Tag: AI Infrastructure

Native K8s orchestration is evolving to handle GPU scheduling, checkpointing, and live migration at the scale that AI demands.

The infrastructure hacks required to make scale-to-zero LLM inference viable for production latency.

Why enterprise teams are moving away from direct API calls and building internal proxy gateways to handle rate limits, caching, and automatic vendor failovers.

As context windows scale to a million tokens, the KV cache becomes too large for GPU memory. The solution is a multi-tiered cache that offloads data to CPU and NVMe without killing latency.

vLLM continuous batching and PagedAttention explained: see how dynamic KV cache allocation eliminates memory fragmentation and boosts GPU throughput by 3x–5x.