As LLM-powered systems mature, operational weaknesses surface across lifecycle management, deployment automation, and performance tracking. Best practices in LLM operations are required to move models safely from development to production and keep them stable at scale.
To win, your GenAI solutions must operate with disciplined lifecycle management, automated delivery, and continuous performance assurance.
When LLM operational practices are inconsistent or ad hoc, teams face compounding delivery and reliability issues:
- Uncontrolled model lifecycles: Models drift as they move from development to production without consistent promotion and rollback practices.
- Poor reproducibility: Inadequate versioning and artifact tracking make it difficult to reproduce results or diagnose regressions.
- Fragile deployment pipelines: Manual or incomplete CI/CD processes slow delivery and increase production risk.
These failures lead to unreliable deployments, degraded model performance, and slow response to production issues.
In this hands-on workshop, your team applies proven LLM operations best practices to build reliable, repeatable, and scalable model delivery workflows.
- Map and manage the full model lifecycle from development through production environments.
- Apply versioning and reproducibility practices to models, data, and configurations.
- Design and implement CI/CD pipelines tailored to LLM workflows.
- Track performance metrics and regression trends across model versions.
- Scale LLM deployment while maintaining reliability and operational confidence.
- Managing Model Lifecycle from Dev to Prod
- Versioning and Reproducibility Best Practices
- Automating CI/CD for LLMs
- Tracking Performance and Regression Trends
- Scaling Model Deployment with Reliability
- Operate LLMs across environments with consistent lifecycle controls.
- Apply reproducible versioning practices to models and supporting artifacts.
- Automate LLM delivery using CI/CD pipelines designed for model workflows.
- Detect performance regressions using systematic tracking and analysis.
- Scale LLM deployments without sacrificing reliability or control.
Who Should Attend:
Solution Essentials
Facilitated workshop (in-person or virtual)
8 hours
Intermediate
LLM platforms, CI/CD pipelines, model tracking, and monitoring tooling