Announcing the NICE DCV Amazon-managed component for EC2 Image Builder

Workloads requiring a high-performance remote display protocol for secure access can now utilize the NICE DCV Amazon-managed component within EC2 Image Builder. Within EC2 Image Builder, Amazon-managed components offer a quick start path to get workload dependencies added to your EC2 Image Builder pipeline. This component provides an automated mechanism to add DCV to visualization workloads in AWS with no additional cost for the display protocol. Since DCV server is offered as an Amazon-managed component, Amazon takes responsibility of keeping the component secure and up-to-date. Automating your image management with EC2 Image Builder helps reduce the administrative overhead associated with image maintenance.

Amazon-managed DCV components

DCV offers support for both Windows and Linux. You can verify support for your operating system in the NICE DCV Servers section of the DCV Administrator Guide. There is a respective Amazon-managed component for each supported platform. When a GPU is present, ensure your base Amazon Machine Image (AMI) has the appropriate GPU drivers installed. Alternatively, a preceding component can install them. For Windows, there are no additional prerequisites to utilize the component. For Linux, the image needs to have packages installed to present a GUI for DCV to stream. For more information, see the Prerequisites for Linux NICE DCV servers section of the DCV Administrator Guide.

Customization

The DCV components offer parameters to customize the DCV configuration within the image. If you use a brokering mechanism, such as DCV Session Manager or Leostream, you will not need to set a session owner. In a broker configuration, session management is managed through the broker. For the component’s usage instructions, see the Imaging section of the DCV Administrator Guide.

If you have unique DCV parameter requirements, you can create a new version of the DCV component to append your modifications. For example, if you use DCV external authentication, you need to configure an authentication token verifier endpoint within the DCV configuration. For more information on creating a new component version, see the Create a component using the Image Builder console page within the EC2 Image Builder User Guide. When adding a component to your EC2 Image Builder recipe, the recipe default’s to Use latest available component version. This is recommended and allows you to seamlessly inherit updates you make to components in your image pipeline. EC2 Image Builder offers a variety of features to customize your pipeline. To read more, see the EC2 Image Builder Administrator Guide.

Testing a custom component

When authoring custom components, you may want to test your customizations outside of EC2 Image builder. To test your custom component, you can utilize the AWS Task Orchestrator and Executor (AWSTOE) application. AWSTOE is a standalone application that allows you to validate and test your component on a supported platform. For more information on using AWSTOE, see the Get started with AWSTOE section of the EC2 Image Builder User Guide.

Conclusion

EC2 Image Builder offers a clear path to mitigate the administrative overhead associated with image maintenance. Automating image pipelines within the service increases productivity and reduces operations for building compliant and up-to-date images. By utilizing the Amazon-managed component for DCV, you can seamlessly add a high-performance remote display protocol to your visualization AWS workload with no additional cost for the protocol. DCV is a flexible component that can be utilized to benefit a variety of workloads. To learn more on how DCV can be architected for your use case, see the DCV related blogs in the AWS End User Computing blog channel.

Stefano joined AWS in 2016. He developed a passion for infrastructure automation and specializes in Linux-based workloads. In 2019, he started his current role as a DCV Quality Assurance Engineer.

Andrew came to AWS in 2019 from a large datacenter environment where he specialized in VMware, Cisco UCS, and automation. Through his time at AWS, he developed a passion for visualization workloads. In 2022, he started his current role as a Sr. Developer Advocate for DCV.