Custom images - Amazon SageMaker AI
Health check and URL for applicationsDockerfile examples
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Custom images

If you need functionality that is different than what's provided by SageMaker distribution, you can bring your own image with your custom extensions and packages. You can also use it to personalize the Code Editor UI for your own branding or compliance needs.

The following page will provide Code Editor-specific information and templates to create your own custom SageMaker AI images. This is meant to supplement the Amazon SageMaker Studio information and instructions on creating your own SageMaker AI image and bringing your own image to Studio. To learn about custom Amazon SageMaker AI images and how to bring your own image to Studio, see Bring your own image (BYOI).

Health check and URL for applications

  • Base URL – The base URL for the BYOI application must be CodeEditor/default. You can only have one application and it must always be named default.

  • Health check endpoint – You must host your Code Editor server at 0.0.0.0 port 8888 for SageMaker AI to detect it.

  • Authentication – You must pass --without-connection-token when opening sagemaker-code-editor to allow SageMaker AI to authenticate your users.

Note

If you are using Amazon SageMaker Distribution as the base image, these requirements are already taken care of as part of the included entrypoint-code-editor script.

Dockerfile examples

The following examples are Dockerfiles that meets the above information and Custom image specifications.

Note

If you are bringing your own image to SageMaker Unified Studio, you will need to follow the Dockerfile specifications in the Amazon SageMaker Unified Studio User Guide.

Dockerfile examples for SageMaker Unified Studio can be found in Dockerfile example in the Amazon SageMaker Unified Studio User Guide.

Example micromamba Dockerfile

The following is an example Dockerfile to create an image from scratch using a micromamba base environment: 

FROM mambaorg/micromamba:latest
ARG NB_USER="sagemaker-user"
ARG NB_UID=1000
ARG NB_GID=100

USER root

RUN micromamba install -y --name base -c conda-forge sagemaker-code-editor

USER $NB_UID

CMD eval "$(micromamba shell hook --shell=bash)"; \
    micromamba activate base; \
    sagemaker-code-editor --host 0.0.0.0 --port 8888 \
        --without-connection-token \
        --base-path "/CodeEditor/default"
Example SageMaker AI Distribution Dockerfile

The following is an example Dockerfile to create an image based on Amazon SageMaker AI Distribution:

FROM public.ecr.aws/sagemaker/sagemaker-distribution:latest-cpu
ARG NB_USER="sagemaker-user"
ARG NB_UID=1000
ARG NB_GID=100
ENV MAMBA_USER=$NB_USER

USER root

 # install scrapy in the base environment
RUN micromamba install -y --name base -c conda-forge scrapy

 # download VSCodeVim
RUN \
  wget https://github.com/VSCodeVim/Vim/releases/download/v1.27.2/vim-1.27.2.vsix \
  -P /tmp/exts/ --no-check-certificate

 # Install the extension
RUN \
  extensionloc=/opt/amazon/sagemaker/sagemaker-code-editor-server-data/extensions \
  && sagemaker-code-editor \
    --install-extension "/tmp/exts/vim-1.27.2.vsix" \
    --extensions-dir "${extensionloc}"

USER $MAMBA_USER
ENTRYPOINT ["entrypoint-code-editor"]