container-debugging

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Container Debugging

容器调试

Overview

概述

Container debugging focuses on issues within Docker/Kubernetes environments including resource constraints, networking, and application runtime problems.

容器调试主要针对Docker/Kubernetes环境中的问题，包括资源限制、网络问题以及应用运行时故障。

When to Use

适用场景

Container won't start
Application crashes in container
Resource limits exceeded
Network connectivity issues
Performance problems in containers

容器无法启动
应用在容器内崩溃
超出资源限制
网络连接问题
容器性能问题

Instructions

操作指南

1. Docker Debugging Basics

1. Docker调试基础

bash

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bash

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Check container status

docker ps -a docker inspect <container-id> docker stats <container-id>

View container logs

docker logs <container-id> docker logs --follow <container-id> # Real-time docker logs --tail 100 <container-id> # Last 100 lines

Connect to running container

docker exec -it <container-id> /bin/bash docker exec -it <container-id> sh

Inspect container details

docker inspect <container-id> | grep -A 5 "State" docker inspect <container-id> | grep -E "Memory|Cpu"

Check container processes

docker top <container-id>

View resource usage

docker stats <container-id>

Shows: CPU%, Memory usage, Network I/O

Copy files from container

docker cp <container-id>:/path/to/file /local/path

View image layers

docker history <image-name> docker inspect <image-name>

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docker history <image-name> docker inspect <image-name>

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2. Common Container Issues

2. 常见容器问题

yaml

Issue: Container Won't Start

Diagnosis:
  1. docker logs <container-id>
  2. Check exit code: docker inspect (ExitCode)
  3. Verify image exists: docker images
  4. Check entrypoint: docker inspect --format='{{.Config.Entrypoint}}'

Common Exit Codes:
  0: Normal exit
  1: General application error
  127: Command not found
  128+N: Terminated by signal N
  137: Out of memory (SIGKILL)
  139: Segmentation fault

Solutions:
  - Fix application error
  - Ensure required files exist
  - Check executable permissions
  - Verify working directory

---

Issue: Out of Memory

Symptoms: Exit code 137 (SIGKILL)

Debug:
  docker stats <container-id>
  # Check Memory usage vs limit

Solution:
  docker run -m 512m <image>
  # Increase memory limit
  docker inspect (MemoryLimit)
  # Check current limit

---

Issue: Port Already in Use

Error: "bind: address already in use"

Debug:
  docker ps  # Check running containers
  netstat -tlnp | grep 8080  # Check port usage

Solution:
  docker run -p 8081:8080 <image>
  # Use different host port

---

Issue: Network Issues

Symptom: Cannot reach other containers

Debug:
  docker network ls
  docker inspect <container-id> | grep IPAddress
  docker exec <container-id> ping <other-container>

Solution:
  docker network create app-network
  docker run --network app-network <image>

yaml

Issue: Container Won't Start

Diagnosis:
  1. docker logs <container-id>
  2. Check exit code: docker inspect (ExitCode)
  3. Verify image exists: docker images
  4. Check entrypoint: docker inspect --format='{{.Config.Entrypoint}}'

Common Exit Codes:
  0: Normal exit
  1: General application error
  127: Command not found
  128+N: Terminated by signal N
  137: Out of memory (SIGKILL)
  139: Segmentation fault

Solutions:
  - Fix application error
  - Ensure required files exist
  - Check executable permissions
  - Verify working directory

---

Issue: Out of Memory

Symptoms: Exit code 137 (SIGKILL)

Debug:
  docker stats <container-id>
  # Check Memory usage vs limit

Solution:
  docker run -m 512m <image>
  # Increase memory limit
  docker inspect (MemoryLimit)
  # Check current limit

---

Issue: Port Already in Use

Error: "bind: address already in use"

Debug:
  docker ps  # Check running containers
  netstat -tlnp | grep 8080  # Check port usage

Solution:
  docker run -p 8081:8080 <image>
  # Use different host port

---

Issue: Network Issues

Symptom: Cannot reach other containers

Debug:
  docker network ls
  docker inspect <container-id> | grep IPAddress
  docker exec <container-id> ping <other-container>

Solution:
  docker network create app-network
  docker run --network app-network <image>

3. Container Optimization

3. 容器优化

yaml

Resource Limits:

Set in docker-compose:
  version: '3'
  services:
    app:
      image: myapp
      environment:
        - NODE_ENV=production
      resources:
        limits:
          cpus: '1.0'
          memory: 512M
        reservations:
          cpus: '0.5'
          memory: 256M

Limits: Maximum resources
Reservations: Guaranteed resources

---

Multi-Stage Builds:

FROM node:16 AS builder
WORKDIR /app
COPY package*.json ./
RUN npm install
COPY . .
RUN npm run build

FROM node:16-alpine
WORKDIR /app
COPY --from=builder /app/dist ./dist
COPY package*.json ./
RUN npm install --production
EXPOSE 3000
CMD ["node", "dist/index.js"]

Result: 1GB → 200MB image size

yaml

Resource Limits:

Set in docker-compose:
  version: '3'
  services:
    app:
      image: myapp
      environment:
        - NODE_ENV=production
      resources:
        limits:
          cpus: '1.0'
          memory: 512M
        reservations:
          cpus: '0.5'
          memory: 256M

Limits: Maximum resources
Reservations: Guaranteed resources

---

Multi-Stage Builds:

FROM node:16 AS builder
WORKDIR /app
COPY package*.json ./
RUN npm install
COPY . .
RUN npm run build

FROM node:16-alpine
WORKDIR /app
COPY --from=builder /app/dist ./dist
COPY package*.json ./
RUN npm install --production
EXPOSE 3000
CMD ["node", "dist/index.js"]

Result: 1GB → 200MB image size

4. Debugging Checklist

4. 调试检查清单

yaml

Container Issues:

[ ] Container starts without error
[ ] Ports mapped correctly
[ ] Logs show no errors
[ ] Environment variables set
[ ] Volumes mounted correctly
[ ] Network connectivity works
[ ] Resource limits appropriate
[ ] Permissions correct
[ ] Dependencies installed
[ ] Entrypoint working

Kubernetes Issues:

[ ] Pod running (not Pending/CrashLoop)
[ ] All containers started
[ ] Readiness probes passing
[ ] Liveness probes passing
[ ] Resource requests/limits set
[ ] Network policies allow traffic
[ ] Secrets/ConfigMaps available
[ ] Logs show no errors

Tools:

docker:
  - logs
  - stats
  - inspect
  - exec

docker-compose:
  - logs
  - ps
  - config

kubectl (Kubernetes):
  - logs
  - describe pod
  - get events
  - port-forward

yaml

Container Issues:

[ ] Container starts without error
[ ] Ports mapped correctly
[ ] Logs show no errors
[ ] Environment variables set
[ ] Volumes mounted correctly
[ ] Network connectivity works
[ ] Resource limits appropriate
[ ] Permissions correct
[ ] Dependencies installed
[ ] Entrypoint working

Kubernetes Issues:

[ ] Pod running (not Pending/CrashLoop)
[ ] All containers started
[ ] Readiness probes passing
[ ] Liveness probes passing
[ ] Resource requests/limits set
[ ] Network policies allow traffic
[ ] Secrets/ConfigMaps available
[ ] Logs show no errors

Tools:

docker:
  - logs
  - stats
  - inspect
  - exec

docker-compose:
  - logs
  - ps
  - config

kubectl (Kubernetes):
  - logs
  - describe pod
  - get events
  - port-forward

Key Points

核心要点

Check logs first:
```
docker logs <container>
```
Understand exit codes (137=OOM, 127=not found)
Use resource limits appropriately
Network containers on same network
Multi-stage builds reduce image size
Monitor resource usage with stats
Port mappings: host:container
Exec into running containers for debugging
Update base images regularly
Include health checks in containers

优先查看日志：
```
docker logs <container>
```
理解退出码含义（137=内存不足，127=命令未找到）
合理设置资源限制
将容器部署在同一网络中
多阶段构建可减小镜像体积
使用stats监控资源使用情况
端口映射格式：主机端口:容器端口
进入运行中的容器进行调试
定期更新基础镜像
在容器中包含健康检查