1. Use Docker Logs: The most basic and common way of debugging a Docker container is using the Docker logs command. Docker logs fetch the logs of a container.
```
docker logs
```
1. Inspecting the Docker Container: Docker inspect command allows you to dig deeper into a Docker container’s metadata to find more details about it.
```
docker inspect
```
1. Docker Events: Docker events command outputs real-time events from the Docker service which can be handy if you’re troubleshooting a problem that you suspect is being caused by Docker itself.
```
docker events
```
1. Docker Stats: Docker stats command will display a live data stream of CPU, memory usage, network I/O, disk I/O, and PID details for all the running containers.
```
docker stats
```
1. Use Debugging Tools: Depending on the language used in the container, you may use different debugging tools for an indepth debugging. Tools such as pdb for Python, gdb for Golang or prmpt for node.js can be usefurl.
1. Attaching to a Running Docker Container: If you need to execute commands inside a running Docker container, you can attach to it.
```
docker attach
```
1. Debugging during the Build Process: Sometime the debugging needs to be done during the build process. Docker offers a switch —progress=plain to its build command.
```
docker build —progress=plain .
```
1. Failing Builds and Volumes: In case of failing builds, you can investigate by building without using cache or You can use volumes to interact directly with the code that you’re running within your container.
1. Docker Compose: If you’re working with multi-container applications orchestrated with Docker Compose, you can check its logs
```
docker-compose logs
```
1. Debugging Healthcheck: In case of issues revolving around the application inside the Docker container, understanding if the web server inside the container is up and running ca be found by the healthcheck.
\`\`\`
docker inspect —format=’{{json .State.Health}}’
\`\`\`
Lastly, for complex problems, you might want to use external monitoring and logging services like Datadog, Loggly, etc. to understand the status and performance of your Docker containers over time.
