Creative Cloud Infrastructure

Business Impact

What this means for your business: Ship titles and creative projects faster. Reduce GPU infrastructure costs by up to 40%. Scale your team from 10 to 200 workstations without scaling your server room — and stop losing production days to hardware failures and slow builds.

The Problem

Content creation at scale — whether you are building an open-world AAA title, rendering episodic VFX shots, or training generative AI models — demands sustained, high-throughput compute. Most studios still run that compute on premises: racks of GPU workstations, manually patched Perforce servers, and CI runners duct-taped to Jenkins instances under someone’s desk.

The result is predictable. Hardware refresh cycles slip. Artists wait for renders. Engineers babysit nightly builds. And when your team goes remote or scales for crunch, the infrastructure cannot follow.

Remangu replaces that entire stack with a managed, AWS-native platform purpose-built for content pipelines.

How It Works

GPU Workstations in the Cloud

We provision NVIDIA-accelerated EC2 instances (G5, G6, P4d, P5) pre-configured with your DCC toolchain — Unreal Engine, Maya, Houdini, Blender, DaVinci Resolve, or whatever your pipeline requires. Each workstation is backed by high-performance NVMe storage and connected to your Perforce depot over a low-latency private link.

Artists and engineers connect via NICE DCV or Teradici, getting sub-frame latency even from home. Workstations spin up in minutes and scale down when idle, so you pay only for active seat-hours instead of depreciating fixed hardware.

Virtual Desktops for Distributed Teams

For producers, QA, and support staff who need secure access to internal tools without a full GPU instance, we deploy Amazon WorkSpaces or AppStream 2.0 fleets with SSO integration, session recording, and endpoint compliance policies. This gives every team member a consistent, auditable workspace regardless of their physical location or device.

Managed Perforce Infrastructure

Perforce Helix Core remains the version control system of choice for large binary assets, but running it well at scale is non-trivial. Remangu deploys and manages your Perforce infrastructure on AWS — including commit servers, edge proxies in every region your team operates, automated checkpoint/journal backups to S3, and real-time replication for disaster recovery.

We handle server tuning, typemap optimization, trigger scripting, and capacity planning so your DevOps team can focus on the pipeline rather than the plumbing.

CI/CD Pipelines

Build automation is where all the pieces come together. We design and operate CI/CD pipelines using a combination of AWS CodeBuild, GitHub Actions, and custom orchestration that understands your asset graph. Shader compilation, lightmap baking, cook stages, packaging, and deployment to storefronts or CDN — all automated, parallelized across spot instances, and observable through centralized dashboards.

Every pipeline run is reproducible. Every artifact is versioned. Every deployment is one approval away from production.

Why AWS

AWS provides the broadest selection of GPU instance types, the deepest integration with content-creation tooling, and the global backbone needed to serve distributed teams. Combined with Remangu’s operational expertise, you get enterprise-grade infrastructure without the enterprise-grade overhead.

• Elastic GPU capacity — Scale from 10 to 200 workstations in hours, not quarters.
• Global edge proxies — Perforce edge servers in any of 31 AWS regions, co-located with your talent.
• Cost controls — Savings Plans, Spot Instances, and automated scheduling reduce GPU spend by up to 40%.
• Security and compliance — VPC isolation, encryption at rest and in transit, IAM policies, and SOC 2 audit trails baked in from day one.

Who This Is For

• Gaming studios building on Unreal Engine, Unity, or proprietary engines who need elastic GPU compute and managed Perforce.
• VFX and post-production houses rendering with Houdini, Nuke, or Blender at burst scale.
• Media companies running AI/ML pipelines for content generation, upscaling, or localization.
• Any creative technology team that has outgrown its on-prem footprint and wants to stop managing hardware.

Getting Started

Remangu engages with a lightweight discovery phase — typically one to two weeks — where we audit your current pipeline, map dependencies, and design a target architecture on AWS. From there, we migrate workloads incrementally, validate performance benchmarks with your team, and hand off a fully managed environment with 24/7 monitoring and support.

No lift-and-shift surprises. No six-month runway. Just faster builds, lower costs, and infrastructure that scales with your ambition.

Further Reading

• GPU Infrastructure for ML Training: Cloud vs. On-Prem in 2026