feat: update notebook server images (kubeflow/kubeflow#7687)

Signed-off-by: Mathew Wicks <5735406+thesuperzapper@users.noreply.github.com>

Author: thesuperzapper

components/example-notebook-servers/base/Dockerfile

@@ -39,8 +39,8 @@ ENV S6_BEHAVIOUR_IF_STAGE2_FAILS 2
 # args - software versions
 # https://kubernetes.io/releases/
 # https://github.com/just-containers/s6-overlay/releases
-ARG KUBECTL_VERSION=v1.29.9
-ARG S6_VERSION=v3.2.0.0
+ARG KUBECTL_VERSION=v1.31.6
+ARG S6_VERSION=v3.2.0.2
 
 # set shell to bash
 SHELL ["/bin/bash", "-c"]

components/example-notebook-servers/codeserver-python/Dockerfile

@@ -10,11 +10,15 @@ ARG TARGETARCH
 USER root
 
 # args - software versions
-# https://github.com/microsoft/vscode-python/releases
-ARG CODESERVER_PYTHON_VERSION=2024.14.1
-ARG MINIFORGE_VERSION=24.7.1-2
-ARG PIP_VERSION=24.2
-ARG PYTHON_VERSION=3.11.10
+# https://open-vsx.org/extension/ms-python/python
+# https://open-vsx.org/extension/ms-toolsai/jupyter
+# https://github.com/ipython/ipykernel/releases
+ARG CODESERVER_PYTHON_VERSION=2025.0.0
+ARG CODESERVER_JUPYTER_VERSION=2024.11.0
+ARG IPYKERNEL_VERSION=6.29.5
+ARG MINIFORGE_VERSION=24.11.3-0
+ARG PIP_VERSION=24.3.1
+ARG PYTHON_VERSION=3.11.11
 
 # setup environment for conda
 ENV CONDA_DIR /opt/conda
@@ -52,15 +56,26 @@ RUN case "${TARGETARCH}" in \
  && conda update -y -q --all \
  && conda clean -a -f -y
 
+# install - ipykernel
+# NOTE: we need this for jupyter codeserver extension to work
+RUN echo "ipykernel ==${IPYKERNEL_VERSION}" >> ${CONDA_DIR}/conda-meta/pinned \
+ && conda install -y -q \
+    ipykernel==${IPYKERNEL_VERSION} \
+ && conda clean -a -f -y
+
 # install - requirements.txt
 COPY --chown=${NB_USER}:${NB_GID} requirements.txt /tmp
 RUN python3 -m pip install -r /tmp/requirements.txt --quiet --no-cache-dir \
  && rm -f /tmp/requirements.txt
 
 # install - codeserver extensions
 RUN code-server --install-extension "ms-python.python@${CODESERVER_PYTHON_VERSION}" --force \
+ && code-server --install-extension "ms-toolsai.jupyter@${CODESERVER_JUPYTER_VERSION}" --force \
  && code-server --list-extensions --show-versions
 
+# home - pre-populate home with files for this image
+COPY --chown=${NB_USER}:${NB_GID} home/. ${HOME}/
+
 # s6 - 01-copy-tmp-home
 # NOTE: the contents of $HOME_TMP are copied to $HOME at runtime
 #       this is a workaround because a PVC will be mounted at $HOME

components/example-notebook-servers/codeserver-python/home/README__CODESERVER_PYTHON.md

@@ -0,0 +1,13 @@
+# About the Code-Server Python Image
+
+This file contains notes about the Kubeflow Notebooks _Code-Server Python_ image.
+
+## Jupyter Extension required HTTPS
+
+This image comes with the jupyter extension installed, which allows you to run and edit jupyter notebooks in code-server.
+
+However, because the jupyter extension uses [Service Workers](https://developer.mozilla.org/en-US/docs/Web/API/Service_Worker_API), it requires HTTPS to work.
+That is, if you access this notebook over HTTP, the Jupyter extension will NOT work.
+
+Additionally, if you are using __Chrome__, the HTTPS certificate must be __valid__ and trusted by your browser.
+As a workaround, if you have a self-signed HTTPS certificate, you could use Firefox, or set the [`unsafely-treat-insecure-origin-as-secure`](chrome://flags/#unsafely-treat-insecure-origin-as-secure) flag in Chrome.

components/example-notebook-servers/codeserver-python/requirements.txt

@@ -1,2 +1,2 @@
 # kubeflow packages
-kfp==2.9.0
+kfp==2.11.0

components/example-notebook-servers/codeserver/Dockerfile

@@ -9,7 +9,7 @@ ARG TARGETARCH
 
 # args - software versions
 # https://github.com/coder/code-server/releases
-ARG CODESERVER_VERSION=4.93.1
+ARG CODESERVER_VERSION=4.96.4
 
 USER root
 

components/example-notebook-servers/codeserver/s6/services.d/code-server/run

@@ -1,6 +1,13 @@
 #!/command/with-contenv bash
 
-cd "${HOME}"
+# many tools default to using the home directory for runtime data.
+# as we mount a PVC to the home directory, these files might have the wrong permissions.
+# to avoid this, we set the runtime directory to a path that is NOT a persistent volume.
+export XDG_RUNTIME_DIR="/tmp/runtime-${NB_USER}"
+mkdir -p "${XDG_RUNTIME_DIR}"
+chmod 700 "${XDG_RUNTIME_DIR}"
+
+cd "${HOME}" || { echo "ERROR: failed to cd to ${HOME}"; exit 1; }
 echo "INFO: starting code-server..."
 exec 2>&1
 exec /usr/bin/code-server \

components/example-notebook-servers/jupyter-pytorch-cuda-full/Dockerfile

@@ -8,18 +8,18 @@ FROM $BASE_IMG
 # install - conda packages
 # NOTE: we use mamba to speed things up
 RUN mamba install -y -q \
-    bokeh==3.3.4 \
-    cloudpickle==2.2.1 \
-    dill==0.3.8 \
-    ipympl==0.9.4 \
-    matplotlib==3.8.4 \
-    numpy==1.24.4 \
-    pandas==2.1.4 \
-    scikit-image==0.22.0 \
-    scikit-learn==1.3.2 \
-    scipy==1.11.3 \
+    bokeh==3.6.3 \
+    cloudpickle==3.1.1 \
+    dill==0.3.9 \
+    ipympl==0.9.6 \
+    matplotlib==3.10.0 \
+    numpy==1.26.4 \
+    pandas==2.2.3 \
+    scikit-image==0.25.1 \
+    scikit-learn==1.6.1 \
+    scipy==1.15.1 \
     seaborn==0.13.2 \
-    xgboost==1.7.6 \
+    xgboost==2.1.4 \
  && mamba clean -a -f -y
 
 # install - requirements.txt

components/example-notebook-servers/jupyter-pytorch-cuda-full/requirements.txt

@@ -1,5 +1,5 @@
 # kubeflow packages
-kfp==2.9.0
+kfp==2.11.0
 
 # jupyterlab extensions
-jupyterlab-git==0.50.1
+jupyterlab-git==0.50.2

components/example-notebook-servers/jupyter-pytorch-cuda/Dockerfile

@@ -9,18 +9,23 @@ FROM $BASE_IMG
 # https://github.com/pytorch/pytorch/releases
 # https://github.com/pytorch/audio/releases
 # https://github.com/pytorch/vision/releases
-ARG PYTORCH_VERSION=2.3.1
-ARG TORCHAUDIO_VERSION=2.3.1
-ARG TORCHVISION_VERSION=0.18.1
+# NOTE: correct version alignments are found at https://pytorch.org/get-started/previous-versions/
+#       they sometimes forget to publish a github release of `torchaudio` or `torchvision` when the cut a
+#       patch release of `torch`, but they still publish a patch of `torchaudio` and `torchvision` on pypi
+# TODO: it seems like torch 2.6.0+ with CUDA 12.6+ will have experimental aarch64 support
+#       when updating past that version, remember to test building these images on arm
+ARG PYTORCH_VERSION=2.5.1
+ARG TORCHAUDIO_VERSION=2.5.1
+ARG TORCHVISION_VERSION=0.20.1
 
 # nvidia container toolkit
 # https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/docker-specialized.html
 ENV NVIDIA_VISIBLE_DEVICES all
 ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
-ENV NVIDIA_REQUIRE_CUDA "cuda>=12.1"
+ENV NVIDIA_REQUIRE_CUDA "cuda>=12.4"
 
 # install - pytorch (cuda)
-RUN python3 -m pip install --quiet --no-cache-dir --index-url https://download.pytorch.org/whl/cu121 \
+RUN python3 -m pip install --quiet --no-cache-dir --index-url https://download.pytorch.org/whl/cu124 \
     torch==${PYTORCH_VERSION} \
     torchaudio==${TORCHAUDIO_VERSION} \
     torchvision==${TORCHVISION_VERSION}

components/example-notebook-servers/jupyter-pytorch-full/Dockerfile

@@ -8,18 +8,18 @@ FROM $BASE_IMG
 # install - conda packages
 # NOTE: we use mamba to speed things up
 RUN mamba install -y -q \
-    bokeh==3.3.4 \
-    cloudpickle==2.2.1 \
-    dill==0.3.8 \
-    ipympl==0.9.4 \
-    matplotlib==3.8.4 \
-    numpy==1.24.4 \
-    pandas==2.1.4 \
-    scikit-image==0.22.0 \
-    scikit-learn==1.3.2 \
-    scipy==1.11.3 \
+    bokeh==3.6.3 \
+    cloudpickle==3.1.1 \
+    dill==0.3.9 \
+    ipympl==0.9.6 \
+    matplotlib==3.10.0 \
+    numpy==1.26.4 \
+    pandas==2.2.3 \
+    scikit-image==0.25.1 \
+    scikit-learn==1.6.1 \
+    scipy==1.15.1 \
     seaborn==0.13.2 \
-    xgboost==1.7.6 \
+    xgboost==2.1.4 \
  && mamba clean -a -f -y
 
 # install - requirements.txt