Updates and recent posts about vLLM..

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@laura_garcia shared a post, 1 week ago

Software Developer, RELIANOID

SOC2 compliance

🔐 𝗦𝗢𝗖 𝟮 alignment is about trust, resilience, and doing security right by design. At 𝗥𝗘𝗟𝗜𝗔𝗡𝗢𝗜𝗗, our load balancing and application delivery platform is aligned with the 𝗦𝗢𝗖 𝟮 𝗧𝗿𝘂𝘀𝘁 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝗖𝗿𝗶𝘁𝗲𝗿𝗶𝗮—𝗰𝗼𝘃𝗲𝗿𝗶𝗻𝗴 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆, 𝗔𝘃𝗮𝗶𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆, 𝗖𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝘁𝗶𝗮𝗹𝗶𝘁𝘆, 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 𝗜𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆, 𝗮𝗻𝗱 𝗣𝗿𝗶𝘃𝗮𝗰𝘆. From encryption ..

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@kevin-faun started using tool BOOM , 1 week ago.

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@goutham-annem started using tool vLLM , 1 week, 1 day ago.

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@goutham-annem started using tool Kubernetes , 1 week, 1 day ago.

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@goutham-annem started using tool Istio , 1 week, 1 day ago.

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@goutham-annem started using tool GPT-5.3-Codex , 1 week, 1 day ago.

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@goutham-annem started using tool Google Kubernetes Engine (GKE) , 1 week, 1 day ago.

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@goutham-annem started using tool Claude Code , 1 week, 1 day ago.

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@goutham-annem started using tool Azure Kubernetes Service (AKS) , 1 week, 1 day ago.

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@goutham-annem started using tool AWS EKS , 1 week, 1 day ago.

vLLM is an advanced open-source framework for serving and running large language models efficiently at scale. Developed by researchers and engineers from UC Berkeley and adopted widely across the AI industry, vLLM focuses on optimizing inference performance through its innovative PagedAttention mechanism — a memory management system that enables near-zero waste in GPU memory utilization. It supports model parallelism, continuous batching, tensor parallelism, and dynamic batching across GPUs, making it ideal for real-world deployment of foundation models. vLLM integrates seamlessly with Hugging Face Transformers, OpenAI-compatible APIs, and popular orchestration tools like Ray Serve and Kubernetes. Its design allows developers and enterprises to host LLMs with reduced latency, lower hardware costs, and increased throughput, powering everything from chatbots to enterprise-scale AI services.