Derived Data Cache Service (DDCS)

The Derived Data Cache Service (DDCS) caches derived content to reduce scene load time and improve rendering performance. DDCS trades network bandwidth for compute time by caching derived data, allowing multiple GPUs to share pre-generated content.

Overview

DDCS reduces scene load time and improves performance when properly configured and sized for the workload. Derived data generation is computationally expensive and time-consuming. During initial scene loads, GPUs generate the most derived content as they encounter assets for the first time. While DDCS may add some time to cold scene loads (as content must be generated and written to DDCS synchronously), the generated data becomes immediately available to other GPUs. During “warm” scene loads, render workers read all derived content from DDCS instead of regenerating it, significantly reducing load times.

When to Use DDCS

Use DDCS when:

• You’re running distributed simulation and rendering workloads

• You need to cache derived content (processed source content)

• You want to reduce scene load times for warm scene loads

• Multiple render workers need access to the same derived content

Documentation

DDCS documentation covers configuration, deployment, TLS setup, and AWS EKS instance selection:

DDCS Guides:

• DDCS: Configure
  • Base Configuration
  • Configuration Recommendations
  • Summary
• DDCS: Deployment
  • Configuration
  • Deployment Steps
  • Uninstall Instructions
  • Summary
• DDCS: TLS Configuration
  • 1. Create the TLS Secret
  • 2. Enable TLS in values.yaml
  • 3. Optional: Configure CA Root Certificate
  • 4. Complete Example Configuration
  • 5. Apply Configuration Changes
  • 6. Verify TLS Configuration

Configuration

DDCS is configured using Helm values files. The configuration guide includes:

• Base configuration examples

• Scaling and provisioning recommendations

• Memory allocation settings

• Storage configuration

• Monitoring setup

Deployment

DDCS is deployed using Helm charts. The deployment guide covers:

• Helm repository setup

• Namespace creation

• Secret configuration

• Chart installation

• Verification steps

Advanced Topics

• TLS Configuration: Enable encrypted communication between DDCS and clients

• AWS EKS Instance Selection: Optimize instance types for cost and performance

• Burstable Instance Analysis: Evaluate burstable instances for cost savings

Monitoring

DDCS includes Prometheus metrics for monitoring:

• Cache hit ratios

• Storage utilization

• Network performance

• Request throughput

Next Steps

1. Review the configuration guide - Understand DDCS configuration options

2. Plan your deployment - Determine replica count and resource requirements

3. Configure DDCS - Set up Helm values files based on your workload

4. Deploy DDCS - Install using Helm following the deployment guide

5. Monitor performance - Set up monitoring dashboards and alerts