DockerfileDescription.md

# 5 Terraform commands you should know:

1. terraform init: https://developer.hashicorp.com/terraform/cli/commands/init
2. terraform plan: https://developer.hashicorp.com/terraform/cli/commands/plan
3. terraform apply: https://developer.hashicorp.com/terraform/cli/commands/apply
4. terraform import: https://developer.hashicorp.com/terraform/cli/import
5. terraform destroy: https://developer.hashicorp.com/terraform/cli/commands/destroy

# Azure Resources TF Management:

| Step | Title              | Tasks                                                                                                       |
|------|--------------------|-------------------------------------------------------------------------------------------------------------|
| 1    | PreReqs            | Terraform installed, Azure cloud account, VSCode extensions, Docker, ACR, Deploy and Test                   |
| 2    | Demo               | Create resources in Azure cloud                                                                             |
| 3    |                    | Create terraform files for those resources                                                                  |
| 4    |                    | Run terraform apply                                                                                         |
| 5    |                    | Run terraform import for each resource                                                                      |
| 6    |                    | Verify terraform state                                                                                      |
| 7    |                    | Perform terraform destroy to clean up resources                                                             |


# Docker and Linux SOAR Setup:

| Step | Title              | Tasks                                                                                                       |
|------|--------------------|-------------------------------------------------------------------------------------------------------------|
| 1    | PreReqs            | Docker, ACR, Deploy and Test                   |
| 2    | Demo               | Modify Dockerfile to start and configure resources                                                           |
| 3    |                    | Modify Docker base image to remove old apts w security issuesand cert issues                                 |
| 4    |                    | Modify Docker base image to configure soar and python components including packages, requirements                |                                 |
| 5    |                    | Run Docker push, deploy to ACR and test                                                                      |





Give me an analysis on what this dockerfile does:  FROM nvidia/cuda:11.3.1-base-ubuntu20.04

ENV DEBIAN_FRONTEND=noninteractive \
	TZ=Europe/Paris

# Remove any third-party apt sources to avoid issues with expiring keys.
# Install some basic utilities
RUN rm -f /etc/apt/sources.list.d/*.list && \
    apt-get update && apt-get install -y \
    curl \
    ca-certificates \
    sudo \
    git \
    git-lfs \
    zip \
    unzip \
    htop \
    bzip2 \
    libx11-6 \
    build-essential \
    libsndfile-dev \
    software-properties-common \
 && rm -rf /var/lib/apt/lists/*

ARG BUILD_DATE
ARG VERSION
ARG CODE_RELEASE
RUN \
  echo "**** install openvscode-server runtime dependencies ****" && \
  apt-get update && \
  apt-get install -y \
    jq \
    libatomic1 \
    nano \
    net-tools \
    netcat && \
  echo "**** install openvscode-server ****" && \
  if [ -z ${CODE_RELEASE+x} ]; then \
    CODE_RELEASE=$(curl -sX GET "https://api.github.com/repos/gitpod-io/openvscode-server/releases/latest" \
      | awk '/tag_name/{print $4;exit}' FS='[""]' \
      | sed 's|^openvscode-server-v||'); \
  fi && \
  mkdir -p /app/openvscode-server && \
  curl -o \
    /tmp/openvscode-server.tar.gz -L \
    "https://github.com/gitpod-io/openvscode-server/releases/download/openvscode-server-v${CODE_RELEASE}/openvscode-server-v${CODE_RELEASE}-linux-x64.tar.gz" && \
  tar xf \
    /tmp/openvscode-server.tar.gz -C \
    /app/openvscode-server/ --strip-components=1 && \
  echo "**** clean up ****" && \
  apt-get clean && \
  rm -rf \
    /tmp/* \
    /var/lib/apt/lists/* \
    /var/tmp/*
COPY root/ /

RUN add-apt-repository ppa:flexiondotorg/nvtop && \
    apt-get upgrade -y && \
    apt-get install -y --no-install-recommends nvtop

RUN curl -sL https://deb.nodesource.com/setup_14.x  | bash - && \
    apt-get install -y nodejs && \
    npm install -g configurable-http-proxy
# Create a working directory
WORKDIR /app
# Create a non-root user and switch to it
RUN adduser --disabled-password --gecos '' --shell /bin/bash user \
 && chown -R user:user /app
RUN echo "user ALL=(ALL) NOPASSWD:ALL" > /etc/sudoers.d/90-user
USER user
# All users can use /home/user as their home directory
ENV HOME=/home/user
RUN mkdir $HOME/.cache $HOME/.config \
 && chmod -R 777 $HOME
# Set up the Conda environment
ENV CONDA_AUTO_UPDATE_CONDA=false \
    PATH=$HOME/miniconda/bin:$PATH
RUN curl -sLo ~/miniconda.sh https://repo.continuum.io/miniconda/Miniconda3-py39_4.10.3-Linux-x86_64.sh \
 && chmod +x ~/miniconda.sh \
 && ~/miniconda.sh -b -p ~/miniconda \
 && rm ~/miniconda.sh \
 && conda clean -ya

WORKDIR $HOME/app

#######################################
# Start root user section
#######################################

USER root

# User Debian packages
## Security warning : Potential user code executed as root (build time)
RUN --mount=target=/root/packages.txt,source=packages.txt \
    apt-get update && \
    xargs -r -a /root/packages.txt apt-get install -y --no-install-recommends \
    && rm -rf /var/lib/apt/lists/*

RUN --mount=target=/root/on_startup.sh,source=on_startup.sh,readwrite \
	bash /root/on_startup.sh

#######################################
# End root user section
#######################################

USER user

# Python packages
RUN --mount=target=requirements.txt,source=requirements.txt \
    pip install --no-cache-dir --upgrade -r requirements.txt

# Copy the current directory contents into the container at $HOME/app setting the owner to the user
COPY --chown=user . $HOME/app

RUN chmod +x start_server.sh

ENV PYTHONUNBUFFERED=1 \
	GRADIO_ALLOW_FLAGGING=never \
	GRADIO_NUM_PORTS=1 \
	GRADIO_SERVER_NAME=0.0.0.0 \
	GRADIO_THEME=huggingface \
	SYSTEM=spaces \
	SHELL=/bin/bash

EXPOSE 7860 3000

CMD ["./start_server.sh"]
This Dockerfile describes the steps to create a Docker image with an environment that includes various tools, libraries, and applications. The image is based on the nvidia/cuda:11.3.1-base-ubuntu20.04 image, which is a Ubuntu 20.04 base image with NVIDIA CUDA 11.3.1 libraries pre-installed. The steps in this Dockerfile can be broken down as follows:

Set environment variables:

Set the timezone to Europe/Paris
Set the Debian frontend to noninteractive mode for silent installations
Remove third-party apt sources to avoid issues with expiring keys.

Install basic utilities and libraries using apt-get.

Install the OpenVSCode-Server, which is an open-source version of VSCode Server, allowing you to run a remote VSCode environment.

Add the flexiondotorg/nvtop repository and install the NVTop GPU monitoring tool.

Install Node.js 14.x and the configurable-http-proxy package.

Create a non-root user named user and set appropriate permissions.

Set up the Conda environment with Miniconda3 and Python 3.9.

Install user-specified Debian packages by reading from a packages.txt file.

Execute a script named on_startup.sh as the root user.

Switch back to the non-root user user.

Install Python packages specified in a requirements.txt file.

Copy the current directory contents into the container at $HOME/app.

Set environment variables for Gradio and other configurations.

Expose ports 7860 and 3000.

Set the CMD to execute the start_server.sh script when the container starts.

This Dockerfile sets up a development environment with NVIDIA CUDA support, a Conda environment, OpenVSCode-Server, NVTop, and various other utilities. It also installs user-specified Debian and Python packages, and runs a user-specified script at startup. The image is prepared to run a server using Gradio, a library for creating web-based UIs for ML models, and exposes two ports for external communication.