Design an asynchronous inference queue for handling high-volume LLM requests. ## Volume Requirements {{volume_requirements}} ## Latency SLAs - P50: {{p50_latency}}s - P99: {{p99_latency}}s ## Queue Technology {{queue_technology}} Design the system: **Queue Architecture** - Priority lanes - Dead letter handling - Retry policies **Worker Design** - Auto-scaling triggers - Health checking - Graceful shutdown **Result Delivery** - Webhook callbacks - Polling endpoint - WebSocket streaming **Observability** - Queue depth monitoring - Latency tracking - Error rate alerting Provide: - Architecture diagram - Configuration schemas - Implementation code - Capacity planning formulas
Async Inference Queue Design
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Design a high-volume async inference queue with priority lanes, auto-scaling workers, multiple delivery mechanisms, and comprehensive observability.
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Queue designAsync processingScale architecture
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claude-sonnet-4-20250514gpt-4o
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