quiz.json

{
  "questions": [
    {
      "stage": "pre",
      "question": "What is the primary difference between a Docker container and a virtual machine?",
      "options": ["Containers are slower but more secure than VMs", "Containers share the host OS kernel while VMs run their own full OS", "Containers can only run Linux while VMs support any OS", "There is no practical difference"],
      "correct": 1,
      "explanation": "Containers share the host kernel and isolate at the process level, making them start in seconds. VMs run a complete guest OS with its own kernel, requiring more resources and slower startup."
    },
    {
      "stage": "pre",
      "question": "What is a Dockerfile?",
      "options": ["A configuration file for the Docker daemon", "A set of instructions for building a Docker image layer by layer", "A log file that records container activity", "A file that lists running containers"],
      "correct": 1,
      "explanation": "A Dockerfile contains sequential instructions (FROM, RUN, COPY, etc.) that Docker executes to build an image. Each instruction creates a cached layer."
    },
    {
      "stage": "post",
      "question": "Why are volume mounts critical for AI development with Docker?",
      "options": ["Volumes make containers run faster by using host disk speed", "Volumes persist data (models, datasets, code) across container rebuilds so you don't re-download gigabytes each time", "Volumes are required for Python packages to install correctly", "Volumes allow multiple containers to share the same GPU"],
      "correct": 1,
      "explanation": "Without volumes, everything inside a container is lost when it stops. Volume mounts map host directories into the container, so model weights (14+ GB) and datasets survive rebuilds."
    },
    {
      "stage": "post",
      "question": "What does the NVIDIA Container Toolkit enable?",
      "options": ["Installing CUDA drivers inside the container", "Exposing host GPUs to Docker containers via the --gpus flag", "Running NVIDIA GPU containers on AMD hardware", "Compiling CUDA code during the Docker build process"],
      "correct": 1,
      "explanation": "The NVIDIA Container Toolkit is a runtime hook that exposes host GPUs to containers. The CUDA toolkit lives inside the container, but the GPU driver is shared from the host."
    },
    {
      "stage": "post",
      "question": "In a Docker Compose file for AI, how does the 'ai-dev' service reach the 'qdrant' vector database?",
      "options": ["By using the host machine's IP address and port", "By using the service name 'qdrant' as the hostname, since Compose creates a shared network", "By mounting a shared volume between the two containers", "By configuring a VPN between the containers"],
      "correct": 1,
      "explanation": "Docker Compose automatically creates a shared network where services can reach each other by name. The ai-dev container connects to 'http://qdrant:6333' using the service name as hostname."
    }
  ]
}