# Kubernetes Troubleshooting Mindset: How I Approach Production Issues One of the biggest lessons I’ve learned in my Kubernetes journey is this: > *Most production incidents are not solved by knowing more commands.* > > *They’re solved by having a systematic troubleshooting process.* When I first started learning Kubernetes, my troubleshooting strategy was simple: ```plaintext Try random commands until something makes sense. ``` Sometimes it worked. Most of the time, it wasted valuable time and created more confusion. After preparing for the [CKA](https://www.credly.com/badges/e72821a9-97a5-4ee8-a7f6-93f40246e864/public_url), working with Kubernetes, and spending countless hours troubleshooting broken deployments, failed Pods, networking issues, and cluster problems, I realized that effective troubleshooting is more about mindset than commands. This article covers the troubleshooting framework I follow whenever I face Kubernetes issues. ## **The Biggest Mistake Engineers Make** When something breaks, many engineers immediately jump to conclusions. Examples: * “The application must be broken.” * “The network is down.” * “Kubernetes is acting weird.” * “The deployment failed.” These assumptions often lead troubleshooting in the wrong direction. Instead, I try to follow a simple principle: > *Observe first. Assume later.* ## **My Kubernetes Troubleshooting Framework** Whenever I encounter a problem, I follow this sequence: ```plaintext Observe ↓ Scope ↓ Gather Evidence ↓ Validate Assumptions ↓ Fix ↓ Verify ↓ Document ``` Let’s break it down. ## **Step 1: Observe the Symptoms** Before touching anything, I ask: What exactly is failing? Examples: * Pod not starting * Service unreachable * Node NotReady * Application crashing * Storage issue * DNS issue At this stage, I avoid making assumptions. I simply gather facts. Commands I often use: ```plaintext kubectl get pods -A kubectl get nodes kubectl get svc -A ``` The goal is visibility. ## **Step 2: Define the Scope** The next question is: How big is the problem? Is it: * One Pod? * One Deployment? * One Namespace? * One Node? * The entire cluster? This step is important because it narrows the investigation. For example: If only one Pod is affected, the problem is likely application-related. If every workload is failing, the issue may be cluster-wide. ## **Step 3: Gather Evidence** This is where most troubleshooting begins. Instead of guessing, collect information. My favorite commands: ```plaintext kubectl describe pod ``` ```plaintext kubectl logs ``` ```plaintext kubectl logs --previous ``` ```plaintext kubectl describe node ``` ```plaintext kubectl get events --sort-by=.metadata.creationTimestamp ``` Events often reveal the story behind the failure. ## **Step 4: Follow the Dependency Chain** One of the most powerful troubleshooting techniques is following dependencies. For example: Application not working? Check: ```plaintext Application ↓ Pod ↓ Deployment ↓ Service ↓ DNS ↓ Network ↓ Node ↓ Cluster ``` Instead of randomly jumping between components, I trace the path systematically. This prevents missing critical clues. ## **Step 5: Validate Assumptions** This is where many engineers get stuck. Let’s say you believe DNS is broken. Don’t assume. Prove it. Example: ```plaintext kubectl exec -it pod-name -- nslookup kubernetes.default ``` If DNS works, move on. If DNS fails, investigate further. Evidence should drive conclusions — not intuition. ## **Step 6: Fix One Thing at a Time** A common mistake during incidents is changing multiple things simultaneously. Example: * Update deployment * Restart pods * Modify service * Change ConfigMap Now you don’t know which change fixed the issue. My rule: > *Make one change.* > > *Verify the result.* > > *Continue if necessary.* This makes troubleshooting much easier. ## **Step 7: Verify the Resolution** Never assume a problem is fixed. Verify it. Check: ```plaintext kubectl get pods ``` ```plaintext kubectl logs ``` ```plaintext kubectl get endpoints ``` ```plaintext kubectl get events ``` And most importantly: Verify that the application itself is functioning correctly. A green Pod does not always mean a healthy application. ## **Step 8: Document the Incident** This step is often skipped. After resolving an issue, document: * Root cause * Symptoms * Fix applied * Prevention steps Future-you will thank present-you. Many recurring issues can be solved in minutes if previous incidents were documented properly. ## **My Mental Checklist for Common Issues** ### **Pod Not Starting** Check: ```plaintext kubectl describe pod kubectl logs kubectl logs --previous ``` Look for: * ImagePullBackOff * CrashLoopBackOff * Resource limits * Missing ConfigMaps * Missing Secrets ### **Service Not Working** Check: ```plaintext kubectl get svc kubectl get endpoints kubectl describe svc ``` Verify: * Selectors * Ports * Target Ports * Pod readiness ### **DNS Problems** Check: ```plaintext kubectl get pods -n kube-system ``` Verify CoreDNS is healthy. Test: ```plaintext nslookup kubernetes.default ``` ### **Node NotReady** Check: ```plaintext kubectl describe node ``` Investigate: * Kubelet status * Disk pressure * Memory pressure * Networking ## **The Most Important Skill** After years of working in IT and preparing for Kubernetes certifications, I’ve come to believe that the most valuable Kubernetes skill is not: * Writing YAML * Memorizing commands * Passing certifications It’s troubleshooting. Production environments are unpredictable. Applications fail. Nodes fail. Networks fail. Configurations fail. The engineers who remain calm, gather evidence, and troubleshoot systematically are the ones who solve problems quickly. ## **Final Thoughts** Kubernetes troubleshooting is not about finding the perfect command. It’s about developing a repeatable process. Whenever something breaks, I remind myself: ```plaintext Observe ↓ Scope ↓ Gather Evidence ↓ Validate Assumptions ↓ Fix ↓ Verify ↓ Document ``` This simple framework has helped me solve countless Kubernetes issues more effectively than any command cheat sheet ever could. The goal isn’t to know everything. The goal is to know how to find the answer when things go wrong. And that’s what separates Kubernetes users from Kubernetes operators. ## **Connect With Me** If you’re preparing for Kubernetes certifications, pursuing the Kubestronaut journey, or working in the cloud-native ecosystem, I’d love to connect. Follow me for more articles on Kubernetes, CNCF certifications, DevOps, Platform Engineering, and Cloud-Native technologies. 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