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Carlos Bravo
5 November 2026

Ubuntu Pro is now available on AWS Deep Learning Amazon Machine Images (DLAMI)


In September 2026, Amazon Web Services (AWS) published its first DLAMIs built on Ubuntu Pro in the Base GPU family. By choosing Ubuntu Pro, enterprises launching DLAMIs gain a stronger security maintenance posture at launch thanks to Expanded Security Maintenance (ESM).

What are the DLAMIs?

The DLAMIs are AWS-maintained machine images for GPU and accelerator instances. Each ships the NVIDIA driver, CUDA, the Elastic Fabric Adapter (EFA) networking stack, and the surrounding tooling already installed and tested together. This means a GPU node is productive on first boot, rather than after a day of driver work. 

These images cover 31 actively built lines: Base AMIs carrying the drivers alone, framework images with PyTorch preinstalled, and Neuron images for Trainium and Inferentia. 

What is included in Ubuntu Pro DLAMI images?

Ubuntu Pro DLAMI is available as a base GPU image for typical AI workloads on the latest GPU hardware. There are four versions of the image split across 2 Ubuntu releases and 2 architectures. This enables a broad support of instance types, including Grace Blackwell architecture. It ships with NVIDIA driver 595.91.07 and several CUDA toolkits.

ImageArchitectureKernelCUDA
Base GPU AMI (Ubuntu Pro 24.04 Long Term Supported (LTS))x86_647.0.0-1013-aws12.8, 12.9, 13.0, 13.2 (13.2 default)
Base GPU AMI (Ubuntu Pro 22.04 LTS)x86_646.8.0-1064-aws12.8, 12.9, 13.0, 13.2 (13.2 default)
ARM64 Base GPU AMI (Ubuntu Pro 24.04 LTS)ARM647.0.0-1013-aws12.8, 12.9, 13.0, 13.2 (13.2 default)
ARM64 Base GPU AMI (Ubuntu Pro 22.04 LTS)ARM646.8.0-1064-aws12.8, 12.9, 13.0, 13.2 (13.2 default)

The x86 images cover 14 GPU families, from G4dn and G5 through P4d, P5, and P5en, to the Blackwell P6-B200 and P6-B300. The ARM images cover G5g and the Grace Blackwell P6e-GB200 and P6e-GB300 instance families.

Enterprise grade images with Ubuntu Pro

GPU images have been preconfigured with a pinned kernel for stability and compatibility purposes. The NVIDIA and EFA drivers are compiled against it, so AWS holds the kernel packages and ships security fixes as a new image every week or two. 

Ubuntu Pro comes with ESM by default, which expands security updates from the Main repository (the primary Ubuntu repository, maintained by Canonical’s engineers) to Universe (the community-maintained repository of Ubuntu) and extends the overall security coverage from 5 to 10 years. This solves a major compliance challenge for enterprises that cannot rely solely on community support. The Universe repository contains many key AI/ML dependencies, which the default DLAMI already has included at launch. 

It also enables Kernel Livepatch, delivering in-memory security updates for the active kernel to prevent unexpected reboots. This is especially important for GPU accelerated machines, which are typically dedicated to continuous, long-running operations.

Supporting NVIDIA Grace Blackwell P6e-GB200 and P6e-GB300 instance types

For the first time on AWS, Ubuntu Pro DLAMIs provide out-of-the-box NVIDIA Grace Blackwell support across its two variants: GB200 and GB300.  While Ubuntu Pro 24.04 LTS supports both P6e-GB200 and P6e-GB300, Ubuntu Pro 22.04 LTS supports only P6e-GB200. 

Kernel livepatch on ARM64 is available from Ubuntu 26.04 LTS onwards.

What ESM covers on the image

If you’re curious to know whether the Ubuntu Pro variant is for you, you can either run pro security-status --esm-apps on the Ubuntu Pro 24.04 LTS Base GPU image, or continue reading.

The Ubuntu Pro DLAMI base image comes with 38 pre-installed packages from the Universe repository. These packages are covered by Ubuntu Pro from launch, and include key packages commonly used on AI workloads at scale:

What it isPackages covered by ESM
MPI and RDMA fabriclibopenmpi3t64
libfabric1
libpmix2t64
libucx0
libpsm2-2
libpsm-infinipath1
libhwloc15
libhwloc-plugins
libibdm1
libopensm9
libosmcomp5
libosmvendor5
ibutils
libmunge2
GPU and accelerator runtimelibamdhip64-5
libamd-comgr2
libhsa-runtime64-1
libhsakmt1
ocl-icd-libopencl1
Python packagingpython3-pip
python3-pip-whl
python3-wheel
python3-venv
python3.12-venv
python3-setuptools-whl
Everything elseapt-transport-https
check
environment-modules
fuse
libfuse2t64
libsnmp-dev
libsnmp-perl
libnetsnmptrapd40t64
libsubunit0
libsubunit-dev
pahole
pigz

However, these packages are only the starting point. With every deployment built, more packages and dependencies will be drawn in, the majority of which often come from the Universe repository. These packages receive support only through a Canonical Pro subscription, through ESM. 

How to get the images

Each image line has a public AWS Systems Manager (SSM) parameter that resolves to its latest build. You can get the images by running the following commands with AWS CLI.

For AMD64 images:

aws ssm get-parameters --names /aws/service/deeplearning/ami/x86_64/base-oss-nvidia-driver-gpu-ubuntu-pro-24.04/latest/ami-id
aws ssm get-parameters --names /aws/service/deeplearning/ami/arm64/base-oss-nvidia-driver-gpu-ubuntu-pro-24.04/latest/ami-id

For ARM64 (Graviton and NVIDIA Grace Blackwell):

aws ssm get-parameters --names /aws/service/deeplearning/ami/arm64/base-oss-nvidia-driver-gpu-ubuntu-pro-24.04/latest/ami-id

If you want to check whether your Ubuntu Pro subscription is active, run pro status on a live instance to see your active entitlements and configurations.

Conclusion and Next Steps

Bringing Ubuntu Pro to the AWS DLAMIs provides enterprises with an ESM posture right out of the box. With Canonical’s commitment to support and maintain Universe packages for 10 years, and Kernel Livepatch enabling seamless patching without reboots, organizations can confidently run AI workloads while meeting stringent security and compliance standards.

Ready to enhance your GPU workloads? Get started today by launching the new Ubuntu Pro DLAMIs on AMD64 images or ARM64, or visit the AWS Deep Learning AMI Documentation for detailed setup guides and deployment options. If you have any questions, contact us here. 

Learn more:


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