Cluster API Quickstart: A Step-by-Step Guide

Cluster API introduces a powerful architectural pattern: using a dedicated Kubernetes cluster to create and manage other Kubernetes clusters. This central "management cluster" runs the CAPI controllers, acting as a single control plane for your entire fleet of "workload clusters." This model provides a unified point for automation, policy enforcement, and observability across multiple cloud providers or on-premises environments. It's the key to eliminating configuration drift and streamlining operations at scale.

This guide will walk you through the entire process of building this architecture, starting with the fundamentals of a cluster api quickstart and progressing to advanced techniques for managing a secure and consistent multi-cluster infrastructure.

Key takeaways:

• Treat clusters as code: Cluster API enables a declarative approach to lifecycle management. By defining clusters in version-controlled YAML, you can automate provisioning, enforce consistency, and eliminate configuration drift across your fleet.
• The management cluster is your control plane: All workload clusters are orchestrated from a central management cluster. Securing this cluster and correctly configuring its providers is critical, as it governs the stability and security of your entire infrastructure.
• Scale beyond the CLI with a unified platform: While clusterctl is useful for individual tasks, managing a fleet requires a higher-level solution. Plural builds on Cluster API to provide GitOps automation, a single-pane-of-glass dashboard, and centralized security.

What Is Cluster API?

Cluster API (CAPI) is a Kubernetes project that automates cluster lifecycle management through a declarative, Kubernetes-style API. Instead of relying on scripts, installers, or ad-hoc tooling, you define the desired state of a cluster—Kubernetes version, node count, machine types, networking—in YAML, and CAPI’s controllers continuously reconcile the real environment to match that specification.

How Cluster API Works

CAPI requires an existing Kubernetes cluster, called the management cluster, which runs the CAPI controllers. This cluster is dedicated to managing other clusters and shouldn’t run application workloads. From here, you can provision any number of workload clusters across cloud or on-prem environments.

CAPI relies on a modular architecture built on CRDs and providers:

Core Components

• Management cluster
  The Kubernetes cluster hosting all CAPI controllers and acting as the control plane for fleet operations.
• Infrastructure providers
  Required components that provision VMs, load balancers, networks, and other resources on platforms such as AWS, Azure, GCP, or vSphere.
• Bootstrap providers
  Responsible for preparing machines to join a Kubernetes cluster, commonly using kubeadm.
• Control plane providers
  Provision and manage the Kubernetes control plane for workload clusters.

This design lets teams define and manage clusters the same way they manage any Kubernetes object, using reconciliation loops rather than imperative scripts.

Why CAPI Matters for Fleet Management

For teams operating multiple Kubernetes clusters, CAPI brings consistency, automation, and standardization. Treating clusters as code eliminates configuration drift and adds version control to your infrastructure. This helps platform teams enforce baseline configurations, apply GitOps practices, and operate a scalable fleet without fragile custom tooling.

Plural integrates directly with Cluster API, turning Plural into your management control plane. You can provision and manage clusters across environments while orchestrating application deployments from the same interface. This unifies infrastructure and workload automation under a secure, GitOps-driven workflow, making multi-cluster operations significantly easier to operate at scale.

What You Need Before You Start

Before you initialize a management cluster, you need a clean local environment and the right tooling in place. Proper setup avoids compatibility issues and lays the groundwork for a reliable Cluster API workflow. This section covers the essentials: the command-line tools you need, how to configure clusterctl, and what to know about CAPI’s provider model. With these prerequisites ready, you’ll have a stable foundation for building and managing Kubernetes clusters at scale with Plural.

Gather Your Tools and Dependencies

Cluster API relies on standard Kubernetes tooling. Make sure the following are installed and configured:

• kubectl
  Your primary interface to the management and workload clusters.
• kind
  Useful for creating a local management cluster for testing. It runs Kubernetes “nodes” as Docker containers.
• Docker
  Required for kind to function.
• Helm
  Kubernetes’ package manager, used for installing and managing CAPI providers.

These tools follow the typical installation paths on macOS, Linux, and Windows. For step-by-step instructions, see the official Cluster API Quick Start.

Install and Configure clusterctl

clusterctl is the main CLI for managing Cluster API. It installs providers, initializes management clusters, and handles upgrades. Install it via Homebrew (macOS/Linux) or download the binary directly.

After installation, confirm the version:

clusterctl version

Use a current release to ensure compatibility with provider components. The clusterctl init command prepares your management cluster by installing CRDs and all selected providers.

Review Provider-Specific Requirements

Cluster API uses a provider model to support different infrastructures and Kubernetes distributions. Before initializing your management cluster, identify which providers you need and ensure their prerequisites are in place:

• Infrastructure providers
  Required for provisioning compute, networking, and load balancers (AWS, Azure, GCP, vSphere, and others).
• Bootstrap providers
  Convert raw machines into Kubernetes nodes. kubeadm is the default and most widely used.
• Control plane providers
  Manage the Kubernetes control plane components. The kubeadm control plane provider is the standard option.

Each infrastructure provider comes with its own setup requirements, such as cloud credentials, IAM permissions, or network configuration. These must be ready before you run clusterctl init so your management cluster can successfully provision workload clusters.

Set Up Your Management Cluster

The management cluster is the backbone of any Cluster API deployment. It runs the CAPI controllers that coordinate the creation, upgrade, and deletion of workload clusters. This cluster should be dedicated to management tasks, especially in production, because it effectively becomes the control plane for your entire Kubernetes fleet.

Plural follows the same model: the Plural control plane runs inside a management cluster and communicates with lightweight agents deployed to workload clusters. This architecture gives you centralized governance and lifecycle management without exposing workload clusters directly.

Select and Configure a Provider

Before initializing the management cluster, decide which providers you’ll use. Providers determine how CAPI interacts with your infrastructure:

• Infrastructure providers provision VMs, networks, and load balancers for a specific cloud or on-prem platform (AWS, Azure, vSphere, and others).
• Bootstrap providers configure those machines into Kubernetes nodes.

Your chosen infrastructure provider determines which controllers clusterctl will install. For example, using AWS requires the Cluster API Provider for AWS (CAPA), which in turn requires that you configure AWS credentials and IAM permissions so CAPI can provision resources on your behalf.

Initialize the Management Cluster

Once your Kubernetes cluster is ready, use clusterctl to install all required CAPI components. You “convert” a regular cluster into a management cluster by running:

clusterctl init --infrastructure aws

This installs the core Cluster API controllers and the AWS provider controllers, along with the CRDs that define cluster, machine, and control plane resources. After initialization, the cluster becomes capable of managing workload clusters across your selected provider.

Validate and Check Cluster Health

After initialization, verify that the controllers are running:

• Check the pods created in the CAPI namespaces, such as capi-system and the provider-specific namespace.
• Look for controller deployments like capi-controller-manager or capa-controller-manager.
• Confirm that the new CRDs are available with kubectl get clusters.

Manual checks work for development, but managing a fleet at scale is easier with integrated tooling. Plural’s multi-cluster dashboard provides a consolidated view of cluster health and resources across all environments, removing the need to switch kubeconfigs.

Apply Security Best Practices

Because the management cluster governs every workload cluster, its security must be tightly controlled. Apply strict RBAC, limit API server access, and ensure cloud credentials follow least-privilege principles. Many bootstrap and provisioning failures stem from misconfigured credentials, which makes early validation essential.

Plural enforces consistent security policies across your fleet. Using Global Services, you can define standardized RBAC and propagate it automatically to every cluster, minimizing drift and reducing operational risk.

Create and Manage Workload Clusters

With your management cluster ready, you can start provisioning and operating workload clusters. This is where Cluster API’s declarative model becomes most valuable—clusters are defined, updated, and versioned as code. That makes cluster creation predictable, testable, and easily integrated into GitOps pipelines. By treating clusters as version-controlled artifacts, you gain repeatable rollouts, safer updates, and reliable recovery procedures.

While the CLI workflow works for small environments, it becomes difficult to scale. Managing dozens or hundreds of clusters manually introduces drift, complicates upgrades, and increases operational overhead. At that point you need a platform-wide orchestration layer. Plural extends Cluster API with a unified control plane that centralizes visibility, policy enforcement, and lifecycle automation across your entire fleet.

Configure Your First Workload Cluster

Start by generating a manifest for your workload cluster. clusterctl provides a templating workflow that produces a ready-to-edit YAML definition:

clusterctl generate cluster <name> --kubernetes-version <version>

This generates a full cluster specification, including control-plane and worker nodes. You can adjust machine types, regions, or provider-specific fields before committing the manifest to version control. When ready, create the cluster:

kubectl apply -f <cluster.yaml>

Cluster API then begins provisioning all required infrastructure and Kubernetes components.

Deploy and Scale the Cluster

Once the manifest is applied, CAPI’s controllers reconcile your desired state automatically. You interact with clusters the same way you interact with other Kubernetes resources. Scaling becomes a matter of updating a MachineDeployment’s replica count and re-applying the file. Because the workflow is entirely declarative, it fits naturally into CI/CD pipelines and enforces consistent configuration across environments.

Monitor and Verify Your Setup

After initiating provisioning, check cluster status with:

kubectl get clusters

or use -o wide for more detail. You can inspect machine readiness, control-plane status, and infrastructure objects through standard Kubernetes commands.

CLI tools work well when you only manage one or two clusters, but fleet-wide monitoring quickly becomes unmanageable. Plural provides a centralized, multi-cluster dashboard that surfaces cluster state and resource health across all environments without requiring context switches or juggling kubeconfig files.

Develop an Update Strategy

Cluster upgrades and node replacements are routine, but they can fail due to configuration issues or infrastructure constraints. To diagnose provisioning or bootstrap failures, use:

clusterctl describe --show-conditions all <cluster-name>

This surfaces detailed conditions, events, and reconciliation errors, making it easier to locate root causes.

A solid update strategy involves more than applying patches—it requires consistent validation and predictable rollback paths. Plural enhances this workflow with automated preflight checks to catch incompatible updates before they break workloads. This reduces downtime and simplifies long-term cluster maintenance, especially at fleet scale.

Troubleshoot Common Issues

Even with a well-configured environment, Cluster API workflows occasionally fail during installation, provisioning, or updates. Most issues fall into predictable categories—bootstrap failures, configuration mistakes, or infrastructure constraints. The management cluster is the source of truth for diagnosing all of them, since it hosts the controllers responsible for reconciling your workload clusters.

Troubleshooting typically involves reviewing resource definitions, checking controller logs, and validating the underlying infrastructure. Understanding common failure modes helps you resolve issues quickly and keep clusters healthy. Plural simplifies this process by centralizing logs, events, and cluster states in a single dashboard, eliminating the need to jump between kubeconfigs or cloud consoles.

Solve Installation Challenges

Provisioning failures often originate during bootstrap or infrastructure setup:

• A node may fail to join the control plane because a network policy blocks communication.
• Infrastructure providers may fail to provision VMs or load balancers due to incorrect IAM permissions or missing credentials.

When bootstrap fails, start by inspecting the relevant controller logs in the management cluster. These messages typically point directly to misconfigurations in Cluster API resources or provider credentials. Most installation failures leave clear traces in these logs.

Fix Configuration Problems

Misconfigured manifests are a frequent source of errors. Invalid instance types, wrong image IDs, or incorrect network settings can all prevent clusters from provisioning. For example, with CAPZ, failures to create VMs usually trace back to missing or invalid Azure credentials, which appear as explicit authentication errors in the controller logs.

Validate your manifests before applying them and enforce reviews through GitOps. Plural’s Stacks feature extends this with a Kubernetes-native workflow for managing Terraform at scale, giving you versioning, automation, and guardrails that help prevent configuration drift and reduce manual mistakes.

Address Network and Resource Issues

As environments grow, network and system limits can become bottlenecks. With the Docker provider, a common issue is hitting OS-level inotify limits when creating many nodes. You’ll see errors like:

Failed to create inotify object: Too many open files

Cloud platforms expose different constraints: subnet IP exhaustion, API rate limits, or quota caps. Monitoring these limits across clusters is essential to prevent provisioning failures. Plural provides unified observability across your fleet, helping surface resource exhaustion before it disrupts reconciliation.

Key Debugging Tips

Your most effective troubleshooting tool is:

clusterctl describe cluster <cluster-name> --show-conditions all

It provides a consolidated view of Cluster API objects and their conditions, making it easy to identify stuck machines or failed control-plane operations.

Additional debugging steps include:

• Inspect controller logs in the management cluster.
• Check Kubernetes events: kubectl get events --sort-by='.lastTimestamp'
• For node-level issues, SSH into machines to review kubelet logs.

Plural brings these workflows into a single interface, letting you inspect logs, events, and resource states for any cluster without juggling contexts. This significantly reduces the overhead of debugging across environments and improves operational efficiency at fleet scale.

Explore Advanced Features and Best Practices

Once your initial clusters are online, the next step is building a scalable, production-ready operational model. Cluster API provides several advanced capabilities that help automate remediation, enforce configuration consistency, and improve resilience. Adopting these features reduces manual maintenance, prevents drift, and strengthens your overall multi-cluster strategy. Plural extends these workflows by giving you centralized visibility and automation across your entire fleet.

Implement Machine Health Checks

MachineHealthCheck provides automated node remediation based on health conditions. When a node enters a prolonged NotReady state or fails other readiness checks, CAPI can delete and recreate it without operator intervention.

For manual debugging, use:

clusterctl describe --show-conditions <machine>

MachineHealthCheck gives your clusters self-healing capabilities that prevent common node failures from escalating into outages. Plural layers on top of this by surfacing machine health across clusters in a unified dashboard.

Use ClusterClass for Standardization

Maintaining consistency across many clusters is challenging without a templating framework. ClusterClass provides reusable, parameterized definitions for cluster topology, node pools, versions, and infrastructure settings. It becomes the authoritative blueprint for every cluster you deploy.

By standardizing control-plane layouts, machine types, networking settings, and Kubernetes versions, ClusterClass:

• Reduces configuration errors
• Makes new clusters faster to provision
• Ensures uniform compliance and operational baselines

This becomes essential when operating dozens or hundreds of clusters, and Plural integrates cleanly with ClusterClass to enforce organizational defaults.

Plan for Backup and Recovery

Your management cluster stores the entire declarative state of your fleet, making backup and disaster recovery critical. Losing it without backups means losing the ability to reconcile or update workload clusters.

A sound strategy includes:

• Regular backups of the management cluster’s etcd
• Backups of workload cluster resources and persistent volumes (e.g., via Velero)
• Periodic restore testing to validate procedures

These practices protect against data loss and ensure rapid recovery in case of failures.

Optimize for Performance

As the number of clusters and machines grows, understanding the limits of your infrastructure and Cluster API controllers becomes essential.

Examples include:

• Local Docker environments hitting inotify limits during heavy provisioning
• Cloud environments running into subnet IP exhaustion or API rate limits
• Management cluster controller managers becoming bottlenecked under heavy workloads

Monitor API server and controller performance and tune concurrency and resource settings accordingly. Ensuring your management cluster has adequate CPU, memory, and storage IOPS is critical for handling large-scale reconciliation.

By combining CAPI’s advanced features with Plural’s centralized automation and observability, you can operate a robust, secure, and consistent multi-cluster platform with significantly lower overhead.

How Plural Simplifies Cluster API Management

Cluster API delivers a strong foundation for declarative cluster lifecycle management, but scaling it across many clusters introduces operational complexity. Managing templates, securing access, coordinating upgrades, and keeping visibility across environments all become challenging as your fleet grows. Plural builds directly on Cluster API’s architecture and removes these bottlenecks by providing a unified control plane, GitOps-driven automation, and centralized security. The result is a streamlined, enterprise-ready workflow for managing Kubernetes at scale.

Automate Deployments

Cluster API works well at the command-line level, but relying on manual clusterctl workflows does not scale. Plural integrates CAPI providers into its GitOps-based deployment engine so that your entire cluster lifecycle is defined declaratively in Git.

When you commit changes—cluster creation, configuration updates, version bumps, or retirement—Plural’s deployment operator automatically detects them and reconciles the desired state across the fleet. This eliminates manual steps, prevents drift, and ensures all clusters remain consistently configured over time.

Gain Fleet-Wide Visibility

Running CAPI across multiple providers makes it difficult to maintain a consistent view of cluster health. Plural solves this with a built-in multi-cluster dashboard that provides real-time observability for every cluster, regardless of where it runs.

Plural’s agent-based, egress-only architecture means that clusters never need to expose inbound endpoints or rely on VPNs. You get detailed metrics and status for control planes, nodes, and workloads from a single interface, covering cloud, private network, and on-prem installations.

Centralize Security Controls

Managing credentials, RBAC, and access policies across many clusters is one of the hardest operational challenges in CAPI environments. Plural centralizes this by integrating with your existing SSO provider and mapping user actions through Kubernetes impersonation. All access is tied back to a verified identity.

Plural’s Global Services feature lets you define security policies once and propagate them across your entire fleet. This ensures that every cluster enforces the same RBAC and credential standards, reducing the risk of misconfiguration and simplifying compliance.

Streamline Operations

Debugging CAPI often requires combing through logs from multiple controllers, infrastructure providers, and machines. Plural reduces this friction by unifying Cluster API operations with infrastructure-as-code.

Using Plural Stacks, you can manage Terraform for provisioning cloud resources alongside the Cluster API definitions that consume those resources. This gives you a single view from the infrastructure layer up to the workload layer. When issues occur, you can inspect events, logs, and resource states directly in the Plural UI, making root-cause analysis significantly faster.

By layering automation, visibility, and centralized security on top of Cluster API, Plural provides a complete operational platform for running large-scale, multi-provider Kubernetes environments with confidence.

Related Articles

• Enterprise Kubernetes management, accelerated.
• Kubernetes Multi-Cluster Management: A Practical Guide

Frequently Asked Questions

What's the difference between a management cluster and a workload cluster? Think of the management cluster as the control center. It's a dedicated Kubernetes cluster that runs the Cluster API controllers, which are responsible for creating and managing other clusters. Your workload clusters are the ones that actually run your applications. This separation is key because it isolates the critical management functions from your application environments, improving security and stability.

Can I use an existing Kubernetes cluster as my management cluster? Yes, you can, and it's a common approach for testing or getting started. However, for production environments, it is strongly recommended to use a dedicated cluster for management. The management cluster holds the credentials and control over your entire fleet, so mixing it with application workloads increases the potential attack surface. A dedicated cluster ensures that your infrastructure's control plane is isolated and properly secured.

How does Cluster API relate to infrastructure-as-code tools like Terraform? They are complementary and often used together. Terraform is typically used to provision the foundational infrastructure that Cluster API needs, such as VPCs, subnets, and IAM roles. Once that base layer is ready, Cluster API takes over to manage the lifecycle of the Kubernetes clusters themselves. Plural Stacks streamlines this by providing a Kubernetes-native workflow to run and manage your Terraform configurations alongside your cluster definitions.

What happens if my management cluster goes down? Your existing workload clusters will continue to run their applications without any immediate impact. However, you will lose the ability to perform any management tasks on them. This means you won't be able to create new clusters, scale existing ones, or apply updates until the management cluster is restored. This scenario underscores the importance of having a solid backup and recovery plan for your management cluster.

Do I need to manage every cluster with command-line tools? While clusterctl and kubectl are the standard tools for interacting with Cluster API, relying on them alone becomes inefficient and error-prone as your fleet expands. Managing numerous clusters from the command line makes it difficult to enforce consistency or maintain a clear view of your infrastructure's health. A platform like Plural provides a unified dashboard and a GitOps workflow to manage your entire fleet from a single interface, transforming a manual process into an automated and observable one.