As adoption of Kubernetes autoscalers like Karpenter accelerates, a new set of platform-agnostic observability practices is emerging, shifting focus from traditional infrastructure metrics to...

本研究提出了名为Chiron的自适应扩展器，旨在优化云服务中大型语言模型的自适应扩展，特别是服务水平目标（SLO）。Chiron通过排队大小、利用率和SLO的层次反压估计，显著提高了SLO达成率90%和GPU效率70%。

In this article, I’ll show Neon autoscaling in action by running a load test using one of Postgres’ most popular benchmarking tool, pgbench. The test simulates 30 clients running a heavy query. ...