🎨 3D Rendering & VFX · Deployment · Pro
Cloud Render Farm Deployment
Where each part of a cloud render farm runs: artists' workstations, the render queue manager, autoscaling GPU render nodes and shared storage.
Deployment diagrams are part of Pro. Anyone can view this one; generating and editing it needs Pro.
Drawing diagram…
What this diagram shows
- Artists submit jobs from their 3D tools to a queue manager
- GPU render nodes scale up with the queue and down when idle
- Scene files and frames live on shared high-speed storage
Prompt used
Deployment of a cloud render farm: artists in the studio work in Blender/Maya/Houdini and submit render jobs to a render queue manager (Deadline) in the cloud. An autoscaler adds or removes GPU render nodes (spot instances) based on queue length. Render nodes read scenes and textures from a shared file system and write finished frames back; a licence server hands out renderer licences. The studio connects over a site-to-site VPN, and finished frames sync back to the studio NAS.
Mermaid code
flowchart TB
subgraph Studio[Studio Office]
WS[Artist Workstations - Blender / Maya / Houdini]
NAS[(Studio NAS)]
end
subgraph Cloud[Cloud Region]
QM[Render Queue Manager - Deadline]
AS[Autoscaler]
LIC[Licence Server]
subgraph Pool[GPU Render Node Pool - spot instances]
N1[Render Node 1]
N2[Render Node 2]
N3[Render Node N]
end
FS[(Shared File System - scenes, textures, frames)]
end
WS -->|Site-to-site VPN| QM
WS -->|Upload scenes| FS
QM -->|Queue length| AS
AS -->|Add / remove nodes| Pool
QM --> N1
QM --> N2
QM --> N3
N1 --> LIC
N1 <--> FS
N2 <--> FS
N3 <--> FS
FS -->|Finished frames sync| NASRelated templates
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