How Temporal powers workflows at HeyGen

HeyGen replaced a custom video-generation orchestration system based on MySQL, RabbitMQ, Celery, polling, and callbacks with Temporal to improve reliability, recovery, and development speed across complex media and AI workflows. Temporal now coordinates millions of daily workflow executions involving speech generation, scene preparation, GPU avatar inference, rendering, compositing, billing, progress reporting, and failure compensation, while persisting workflow history so work can resume after worker failures without manual reconciliation. The company models end-to-end videos as workflows containing activities, runs scene processing concurrently with stage-specific limits, and uses child workflows only where separate timeout or failure boundaries are useful. HeyGen also built a shared platform for reusable workflow modules, consistent retries, identity propagation, metrics, search metadata, heartbeats, worker scaffolding, and deterministic-code checks. To manage heterogeneous GPU infrastructure across Kubernetes and serverless providers, it applies customer-level admission controls and task priorities, operates workload-specific queues and workers, and uses Temporal-based global autoscaling workflows to allocate capacity according to readiness, demand, cost, and provider preference. Additional worker-slot controls overlap input downloads with GPU inference while ensuring only one task uses a GPU at a time, improving utilization without distorting performance metrics.

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