instruction: Explain docker concepts and implementation
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  By default all files created inside a container are stored on a writable
  container layer that sits on top of the read-only, immutable image layers.
  Data written to the container layer doesn't persist when the container is
  destroyed. This means that it can be difficult to get the data out of the
  container if another process needs it.
  The writable layer is unique per container. You can't easily extract the data
  from the writeable layer to the host, or to another container.
  Storage mount options
  Docker supports the following types of storage mounts for storing data outside
  of the writable layer of the container:
  Volume mounts
  Bind mounts
  tmpfs mounts
  Named pipes
  No matter which type of mount you choose to use, the data looks the same from
  within the container. It is exposed as either a directory or an individual file
  in the container's filesystem.
  Volume mounts
  Volumes are persistent storage mechanisms managed by the Docker daemon. They
  retain data even after the containers using them are removed. Volume data is
  stored on the filesystem on the host, but in order to interact with the data in
  the volume, you must mount the volume to a container. Directly accessing or
  interacting with the volume data is unsupported,  behavior, and may
  result in the volume or its data breaking in unexpected ways.
  Volumes are ideal for performance-critical data processing and long-term
  storage needs. Since the storage location is managed on the daemon host,
  volumes provide the same raw file performance as accessing the host filesystem
  directly.
  Bind mounts
  Bind mounts create a direct link between a host system path and a container,
  allowing access to files or directories stored anywhere on the host. Since they
  aren't isolated by Docker, both non-Docker processes on the host and container
  processes can modify the mounted files simultaneously.
  Use bind mounts when you need to be able to access files from both the
  container and the host.
  tmpfs mounts
  A tmpfs mount stores files directly in the host machine's memory, ensuring the
  data is not written to disk. This storage is ephemeral: the data is lost when
  the container is stopped or restarted, or when the host is rebooted. tmpfs
  mounts do not persist data either on the Docker host or within the container's
  filesystem.
  These mounts are suitable for scenarios requiring temporary, in-memory storage,
  such as caching intermediate data, handling sensitive information like
  credentials, or reducing disk I/O. Use tmpfs mounts only when the data does not
  need to persist beyond the current container session.
  Named pipes
  Named pipes
  can be used for communication between the Docker host and a container. Common
  use case is to run a third-party tool inside of a container and connect to the
  Docker Engine API using a named pipe.
  Next steps
  Learn more about
  volumes
  Learn more about
  bind mounts
  Learn more about
  tmpfs mounts
  Learn more about
  storage drivers
  , which
  are not related to bind mounts or volumes, but allow you to store data in a
  container's writable layer.
  
  ## Error Handling and Troubleshooting
  
  ### Common Issues and Solutions
  
  **Issue 1: Container startup failures**
  ```bash
  # Check container logs
  docker logs <container_id>
  
  # Debug with interactive shell
  docker run -it --entrypoint /bin/sh <image_name>
  ```
  
  **Issue 2: Resource constraints**
  ```bash
  # Check resource usage
  kubectl top pods
  kubectl describe pod <pod_name>
  
  # Scale resources if needed
  kubectl patch deployment <deployment_name> -p '{{"spec":{{"template":{{"spec":{{"containers":[{{"name":"<container_name>","resources":{{"requests":{{"memory":"256Mi","cpu":"200m"}},"limits":{{"memory":"512Mi","cpu":"400m"}}}}}}]}}}}}}}'
  ```
  
  **Issue 3: Network connectivity**
  ```bash
  # Test service connectivity
  kubectl exec -it <pod_name> -- wget -qO- <service_name>:<port>/health
  
  # Check service endpoints
  kubectl get endpoints <service_name>
  ```
  
  ### Monitoring and Alerts
  
  Set up proper monitoring to catch issues early:
  
  ```yaml
  # Example alert rule
  groups:
  - name: application.rules
    rules:
    - alert: HighErrorRate
      expr: rate(http_requests_total{{status=~"5.."}}}[5m]) > 0.1
      for: 5m
      annotations:
        summary: "High error rate detected"
        description: "Error rate is above 10% for 5 minutes"
  ```