and Azure, as well as standard CNCF-conformant clusters, from Google Cloud.
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Are OpenStack and Kubernetes alternatives?
Only if the question is stated at a very high level. OpenStack answers, “How do we provide and govern infrastructure resources?” Kubernetes answers, “How do we deploy and keep container workloads running?” They can be deployed independently, but they are often used together.
OpenStack without Kubernetes
OpenStack can host traditional virtual machines, databases, middleware and applications that are not packaged as containers. Teams that need self-service virtual machines, private networking, block storage or strict datacenter locality may use OpenStack as their primary cloud without operating Kubernetes.
Kubernetes without OpenStack
Kubernetes can run on physical servers, another private virtualization platform, or a public cloud. A managed service removes much of the control-plane work; a self-managed cluster leaves the organization responsible for installation, upgrades, security and recovery.
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OpenStack can provide the virtual machines, networks, load-balancing integration and persistent storage consumed by a Kubernetes cluster. The OpenStack container whitepaper describes Magnum as an OpenStack project with an API for deploying managed clusters backed by several application platforms, including Kubernetes. Kubernetes drivers can consume OpenStack networking and storage services.
This layered design is common for private or regional clouds: OpenStack supplies infrastructure and tenancy, while Kubernetes supplies the application platform. It also creates an integration contract. CCM and CSI implementations, authentication, load-balancer behavior, storage classes and supported Kubernetes versions must be maintained together.
OpenStack, self-managed Kubernetes and managed Kubernetes compared
| Dimension | OpenStack | Self-managed Kubernetes | Managed Kubernetes service |
|---|---|---|---|
| Primary abstraction | Compute, storage and networking infrastructure | Container scheduling and application orchestration | Kubernetes orchestration with a provider-operated control plane |
| Main unit users provision | Virtual machines, networks, volumes and related cloud resources | Pods, workloads, services, policies and cluster resources | Clusters and Kubernetes workloads through the provider’s service and Kubernetes APIs |
| Control-plane responsibility | Owned by the OpenStack operator | Owned by the organization | Shared with the provider; exact boundary depends on the service |
| Infrastructure control | High control over hardware, locality, tenancy and service integration | Depends on the infrastructure beneath the cluster | Provider ecosystem and regional capacity, with provider-specific limits |
| Portability | Infrastructure APIs vary by deployment | Kubernetes APIs can be portable, but infrastructure integrations still vary | Kubernetes APIs support portability; provider networking, identity, storage and observability can create migration work |
| Typical operational burden | Hardware, capacity, networking, storage, upgrades, security and failure recovery | Control plane, nodes, upgrades, security, add-ons, networking, storage and recovery | Workloads, configuration, security, networking choices, observability, cost and the service-specific responsibilities |
| Best-fit priority | Private-cloud control, data locality or customized infrastructure | Direct ownership of a portable container platform | Faster delivery with less control-plane operations |
How to run Kubernetes on OpenStack
Running Kubernetes on OpenStack is a platform-integration project, not a matter of installing one package. The following sequence keeps the infrastructure and application responsibilities explicit.
- Define the boundary. Decide which team owns OpenStack projects, quotas, images, networks, storage and upgrades, and which team owns Kubernetes namespaces, workloads and policies. Write the supported Kubernetes, OpenStack, CCM and CSI versions before deployment.
- Design the OpenStack tenant and network. Create the project or projects that will contain the cluster. Plan management, worker and service networks, security groups, routing, DNS and access to the OpenStack APIs. Reserve capacity for control-plane nodes, worker nodes and failure-domain spreading.
- Prepare compute and storage. Publish approved node images and flavors. Select the block, file or object-storage services that applications will use, and define the corresponding Kubernetes storage classes. Confirm that volume attachment, resizing, snapshots and detachment work with the CSI implementation you intend to run.
- Choose a cluster-provisioning path. Magnum can expose a simple OpenStack API for deploying a managed cluster and supports several application platforms, including Kubernetes. If you use another installer, document how it creates instances, networks, load balancers and credentials; the same compatibility checks still apply.
- Install the external cloud integrations. Configure the OpenStack cloud-controller-manager so Kubernetes can understand infrastructure events and services. Install the compatible CSI driver for persistent storage. Check authentication, endpoint discovery, TLS certificates, load-balancer behavior and the permissions granted to the cluster components.
- Provision and validate nodes. Create the control-plane and worker capacity, then verify node readiness, scheduling, network reachability and failure handling. Test a service that requests a load balancer and a stateful workload that provisions and reattaches a volume. Confirm that deleting and recreating a node does not leave orphaned infrastructure.
- Operate it as one product. Monitor Kubernetes and OpenStack together. Set upgrade order and rollback procedures for the control plane, nodes, CCM, CSI drivers and OpenStack services. Test backups, certificate rotation, quota exhaustion, API outages and storage or network failure before production traffic depends on the cluster.
Compatibility checks that prevent common outages
- Keep Kubernetes, the OpenStack CCM and CSI driver within each project’s supported version range.
- Confirm that the selected OpenStack networking service supports the load-balancer, floating-IP and security-group behavior expected by Kubernetes.
- Test persistent-volume recovery in the same failure domains and availability zones used by production workloads.
- Separate credentials for infrastructure automation, cluster components and human administrators; grant only the API permissions each needs.
- Record which features are OpenStack-native and which are provider-specific Kubernetes extensions so a later migration does not surprise application teams.
Self-managed Kubernetes versus EKS, AKS and GKE
The central trade-off is operational ownership. A self-managed cluster can run on infrastructure you control and can be tuned to your security, hardware or locality requirements. You also inherit every control-plane and node lifecycle task. A managed service removes a substantial part of that work, but it does not remove application operations or eliminate provider coupling.
| Responsibility | Self-managed cluster | Managed service |
|---|---|---|
| Control-plane installation and availability | Organization designs, installs, monitors and repairs it | Provider operates the control plane under the service contract |
| Kubernetes upgrades | Organization selects versions, tests, schedules and executes upgrades | Provider supplies supported upgrade mechanisms; customer still plans compatibility and workload changes |
| Worker capacity | Organization provisions, patches, scales and replaces nodes | Provider offers node or serverless options, but customers still select capacity, images and scaling behavior |
| Application configuration | Customer owns manifests, policies, secrets, ingress and deployment processes | Customer owns the same workload configuration |
| Networking and storage | Customer integrates and operates the infrastructure providers | Customer chooses service options and configures integrations; provider-specific APIs may be involved |
| Observability and security | Customer builds the collection, alerting, hardening and response stack | Provider supplies optional features, while customers remain responsible for workload security, monitoring choices and incident response within their boundary |
| Billing and capacity | Infrastructure utilization and staffing drive cost | Service charges, worker resources, add-ons, transfer and egress can all contribute |
Do not assume that a managed control plane makes an application automatically highly available. Design replicas, disruption budgets, multi-zone placement, backups, identity and recovery separately from the provider’s control-plane SLA.
Choosing the right model
Choose OpenStack first when infrastructure control is the requirement
- You need private-cloud tenancy and self-service infrastructure inside a controlled datacenter or region.
- Data-residency, hardware placement or specialized compute and networking services outweigh the convenience of a public provider.
- Infrastructure teams already have the skills and staffing to operate capacity, storage, networking, upgrades and failure recovery.
- You need one infrastructure layer to support both virtual-machine workloads and container platforms.
Choose Kubernetes directly when application portability is the requirement
- Your main objective is a consistent API for deploying containerized services across different infrastructure environments.
- Application teams need Kubernetes primitives such as deployments, services, jobs, autoscaling and policy controls.
- You are prepared to own cluster lifecycle work, or you have a platform team that can provide it as an internal service.
Choose managed Kubernetes when delivery speed is the requirement
- You want to avoid building a highly available control plane and reduce routine control-plane maintenance.
- Your workloads benefit from a provider’s regional capacity, identity, networking, storage and observability ecosystem.
- The team accepts recurring service charges and the migration work that provider-specific integrations can create.
Choose a combined OpenStack-plus-Kubernetes design
This model fits organizations that need private infrastructure control but want Kubernetes as the developer-facing application platform. It is strongest when the platform team can publish a supported “golden path” for cluster versions, storage classes, load balancers, identity and upgrades. Without that standardization, every application team may end up debugging a different combination of infrastructure and Kubernetes components.
Cost, staffing and lock-in
There is no universally applicable cost figure for this decision. Compare the full operating model rather than a headline service price.
Self-managed cost categories
- Physical or virtual infrastructure capacity, including headroom for failures and upgrades.
- Staffing for OpenStack or Kubernetes installation, patching, security, observability and on-call response.
- Storage, network equipment, backup systems and datacenter or colocation costs.
- Engineering time spent integrating identity, load balancing, persistent storage and automation.
Managed-service cost categories
- Managed control-plane or cluster charges, where applicable.
- Worker compute, storage, load balancing, databases and other attached services.
- Provider add-ons, support plans, cross-region traffic and egress.
- Engineering work to meet the provider’s upgrade, identity, networking and observability model.
Portability has a similar trade-off. Kubernetes resource definitions and CNCF conformance can ease movement, but applications often depend on a provider’s ingress controller, identity integration, storage class, monitoring pipeline or load-balancer behavior. Keep those dependencies behind documented interfaces, and maintain a migration test environment if changing providers is a realistic future requirement.
Operational pitfalls and recovery approaches
“Kubernetes is replacing OpenStack”
This framing confuses application orchestration with infrastructure delivery. If the requirement is virtual machines, private networking, storage services and tenant quotas, Kubernetes does not provide the same abstraction. If the requirement is scheduling containers and rolling out services, OpenStack alone does not provide Kubernetes’ application controllers.
Cloud integrations break after an upgrade
Because provider integrations are external to the Kubernetes core, upgrading Kubernetes without checking CCM and CSI compatibility can disable load balancers, volume provisioning or node lifecycle handling. Pin supported versions, stage upgrades, and test infrastructure operations before allowing application rollouts.
“Managed” is mistaken for “fully operated”
A provider may operate the control plane while your team remains responsible for insecure images, excessive permissions, broken network policies, unavailable replicas, unbounded logs and unexpected data transfer. Define the responsibility boundary in an operations runbook and assign an owner for every component.
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- Kubernetes is an open platform that automates container orchestration, enabling seamless deployment, automatic scaling, self-healing, and efficient management of applications across servers or clouds with high availability and optimal resource use
- Kubernetes is perfect for development operations engineers, cloud architects, site reliability engineers, platform engineering teams and infrastructure specialists who build, operate and maintain modern containerized applications in production environments
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Private-cloud capacity is sized only for normal load
OpenStack and self-managed Kubernetes need spare capacity for node failure, rolling upgrades, rescheduling and storage repair. Quotas, exhausted IP pools, insufficient volume capacity or a single failure domain can look like Kubernetes scheduling defects when the underlying infrastructure is the constraint.
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A workload that uses only standard Kubernetes objects is easier to move than one coupled to a provider’s identity, storage and ingress APIs. Inventory those dependencies, test restore and redeploy procedures, and keep application configuration separate from infrastructure-specific manifests.
A practical evaluation checklist
- List the workloads: virtual machines, stateless containers, stateful services, batch jobs and regulated data.
- Mark locality, hardware, tenancy and network-isolation requirements.
- Assign ownership for control plane, nodes, storage, networking, identity, observability, upgrades and incident response.
- Choose the smallest platform that satisfies those requirements: OpenStack, self-managed Kubernetes, managed Kubernetes, or a layered combination.
- Build a representative proof of concept, including persistent storage, load balancing, identity, upgrades and failure recovery.
- Measure staffing and infrastructure utilization alongside managed-service charges, transfer costs and add-ons.
- Document provider-specific dependencies and the effort required to migrate or restore elsewhere.
- Set version-support, backup, security and deprecation policies before production onboarding.
Learning resource for implementation teams
Kubernetes: Up and Running, 3rd Edition by Brendan Burns, Joe Beda, Kelsey Hightower and Lachlan Evenson was published by O’Reilly Media in August 2022. The 328-page edition covers installing Kubernetes on GKE, AKS and AWS as well as operating clusters. It is useful for engineers who need the Kubernetes application model before deciding how much infrastructure to operate themselves.
For OpenStack-specific implementation, pair Kubernetes fundamentals with the current OpenStack release documentation and the compatibility documentation for the chosen CCM, CSI driver and cluster-provisioning tool. OpenStack 2025.1 documentation was published by the Open Infrastructure Foundation in April 2025; service behavior and support details should be checked against the release you intend to deploy.
The Bottom Line
OpenStack is the infrastructure layer, Kubernetes is the container-operations layer, and managed Kubernetes is a provider-operated version of that application layer. Select based on who must own infrastructure and control-plane work, where data and hardware must reside, and how much provider-specific integration your team can accept.
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