Why kubectl run command is often misunderstood?

#kubernetes #devops #beginners #cloudnative

The kubectl run command is frequently misunderstood due to its evolving behavior, ambiguous use cases, and overlap with other Kubernetes commands. Below is a breakdown of why confusion persists, especially among beginners and those preparing for the CKA exam:

1. Behavior Changed Drastically Across Kubernetes Versions

Pre-1.18: kubectl run created a Deployment by default. For example:
```
kubectl run nginx --image=nginx  
```
This generated a Deployment, ReplicaSet, and Pod. Users familiar with older versions might still expect this behavior.
Post-1.18: The command was simplified to create a Pod directly. The same command now creates a single Pod, not a Deployment. This change caused confusion for users upgrading their Kubernetes clusters or learning from outdated tutorials.

2. Imperative vs. Declarative Workflow Confusion-

kubectl run is an imperative command (directly creates resources), while Kubernetes emphasizes a declarative approach (using YAML manifests).

Beginners often misuse kubectl run for complex or permanent workloads, not realizing it’s designed for quick, temporary tasks.
Example: Using kubectl run to start a Pod instead of writing a Deployment YAML for long-running applications (which is error-prone and not scalable).

3. Misleading Flags and Overlapping Commands

Flags like --replicas or --port suggest it can create Deployments or Services, but this is no longer true post-1.18.
Users might confuse kubectl run with similar commands:
kubectl create deployment: Creates a Deployment.
kubectl create job: Creates a Job.
kubectl expose: Creates a Service.
Example: Running kubectl run web --image=nginx --port=80 only creates a Pod. To expose it as a Service, you must separately run kubectl expose.

4. Lack of Clarity in Documentation

The kubectl run --help output includes legacy flags (e.g., --generator, --schedule) that are deprecated or irrelevant in newer versions.
Users often misinterpret flags like --restart=Never (creates a Pod) vs. --restart=Always (default for Pods) vs. --restart=OnFailure (used for Jobs).

5. Assumptions About Scalability

Users might assume a Pod created with kubectl run is scalable, but a standalone Pod is not managed by a controller (e.g., Deployment, ReplicaSet). If the Pod crashes, Kubernetes will restart it (due to the default restartPolicy: Always), but it won’t self-heal if the node fails.
Example:

kubectl run myapp --image=myapp

This creates a single Pod. For scalability, you need a Deployment:

kubectl create deployment myapp --image=myapp --replicas=3

6. Misuse for Non-Pod Workloads

Users might try to create Jobs, CronJobs, or Deployments with kubectl run, leading to errors.
Example:

kubectl run job --image=busybox --restart=OnFailure -- echo "Hello"

This works (creates a Job) but is inconsistent with the post-1.18 behavior. The safer approach is to use kubectl create job.

7. Confusion with Interactive Pods

While kubectl run can start interactive Pods (e.g., kubectl run -it debug --image=busybox -- sh), users might not realize these Pods are temporary and not production-ready.

8. CKA Exam Pitfalls

In the CKA exam, time pressure leads candidates to use kubectl run for quick fixes. However, misunderstanding its behavior can lead to mistakes:
Expecting a Deployment but getting a Pod.
Forgetting to add --dry-run=client -o yaml to generate YAML templates. - Not cleaning up temporary Pods (using --rm for auto-deletion).

How to Avoid Misunderstandings

Use kubectl run only for temporary tasks:

kubectl run -it --rm test --image=busybox --command -- sleep 3600

Prefer declarative YAML for production workloads.
Learn the modern behavior (post-1.18): Assume it creates Pods unless flags like --schedule (for CronJobs) are used.
Use kubectl create for controllers:

kubectl create deployment nginx --image=nginx

Generate YAML with --dry-run:

kubectl run nginx --image=nginx --dry-run=client -o yaml > pod.yaml

Summary of Key Reasons for Confusion

Reason	Example Misunderstanding
Version behavior changes	Expecting Deployments but getting Pods.
Imperative vs. declarative	Using `run` for production instead of YAML.
Overlapping commands	Confusing `run` with `create deployment` or `expose`.
Deprecated flags	Trying to use `--generator` in newer versions.
Lack of scalability	Assuming Pods created by `run` are self-healing.

By understanding these pitfalls, you’ll avoid common mistakes and use kubectl run effectively—especially in time-sensitive scenarios like the CKA exam!