9.2 Choosing Kubernetes Infrastructure
Abstract
Kubernetes can run on a laptop, virtual machines, physical servers, private cloud, or public cloud.
The right infrastructure choice depends on the purpose of the cluster, team skill level, cloud strategy, production requirements, and operations responsibility.
Infrastructure Options Overview
Kubernetes infrastructure can be grouped into four common options.
| Option | Best For | Responsibility |
|---|---|---|
| Minikube | Learning and local labs | Tool provisions local VM/container |
| kubeadm | Learning, testing, on-prem, custom clusters | You prepare and maintain nodes |
| Turnkey solutions | Private cloud or enterprise platforms | You manage infrastructure, tool automates Kubernetes setup |
| Hosted / managed solutions | Production cloud workloads | Cloud provider manages control plane and much of the platform |
Question
Before choosing an option, ask: Do I want to learn Kubernetes internals, or do I want a production-ready managed platform?
Local Kubernetes Options
For local learning and development, use lightweight tools.
Minikube creates a single-node Kubernetes cluster on your local machine.
Best for:
- education
- local practice
- basic Kubernetes labs
- testing YAML manifests
Key points:
- deploys a local VM or container-based cluster
- creates a single-node cluster
- easy to start and delete
- not designed for production
Tip
Use Minikube when you want the fastest way to practice Kubernetes locally.
kubeadm bootstraps Kubernetes on already prepared Linux machines.
Best for:
- learning cluster setup
- single-node clusters
- multi-node clusters
- on-premises environments
- understanding Kubernetes internals
Key points:
- requires VMs or servers to be ready first
- supports single-node and multi-node clusters
- gives more control than Minikube
- requires manual operations and maintenance
Note
kubeadm does not create VMs for you. You must provision and configure the machines first.
Local Machine Considerations
Kubernetes can run locally, but the setup depends on the operating system.
| OS / Environment | Notes |
|---|---|
| Linux | Can run Kubernetes components directly or through tools |
| macOS | Usually uses VM/container-based tools like Minikube, Kind, or Docker Desktop |
| Windows | Usually requires virtualization such as Hyper-V, VMware, VirtualBox, or WSL2 |
| Cloud VM | Can run kubeadm or lightweight Kubernetes distributions |
Warning
Kubernetes control plane components are Linux-based in most learning setups. On Windows or macOS, tools usually create Linux-based VMs or containers behind the scenes.
Minikube vs kubeadm
| Feature | Minikube | kubeadm |
|---|---|---|
| VM provisioning | Automated | Manual |
| Cluster type | Usually single-node | Single-node or multi-node |
| Best for | Learning and quick labs | Learning real cluster setup |
| Production use | No | Possible, but requires strong operations |
| Complexity | Low | Medium |
| Control | Limited | High |
Success
Use Minikube for quick local practice and kubeadm when you want to understand how Kubernetes clusters are built.
Production Infrastructure Choices
For production, Kubernetes infrastructure is commonly divided into:
- Turnkey solutions
- Hosted / managed solutions
Note
Production clusters require much more than installation. You must plan upgrades, patching, monitoring, backups, scaling, security, and disaster recovery.
Turnkey Solutions
Turnkey solutions help automate Kubernetes deployment, but you still manage the infrastructure.
You are responsible for:
- provisioning VMs
- configuring VMs
- running deployment scripts/tools
- maintaining the machines
- patching operating systems
- upgrading Kubernetes
- monitoring cluster health
Examples:
- OpenShift
- Cloud Foundry Container Runtime
- VMware Cloud PKS / Tanzu Kubernetes Grid
- Vagrant-based Kubernetes labs
- Kubernetes on AWS using kOps
Abstract
Turnkey means the platform helps you deploy Kubernetes, but you still own the infrastructure operations.
Turnkey Solution Examples
| Solution | Description |
|---|---|
| OpenShift | Red Hat platform built on Kubernetes with extra developer and enterprise features |
| Cloud Foundry Container Runtime | Uses BOSH to deploy and manage HA Kubernetes clusters |
| VMware Cloud PKS / Tanzu | Kubernetes platform for VMware environments |
| Vagrant | Useful scripts and VM automation for local/private cluster creation |
| kOps | Popular tool for self-managed Kubernetes clusters on AWS |
Tip
Turnkey solutions are useful when your organization wants Kubernetes but still needs control over the underlying infrastructure.
Hosted / Managed Solutions
Hosted solutions provide Kubernetes as a service.
The provider usually handles:
- VM provisioning
- control plane setup
- control plane availability
- Kubernetes installation
- some upgrades
- integration with cloud networking
- integration with cloud storage
- load balancer support
Examples:
- Google Kubernetes Engine (GKE)
- OpenShift Online
- Azure Kubernetes Service (AKS)
- Amazon Elastic Kubernetes Service (EKS)
Success
Managed Kubernetes is usually the best option for production teams that want to reduce operational overhead.
Hosted Solution Examples
| Hosted Solution | Cloud / Provider | Notes |
|---|---|---|
| GKE | Google Cloud | Managed Kubernetes with strong upgrade and autoscaling support |
| OpenShift Online | Red Hat | Managed OpenShift platform |
| AKS | Azure | Managed Kubernetes integrated with Azure services |
| EKS | AWS | Managed Kubernetes integrated with AWS IAM, ELB, EBS, and VPC |
Note
Older training material may refer to Amazon Elastic Container Service for Kubernetes. The current commonly used name is Amazon Elastic Kubernetes Service (EKS).
Turnkey vs Hosted Solutions
| Area | Turnkey Solutions | Hosted / Managed Solutions |
|---|---|---|
| VM provisioning | You provision | Provider provisions |
| Kubernetes install | Tool/script assisted | Provider installs |
| Control plane | You manage | Provider manages |
| Worker nodes | You manage | You or provider manages, depending on mode |
| Upgrades | You plan and execute | Provider-assisted |
| Customization | High | Medium |
| Operational effort | Higher | Lower |
| Production speed | Slower | Faster |
Warning
Turnkey solutions give more control, but they also increase operational responsibility.
Choosing Based on Use Case
Recommended:
- Minikube
- Kind
- kubeadm single-node cluster
Avoid:
- complex HA clusters
- expensive cloud resources
- production-grade managed add-ons
Tip
For CKA-style learning, kubeadm is very useful because it teaches real cluster setup concepts.
Recommended:
- kubeadm multi-node cluster
- managed Kubernetes dev cluster
- shared team cluster
Include:
- CNI plugin
- StorageClass
- Ingress controller
- basic monitoring
- namespace isolation
Recommended:
- GKE, EKS, AKS, or OpenShift
- HA control plane
- multiple worker nodes
- autoscaling
- monitoring and logging
- backup and restore
- network security controls
Danger
Do not run production workloads on experimental local clusters.
Cloud vs On-Prem
| Decision Factor | Cloud | On-Prem |
|---|---|---|
| Setup speed | Faster | Slower |
| Control | Medium | High |
| Operational burden | Lower with managed services | Higher |
| Hardware ownership | Provider-owned | Organization-owned |
| Scaling | Easier | Requires capacity planning |
| Compliance | Depends on requirements | Often preferred for strict internal control |
| Cost model | OpEx | CapEx + OpEx |
Question
Choose on-prem when you need strict infrastructure control. Choose managed cloud when speed, scalability, and operational simplicity matter more.
Production Best Practices
Recommended
- Prefer managed Kubernetes when possible
- Use kubeadm when you need full control or on-prem deployment
- Use HA control plane for production
- Separate control plane and worker nodes
- Use multiple availability zones in cloud
- Use production-ready CNI and CSI drivers
- Enable centralized logging and monitoring
- Use automated upgrades carefully
- Back up etcd for self-managed clusters
- Use RBAC and least privilege
- Use infrastructure as code for repeatability
Do's
- Choose infrastructure based on cluster purpose
- Use Minikube for local learning
- Use kubeadm to understand real cluster setup
- Use managed Kubernetes for production when possible
- Plan networking, storage, monitoring, and security early
- Validate node sizing before production rollout
- Automate provisioning with IaC tools
- Keep cluster upgrades planned and tested
Don'ts
- Don't use Minikube for production
- Don't choose self-managed clusters without operations expertise
- Don't ignore patching and upgrades
- Don't deploy production clusters without monitoring
- Don't expose the API server without strong security
- Don't use one design for every workload
- Don't forget backup and disaster recovery planning
- Don't assume hosted Kubernetes means zero responsibility
Warning
Managed Kubernetes reduces operational work, but you are still responsible for application security, RBAC, networking policies, workload configuration, and cost control.
Common Infrastructure Selection Mistakes
| Mistake | Problem |
|---|---|
| Using local tools for production | No HA, poor reliability |
| Choosing self-managed without operations skills | Upgrade and security risks |
| Ignoring cloud-native integrations | More manual work |
| No storage planning | Stateful apps fail |
| No CNI evaluation | Network policy or routing issues |
| No cost review | Unexpected cloud bills |
| No HA planning | Outages during node failures |
| No upgrade strategy | Version drift and security gaps |
Bug
Kubernetes installation is only the first step. Long-term operations usually decide whether the platform succeeds.
Example Decision Matrix
| Requirement | Recommended Choice |
|---|---|
| Quick local learning | Minikube |
| CKA practice and internals | kubeadm |
| Local multi-node testing | kubeadm or Kind |
| Enterprise private cloud | OpenShift / VMware Tanzu / kubeadm |
| AWS production | EKS |
| GCP production | GKE |
| Azure production | AKS |
| Full infrastructure control | kubeadm or turnkey |
| Lowest operational overhead | managed Kubernetes |
Reference Architecture for This Course
For learning purposes, a simple local cluster is enough.
Example design:
Cluster layout:
| Node | Role |
|---|---|
| master-01 | Control plane |
| worker-01 | Worker |
| worker-02 | Worker |
Note
This design is good for learning and labs, but production requires HA control plane, multiple worker nodes, monitoring, backups, and stronger security.
Quick Checklist
Before choosing infrastructure, confirm:
- Is this for learning, testing, or production?
- Do you need single-node or multi-node?
- Do you need HA?
- Are you using cloud or on-prem?
- Who will manage upgrades?
- Who will patch the nodes?
- What CNI plugin will be used?
- What storage backend will be used?
- How will monitoring and logging work?
- How will backups be handled?
- What is the expected traffic pattern?
- What is the cost model?
Summary
Quote
- Kubernetes can run locally, on-prem, or in the cloud
- Minikube is best for local learning
- kubeadm is best for learning real cluster setup and custom clusters
- Turnkey solutions automate deployment but still require infrastructure management
- Hosted solutions provide Kubernetes as a managed service
- Production clusters should prioritize HA, security, monitoring, backup, and upgrade strategy