Updates and recent posts about vLLM..

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@anjali shared a link, 5 months, 3 weeks ago

Customer Marketing Manager, Last9

Instrumentation: Getting Signals In

See how instrumentation in OpenTelemetry helps track app issues, know the difference between auto and manual methods, and when to use them.

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@devopslinks added a new tool Syft , 5 months, 3 weeks ago.

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@kaptain added a new tool KubeLinter , 5 months, 3 weeks ago.

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@devopslinks added a new tool Grype , 5 months, 3 weeks ago.

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@kaptain added a new tool Hadolint , 5 months, 3 weeks ago.

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@varbear added a new tool Bandit , 5 months, 3 weeks ago.

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@devopslinks added a new tool JFrog Xray , 5 months, 3 weeks ago.

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@devopslinks added a new tool OWASP Dependency-Check , 5 months, 3 weeks ago.

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@varbear added a new tool pre-commit , 5 months, 3 weeks ago.

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@devopslinks added a new tool GitGuardian , 5 months, 3 weeks 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.