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Getting Started

Load testing helps ensure your Unpod applications can handle concurrent user traffic and maintain optimal performance under various load conditions.

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Performance Targets and SLAs

The platform guarantees 99.99% uptime with automatic failover. SLA documentation

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Metric Commitment

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Baseline Performance Metrics

The following metrics represent measured performance under optimal baseline conditions single session, warm cache, optimal network:

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Concurrent Load Test Results

Platform stability validated under concurrent session load:

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Infrastructure Robustness

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Scalability Architecture

  • Horizontal Scaling: Native HPA Horizontal Pod Autoscaler for all stateless components
  • GPU Node Affinity: Dedicated GPU pools with NVIDIA A10G L4 for inference workloads
  • Regional Infrastructure: Automatic routing through worldwide infrastructure for optimal latency
  • Database Scaling: Postgres read replicas, MongoDB ReplicaSet with automatic failover
  • SaaS Auto-scaling: Instant autoscale vs manual capacity planning for self-hosted

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Latency Optimization Techniques

  • Streaming STT TTS: Real-time processing without full-file buffering
  • Speculative Decoding: Parallel token generation for faster LLM responses
  • Same Availability Zone: Co-located services to minimize network latency
  • gRPC WebSocket: Low-overhead protocols for inter-service communication

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Notes

  • End-to-End latency includes external service providers STT, LLM, TTS which contribute to variability under load.
  • Platform orchestration layer maintains less than 15ms latency regardless of concurrent load.
  • Performance optimizations for high-concurrency scenarios are actively being deployed.
  • Custom SLA tiers available for enterprise customers with dedicated infrastructure.