Keynote: Deploying LLM Workloads on Kubernetes by WasmEdge and Kuasar - Tianyang Zhang & Vivian Hu

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Keynote: Deploying LLM Workloads on Kubernetes by WasmEdge and Kuasar | 主论坛演讲: 使用WasmEdge和Kuasar在Kubernetes上部署LLM工作负载 - Tianyang Zhang, Huawei Cloud & Vivian Hu, Second State
LLMs are powerful artificial intelligence models capable of comprehending and generating natural language. However, the conventional methods for running LLMs pose significant challenges, including complex package installations, GPU devices compatibility concerns, inflexible scaling, limited resource monitoring and statistics, and security vulnerabilities on native platforms. WasmEdge introduces a solution enabling the development of swift, agile, resource-efficient, and secure LLMs applications. Kuasar enables running applications on Kubernetes with faster container startup and reduced management overheads. This session will demonstrate running Llama3-8B on a Kubernetes cluster using WasmEdge and Kuasar as container runtimes. Attendees will explore how Kubernetes enhances efficiency, scalability, and stability in LLMs deployment and operations.
LLM是强大的人工智能模型，能够理解和生成自然语言。然而，传统的运行LLM的方法存在重大挑战，包括复杂的软件包安装、GPU设备兼容性问题、不灵活的扩展性、有限的资源监控和统计，以及在本地平台上的安全漏洞。 WasmEdge提出了一种解决方案，可以开发快速、灵活、资源高效和安全的LLM应用程序。Kuasar使应用程序能够在Kubernetes上运行，具有更快的容器启动速度和减少的管理开销。本场演讲将演示如何使用WasmEdge和Kuasar作为容器运行时，在Kubernetes集群上运行Llama3-8B。与会者将探索Kubernetes如何提高LLM部署和运营的效率、可扩展性和稳定性。