Helm vs Kubectl — What, Why, and When to Use Each

 

☸️ Helm vs Kubectl — What, Why, and When to Use Each

If you work with Kubernetes, you will almost always use both kubectl and Helm — but for different purposes.

The confusion usually comes from thinking they do the same thing.
They don’t.


🧠 One-Line Summary (Remember This)

kubectl manages Kubernetes resources directly
Helm manages Kubernetes applications as packages


🧩 High-Level Picture

Photo Credit: Internet
Helm ───► generates Kubernetes YAML ───► kubectl ───► Kubernetes API Server

👉 Helm uses Kubernetes
👉 kubectl talks directly to Kubernetes


1️⃣ What Is kubectl?

🔹 Definition

kubectl is the official Kubernetes command-line tool to interact with a cluster.

It:

  • creates resources

  • updates resources

  • deletes resources

  • inspects cluster state


🔹 What kubectl Works With

  • Pods

  • Deployments

  • Services

  • ConfigMaps

  • Secrets

  • Nodes

  • Namespaces


🔹 Common kubectl Commands

kubectl get pods kubectl describe pod my-pod kubectl apply -f deployment.yaml kubectl delete service my-service kubectl logs my-pod kubectl exec -it my-pod -- bash

🔹 When to Use kubectl

✅ Debugging
✅ Inspecting cluster state
✅ One-off changes
✅ Day-to-day operations
✅ Troubleshooting production issues


2️⃣ What Is Helm?

🔹 Definition

Helm is a package manager for Kubernetes.

It lets you:

  • package multiple Kubernetes resources together

  • version them

  • deploy them consistently


🔹 Helm Manages Applications, Not Just Resources

An application may include:

  • Deployment

  • Service

  • ConfigMap

  • Secret

  • HPA

  • Ingress

👉 Helm treats all of this as one unit (a chart).


🔹 Helm Terminology (Important)

TermMeaning
ChartKubernetes application template
ReleaseInstalled instance of a chart
ValuesConfiguration inputs
RepositoryChart storage

🔹 Common Helm Commands

helm install myapp ./my-chart helm upgrade myapp ./my-chart helm rollback myapp 1 helm list helm uninstall myapp

🔹 When to Use Helm

✅ Installing applications
✅ Managing complex deployments
✅ Handling multiple environments (dev, stage, prod)
✅ Versioning and rollback
✅ CI/CD pipelines


3️⃣ Key Difference: Resource vs Application

AspectkubectlHelm
LevelResource-levelApplication-level
YAMLRaw YAMLTemplated YAML
Versioning❌ No✅ Yes
Rollback❌ Manual✅ Built-in
ReusabilityLowHigh
Environment configManualValues files

4️⃣ Real-World Example (This Makes It Click)

❌ Without Helm (kubectl only)

kubectl apply -f deployment.yaml kubectl apply -f service.yaml kubectl apply -f configmap.yaml kubectl apply -f ingress.yaml

Problems:

  • Hard to track versions

  • No rollback

  • YAML duplication across environments


✅ With Helm

helm install order-service ./order-chart -f values-prod.yaml

Benefits:

  • One command

  • Versioned release

  • Easy rollback

  • Clean environment separation


5️⃣ How They Work Together (Very Important)

👉 Helm does NOT replace kubectl
👉 They are complementary

Typical Workflow

helm install myapp ./chart kubectl get pods kubectl logs myapp-pod kubectl exec -it myapp-pod -- bash

Helm:

  • deploys the app

kubectl:

  • observes

  • debugs

  • operates


6️⃣ CI/CD Perspective (Real Industry Usage)

In CI/CD Pipelines

StageTool
DeployHelm
UpgradeHelm
RollbackHelm
Debugkubectl
Health checkkubectl

7️⃣ Common Confusions (Cleared)

❓ Can Helm work without kubectl?

❌ No — Helm ultimately uses the Kubernetes API (like kubectl).


❓ Can kubectl replace Helm?

❌ No — kubectl has:

  • no templating

  • no versioning

  • no rollback


❓ Do I need both?

✅ Yes — almost always.


8️⃣ Mental Model (Easy to Remember)

kubectl = screwdriver (low-level tool)
Helm = toolbox with instructions (high-level tool)


🎯 Interview-Ready Answer

kubectl is used to manage and debug individual Kubernetes resources, while Helm is used to package, version, and deploy complete Kubernetes applications. Helm simplifies complex deployments, and kubectl is used for inspection and troubleshooting.


📝 One-Line Takeaway

Use Helm to deploy applications.
Use kubectl to operate and debug the cluster.

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