Docker and Kubernetes Troubleshooting: Common Errors

Docker and Kubernetes troubleshooting represents a critical skill for any infrastructure engineer or developer working with containers. According to the CNCF Annual Survey 2025, 82% of container users run Kubernetes in production. This massive adoption inevitably generates errors that teams must diagnose quickly to maintain service availability.

TL;DR: This guide covers the most common Docker and Kubernetes errors with concrete solutions: CrashLoopBackOff, ImagePullBackOff, OOMKilled, network problems, and build errors. Each section provides diagnostic commands and production-tested fixes.

To master these diagnostic skills, discover the LFS458 Kubernetes Administration training.

Why Docker and Kubernetes Troubleshooting Requires a Structured Methodology

Containerized environments introduce multiple layers of abstraction: Docker runtime, Kubernetes orchestrator, overlay network, persistent storage. Each layer can generate specific errors.

Kubernetes complexity requires a structured diagnostic approach. Teams that master troubleshooting significantly reduce their incident resolution time.

Most common Docker errors include:

• Build failures (misconfigured Dockerfile)
• Large images slowing deployments
• Network problems between containers
• Resource leaks (memory, CPU)

Frequent Kubernetes errors include:

• CrashLoopBackOff (pod restarting in loop)
• ImagePullBackOff (image download failure)
• OOMKilled (memory exceeded)
• Pending (non-schedulable pod)

Key takeaway: Adopt a systematic approach by first diagnosing the Docker layer (image, container), then the Kubernetes layer (pod, service, ingress).

For deeper fundamentals, see our guide on Docker containerization best practices.

How to Resolve Docker Build Errors

Build errors represent the first obstacle in the containerized development cycle.

Error: COPY failed: file not found

This error occurs when the build context doesn't contain the referenced file.

# Diagnostic: check build context contents
docker build --no-cache -t myapp:debug . 2>&1 | head -20

# Check .dockerignore
cat .dockerignore

Solution: Adjust the relative path in the Dockerfile or modify .dockerignore.

# Incorrect
COPY src/app.py /app/

# Correct (verify src/ exists in context)
COPY ./src/app.py /app/

Error: Images too large

Prefer Alpine images and multi-stage builds to drastically reduce image size. See our guide Optimize a Dockerfile for Kubernetes for detailed techniques.

# Optimized multi-stage build
FROM golang:1.22-alpine AS builder
WORKDIR /app
COPY . .
RUN go build -o myapp

FROM alpine:3.19
COPY --from=builder /app/myapp /usr/local/bin/
CMD ["myapp"]

Key takeaway: Target microservice images under 200MB according to DevOpsCube recommendations.

To understand fundamental differences, read our article Kubernetes vs Docker: understanding the differences.

Docker and Kubernetes Troubleshooting: Resolving CrashLoopBackOff

The CrashLoopBackOff error indicates a pod continuously restarting after failures.

Step 1: Examine container logs

# Failing pod logs
kubectl logs <pod-name> --previous

# Logs from all containers in pod
kubectl logs <pod-name> --all-containers=true

# Follow logs in real-time
kubectl logs -f <pod-name>

Step 2: Check events

kubectl describe pod <pod-name> | grep -A 20 Events

Common causes and solutions

# Example: initContainer to wait for dependency
initContainers:
- name: wait-for-db
image: busybox:1.36
command: ['sh', '-c', 'until nc -z postgres-svc 5432; do sleep 2; done']

Getting started with Docker and Kubernetes covers initial setup to avoid these errors.

How to Diagnose ImagePullBackOff in Kubernetes

ImagePullBackOff means Kubernetes cannot download the specified Docker image.

Essential checks

# Error details
kubectl describe pod <pod-name> | grep -A 5 "Warning"

# Manually test pull
docker pull <image-name>:<tag>

Causes and resolutions

1. Non-existent image or incorrect tag

# Verify image existence
docker manifest inspect <image>:<tag>

2. Authentication required for private registry

# Create registry secret
kubectl create secret docker-registry regcred \
--docker-server=registry.example.com \
--docker-username=user \
--docker-password=pass

# Reference in pod
spec:
imagePullSecrets:
- name: regcred

3. Network problem to registry

# Test connectivity from debug pod
kubectl run debug --image=busybox --rm -it -- wget -O- https://registry.example.com/v2/

Key takeaway: Always use explicit tags (v1.2.3) rather than latest to ensure reproducibility.

See Kubernetes vs Docker Swarm, ECS and Nomad comparison to understand how each orchestrator handles images.

Resolving Memory Problems: OOMKilled

OOMKilled (Out Of Memory Killed) indicates the container exceeded its memory limit.

Diagnostic

# Identify OOMKilled pods
kubectl get pods --field-selector=status.phase=Failed

# Check consumed resources
kubectl top pod <pod-name>

# Examine configured limits
kubectl describe pod <pod-name> | grep -A 5 Limits

Resource configuration

resources:
requests:
memory: "256Mi"
cpu: "250m"
limits:
memory: "512Mi"
cpu: "500m"

Sizing rules:

• Requests: guaranteed resources, used for scheduling
• Limits: maximum ceiling before kill
• Recommended ratio: limits = 2x requests for variable applications

Docker and Kubernetes Troubleshooting: Network Errors

Network problems represent 30% of incidents in Kubernetes environments.

Pod not communicating with Service

# Verify Service exists and has endpoints
kubectl get endpoints <service-name>

# Test DNS resolution from a pod
kubectl run dns-test --image=busybox --rm -it -- nslookup <service-name>

# Verify pod labels match Service selector
kubectl get pods --show-labels
kubectl describe svc <service-name> | grep Selector

Ingress not routing traffic

# Check Ingress configuration
kubectl describe ingress <ingress-name>

# Ingress controller logs
kubectl logs -n ingress-nginx deploy/ingress-nginx-controller

# Test from outside
curl -H "Host: example.com" http://<ingress-ip>/

Key takeaway: The NGINX Ingress Controller will be retired in March 2026 according to InfoQ. Plan your migration to Gateway API.

For quick answers, see the Docker and Kubernetes FAQ.

Essential Tools for Advanced Troubleshooting

kubectl debug

Since Kubernetes 1.25, kubectl debug allows attaching a debug container to a production pod:

# Create ephemeral container for debug
kubectl debug <pod-name> -it --image=busybox --target=<container-name>

# Copy pod with debug image
kubectl debug <pod-name> --copy-to=debug-pod --image=ubuntu

Cluster event analysis

# Recent events sorted by date
kubectl get events --sort-by='.lastTimestamp'

# Filter by type
kubectl get events --field-selector type=Warning

Real-time metrics

# Pod CPU/memory usage
kubectl top pods --all-namespaces

# Node usage
kubectl top nodes

Kubernetes CKA CKAD CKS certifications validate these advanced troubleshooting skills.

Quick Troubleshooting Checklist

Before escalating an incident, systematically check:

For complex migrations, our guide Migrate to Kubernetes from Docker Compose, VMs details common pitfalls.

Key takeaway: Document each resolution in an internal knowledge base to accelerate future interventions.

Move from Reactive Troubleshooting to Proactive Mastery

Effective Docker and Kubernetes troubleshooting relies on deep understanding of underlying mechanisms. As TealHQ notes: "Don't let your knowledge remain theoretical - set up a real Kubernetes environment to solidify your skills."

Recommended next steps:

1. Practice on a local cluster with Minikube or Kind
2. Follow structured training to fill your gaps
3. Validate your skills through official certification

SFEIR offers several trainings to develop your expertise:

• LFS458 Kubernetes Administration: 4 days to master cluster administration and prepare for CKA
• LFD459 Kubernetes for Developers: 3 days for application deployment and CKAD preparation
• Kubernetes Fundamentals: 1 day to discover essential concepts

Contact our advisors to define the path suited to your goals.