Overcoming Challenges in Deploying Large Language Models for Generative AI Use Cases: The Role of Containers and Orchestration

© 2024 by IJCTT Journal
Volume-72 Issue-2
Year of Publication : 2024
Authors : Sriramaraju Sagi
DOI :  10.14445/22312803/IJCTT-V72I2P114

How to Cite?

Sriramaraju Sagi, "Overcoming Challenges in Deploying Large Language Models for Generative AI Use Cases: The Role of Containers and Orchestration," International Journal of Computer Trends and Technology, vol. 72, no. 2, pp. 75-81, 2024. Crossref, https://doi.org/10.14445/22312803/IJCTT-V72I2P114

This research delves into using Language Models (LLMs) in converged infrastructure, specifically focusing on container technologies like Kubernetes and OpenShift for orchestration purposes. The passage discusses the challenges involved in implementing LLMs, including scalability, performance issues and security considerations. It suggests that containers can effectively address these challenges. Additionally, it explores the benefits of using containers to deploy LLMs, such as scalability, optimized resource utilization, enhanced flexibility, increased portability, and strengthened security measures. Furthermore, it examines how Suse Rancher plays a role in managing applications that are containerized to ensure both security and scalability. The validation and analysis section provides an assessment of a study that utilizes an infrastructure platform called FlexPod to evaluate LLM models across container orchestration platforms, demonstrating the practicality and advantages of integrating FlexPod Datacenter.

Large Language Models (LLM), Containerization, Scalability, Datacenter, Kubernetes.


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