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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteOpenStack and Kubernetes are not competing products at the same layer. OpenStack is an infrastructure cloud operating system for providing virtual machines, networks and storage. Kubernetes schedules and operates containerized applications. Amazon EKS, Microsoft AKS and Google GKE provide Kubernetes with a provider-operated control plane. You can run Kubernetes on OpenStack, use either platform by itself, or combine private OpenStack infrastructure with Kubernetes for applications.
The right choice depends on what you need to own. Choose OpenStack for control over hardware, tenancy, locality and infrastructure services; choose Kubernetes when portable container operations are the main problem; choose a managed Kubernetes service when reducing control-plane work and moving quickly matter more than operating the underlying platform.
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What each platform actually does
OpenStack: an infrastructure cloud operating system
OpenStack sits at the infrastructure-as-a-service layer. The Open Infrastructure Foundation describes OpenStack as a cloud operating system that controls pools of compute, storage and networking resources in a datacenter, with a dashboard through which administrators control the environment and users provision resources.
In practical terms, an OpenStack deployment gives an organization cloud-like primitives in a private or regional environment: virtual machines, networks, subnets, routers, security controls, block volumes, images and often object storage. The exact services and hardware are selected and operated by the organization or its service provider. OpenStack can therefore be used to create a private cloud with internal tenancy boundaries, specialized hardware and data-residency controls.
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OpenStack does not, by itself, schedule a web service across containers, roll out a new application version or restart a failed container according to a deployment policy. Those are application-platform responsibilities, commonly handled by Kubernetes.
Kubernetes: a container orchestration platform
Kubernetes manages containerized workloads. It schedules Pods onto worker machines, maintains the desired number of replicas, provides service discovery and traffic routing, and coordinates rolling updates, storage claims and configuration. The machines and many of the network and storage integrations come from an infrastructure platform underneath it.
Kubernetes can run on bare metal, a public cloud, OpenStack, VMware or another infrastructure environment. The Kubernetes project moved built-in integrations for Google Cloud, AWS, Azure, OpenStack and vSphere out of the core project into external cloud-provider implementations. That change, announced by the Kubernetes project on May 20, 2024, means a cluster depends on separately maintained cloud-controller-manager, Container Storage Interface and related components that match the Kubernetes versions and the infrastructure provider.
Managed Kubernetes: the provider operates part of the platform
Amazon Elastic Kubernetes Service (EKS), Microsoft Azure Kubernetes Service (AKS) and Google Kubernetes Engine (GKE) are managed Kubernetes offerings. They still expose Kubernetes APIs and run Kubernetes workloads, but the provider installs and operates at least the control plane. Microsoft describes AKS as a fully managed Kubernetes platform intended to simplify deploying, scaling and managing containerized applications in the cloud.
Managed does not mean that every operational task disappears. Customers remain responsible for workload configuration, application and cluster security decisions, network design, identity permissions, observability, capacity choices and cost control. The precise division of responsibility, supported versions, regions, service-level commitments and available add-ons differ by provider and change over time, so verify current terms before choosing a service.
Are OpenStack and Kubernetes alternatives?
Usually, no. They solve different problems and can be layered.
| Platform | Primary abstraction | Typical unit operated | What it does not replace |
|---|---|---|---|
| OpenStack | Infrastructure cloud: compute, networking and storage | Virtual machines, volumes, networks and tenants | A container scheduler and application release controller |
| Kubernetes | Container orchestration | Pods, Deployments, Services and persistent workloads | The underlying servers, network fabric and physical storage |
| Managed Kubernetes such as EKS, AKS or GKE | Kubernetes with a provider-operated control plane | Container clusters and workloads on provider infrastructure | Your application configuration, security choices, observability and spending decisions |
Calling OpenStack an alternative to Kubernetes is therefore like comparing a cloud infrastructure layer with an application orchestration layer. A company may standardize on OpenStack and deploy Kubernetes clusters on top of it. Another may use Kubernetes directly on existing servers. A third may consume EKS, AKS or GKE and never operate physical infrastructure.
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How Kubernetes runs on OpenStack
Kubernetes can consume OpenStack services for the resources a cluster needs. Worker nodes may be OpenStack virtual machines; Kubernetes networking can integrate with OpenStack networks; and persistent volumes can be backed by OpenStack block storage through a compatible CSI driver. The cloud-controller-manager handles infrastructure-related functions such as node and load-balancer integration when the supported implementation is installed.
Magnum as a cluster-provisioning option
The OpenStack Foundation’s container whitepaper identifies Magnum as an OpenStack project that provides an API for deploying managed clusters backed by several application platforms, including Kubernetes. Magnum can give an OpenStack administrator a consistent way to offer clusters to internal users instead of asking every team to assemble a control plane and worker fleet manually.
Magnum does not remove the need to understand Kubernetes operations. You still need a supported Kubernetes version, a plan for control-plane and worker upgrades, network policy, identity, ingress, storage classes, monitoring, backup and recovery. Magnum’s value is the OpenStack-side provisioning workflow and integration, not an exemption from application-platform engineering.
Integration checks before production
- Version alignment: confirm that the Kubernetes release, OpenStack cloud-provider implementation, CSI driver and any cluster-provisioning tool support one another.
- Networking: document how Pods, Services, nodes and external load balancers map to OpenStack networks, routers, security groups and floating addresses.
- Storage: test dynamic volume provisioning, expansion, snapshots and recovery with the OpenStack backend you will actually use.
- Identity: define how users and service accounts obtain OpenStack credentials, and keep infrastructure credentials separate from application permissions.
- Failure behavior: simulate an unavailable compute host, a broken network path and a storage outage so that Kubernetes reconciliation and OpenStack recovery procedures are understood together.
- Upgrade order: establish which component is upgraded first and how rollback works; an independently upgraded cloud integration can break node, volume or load-balancer operations even when the Kubernetes API remains available.
OpenStack, self-managed Kubernetes and managed Kubernetes compared
| Decision axis | OpenStack | Self-managed Kubernetes | Managed Kubernetes |
|---|---|---|---|
| Abstraction | Infrastructure resources and tenancy | Container scheduling and lifecycle on infrastructure you select | Kubernetes APIs with a provider-operated control plane |
| Control-plane responsibility | Not applicable unless you deploy another platform on it | Your team installs, secures, upgrades and restores the control plane | Provider operates core control-plane infrastructure; customer responsibilities vary |
| Infrastructure control | High, including hardware, placement and network design | Depends on the underlying environment | Lower than private infrastructure; provider determines much of the platform |
| Locality and tenancy | Strong fit for private, regional or specialized environments | Can meet these needs if the underlying infrastructure does | Uses provider regions and isolation models; verify residency and tenancy requirements |
| Portability | Infrastructure APIs are specific to OpenStack | Kubernetes APIs can be portable, but integrations and manifests may not be | Core Kubernetes workloads can move, while identity, networking, storage and observability often require migration work |
| Operations staffing | Infrastructure, capacity, hardware and cloud-service expertise | Cluster lifecycle, security, upgrades, networking, storage and recovery | Less control-plane engineering, but workload, security, platform and cost operations remain |
| Pricing basis | Infrastructure utilization plus staffing and facilities | Infrastructure plus staffing and any platform components | Provider service charges, infrastructure usage, add-ons, transfer and egress; exact figures are not universal |
No single cost or performance number applies to all three choices. A heavily utilized private cloud can have a different economics profile from a small team paying for managed control planes, and provider egress or premium add-ons can change a managed-service bill. Compare your own workload, utilization, staffing and traffic rather than relying on a generic benchmark.
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What you still operate with a managed service
Moving from self-managed Kubernetes to EKS, AKS or GKE removes a significant class of control-plane tasks, but it does not turn the platform into an application hosting button. Before signing up, assign ownership for the following areas:
- Workload configuration: Deployments, StatefulSets, resource requests and limits, probes, disruption budgets and rollout policies.
- Security: image provenance, patching of application images, secrets, network policies, admission controls, identity bindings and least-privilege access.
- Networking: virtual networks, subnets, ingress, DNS, private connectivity, firewall rules and traffic costs.
- Storage: storage classes, backup policy, encryption, retention and restore testing.
- Observability: logs, metrics, traces, alert thresholds and the retention cost of each signal.
- Capacity and reliability: node pools, autoscaling limits, availability zones, quotas, maintenance windows and disaster-recovery targets.
- Cost management: idle nodes, overprovisioned requests, persistent disks, load balancers, outbound traffic and paid control-plane or add-on features.
The provider’s control-plane availability does not guarantee that your application is highly available. A single-zone worker pool, an unreplicated database or an incorrect readiness probe can still cause an outage.
How EKS, AKS and GKE fit the choice
Amazon EKS
EKS is Amazon’s managed Kubernetes offering. It is a fit when your workloads already rely on AWS identity, networking, storage or other services and the team wants Kubernetes APIs without building its own control plane. The resulting convenience can also increase dependence on AWS-specific integrations, so identify which manifests, IAM policies, load-balancer behavior and storage classes would need replacement in another environment.
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Microsoft AKS
Microsoft Learn characterizes AKS as a fully managed Kubernetes platform that simplifies deployment, scaling and management of containerized applications in the cloud. AKS can be attractive when Azure networking, identity, policy or monitoring are already standard in the organization. Treat the word managed as a control-plane boundary: worker-node configuration, workload security, application reliability and spending still require an operating model.
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Google GKE
GKE is Google’s managed Kubernetes service. Google documentation also describes managing Kubernetes clusters running on AWS and Azure, as well as standard CNCF-conformant clusters, from Google Cloud. That kind of multi-environment management can help teams centralize policy or visibility, but it does not make every provider’s networking, identity and storage behavior identical. Test the exact features you intend to use across each target environment.
Questions to ask each provider
- Which Kubernetes versions are currently offered, and how long is each version supported?
- Which control-plane, worker-node, upgrade and availability tasks are included, and which incur separate charges?
- How are private clusters, outbound traffic, ingress, load balancers and cross-region transfers billed?
- Which CSI, cloud-controller and identity integrations are supported for the Kubernetes versions you plan to run?
- Can you export workload state, persistent data, logs and policies in a form usable outside the provider?
- What happens during a provider-region outage, quota exhaustion or failed upgrade?
Choosing by organizational need
Choose OpenStack when infrastructure ownership is the requirement
OpenStack is the stronger starting point when you must control the physical estate, create private-cloud tenancy, keep data in a defined locality, attach specialized hardware or expose customized compute, network and storage services. It is also a sensible substrate for teams that want an internal cloud API while retaining responsibility for capacity, hardware lifecycle and platform reliability.
Plan for a real infrastructure organization: OpenStack upgrades, service dependencies, hardware failures, capacity forecasting, identity, networking and storage operations all need owners. Kubernetes can be added later for container workloads; it is not a substitute for operating OpenStack itself.
Choose self-managed Kubernetes when portability and platform control dominate
Run Kubernetes directly when the primary problem is operating portable container workloads and you already have reliable infrastructure expertise. This route can be appropriate for regulated environments, disconnected sites, edge locations or organizations that need to control the entire stack. The trade-off is that your team owns control-plane installation, certificates, etcd or equivalent state protection, upgrades, node replacement, security response and recovery testing.
Choose managed Kubernetes when delivery speed outweighs infrastructure ownership
A managed service is generally the pragmatic choice for a team that wants Kubernetes but does not want to staff control-plane engineering. It can shorten the path to a supported cluster and shift some availability engineering to the provider. Keep enough platform expertise to design networks and identities, secure workloads, operate storage and observability, and manage the bill.
Choose a combined OpenStack-plus-Kubernetes design when both layers matter
In a private or regional cloud, OpenStack can supply virtual machines, networks and volumes while Kubernetes supplies the application platform. This arrangement separates infrastructure and application responsibilities and can provide a familiar Kubernetes interface to development teams without moving sensitive workloads to a public cloud. Its success depends on disciplined integration testing and a clearly owned upgrade sequence.
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Implementation paths
Path A: build a private cloud with OpenStack first
- Define tenancy, data-residency, hardware, network-segmentation and capacity requirements.
- Select the OpenStack services and hardware profiles required by your users; avoid deploying components that have no operational owner.
- Establish identity, image governance, quotas, backup, monitoring and incident procedures before onboarding production tenants.
- Measure utilization and failure-recovery times under realistic workloads, not only during a successful installation.
- Offer Kubernetes through Magnum or another supported provisioning workflow only after the underlying compute, network and storage services are reliable.
Path B: operate Kubernetes on existing infrastructure
- Choose a supported Kubernetes distribution and a release policy that your team can maintain.
- Design control-plane quorum, worker pools, networking, storage, ingress, identity and secrets before deploying applications.
- Install cloud-provider, CSI and related integrations that match the infrastructure and Kubernetes versions.
- Define upgrade, certificate-rotation, backup, restore and node-replacement runbooks; rehearse them on a non-production cluster.
- Set resource requests, limits, disruption budgets and observability standards for every production workload.
Path C: adopt EKS, AKS or GKE
- Compare regions, supported Kubernetes versions, private-network options, identity integrations and service boundaries for the provider you are considering.
- Create a landing zone with network segmentation, access roles, logging, metrics, policy controls, quotas and billing alerts.
- Choose node-pool types and availability layout based on workload requirements rather than default settings.
- Deploy a small representative application and test upgrades, autoscaling, storage recovery, ingress, backup and an intentional zone or node failure.
- Document the provider-specific components you use and maintain an exit plan for identity, networking, storage, observability and data transfer.
Portability: what moves easily and what does not
Kubernetes APIs and CNCF conformance improve the chance that ordinary workload definitions will run on another conformant cluster. Deployments, Services and many stateless application manifests can often be adapted with limited changes.
Portability becomes harder at the edges. Provider-specific load-balancer annotations, IAM bindings, network policies, storage classes, ingress controllers, secret stores, autoscaling integrations and observability agents may have no direct equivalent elsewhere. Persistent data requires a migration method and a tested restore path. A cluster that is technically portable may still be expensive or slow to move because of traffic, data gravity and operational retraining.
To preserve options, isolate provider-specific settings, keep infrastructure configuration under version control, prefer portable interfaces where they meet your requirements, and test a deployment on a second conformant environment before you need an emergency migration.
Common mistakes and how to correct them
Treating the products as substitutes
Symptom: a team compares OpenStack and Kubernetes as if both provision the same resources. Correction: map the requirement to its layer first: infrastructure and tenancy point to OpenStack; container scheduling points to Kubernetes; reduced control-plane work points to a managed service.
Assuming managed means hands-off
Symptom: the control plane is available but an application outage, data-loss event or unexpected bill still occurs. Correction: assign explicit owners for workload security, backups, network design, observability, capacity and cost.
Ignoring external cloud integrations
Symptom: nodes register but volumes or load balancers fail after an upgrade. Correction: pin and verify compatible cloud-provider, CSI and CCM components, and include them in the upgrade runbook.
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Underestimating private-cloud operations
Symptom: a proof-of-concept works but production capacity, hardware replacement or incident response is slow. Correction: budget for facilities, spares, on-call coverage, upgrades, security response and recovery exercises, not only software licenses.
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Using portability as a slogan
Symptom: an application is described as portable, but its identity, storage and ingress are tied to one provider. Correction: inventory every provider-specific dependency and test the migration of both stateless workloads and persistent data.
Costs, staffing and governance
Self-managed OpenStack and Kubernetes exchange provider invoices for engineering responsibility. You pay for servers, facilities, networking, storage, replacements and staff time, while gaining control over placement, utilization and locality. The cost profile improves when infrastructure is well utilized and the organization can sustain the required expertise; it worsens when capacity sits idle or a small team carries a large on-call burden.
Managed Kubernetes introduces recurring service charges and leaves infrastructure consumption, add-ons and network transfer on the bill. It can be economically preferable when a provider’s control-plane operations replace expensive specialist staffing or accelerate product delivery. It can be more expensive when workloads are steady, utilization is high and provider-specific transfer or premium services dominate.
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Learning resources
Kubernetes: Up and Running, 3rd Edition is an August 2022 O’Reilly book by Brendan Burns, Joe Beda, Kelsey Hightower and Lachlan Evenson. The 328-page edition covers installing Kubernetes on GKE, AKS and AWS as well as day-to-day cluster operation. It is useful for learning the Kubernetes layer before deciding whether that layer should run on OpenStack, directly on owned infrastructure or through a managed provider.
For OpenStack terminology and architecture, the Open Infrastructure Foundation’s OpenStack 2025.1 documentation, published in April 2025, is the authoritative starting point. For integration planning, read the Kubernetes project’s May 20, 2024 cloud-provider migration announcement and the OpenStack container guidance on Magnum and Kubernetes drivers. Provider documentation should be checked again immediately before implementation because service boundaries and support windows change.
Bottom line
OpenStack provides the cloud infrastructure; Kubernetes operates container workloads; EKS, AKS and GKE operate part of the Kubernetes control plane for you. Select one based on the responsibility you want to retain, not on a claim that one product replaces the others. When private infrastructure, locality and control are essential, deploy Kubernetes on OpenStack or another owned platform. When the priority is fast, portable application delivery with less control-plane maintenance, use a managed Kubernetes service and govern its provider-specific edges deliberately.
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