Why kubectl run command is often misunderstood?

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 This change caused confusion for users upgrading their Kubernetes clusters or learning from outdated tutorials.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

1. Use kubectl run only for temporary tasks:      

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

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

kubectl create deployment nginx --image=nginx  

1. 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!