Cluster API: Declarative Cluster Lifecycle Management

Introduction

In late 2019, the Cluster API project reached v1alpha1, introducing a declarative, Kubernetes-native approach to managing cluster lifecycles. Unlike infrastructure-specific tools (kops for AWS, kubeadm for on-premises), Cluster API provided a unified API for creating, upgrading, and deleting Kubernetes clusters across cloud providers and on-premises infrastructure.

This mattered because it addressed a fundamental gap: how to manage Kubernetes clusters using Kubernetes itself. Cluster API enabled teams to treat clusters as declarative resources, apply GitOps practices to infrastructure, and manage multi-cloud deployments with consistent tooling. It represented a shift from imperative cluster management (CLI commands, scripts) to declarative infrastructure as code.

Historical note: Cluster API began as a Kubernetes SIG Cluster Lifecycle project in 2018, with v1alpha1 representing the first stable API. It would become the foundation for many Kubernetes management platforms and multi-cluster tools.

Cluster API Concepts

Core Resources

Cluster: Represents a Kubernetes cluster with its desired state (Kubernetes version, infrastructure provider).
Machine: Represents a single node (control plane or worker) with its machine type, image, and configuration.
MachineDeployment: Manages a set of Machines, similar to Deployment managing Pods.
MachineSet: Lower-level controller for managing Machine replicas.
Infrastructure Providers: Cloud-specific implementations (AWS, Azure, GCP, vSphere, etc.).

Declarative Model

Cluster API resources are standard Kubernetes Custom Resources (CRDs), enabling:

GitOps: Store cluster definitions in Git, apply via kubectl apply.
Version Control: Track cluster changes over time.
Automation: Use Kubernetes controllers to manage cluster lifecycles.
Multi-Cluster Management: Manage hundreds of clusters from a single management cluster.

Cluster API vs Terraform + kubeadm vs Cloud-Specific Tools

Capability	Cluster API	Terraform + kubeadm	kops (AWS)
Infrastructure Scope	Multi-cloud, on-premises	Multi-cloud, on-premises	AWS-only
API Model	Kubernetes-native (CRDs)	Terraform HCL	kops CLI + YAML
GitOps	Native (kubectl apply)	Terraform Cloud/Enterprise	Manual (S3 state)
Multi-Cluster	Excellent (management cluster)	Good (Terraform workspaces)	Limited (per-cluster)
Upgrade Model	Declarative (update Cluster spec)	Imperative (Terraform apply)	Imperative (kops upgrade)
Learning Curve	Moderate (Kubernetes concepts)	High (Terraform + kubeadm)	Moderate (AWS + kops)
Provider Support	Multiple (AWS, Azure, GCP, vSphere)	All (via providers)	AWS-only
Best For	Multi-cloud, GitOps, automation	Infrastructure as Code, flexibility	AWS-only deployments

Architecture Patterns

Management Cluster Pattern

Cluster API uses a management cluster (bootstrap cluster) to create and manage workload clusters:

Bootstrap: Create a small management cluster (can be kind, minikube, or existing cluster).
Install Cluster API: Deploy Cluster API controllers and infrastructure providers.
Create Workload Clusters: Define Cluster and Machine resources; Cluster API provisions infrastructure.
Manage Lifecycle: Upgrade, scale, or delete clusters by updating Cluster API resources.

Infrastructure Providers

Cluster API supports multiple infrastructure providers:

AWS (CAPA): Cluster API Provider for AWS
Azure (CAPZ): Cluster API Provider for Azure
GCP (CAPG): Cluster API Provider for GCP
vSphere (CAPV): Cluster API Provider for vSphere
Docker (CAPD): Cluster API Provider for Docker (testing)
Metal3 (CAPM3): Cluster API Provider for bare metal

Getting Started with Cluster API

1. Bootstrap Management Cluster

# Using kind for management cluster
kind create cluster --name cluster-api-management

# Install Cluster API
clusterctl init --infrastructure aws

2. Create Workload Cluster

apiVersion: cluster.x-k8s.io/v1alpha1
kind: Cluster
metadata:
  name: my-workload-cluster
  namespace: default
spec:
  clusterNetwork:
    pods:
      cidrBlocks: ["192.168.0.0/16"]
  controlPlaneEndpoint:
    host: ""
    port: 6443
  infrastructureRef:
    apiVersion: infrastructure.cluster.x-k8s.io/v1alpha1
    kind: AWSCluster
    name: my-workload-cluster
---
apiVersion: infrastructure.cluster.x-k8s.io/v1alpha1
kind: AWSCluster
metadata:
  name: my-workload-cluster
spec:
  region: us-west-2
  sshKeyName: my-keypair

3. Apply Cluster Definition

# Apply cluster definition
kubectl apply -f cluster.yaml

# Watch cluster creation
kubectl get clusters
kubectl get machines

Multi-Cloud Cluster Management

Cluster API excels at managing clusters across multiple cloud providers:

# AWS cluster
apiVersion: cluster.x-k8s.io/v1alpha1
kind: Cluster
metadata:
  name: aws-cluster
spec:
  infrastructureRef:
    kind: AWSCluster
    name: aws-cluster
---
# Azure cluster
apiVersion: cluster.x-k8s.io/v1alpha1
kind: Cluster
metadata:
  name: azure-cluster
spec:
  infrastructureRef:
    kind: AzureCluster
    name: azure-cluster
---
# GCP cluster
apiVersion: cluster.x-k8s.io/v1alpha1
kind: Cluster
metadata:
  name: gcp-cluster
spec:
  infrastructureRef:
    kind: GCPCluster
    name: gcp-cluster

All three clusters can be managed from a single management cluster using standard Kubernetes tooling.

GitOps Integration

Cluster API resources are standard Kubernetes resources, enabling GitOps workflows:

# Store cluster definitions in Git
git add clusters/
git commit -m "Add new workload cluster"
git push

# ArgoCD or FluxCD syncs to management cluster
# Cluster API provisions infrastructure automatically

ArgoCD Example

apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
  name: workload-clusters
spec:
  source:
    repoURL: https://github.com/org/cluster-definitions
    path: clusters
  destination:
    server: https://management-cluster:6443

Practical Considerations

Management Cluster Requirements

Resources: Management cluster needs adequate resources to run Cluster API controllers.
High Availability: Management cluster should be HA; if it fails, workload cluster management stops.
Network Access: Management cluster needs network access to provision infrastructure (AWS, Azure, GCP APIs).

Infrastructure Provider Maturity

In 2019, infrastructure providers were at different maturity levels:

AWS (CAPA): Most mature, production-ready.
Azure (CAPZ): Good support, actively developed.
GCP (CAPG): Early but functional.
vSphere (CAPV): Good for on-premises.
Docker (CAPD): Testing and development only.

Upgrade Workflows

Cluster API enables declarative upgrades:

# Update cluster to new Kubernetes version
apiVersion: cluster.x-k8s.io/v1alpha1
kind: Cluster
metadata:
  name: my-cluster
spec:
  # Update version
  topology:
    version: v1.17.0

Cluster API controllers handle the upgrade process automatically.

Comparison: Cluster API vs Cloud-Specific Tools

Advantages of Cluster API

Unified API: Same API across all cloud providers and on-premises.
GitOps Native: Standard Kubernetes resources enable GitOps workflows.
Multi-Cluster: Manage hundreds of clusters from a single management cluster.
Declarative: Infrastructure changes are declarative, not imperative.

Advantages of Cloud-Specific Tools

Maturity: kops, EKS, AKS, GKE have longer production histories.
Cloud Features: Better integration with cloud-specific features (IAM, networking, storage).
Simplicity: Single-purpose tools are simpler for single-cloud deployments.
Support: Cloud providers offer direct support for their managed services.

Caveats & Lessons Learned

Management Cluster Dependency: Workload clusters depend on management cluster; ensure HA and backups.
Provider Maturity: Infrastructure providers mature at different rates; verify provider stability.
Learning Curve: Cluster API requires understanding Kubernetes internals (CRDs, controllers).
Resource Requirements: Management cluster needs resources to run controllers and manage workload clusters.

Common Failure Modes

“Management cluster down”: If management cluster fails, workload cluster management stops; ensure HA.
“Provider credentials”: Infrastructure providers need cloud credentials; secure credential management is critical.
“Network connectivity”: Management cluster needs API access to cloud providers; verify network connectivity.

Conclusion

Cluster API’s v1alpha1 release in late 2019 introduced a paradigm shift in Kubernetes cluster management: treating clusters as declarative, Kubernetes-native resources. It enabled GitOps for infrastructure, unified multi-cloud management, and automated cluster lifecycles using the same tools and patterns teams used for applications.

While cloud-specific tools (kops, managed services) remained viable for single-cloud deployments, Cluster API opened new possibilities: multi-cloud strategies, infrastructure GitOps, and automated cluster management at scale. It represented the future of Kubernetes infrastructure management, where clusters were managed the same way as applications—declaratively, with version control, and using Kubernetes itself.

For teams managing multiple clusters across cloud providers or on-premises, Cluster API provided a unified approach that reduced operational complexity and enabled infrastructure automation at scale. It would become the foundation for many Kubernetes management platforms and multi-cluster tools in subsequent years.

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