Running LLMs in the Cloud - Best Practices and Deployment Approaches

Explore the growing demand for running Large Language Models (LLMs) in cloud environments and learn best practices for deploying them in cloud-native settings. Discover three key approaches for LLM deployment: Python-based solutions, native runtimes like llama.cpp or vLLM, and WebAssembly as an abstraction layer. Examine the benefits and challenges of each method, focusing on real-world applications, integration ease, portability, and resource efficiency. Gain insights into the CNCF CNAI ecosystem landscape and receive practical advice for selecting and implementing the most suitable strategy for your specific needs. Demystify cloud-native AI and obtain a clear roadmap for deploying LLMs in the cloud, understanding the strengths and trade-offs of different approaches to make informed decisions for your unique requirements.