# Top 50 DevOps & Kubernetes Interview Questions & Answers 2026

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DevOps & Cloud · 2026 Edition
            
# 
              Top 50 DevOps & Kubernetes Interview Questions & Answers for 2026
            

            
              
            
            
              August 22, 2026
              ·
              20 min read
              ·
              RateMyInterview DevOps Experts
            
          

          

          
          
            
## 
              
                
              
              Key Takeaways — DevOps & SRE Interviews 2026
            

            
              - 
                •
                **Kubernetes Architecture Mastery:** Deep knowledge of `kube-apiserver`, etcd Raft consensus, kube-scheduler filters, kube-controller-manager loops, and CNI plugins (Calico/Cilium) is tested in 90% of DevOps interviews.
              

              - 
                •
                **IaC & Terraform State:** Terraform remote backend state locking with DynamoDB and S3, module versioning, drift detection, and `lifecycle &#123; prevent_destroy = true &#125;` rules.
              

              - 
                •
                **Zero-Downtime Deployment Patterns:** Clear distinction between Rolling Updates, Blue-Green, Canary deployments with Flagger/Istio, and GitOps synchronization via ArgoCD.
              

              - 
                •
                **Linux & Production Troubleshooting:** Systematic incident debugging using `strace`, `lsof`, `ss/netstat`, `tcpdump`, `journalctl`, and resolving `CrashLoopBackOff` and `OOMKilled` statuses.
              

            
          

          
          
            
## Table of Contents

            
              - [1. Kubernetes Cluster Architecture & Control Plane Internals](#k8s-architecture)

              - [2. Troubleshooting Pods: CrashLoopBackOff, OOMKilled & Pending](#pod-troubleshooting)

              - [3. Docker & Containerization: Multi-stage Builds & Security](#docker-containerization)

              - [4. Terraform & Infrastructure as Code Best Practices](#terraform-iac)

              - [5. CI/CD, GitOps (ArgoCD) & Progressive Delivery](#cicd-gitops)

              - [6. Frequently Asked DevOps Interview Questions](#devops-faqs)

            
          

          

            
            
              
## 1. Kubernetes Cluster Architecture & Control Plane Internals

              

                Kubernetes coordinates declarative state through a distributed control plane. Interviewers expect candidates to describe how an API request moves through each component.
              

              
              
                
                  
#### 1. kube-apiserver

                  
The only component that communicates with etcd. Validates, authenticates, and configures data for pod, service, replication controller objects.

                
                
                  
#### 2. etcd

                  
Consistent, highly-available key-value store using Raft consensus to persist cluster state. Requires an odd number of nodes (3 or 5) for quorum (N/2 + 1).

                
                
                  
#### 3. kube-scheduler

                  
Assigns unscheduled pods to worker nodes via two phases: *Filtering (Predicates)* to find eligible nodes, and *Scoring (Priorities)* to choose the best node.

                
                
                  
#### 4. kubelet

                  
Node agent ensuring containers described in PodSpecs are running and healthy via the Container Runtime Interface (CRI).

                
              
            

            
            
              
## 2. Troubleshooting Pods: CrashLoopBackOff, OOMKilled & Pending

              
              
                
                  
### CrashLoopBackOff: Root Causes & Fixes

                  
Indicates a pod starts, fails, restarts, and crashes repeatedly with exponential backoff delay.

                  
```
# Debugging step-by-step:
kubectl describe pod <pod-name> -n <namespace>
kubectl logs <pod-name> --previous
# Common causes: Application fatal exception, missing environment variable/ConfigMap, permission error.
```

                

                
                  
### OOMKilled (Exit Code 137)

                  
The container exceeded its configured memory limit and was terminated by the Linux kernel Out-Of-Memory killer. Fix: Increase `resources.limits.memory` or diagnose memory leaks in the app runtime.

                
              
            

            
            
              
## 3. Docker Multi-Stage Builds & Security Hardening

              

                Writing production-grade Dockerfiles requires minimizing image size and eliminating root privileges.
              

              
```
# Stage 1: Build stage with compiler tools
FROM golang:1.24-alpine AS builder
WORKDIR /app
COPY go.mod go.sum ./
RUN go mod download
COPY . .
RUN CGO_ENABLED=0 GOOS=linux go build -o server .

# Stage 2: Minimal runtime image without build bloat
FROM alpine:3.20
RUN adduser -D -u 10001 appuser
USER appuser
COPY --from=builder /app/server /usr/local/bin/server
EXPOSE 8080
ENTRYPOINT ["/usr/local/bin/server"]
```

            

            
            
              
## 4. Terraform & Infrastructure as Code Best Practices

              

                Key questions asked about Terraform state management and security:
              

              
                - **Remote Backend & Locking:** Storing state in AWS S3 with encryption and using DynamoDB for state locking prevents concurrent executions from corrupting infrastructure state.

                - **Terraform Drift:** When physical cloud resources change outside Terraform. Detected with `terraform plan -refresh-only` and aligned with `terraform apply -refresh-only`.

                - **Terraform Modules:** Promote DRY (Don't Repeat Yourself) infrastructure patterns, enabling environment parity between Dev, Staging, and Production.

              
            

            
            
              
## 5. CI/CD, GitOps (ArgoCD) & Progressive Delivery

              

                Modern deployment pipelines rely on declarative Git repositories as the single source of truth:
              

              
                
                  
#### GitOps with ArgoCD & Flux

                  
ArgoCD runs inside the Kubernetes cluster and continuously monitors Git repos. If cluster state drifts from the committed manifests, it automatically reconciles or alerts engineers.

                
                
                  
#### Progressive Delivery & Automated Rollbacks

                  
Using Argo Rollouts or Flagger to automate Canary releases with Prometheus metrics analysis (HTTP error rates, p99 latency) triggers immediate automated rollbacks if thresholds are breached.

                
              
            

            
            
              
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## 6. Frequently Asked DevOps Interview Questions

              
                
                  
                    What is the difference between a Deployment and a StatefulSet in Kubernetes?
                    
                      
                      
                    
                  
                  

                    A `Deployment` manages stateless application replicas with random pod names and shared storage, suitable for web servers. A `StatefulSet` provides unique, persistent ordinal pod identities (e.g., `kafka-0, kafka-1`), dedicated persistent volume claims per pod, and ordered startup/shutdown guarantees, essential for databases and distributed consensus nodes.
                  

                

                
                  
                    What is the difference between Blue-Green and Canary deployments?
                    
                      
                      
                    
                  
                  

                    In Blue-Green deployment, two identical production environments exist; 100% of live traffic flips instantaneously from Blue (old) to Green (new). In Canary deployment, new software is deployed alongside existing versions and receives a small percentage of user traffic (e.g., 5%) while metrics are analyzed before gradually scaling to 100%.

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