As enterprises scale large language models (LLMs) into production, site reliability engineers (SREs) and platform operators face a new set of challenges. Traditional application metrics—CPU usage, request throughput, memory consumption—are no longer enough. With LLMs, reliability and efficacy are defined by entirely new dynamics—token-level performance, cache efficiency, and inference pipeline latency.This article explores how llm-d, an open source project co-developed with the leading AI vendors (Red Hat, Google, IBM, etc.) and integrated into Red Hat OpenShift AI 3.0, redefines observa
As enterprises scale large language models (LLMs) into production, site reliability engineers (SREs) and platform operators face a new set of challenges. Traditional application metrics—CPU usage, request throughput, memory consumption—are no longer enough. With LLMs, reliability and efficacy are defined by entirely new dynamics—token-level performance, cache efficiency, and inference pipeline latency.This article explores how llm-d, an open source project co-developed with the leading AI vendors (Red Hat, Google, IBM, etc.) and integrated into Red Hat OpenShift AI 3.0, redefines observa
For crypto enthusiasts, there was the “gm” app, a self-described “meme app” which only allowed users to greet each other with “gm,” or “good morning,” a common acronym thrown around on Crypto Twitter and Discord. But the gm app was shut down back in September after a hacker reportedly gained access to user data. According to media reports, the privacy watchdog was considering “blacklisting” some online platforms that have repeatedly posted doxxing information, with sources saying most messages were shared on Telegram. Avoid compound hashtags that consist of several words. If you have a hashtag like #marketingnewsinusa, split it into smaller hashtags: “#marketing, #news, #usa. The Standard Channel Telegram users themselves will be able to flag and report potentially false content.
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