Aug 22, 2026 · Operations

Five Overlooked Runtime Risks When Deploying Large Language Models on Kubernetes

Deploying large‑model inference services on Kubernetes can hide five critical runtime risks—such as premature traffic before model loading, GPU memory overflow, LivenessProbe mis‑kills, slow HPA scaling, and missing logs—that only surface under production load, leading to timeouts, crashes, and costly debugging.

AIGPUHPA

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Five Overlooked Runtime Risks When Deploying Large Language Models on Kubernetes

DataFunSummit

Sep 8, 2023 · Artificial Intelligence

AI Compiler Forum at DataFun Summit 2023: Tile-Based Deep Learning Compilation, Graph Scheduling for Domain‑Specific Accelerators, and Triton on Hopper

The DataFun Summit 2023 AI Compiler Forum gathered leading researchers to present cutting‑edge techniques on tile‑based deep learning compilation, efficient graph scheduling for domain‑specific accelerators, large‑model deployment, and the latest advancements of OpenAI Triton on NVIDIA Hopper, offering practical insights for AI system developers.

AI CompilerGraph SchedulingLarge-Model-Deployment

0 likes · 8 min read

AI Compiler Forum at DataFun Summit 2023: Tile-Based Deep Learning Compilation, Graph Scheduling for Domain‑Specific Accelerators, and Triton on Hopper