From LLMOps to DevSecOps for GenAI

Ken Huang (), Vishwas Manral and Wickey Wang
Additional contact information
Ken Huang: DistributedApps.ai
Vishwas Manral: McAfee Enterprise
Wickey Wang: ISACA

Chapter Chapter 8 in Generative AI Security, 2024, pp 241-269 from Springer

Abstract: Abstract This chapter explores the emerging discipline of LLMOps, contrasting it with traditional MLOps approaches and highlighting unique considerations when operationalizing GenAI models and applications. A detailed examination of implementing LLMOps across the model lifecycle is provided, encompassing activities like base model selection, prompt engineering, model tuning, deployment, and monitoring. Recognizing security as a critical priority, strategies for integrating DevSecOps into LLMOps are outlined, establishing security as a shared responsibility across the development and operational lifecycle. The chapter offers conceptual foundations and practical guidance for successfully navigating the intricacies of LLMOps.

Keywords: LLMOps; MLOps; GenAI; Model operations; Model deployment; Monitoring; DevSecOps; Continuous security; CI/CD pipeline; Automated testing; Adaptation; Prompt engineering; Model tuning; Model inference point (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:fuobcp:978-3-031-54252-7_8

Ordering information: This item can be ordered from
http://www.springer.com/9783031542527

DOI: 10.1007/978-3-031-54252-7_8

Access Statistics for this chapter

More chapters in Future of Business and Finance from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().