Kubernetes controllers form the backbone of the Kubernetes control plane by continuously reconciling cluster state. While Kubernetes comes with many built-in controllers, creating custom controllers is essential to automate complex, domain-specific workflows beyond default capabilities. This post dives deep into the architecture, development, and deployment of custom Kubernetes controllers to empower you with the skills to automate advanced application workflows seamlessly.

Why Build Custom Kubernetes Controllers?

Out-of-the-box Kubernetes controllers handle basic resource reconciliation, but real-world applications often require bespoke automation logic for:

  • Complex lifecycle management of application components
  • Integrating third-party APIs or systems
  • Enforcing business rules and compliance
  • Managing composite or multi-resource workflows

Custom controllers, typically packaged as Operators, enable codifying these behaviors declaratively and at scale.

Core Concepts: CRDs and Controller Runtime

Custom controllers primarily revolve around two Kubernetes extensibility constructs:

  • Custom Resource Definitions (CRDs): Extend Kubernetes API by defining your own resource types tailored to your domain.
  • Controller Runtime: A powerful Go library that simplifies building controllers by managing event handling, reconciliation loops, caching, and leader election.

Together, they allow you to design reactive controllers that monitor and modify your custom resources to converge desired and actual state.

Architecture of a Custom Controller

At a high level, a custom controller consists of:

  1. CRD schema: Defines the spec and status fields of your custom resource.
  2. Controller logic: Implements the reconciliation loop to respond to resource events.
  3. Client & cache: Efficiently read and update Kubernetes resources.
  4. Event handlers: Watch resource changes and trigger reconcile requests.
  5. Leader election: Ensures high availability in multi-replica setups.

Kubernetes Custom Controller Architecture

Developing a Basic Custom Controller

Step 1: Define a Custom Resource Definition

Create a CRD YAML to represent your domain object, for example, AppWorkflow.

apiVersion: apiextensions.k8s.io/v1
kind: CustomResourceDefinition
metadata:
  name: appworkflows.example.com
spec:
  group: example.com
  versions:
    - name: v1alpha1
      served: true
      storage: true
      schema:
        openAPIV3Schema:
          type: object
          properties:
            spec:
              type: object
              properties:
                workflowSteps:
                  type: array
                  items:
                    type: string
            status:
              type: object
              properties:
                currentStep:
                  type: string
  scope: Namespaced
  names:
    plural: appworkflows
    singular: appworkflow
    kind: AppWorkflow
    shortNames:
      - awf
Step 2: Scaffold Controller Using Kubebuilder

Use Kubebuilder to generate boilerplate code and APIs:

kubebuilder init --domain example.com
kubebuilder create api --group example --version v1alpha1 --kind AppWorkflow

This scaffolds the project with CRD definitions and the basic reconciliation loop.

Step 3: Implement Reconciliation Logic

Inside the reconciler’s Reconcile method, implement your workflow automation:

func (r *AppWorkflowReconciler) Reconcile(ctx context.Context, req ctrl.Request) (ctrl.Result, error) {
    var appWorkflow examplev1alpha1.AppWorkflow
    if err := r.Get(ctx, req.NamespacedName, &appWorkflow); err != nil {
        return ctrl.Result{}, client.IgnoreNotFound(err)
    }

    // Fetch current status
    currentStep := appWorkflow.Status.CurrentStep

    // Logic to advance workflow steps
    nextStep := determineNextStep(currentStep, appWorkflow.Spec.WorkflowSteps)
    if nextStep != currentStep {
        appWorkflow.Status.CurrentStep = nextStep
        if err := r.Status().Update(ctx, &appWorkflow); err != nil {
            return ctrl.Result{}, err
        }
    }

    // Schedule next reconciliation
    return ctrl.Result{RequeueAfter: time.Minute * 5}, nil
}
Step 4: Deploy the Controller

Build and deploy your controller into the cluster:

make docker-build docker-push IMG=<your-image>
kubectl apply -f config/crd/bases/appworkflows.example.com.yaml
kubectl apply -f config/default

The controller now continuously reconciles AppWorkflow resources to automate complex multi-step processes.

Best Practices for Building Robust Controllers

  • Idempotency: Ensure reconciliation logic is safe to run multiple times without side effects.
  • Event Filtering: Use predicates to minimize unnecessary reconcile calls.
  • Status Subresource: Always update resource status via the status subresource to avoid conflicts.
  • Rate Limiting: Implement backoff and rate limiting to avoid overwhelming the API server.
  • Leader Election: Support multi-replica controller deployment with leader election for high availability.

Use Cases for Custom Controllers

  • Database Operators: Automate backups, schema migrations, failover for databases like Postgres or MySQL.
  • Machine Learning Pipelines: Manage ML workflows with custom resources representing datasets, models, and training jobs.
  • Complex Application Stacks: Automate multi-component apps with custom orchestration beyond Helm or plain manifests.
  • Security Enforcement: Implement policy controllers for compliance and governance automation.

Conclusion

Creating custom Kubernetes controllers unlocks the true power of Kubernetes extensibility by embedding domain logic directly into the cluster’s control loop. By mastering CRDs, controller-runtime, and reconciliation patterns, you can automate intricate application workflows, improve reliability, and accelerate delivery.

Whether you are managing big data pipelines, cloud-native applications, or enterprise workloads, custom controllers give you the ability to declaratively automate every step — enabling scalable and maintainable Kubernetes-native automation.