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Deployment

Container Orchestration for AI Workloads

1 min read

AI inference needs GPUs. Web serving does not. Running both on the same cluster means mixed node pools and custom scheduling.

section

Our Approach

  • Mixed Node Pools: CPU for web, GPU for inference, with node affinity
  • Model Preloading: Init containers cache model weights, eliminating cold starts
  • Spot Instances: 60-70% cost savings with graceful eviction migration
  • Request Queuing: Custom queue smooths traffic spikes
section

Economics

T4 GPUs 24/7: $2,400/month per node. With spot + scheduling: $680/month — 72% reduction.

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Multi-Region Data Sovereignty

How we route voice data to region-specific nodes and prove compliance with automated audit trails.

1 min read

Deployment

Edge Deployment Patterns

Moving from serverless to edge-first changes everything. Zero-downtime deployments and cold start elimination.

1 min read

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