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

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

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 KUBECTL_VERSION=v1.31.6
-ARG S6_VERSION=v3.2.0.0
+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
+# https://open-vsx.org/extension/ms-python/python
-ARG CODESERVER_PYTHON_VERSION=2024.14.1
+# https://open-vsx.org/extension/ms-toolsai/jupyter
-ARG MINIFORGE_VERSION=24.7.1-2
+# https://github.com/ipython/ipykernel/releases
-ARG PIP_VERSION=24.2
+ARG CODESERVER_PYTHON_VERSION=2025.0.0
-ARG PYTHON_VERSION=3.11.10
+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
@@ -52,6 +56,13 @@ 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 \
@@ -59,8 +70,12 @@ RUN python3 -m pip install -r /tmp/requirements.txt --quiet --no-cache-dir \
 
 # 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 \
+    bokeh==3.6.3 \
-    cloudpickle==2.2.1 \
+    cloudpickle==3.1.1 \
-    dill==0.3.8 \
+    dill==0.3.9 \
-    ipympl==0.9.4 \
+    ipympl==0.9.6 \
-    matplotlib==3.8.4 \
+    matplotlib==3.10.0 \
-    numpy==1.24.4 \
+    numpy==1.26.4 \
-    pandas==2.1.4 \
+    pandas==2.2.3 \
-    scikit-image==0.22.0 \
+    scikit-image==0.25.1 \
-    scikit-learn==1.3.2 \
+    scikit-learn==1.6.1 \
-    scipy==1.11.3 \
+    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
+# NOTE: correct version alignments are found at https://pytorch.org/get-started/previous-versions/
-ARG TORCHAUDIO_VERSION=2.3.1
+#       they sometimes forget to publish a github release of `torchaudio` or `torchvision` when the cut a
-ARG TORCHVISION_VERSION=0.18.1
+#       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 \
+    bokeh==3.6.3 \
-    cloudpickle==2.2.1 \
+    cloudpickle==3.1.1 \
-    dill==0.3.8 \
+    dill==0.3.9 \
-    ipympl==0.9.4 \
+    ipympl==0.9.6 \
-    matplotlib==3.8.4 \
+    matplotlib==3.10.0 \
-    numpy==1.24.4 \
+    numpy==1.26.4 \
-    pandas==2.1.4 \
+    pandas==2.2.3 \
-    scikit-image==0.22.0 \
+    scikit-image==0.25.1 \
-    scikit-learn==1.3.2 \
+    scikit-learn==1.6.1 \
-    scipy==1.11.3 \
+    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-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-gaudi-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 \
+    bokeh==3.6.3 \
-    cloudpickle==2.2.1 \
+    cloudpickle==3.1.1 \
-    dill==0.3.8 \
+    dill==0.3.9 \
-    ipympl==0.9.4 \
+    ipympl==0.9.6 \
-    matplotlib==3.8.4 \
+    matplotlib==3.10.0 \
-    numpy==1.24.4 \
+    numpy==1.26.4 \
-    pandas==2.1.4 \
+    pandas==2.2.3 \
-    scikit-image==0.22.0 \
+    scikit-image==0.25.1 \
-    scikit-learn==1.3.2 \
+    scikit-learn==1.6.1 \
-    scipy==1.11.3 \
+    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-gaudi-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-gaudi/Dockerfile

@@ -164,8 +164,8 @@ COPY --chown=${NB_USER}:users requirements.txt /tmp
 RUN python3 -m pip install -r /tmp/requirements.txt --quiet --no-cache-dir \
  && rm -f /tmp/requirements.txt
 
-# install - note about Gaudi workloads and hugepages
+# home - pre-populate home with files for this image
-COPY README.md "${HOME}"
+COPY --chown=${NB_USER}:${NB_GID} home/. ${HOME}/
 
 # s6 - 01-copy-tmp-home
 # NOTE: the contents of $HOME_TMP are copied to $HOME at runtime

components/example-notebook-servers/jupyter-pytorch-gaudi/README.md

@@ -1,9 +0,0 @@
-# A note about Gaudi workloads
-
-Some Gaudi workloads require hugepages to run correctly. One can find a list of workloads listed [here](https://console.cloud.intel.com/docs/guides/k8s_guide.html#hugepages-settings-by-model). As of now, Kubeflow Notebooks lack the capability to request hugepages resources for individual notebooks.
-
-To add hugepages resources for the Notebook Pod, there are a couple of options:
-* Use [Limit Ranges](https://kubernetes.io/docs/concepts/policy/limit-range/) to set default hugepages amount for all Pods in the namespace.
-* Edit the Kubeflow's notebook object after it has been created and add the hugepages resources to the pod template.
-
-The upcoming Notebooks 2.0 release will improve the situation with its `podTemplate` feature.

components/example-notebook-servers/jupyter-pytorch-gaudi/home/README__PYTORCH_GAUDI.md

@@ -0,0 +1,15 @@
+# About the PyTorch Gaudi Image
+
+This file contains notes about the Kubeflow Notebooks _PyTorch Gaudi_ image.
+
+## Hugepages Support
+
+Some Gaudi workloads require hugepages to run correctly. 
+One can find a list of workloads listed [here](https://console.cloud.intel.com/docs/guides/k8s_guide.html#hugepages-settings-by-model). 
+As of now, Kubeflow Notebooks lacks the capability to request hugepages resources for individual notebooks.
+
+To add hugepages resources for the Notebook Pod, there are a couple of options:
+* Use [Limit Ranges](https://kubernetes.io/docs/concepts/policy/limit-range/) to set a default hugepages amount for all Pods in the namespace.
+* Edit the Notebook object after it has been created and add the hugepages resources to the pod template.
+
+The upcoming Notebooks 2.0 release will improve the situation with its `podTemplate` feature.

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

@@ -9,9 +9,12 @@ 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
+# NOTE: correct version alignments are found at https://pytorch.org/get-started/previous-versions/
-ARG TORCHAUDIO_VERSION=2.3.1
+#       they sometimes forget to publish a github release of `torchaudio` or `torchvision` when the cut a
-ARG TORCHVISION_VERSION=0.18.1
+#       patch release of `torch`, but they still publish a patch of `torchaudio` and `torchvision` on pypi
+ARG PYTORCH_VERSION=2.5.1
+ARG TORCHAUDIO_VERSION=2.5.1
+ARG TORCHVISION_VERSION=0.20.1
 
 # install - pytorch (cpu)
 RUN python3 -m pip install --quiet --no-cache-dir --index-url https://download.pytorch.org/whl/cpu --extra-index-url https://pypi.org/simple \

components/example-notebook-servers/jupyter-scipy/Dockerfile

@@ -22,32 +22,34 @@ USER $NB_UID
 # NOTE: we use mamba to speed things up
 RUN mamba install -y -q \
     altair \
-    beautifulsoup4==4.12.3 \
+    beautifulsoup4==4.13.3 \
-    bokeh==3.3.4 \
+    bokeh==3.6.3 \
     bottleneck \
     brotli \
     cloudpickle \
-    dask==2024.5.1 \
+    dask==2024.12.1 \
     dill \
     h5py \
     ipympl \
-    matplotlib==3.8.4 \
+    matplotlib==3.10.0 \
     numba \
     numexpr \
-    openblas==0.3.25 \
+    numpy==1.26.4 \
+    openblas==0.3.28 \
     openpyxl \
-    pandas==2.1.4 \
+    pandas==2.2.3 \
     patsy \
     protobuf \
-    pytables==3.9.2 \
+    pytables==3.10.2 \
-    scikit-image==0.22.0 \
+    scikit-image==0.25.1 \
-    scikit-learn==1.3.2 \
+    scikit-learn==1.6.1 \
-    scipy==1.11.3 \
+    scipy==1.15.1 \
     seaborn==0.13.2 \
-    sqlalchemy==2.0.30 \
+    sqlalchemy==2.0.38 \
     statsmodels \
     sympy \
     vincent \
+    xgboost==2.1.4 \
     xlrd \
  && mamba clean -a -f -y
 

components/example-notebook-servers/jupyter-scipy/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-tensorflow-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 \
+    bokeh==3.6.3 \
-    cloudpickle==2.2.1 \
+    cloudpickle==3.1.1 \
-    dill==0.3.8 \
+    dill==0.3.9 \
-    ipympl==0.9.4 \
+    ipympl==0.9.6 \
-    matplotlib==3.8.4 \
+    matplotlib==3.10.0 \
-    numpy==1.24.4 \
+    numpy==1.26.4 \
-    pandas==2.1.4 \
+    pandas==2.2.3 \
-    scikit-image==0.22.0 \
+    scikit-image==0.25.1 \
-    scikit-learn==1.3.2 \
+    scikit-learn==1.6.1 \
-    scipy==1.11.3 \
+    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-tensorflow-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-tensorflow-cuda/Dockerfile

@@ -10,10 +10,10 @@ ARG TARGETARCH
 # args - software versions
 #  - TensorFlow CUDA version matrix: https://www.tensorflow.org/install/source#gpu
 #  - Extra PyPi from NVIDIA (for TensorRT): https://pypi.nvidia.com/
-#  - TODO: it seems like TensorRT will be removed from TensorFlow in 2.18.0
+#  - TODO: TensorRT will be removed from TensorFlow in 2.18.0
-#          when updating past that version, remember to remove all TensorRT
+#          when updating past that version, either remove all TensorRT related packages,
-#          related packages and configs in this Dockerfile
+#          or investigate if there is a way to keep TensorRT support
-ARG TENSORFLOW_VERSION=2.15.1
+ARG TENSORFLOW_VERSION=2.17.1
 ARG TENSORRT_VERSION=8.6.1.post1
 ARG TENSORRT_LIBS_VERSION=8.6.1
 ARG TENSORRT_BINDINGS_VERSION=8.6.1
@@ -22,10 +22,12 @@ ARG TENSORRT_BINDINGS_VERSION=8.6.1
 # 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>=12.2"
+ENV NVIDIA_REQUIRE_CUDA "cuda>=12.3"
 
 # install - tensorflow
-#  - About '[and-cuda]' option: https://github.com/tensorflow/tensorflow/blob/v2.15.1/tensorflow/tools/pip_package/setup.py#L166-L177
+#  - About '[and-cuda]' option: https://github.com/tensorflow/tensorflow/blob/v2.17.1/tensorflow/tools/pip_package/setup.py#L153-L164
+#  - TODO: when updating TensorRT, you might need to change `tensorrt`, `tensorrt-libs`, and `tensorrt-bindings`
+#          to `tensorrt-cu12`, `tensorrt-cu12-libs`, and `tensorrt-cu12-bindings` respectively
 RUN python3 -m pip install --quiet --no-cache-dir --extra-index-url https://pypi.nvidia.com \
     tensorflow[and-cuda]==${TENSORFLOW_VERSION} \
     tensorrt==${TENSORRT_VERSION} \
@@ -34,6 +36,7 @@ RUN python3 -m pip install --quiet --no-cache-dir --extra-index-url https://pypi
 
 # create symlinks for TensorRT libs
 #  - https://github.com/tensorflow/tensorflow/issues/61986#issuecomment-1880489731
+#  - We are creating symlinks for the following libs, as this is where TF looks for them:
 #     - libnvinfer.so.8.6.1 -> libnvinfer.so.8
 #     - libnvinfer_plugin.so.8.6.1 -> libnvinfer_plugin.so.8
 ENV PYTHON_SITE_PACKAGES /opt/conda/lib/python3.11/site-packages

components/example-notebook-servers/jupyter-tensorflow-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 \
+    bokeh==3.6.3 \
-    cloudpickle==2.2.1 \
+    cloudpickle==3.1.1 \
-    dill==0.3.8 \
+    dill==0.3.9 \
-    ipympl==0.9.4 \
+    ipympl==0.9.6 \
-    matplotlib==3.8.4 \
+    matplotlib==3.10.0 \
-    numpy==1.24.4 \
+    numpy==1.26.4 \
-    pandas==2.1.4 \
+    pandas==2.2.3 \
-    scikit-image==0.22.0 \
+    scikit-image==0.25.1 \
-    scikit-learn==1.3.2 \
+    scikit-learn==1.6.1 \
-    scipy==1.11.3 \
+    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-tensorflow-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-tensorflow/Dockerfile

@@ -7,14 +7,7 @@ FROM $BASE_IMG
 
 # args - software versions
 # https://github.com/tensorflow/tensorflow/releases
-ARG TENSORFLOW_VERSION=2.15.1
+ARG TENSORFLOW_VERSION=2.17.1
-
-# install - h5py
-# TODO: remove when upstream ARM wheels for `h5py` are available again:
-#       https://github.com/h5py/h5py/issues/2408
-RUN mamba install -y -q \
-    h5py==3.11.0 \
- && mamba clean -a -f -y
 
 # install - tensorflow
 RUN python3 -m pip install --quiet --no-cache-dir \

components/example-notebook-servers/jupyter/Dockerfile

@@ -12,12 +12,12 @@ USER root
 # args - software versions
 # https://github.com/jupyterlab/jupyterlab/releases
 # https://github.com/jupyter/notebook/releases
-ARG JUPYTERLAB_VERSION=4.2.5
+ARG JUPYTERLAB_VERSION=4.3.5
-ARG JUPYTER_VERSION=7.2.2
+ARG JUPYTER_VERSION=7.3.2
-ARG MINIFORGE_VERSION=24.7.1-2
+ARG MINIFORGE_VERSION=24.11.3-0
 ARG NODE_MAJOR_VERSION=20
-ARG PIP_VERSION=24.2
+ARG PIP_VERSION=24.3.1
-ARG PYTHON_VERSION=3.11.10
+ARG PYTHON_VERSION=3.11.11
 
 # install -- node.js
 RUN export DEBIAN_FRONTEND=noninteractive \

components/example-notebook-servers/jupyter/s6/services.d/jupyterlab/run

@@ -1,10 +1,18 @@
 #!/command/with-contenv bash
 
-# the runtime directory must be a path that is NOT a persistent volume
+# 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}"
+
+# the jupyter runtime directory must be a path that is NOT a persistent volume
 # as volumes often cause permission issues https://github.com/jupyter/notebook/issues/5058
+# note, jupyter ignores XDG_RUNTIME_DIR: https://github.com/jupyter/jupyter_core/pull/143
 export JUPYTER_RUNTIME_DIR="/tmp/jupyter_runtime"
 
-cd "${HOME}"
+cd "${HOME}" || { echo "ERROR: failed to cd to ${HOME}"; exit 1; }
 echo "INFO: starting jupyter..."
 exec 2>&1
 exec /opt/conda/bin/jupyter lab \

components/example-notebook-servers/rstudio/Dockerfile

@@ -8,9 +8,9 @@ FROM $BASE_IMG
 ARG TARGETARCH
 
 # args - software versions (python)
-ARG MINIFORGE_VERSION=24.7.1-2
+ARG MINIFORGE_VERSION=24.11.3-0
-ARG PIP_VERSION=24.2
+ARG PIP_VERSION=24.3.1
-ARG PYTHON_VERSION=3.11.10
+ARG PYTHON_VERSION=3.11.11
 
 # args - software versions (R)
 # - rstudio: https://dailies.rstudio.com/release/
@@ -18,11 +18,11 @@ ARG PYTHON_VERSION=3.11.10
 # - r-png: https://www.rforge.net/png/news.html
 # - r-reticulate: https://github.com/rstudio/reticulate/releases
 # - r-shiny: https://github.com/rstudio/shiny/releases
-ARG RSTUDIO_VERSION=2024.09.0-375
+ARG RSTUDIO_VERSION=2024.12.1-563
-ARG R_BASE_VERSION=4.4.1
+ARG R_BASE_VERSION=4.4.2
 ARG R_PNG_VERSION=0.1_8
-ARG R_RETICULATE_VERSION=1.39.0
+ARG R_RETICULATE_VERSION=1.40.0
-ARG R_SHINY_VERSION=1.9.1
+ARG R_SHINY_VERSION=1.10.0
 
 USER root
 

components/example-notebook-servers/rstudio/s6/services.d/rstudio/run

@@ -1,5 +1,12 @@
 #!/command/with-contenv bash
 
+# 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}"
+
 # the runtime state directory must be a path that is NOT a persistent volume
 # note, this env-var is not read by rstudio, but is used later in this script
 export RSTUDIO_RUNTIME_DIR="/tmp/rstudio_runtime"