Production-Ready LLM Deployment and Observability
In the previous chapter, we tested and evaluated our LLM app. Now that our application is fully tested, we should be ready to bring it into production! However, before deploying, it’s crucial to go through some final checks to ensure a smooth transition from development to production. This chapter explores the practical considerations and best practices for productionizing generative AI, specifically LLM apps.
Before we deploy an application, performance and regulatory requirements need to be ensured, it needs to be robust at scale, and finally, monitoring has to be in place. Maintaining rigorous testing, auditing, and ethical safeguards is essential for trustworthy deployment. Therefore, in this chapter, we’ll first examine the pre-deployment requirements for LLM applications, including performance metrics and security considerations. We’ll then explore deployment options, from simple web servers to more sophisticated...
