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Disambiguating Inputs from Multiple Users on One Nice DCV Client

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Hello,

I am working on a project where I would like to have multiple people remote into the same EC2 instance. While NICE DCV allows this, all users share a mouse and keyboard. I am trying to figure out a way to be able to separate the inputs of each user (i.e. mouse from IP 1 and mouse from IP 2), but it seems like DCV merges the signals at some point such that my Windows client only recognizes one USB driver.

My main question is whether this is feasible or not. I'd appreciate any advice or workarounds. Thank you!

질문됨 2달 전71회 조회
1개 답변
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Amazon DCV is designed for collaboration where multiple users share the same session, but it doesn't natively support distinguishing between different users' input devices. When multiple users collaborate on a DCV session, the system is designed to have all users share the same mouse and keyboard inputs.

When collaborating on an Amazon DCV session, users join by selecting the "Collaborators" icon in the DCV toolbar and choosing the session to join. The session owner has the ability to disconnect other users from the session using the "Disconnect" option, but there's no built-in functionality to separate or distinguish between different users' input devices.

It's important to note that Amazon DCV's collaboration feature is primarily designed for screen sharing and collaborative work where users take turns controlling the session, rather than simultaneous independent control by multiple users.

For virtual sessions on Linux DCV servers, while each virtual session has an independent Xdcv display, many system resources are shared when the same user runs multiple sessions. However, this doesn't solve the issue of distinguishing between different users' inputs within the same session.

As a workaround, you might consider having each user connect to their own separate DCV session on the EC2 instance instead of collaborating on the same session, though this would mean they wouldn't see each other's work in real-time.
Sources
Collaborating on a Amazon DCV session - Amazon DCV
Understanding Amazon DCV sessions - Amazon DCV

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