For many years Amazon Web Services (AWS) has been guiding customers in the deployment of powerful NVIDIA GPU-backed workstations for graphics-intensive workloads. With the recent expansion of our G-series Amazon Elastic Compute Cloud (Amazon EC2) graphics-based instances, we are excited to introduce new instance families that deliver enhanced performance and capabilities. We are also refreshing our comprehensive guidance on choosing and configuring these powerful virtual workstations.

This is the third post in a five-part series, focusing on the deployment of a Windows Server 2025 visual effects (VFX) workstation, using Amazon DCV as a performant desktop display protocol.

“Amazon DCV has unlocked previously unrealised playback performance, that has massively increased my productivity. Amazon DCV is performant on a range of systems and where other solutions have failed, I have been able to continue working and most importantly, continue delivering”

— Chris Coupe, CG Supervisor, Outpost VFX

Prerequisites

This post assumes that you have configured the following:

  1. An active AWS account with increased GPU Amazon EC2 service quota limits.
  2. A valid key pair in your AWS Region of choice.
  3. A configured virtual firewall security group, with open TCP/UDP ports 22, 443, 8443, and 3389 limited to only your own IP address.
  4. An AWS Identity and Access Management (IAM) profile with least-permissions Amazon Simple Storage Service (Amazon S3) read access.

We strongly recommend that you follow Part 1 of the series, Build a GPU workstation for visual effects on Amazon EC2: Part 1 – Setup, which goes through the preceding steps in detail.

Launching the Windows workstation

We use the latest AWS provided Windows Server 2025 Amazon Machine Image (AMI) for our deployment, and install the NVIDIA, Amazon DCV, and Wacom components to create a fully functioning VFX Windows desktop environment.

Follow these steps to launch a g6.4xlarge instance in your chosen AWS Region. If you want to use multiple GPU cards (for example, by using the 12xlarge, 24xlarge, or 48xlarge instance types), then Windows requires you to have that number of GPU cards present when setting up the GPU driver. In this case, we recommend starting the relevant multiple GPU instance size when making your AMI.

  1. Log in to the AWS Management Console and choose EC2 Dashboard in the top left.
  2. Choose Launch instances to start the prompt to launch a new instance.
  3. Give the instance a name, for example my_windows_workstation.
  4. Choose Windows under the Quick Start AMI and use the default Microsoft Windows Server Base Image 2025.
  5. Under Instance type, choose g6.4xlarge.
  6. Under Key pair name, choose the menu and choose your key pair. In the previous post we called it ec2_test_keypair to specify the password security credentials.
  7. Edit the Network settings to adjust security and network placement:
    1. Leave the Subnet to No preference.
    2. Make sure that Auto-assign public IP is set to Enable, so that you can access the instance through the internet.
  8. Under the Firewall (security groups) section of the Network Settings, choose Select existing security group, and specify your security group. In the previous post we named it ec2_test_sg to set up the firewall for the machine.
  9. In Configuration storage, expand the default root volume from 10 GiB to 50 GiB of gp3 storage.Important: Turn on encryption in the Advanced options by selecting the Encrypted option and selecting the default AWS managed key (aws/ebs) or a customer-managed KMS key for enhanced control. Amazon Elastic Block Store (Amazon EBS) encryption protects your VFX project files, renders, and application data at rest. Encryption uses industry-standard AES-256 encryption and is transparent to applications with minimal performance impact.
  10. Under Advanced details, specify the role that you created for workstation usage. In the previous post we called it basic_workstation_role through the IAM instance profile menu, so your workstation can access more services.
  11. Choose Launch instance on the right-hand side, as shown in the following figure.

Choose the link to the EC2 instance that has been launched, or view it through the Instances pane in the Amazon EC2 Service page. The following screen capture shows the newly launched workstation in the EC2 Instances list, where you can confirm it is ready to use. Wait until the my_windows_workstation instance shows an Instance state of Running and a Status check of 3/3 checks passed. Once both conditions are met, you can continue.

EC2 Instances page showing the my_windows_workstation instance with an Instance state of Running and a Status check of 3/3 checks passed

Figure 1: A screen capture of the EC2 Instances page, showing the my_windows_workstation in a ready state

Configuring the Windows workstation

In the last part of our series, Building a GPU workstation for visual effects with Amazon EC2: Part 4 – Optimizations, we show how to add scripting capabilities to the boot sequence of EC2 instances. This runs processes such as the NVIDIA GPU driver and Wacom tablet driver automatically during the startup of a machine. For the purposes of this post, we take a more manual approach, showing how you can remote into the machine to perform setup tasks.

You initially connect to the instance through the Windows Remote Desktop Protocol (RDP). In the Amazon EC2 Service page browser tab with the list of EC2 instances running, again choose the my_windows_workstation and choose Connect.

Choose the RDP client tab to connect to the machine through RDP with the following steps:

  1. Choose the Get password option to retrieve the Administrator password for the machine through your key pair credential.
  2. Upload the private ec2_test_keypair .pem key file that you downloaded previously and choose Decrypt password.
  3. The password is now displayed. Copy the password into the clipboard memory by choosing the copy icon, and choose OK, as shown in the following figure.
Get Windows Password page showing the instance ID, the private IP address, the username, and a redacted password

Figure 2: A screen capture of the Get Windows Password retrieval options available to EC2 instances

  1. Choose Download remote desktop file to download the .rdp file to your local machine.
  2. Run the .rdp file with your Remote Desktop Application of choice.
  3. When prompted, paste the previously copied Administrator password and choose OK.
  4. Choose Yes to trust the machine, and the session is authenticated and opened.

Security

We recommend setting a new, private password when you first start the fresh instance.

Open a Windows PowerShell to configure and make changes to the workstation. In the shell, configure that change and store your new password in a safe place.

net user Administrator <<NewPassword>>

Tools

To install the AWS Command Line Interface (AWS CLI) enter the following into the shell, and follow the on-screen prompts:

msiexec.exe /i https://awscli.amazonaws.com/AWSCLIV2.msi

Graphics

You must use AWS approved NVIDIA GPU drivers, issued through Amazon S3, not only for optimal compatibility and performance, but also to make sure that the necessary professional GRID drivers are automatically provisioned. You can always find the latest instructions in the Amazon EC2 Windows User Guide. At the time of writing, you can download the latest version to your desktop by running the following in a new Windows PowerShell:

$Bucket = "ec2-windows-nvidia-drivers" $KeyPrefix = "latest" $LocalPath = "$home\Desktop\NVIDIA" $Objects = Get-S3Object -BucketName $Bucket -KeyPrefix $KeyPrefix -Region us-east-1 foreach ($Object in $Objects) { $LocalFileName = $Object.Key if ($LocalFileName -ne '' -and $Object.Size -ne 0) { $LocalFilePath = Join-Path $LocalPath $LocalFileName Copy-S3Object -BucketName $Bucket -Key $Object.Key -LocalFile $LocalFilePath -Region us-east-1 } }

When it is downloaded, navigate to your Desktop, open the NVIDIA folder, then the latest folder inside, and run the NVIDIA installer executable, following the instructions.

Wacom support and Wacom Bridge

To add Wacom stylus support on the workstation, open Microsoft Edge (or install your browser of choice) and download and install the latest drivers from the Wacom drivers page.

Wacom Bridge is now generally available on Windows and Mac, and offers new advantages for Wacom users on AWS:

  • Applications running locally and remotely on AWS transfer their Wacom-specific settings automatically.
  • Artists can switch from local to remote use of the pen by choosing the necessary application window.
  • Wacom Inkline draws an instant temporary line on your screen, to bridge any gap between the local pen tip and the remote drawn line.
  • Amazon DCV provides enhanced security through data transport encrypted through HTTPS/TLS connections.

You can purchase a Wacom Bridge license (or request a trial) from a Wacom Sales representative.

Amazon DCV setup

To use Amazon DCV, you need to download the server application for the Amazon EC2 workstation from https://www.amazondcv.com/.

On the Amazon EC2 workstation, open the preceding link in your browser of choice, expand the latest Amazon DCV Server entry (2026.0 at the time of this post), choose the Windows (x86_64) link, download the installer, and run it. The default options automatically configure firewall entries for the Amazon DCV server ports, and start the Amazon DCV server.

Instance store setup

Finally, consider setting up the instance store on the instance:

  1. In the search bar at the bottom of the screen, enter Computer Management and press Enter.
  2. Choose Disk Management in the left pane.
  3. If prompted, then choose OK to accept the requested formatting of the instance store. The following figure shows such a prompt.
  4. Open the context menu for the Unallocated drive and choose New Simple Volume.
  5. Accept the requests, making any wanted changes to the drive name, or assigning to a folder instead.
  6. Choose Finish and the new volume is available to use as a temporary drive.
Disk Management prompt requesting automatic formatting of the newly found instance store

Figure 3: The Disk Management tool prompting the automatic formatting of the instance store

Proceed to the next section to log in to your workstation to use Amazon DCV.

Logging into your workstation through Amazon DCV

To log in to your machine using Amazon DCV, you must first set up the client software on your local machine:

  1. On your local machine or laptop, open Amazon DCV.
  2. Expand the Amazon DCV Client entry that matches the Server version that you installed on your workstation.
  3. Choose the relevant OS for your machine or laptop, for example Windows (x86_64).
  4. Download the installer.
  5. Run the installer.

When it is installed, you must determine the public IP address of the workstation to connect to:

  1. In the Amazon EC2 Console, choose Amazon EC2 Dashboard in the top left.
  2. Choose Instances (running).
  3. Choose the my_windows_workstation EC2 instance, in the top pane of the screen.
  4. Choose the copy icon next to the Public IPv4 address in the lower pane to copy the IP address.

Finally, use the Amazon DCV client to view the workstation:

  1. Open the Amazon DCV client on your local machine.
  2. Paste the previous IP address and press Enter, then trust the connection.
  3. You will see a security warning about an untrusted certificate. This is expected behavior because Amazon DCV uses a self-signed certificate by default. For this initial setup, it is safe to accept the certificate and proceed with the connection. For a detailed explanation of why this warning appears and how to implement proper certificate security for production environments, see Amazon DCV Connection Security in Building a GPU workstation for visual effects with Amazon EC2: Part 5 – Security.
  4. In the next Username / Password entry field, choose Administrator, and the appropriate password to which you set that user.

After the connection is established, Amazon DCV opens and displays the remote workstation desktop. The following screen capture shows the running workstation, confirming that your remote session is active and the environment is ready to use. In this example, the Windows Server 2025 desktop is shown with SideFX Houdini open, displaying a rendered scene in the viewport above the Windows taskbar.

Windows Server 2025 workstation running SideFX Houdini, with a rendered scene shown above the Windows taskbar

Figure 4: A screen capture of a Windows Server 2025 based workstation

With Windows, you automatically get brush sensitivity with Wacom and Amazon DCV connectivity. You don’t need to configure additional steps for your brushes to dynamically use the tablet’s controls.

Note: If you have need for a managed, non-persistent Windows desktop where several users share one GPU instance, consider Amazon WorkSpaces Applications multi-session fleets. They’re best for lighter graphics users such as reviewers, CAD viewers and editors, rather than artists working heavily in the viewport.

Cleaning up

Finally, you must remember to turn off your instances when not in use, either through the AWS Management Console, or through other programmatic methods such as AWS CLI. You incur costs associated with a running machine, and so deactivating machines when not in use reduces your expenditure.

This can be done by choosing Terminate instance from the Instance state options of the workstation in the Amazon EC2 console. The instance shuts down and reports a Terminated state on the console, but it automatically disappears after a short time.

However, if you want to learn more about the various methods to deactivate an EC2 instance, and create a persistent machine image of your Windows instance, then refer to Part 4 of the series, Building a GPU workstation for visual effects with Amazon EC2: Part 4 – Optimizations.

Conclusion

This post has shown how Amazon EC2 instances running Windows Server 2025 can create a GPU-backed VFX workstation. Your artists can use the latest technologies to unlock efficiencies, unhampered by the lengthy hardware renewal cycles typically found in on-premises environments.

We recommend that you continue to Part 4 of our series, Building a GPU workstation for visual effects with Amazon EC2: Part 4 – Optimizations, to learn how to implement GPU optimizations and infrastructure to streamline the provisioning of workstations. Part 4 also covers essential information on security practices for Windows EC2 instances, including build-time hardening and automated patch management to protect your workstation infrastructure from evolving threats.

For more information, contact us at .

Further reading

If you want to augment a VFX workstation environment with a dedicated render farm, then consider the managed service AWS Deadline Cloud.

EC2 instance metrics, such as CPU and memory usage, are sent to Amazon CloudWatch logs, so you can access this data through the console and AWS CLI. This information helps you discern whether an EC2 instance is over- or under-provisioned for the work at hand. For example, an instance might have excessive CPU, memory, and networking resources for the current tasks and could be optimized for price. Alternatively, it might not have enough resources to cope. For more information, visit the Amazon EC2 User Guide.

Windows instances can be lengthy to boot. Amazon EC2 Fast Launch for Windows is an AWS feature for faster launching of Windows machines through smart snapshots of the AMI.

Another post shows how to programmatically configure a Windows EC2 instance as part of a domain. This is particularly useful when the instances are used ephemerally, for example as part of a fleet of instances that spool up and down for rendering, and you need methods to bind and remove instances quickly.

More advanced examples of using Amazon DCV can be found in the aws-samples dcv-samples GitHub repo. This includes methods to broker multiple users and instances. Amazon DCV Connection Gateway provides a single entry point for users to connect to multiple Amazon DCV sessions across different instances, streamlining access management and improving security through centralized authentication.

Commercial options also exist to perform artist/instance brokering, using Amazon DCV and Amazon EC2 launch templates. An example of such an offering is Leostream.

For reference, examples of setting up Amazon DCV-capable instances and using AWS CloudFormation templates as a deployment method can be found in the amazon-ec2-nice-dcv-samples GitHub repo.

A deeper analysis of bit rates and latency for Amazon DCV connections can be found in this AWS HPC Blog post.

More information about Wacom Bridge running on Amazon DCV can be found in this AWS Wacom post and re:Invent 2024 talk.

About the authors

Andy Hayes

Andy Hayes

Andy is a Senior Visual Computing Solutions Architect at AWS. With 20 years’ experience in Visual Effects and Animation, Andy has led CG divisions and departments and added supervision to film projects, earning both Annie and Visual Effects Society Awards along the way. At AWS, he partners with studios and creative technology companies across the Media & Entertainment industry, spanning VFX and animation to rendering, virtual production, and games, helping them design and scale the cloud infrastructure and workflows behind their content pipelines. Drawing on his production background, Andy bridges the worlds of artists and engineers, guiding customers as they adopt technologies like high-performance rendering, GPU compute, and increasingly AI and machine learning to solve real creative and technical challenges. He remains passionate about the marriage of art and science that leads to the creation of compelling imagery, and about aligning technology to the evolving needs of the industry.

Mike Owen

Mike Owen

Mike is a Principal Visual Computing Solutions Architect at AWS, where he has spent many years helping studios move their creative work to the cloud. He focuses on the architecture behind high-end content creation: cloud workstations, render farm scaling and storage that spans multiple sites. Mike works with studios and creative technology companies across Media & Entertainment, from VFX and animation to finishing and colour. He has pioneered the concept of “Studio in the Cloud” and helped bring industry tools such as Autodesk Flame to AWS, and has contributed to a range of AWS Thinkbox Deadline improvements. Most recently he has led development of KNFSD File Cache, an open-source NFS caching solution from AWS. It lets studios burst large render workloads into the cloud whilst their data stays on existing on-premises storage. He cares about giving artists the same seamless, colour-accurate experience in the cloud that they expect on-premises, and about removing the cost and complexity that usually come with building a global studio.