Azure Data Science Virtual Machine release notes
This article describes Azure Data Science Virtual Machine releases. For a full list of included tools, along with version numbers, visit this resource.
Because of rapidly evolving needs and packages updates, we target new releases of Azure Data Science Virtual Machine for Windows and Ubuntu images every month.
Azure portal users can find the latest image available for provisioning the Data Science Virtual Machine. For CLI or Azure Resource Manager (ARM) users, we keep images of individual versions available for 12 months. After that period, specific image versions are no longer available for provisioning.
Visit the list of known issues to learn about known bugs and workarounds.
Data Science Virtual Machine – Ubuntu 22.04
DSVM-Ubuntu-22.04 image is a tailored Data Science Virtual Machine built on the robust Ubuntu 22.04 platform. It comes pre-installed with a comprehensive suite of popular data science and AI tools, including deep learning frameworks, Jupyter notebooks, and visualization libraries. Optimized for seamless development and deployment, this image offers enhanced compatibility with modern hardware, enabling data scientists, machine learning engineers, and AI researchers to accelerate their workflows efficiently. Whether you're building models, running simulations, or analyzing large datasets, DSVM-Ubuntu-22.04 empowers you with the tools and performance needed to drive innovation.
- OS:
Ubuntu-22.04
- ImageVersion:
24.10.02
- SDK-version:
1.57.0
- Python Version:
3.10.8
DSVM 22.04 has all the latest packages that we had installed and shipped with 20.04
Data Science Virtual Machine – Ubuntu 20.04
Version 24.10.01
- SDK
1.57.0
- NVIDIA
535.183.01
- Cuda
cuda_12.2.r12
- Python Version
3.10.8
Data Science Virtual Machine - Windows 2022
Version 24.09.26
- SDK
1.57.0
Data Science Virtual Machine - Windows 2019
Version 24.10.07
- SDK
1.57.0
Data Science Virtual Machine - Windows 2022
Version 24.05.20
- SDK
1.56.0
Data Science Virtual Machine - Windows 2019
Version 24.05.20
- SDK
1.56.0
Data Science VM – Ubuntu 20.04
Version 24.05.24
- SDK
1.56.0
Data Science Virtual Machine - Windows 2022
Version 24.05.03
- SDK
1.55
azureml-dataset-runtime
version1.55.0
azureml-train-automl-client
azureml-dataset-runtime [fuse,pandas]
version1.55.0
GitPython
version3.1.41
pyarrow
version14.0.2
Resolved issue: Office365ProPlus installation
Data Science VM – Ubuntu 20.04
Version 23.12.18
Primary changes:
numpy
version1.22.3
pytz
version2022.6
torch
version1.12.0
certifi
version2023.7.2
azure-mgmt-network
to version25.1.0
scikit-learn
version1.0.2
scipy
version1.9.2
accuracy
pickle5
pillow
version10.1.0
experimental
ipykernel
version6.14.0
en_core_web_sm
Data Science Virtual Machine - Windows 2019
Version 23.12.11
Primary changes:
- SDK
1.54.0
- numba
- Scipy
azure-core
to version1.29.4
azure-identity
to version1.14.0
azure-storage-queue
to version12.7.2
The Data Science Virtual Machine (DSVM) offering for Data Science VM – Windows 2022 is now generally available in the marketplace.
Version 23.11.23
Primary changes:
- SDK
1.54.0
- numba
- Scipy
azure-core
to version1.29.4
azure-identity
to version1.14.0
azure-storage-queue
to version12.7.2
A new Data Science Virtual Machine (DSVM) offering for Data Science VM – Windows 2022 (Preview) is now live in the marketplace.
Version 23.06.25
Primary changes:
- SDK
1.51.0
Data Science VM – Ubuntu 20.04
Version 23.04.24
Primary changes:
- SDK
1.50.0
- Dotnet upgraded to
6.0
SDK - PyTorch GPU functionality fixed in `azureml_py38_PT_and_TF environment.
- Blobfuse upgraded to blobfuse2
Data Science Virtual Machine - Windows 2019
Version: 23.03.31
Primary changes:
- SDK
1.49
- Cuda drivers upgraded to
11.4
- PyTorch GPU functionality fixed on
azureml_py38
andazureml_py28_PT_and_TF
environments Dotnet
upgraded to6.0
Data Science VM – Ubuntu 20.04
Version: 23.01.06
Primary changes:
- Added R package "ranger"
- Pinned
pandas==1.1.5
andnumpy==1.23.0
inazureml_py38
environment
Data Science VM – Ubuntu 20.04
Version: 22.11.25
Primary changes:
Azure Machine Learning SDK V2
samples includedRay
to version2.0.0
- Added
clock
,recipes
R
packages azureml-core
to version1.47.0
azure-ai-ml
to version1.1.1
Data Science Virtual Machine - Windows 2019
Version: 22.11.27
Primary changes:
Azure Machine Learning SDK V2
samples includedRScirpt
environment path alignmentRay
version2.0.0
package added toazureml_py38
andazureml_py38_PT_TF
environments.azureml-core
to version1.47.0
azure-ai-ml
to version1.1.1
Announcement: Beginning October 1, 2022, the Ubuntu 18 Data Science Virtual Machine (DSVM) will not be available on the marketplace. We recommend that users switch to the Ubuntu 20 DSVM as we continue to ship updates/patches on our latest Data Science VM – Ubuntu 20.04
Users who use the Azure Resource Manager (ARM) template/virtual machine scale, set to deploy the Ubuntu DSVM machines, should set the configuration to
Offer | SKU |
---|---|
ubuntu-2004 | 2004 for Gen1 or 2004-gen2 for Gen2 VM sizes |
instead of:
Offer | SKU |
---|---|
ubuntu-1804 | 1804 for Gen1 or 1804-gen2 for Gen2 VM sizes |
Note
There's no problem for existing customers who still use the Ubuntu-18 DSVM, as of our October 2022 update. However, the deprecation plan is scheduled for December 2022. We recommend that you switch to Ubuntu-20 DSVM at your earliest convenience.
Data Science VM – Ubuntu 20.04
Version 22.09.19
Primary changes:
.NET Framework
to version3.1.423
Azure Cli
to version2.40.0
Intelijidea
to version2022.2.2
- Microsoft Edge Browser to version
107.0.1379.1
Nodejs
to versionv16.17.0
Pycharm
to version2022.2.1
Environment Specific Updates:
azureml_py38
:
azureml-core
to version1.45.0
py38_default
:
Jupyter Lab
to version3.4.7
azure-core
to version1.25.1
keras
to version2.10.0
tensorflow-gpu
to version2.10.0
Data Science Virtual Machine - Windows 2019
Version 22.09.06
Primary changes:
- Base OS level image updates.
Data Science VM – Ubuntu 20.04
Version 22.08.11
Primary changes:
- Jupyterlab upgraded to version
3.4.5
matplotlib
,azureml-mlflow
added tosdkv2
environment.- Jupyterhub spawner reconfigured to root environment.
Data Science VM – Ubuntu 20.04
Version 22.07.19
Primary changes:
Updated
Azure Cli
to version2.38.0
Updated
Nodejs
to versionv16.16.0
Updated
Scala
to version2.12.15
Updated
Spark
to version3.2.2
MMLSpark
notebook featuresv0.10.0
4 other R libraries:
Added new Azure Machine Learning Environment
azureml_310_sdkv2
Data Science Virtual Machine - Windows 2019
Version 22.07.18
Primary changes:
- General OS level updates.
Data Science VM – Ubuntu 18.04 Data Science VM – Ubuntu 20.04
Version 22.07.08
Primary changes:
- Minor bug fixes.
Data Science Virtual Machine - Windows 2019 Data Science VM – Ubuntu 20.04
Version 22.06.10
Data Science VM – Ubuntu 18.04
Version 22.06.13
Primary changes:
- Remove
Rstudio
software tool from Data Science Virtual Machine (DSVM) images.
Data Science VM – Ubuntu 20.04
Version 22.05.11
Primary changes:
- Upgraded
log4j(v2)
to version2.17.2
Data Science VM – Ubuntu 18.04 Data Science VM – Ubuntu 20.04
Version 22.04.27
Primary changes:
Plotly
andsummarytools
R studio extensions runtime import fix.Cudatoolkit
andCUDNN
upgraded to13.1
and2.8.1
respectively.- Fix
Python 3.8
- Azure Machine Learning notebook run, pinnedmatplotlib
to3.2.1
andcycler
to0.11.0
packages inAzureml_py38
environment.
Data Science Virtual Machine - Windows 2019
Version: 22.04.21
Primary changes:
Plotly
R studio extension patch.- Update
Rscript
env path to support latest R studio version4.1.3
.
A new Data Science Virtual Machine (DSVM) offering for Data Science VM – Ubuntu 20.04 is currently live in the marketplace.
Version: 22.04.05
A new image for Data Science VM – Ubuntu 18.04
Version: 22.04.01
Primary changes:
Updated R environment - added these libraries:
Cluster
Devtools Factoextra
GlueHere
Ottr
Paletteer
Patchwork
Plotly
Rmd2jupyter
Scales
Statip
Summarytools
Tidyverse
Tidymodels
Testthat
Further
Log4j
vulnerability mitigation - although not used, we moved alllog4j
to versionv2
, we removed oldlog4j jars1.0
, and we movedlog4j
version 2.0 jarsAzure CLI
to version2.33.1
Fixed
jupyterhub
access issue using public ip addressRedesign of Conda environments - as we proceed with alignment and refinement of the Conda environments, we created:
azureml_py38
: environment based on Python 3.8 with preinstalled Azure Machine Learning SDK that also contains the AutoML environmentazureml_py38_PT_TF
: an additionalazureml_py38
environment, preinstalled with latestTensorFlow
andPyTorch
py38_default
: default system environment based onPython 3.8
- We removed the
azureml_py36_tensorflow
azureml_py36_pytorch
py38_tensorflow
py38_pytorch
environments
Data Science Virtual Machine - Windows 2019
Version: 22.03.09
Primary changes:
Updated R environment - added these libraries:
Cluster
Devtools Factoextra
GlueHere
Ottr
Paletteer
Patchwork
Plotly
Rmd2jupyter
Scales
Statip
Summarytools
Tidyverse
Tidymodels
Testthat
Further
Log4j
vulnerability mitigation - although not used, we moved alllog4j
to version v2, we removed old log4j jars1.0, and we movedlog4j
version 2.0 jars.Azure CLI to version 2.33.1
Redesign of Conda environments - as proceed with alignment and refinement of the Conda environments, we created:
azureml_py38
: environment based on Python 3.8 with preinstalled Azure Machine Learning SDK containing also AutoML environmentazureml_py38_PT_TF
: complementary environmentazureml_py38
with preinstalled with latest TensorFlow and PyTorchpy38_default
: default system environment based on Python 3.8- we removed
azureml_py36_tensorflow
,azureml_py36_pytorch
,py38_tensorflow
andpy38_pytorch
environments.
Data Science Virtual Machine - Windows 2019
Version: 21.12.03
The Windows 2019 Data Science Virtual Machine (DSVM) is supported under publisher: microsoft-dsvm, offer ID: dsvm-win-2019, plan ID/SKU ID: winserver-2019
Users who use the Azure Resource Manager (ARM) template / virtual machine scale, set to deploy the Windows DSVM machines, should configure the SKU with winserver-2019
instead of server-2019
, since we continue to ship updates to Windows DSVM images on the new SKU from March 2022.
A new image for Windows Server 2019
Version: 21.12.03
Primary changes:
- Updated pytorch to version 1.10.0
- Updated tensorflow to version 2.7.0
- Fix for Azure Machine Learning SDK & AutoML environment
- Windows Security update
- Improvement of stability and minor bug fixes
A new image for Ubuntu 18.04
Version: 21.11.04
Primary changes:
- Changed .NET Framework to version 3.1.414
- Changed Azcopy to version 10.13.0
- Changed Azure CLI to version 2.30.0
- Changed CUDA to version 11.5
- Changed Docker to version 20.10.10
- Changed Intellijidea to version 2021.2.3
- Changed NVIDIA Drivers to version 470.103.01
- Changed NVIDIA SMI to version 470.103.01
- Changed Nodejs to version v16.13.0
- Changed Pycharm to version 2021.2.3
- Changed VS Code to version 1.61.2
- Conda
- azureml_py36_automl
- Changed azureml-core to version 1.35.0
- py38_default
- Changed Jupyter Lab / jupyterlab to version 3.2.1
- Changed Jupyter Notebook / notebook to version 6.4.5
- Changed Jupyter Server / jupyter_server to version 1.11.2
- Changed PyTorch Profiler TensorBoard Plugin / torch-tb-profiler to version 0.3.1
- Changed azure-core to version 1.19.1
- Changed matplotlib to version 3.4.3
- Changed mkl to version 2021.4.0
- Changed onnx to version 1.10.2
- Changed opencv-python to version 4.5.4.58
- Changed pandas to version 1.3.4
- Changed pytorch to version 1.10.0
- Changed scikit-learn to version 1.0.1
- Changed tensorflow-gpu to version 2.6.2
- azureml_py36_automl
A new image for Ubuntu 18.04
Version: 21.10.07
Primary changes:
- Changed pytorch to version 1.9.1
- Changed Docker to version 20.10.9
- Changed Intellijidea to version 2021.2.2
- Changed Nodejs to version v14.18.0
- Changed Pycharm to version 2021.2.2
- Changed VS Code to version 1.60.2
- Fixed AutoML environment (azureml_py36_automl)
- Fixed Azure Storage Explorer stability
- Improvement of stability and minor bug fixes
A new image for Windows Server 2019
Version: 21.08.11
Primary changes:
- Windows Security update
- Update of Nvidia CuDNN to 8.1.0
- Update of Jupyter Lab -to 3.0.16
- Added MLFLow for experiment tracking
- Improvement of stability and minor bug fixes
A new image for Ubuntu 18.04
Primary changes:
- Updated to PyTorch 1.9.0
- Updated Azure CLI to 2.26.1
- Updated Azure CLI Azure Machine Learning extension to 1.29.0
- Update VS Code version 1.58.1
- Improvement of stability and minor bug fixes
A new image for Windows Server 2019
Version: 21.06.22
Primary changes:
- Updated to PyTorch 1.9.0
- Fixed a bug where git wasn't available
A new image for Ubuntu 18.04
Version: 21.06.01
Primary changes:
- Docker is enabled by default
- JupyterHub uses JupyterLab by default
- Updated Python versions to fix CVE-2020-15523
- Updated IntelliJ IDEA to version 2021.1 to fix CVE-2021-25758
- Updated PyCharm Community to 2021.1
- Updated TensorFlow to version 2.5.0
Removed several icons from desktop.
A new image for Windows Server 2019
Version: 21.05.22
Selected version updates include:
- AzCopy 10.10.0
- Azure CLI 2.23.0
- Azure Data Studio 1.28.0
- CUDA 11.1
- Java 11
- Julia 1.0.5
- Jupyter Lab 2.2.6
- Microsoft Edge browser
- NodeJS 16.2.0
- Power BI Desktop 2.93.641.0 64-bit (May 2021)
- PyCharm Community Edition 2021.1.1
- Python 3.8
- PyTorch 1.8.1
- R 4.1.0
- RStudio 1.4.1106
- Spark 3.1.1
- Storage Explorer 1.19.1
- TensorFlow 2.5.0
- Visual Studio Code 1.56.2 incl. Azure Machine Learning extension
- Visual Studio Community Edition 2019 (version 16.9.6)
Removed Firefox, Apache Drill and Azure Integration Runtime.
Dark mode; changed icons on desktop; wallpaper background change.
A new image for Ubuntu 18.04
Selected version updates include:
- azcopy 10.10
- Azure CLI 2.23.0
- Azure Data Studio 1.22.1
- Azure Storage Explorer 1.19.1
- CUDA 11.3, cuDNN 8, NCCL2
- dask 2021.01.0
- Java 11 (OpenJDK)
- Jupyter Lab 3.0.14
- Microsoft Edge browser (beta)
- Python 3.8
- PyTorch 1.8.1 incl. torchaudio torchtext torchvision, torch-tb-profiler
- R 4.0.5
- Spark 3.1 incl. mmlspark, connectors to Blob Storage, Data Lake, Azure Cosmos DB
- TensorFlow 2.4.1 incl. TensorBoard
- VS.Code 1.56
Added docker. To save resources, the docker service isn't started by default. To start the docker service, run this command at the command line:
sudo systemctl start docker
Note
If your machine has GPU(s), you can make use of the GPU(s) inside the containers by adding a --gpus
parameter to your docker command.
For example, this command
sudo docker run --gpus all -it --rm -v local_dir:container_dir nvcr.io/nvidia/pytorch:18.04-py3
runs an Ubuntu 18.04 container with PyTorch pre-installed and all GPUs enabled. It also builds a local local_dir folder available in the container under container_dir.
The Data Science Virtual Machine (DSVM) images for Ubuntu 18.04 and Windows 2019 images are now available.
- Azure Storage Explorer 1.10.1
- Firefox 69.0.2
- Power BI Desktop 2.73.55xx
- PyCharm 19.2.3
- RStudio 1.2.50xx
Earlier, the default browser was set to Internet Explorer. Users are now prompted to choose a default browser when they first sign in.