As GenAI systems move from experiments to services, teams struggle to operationalize training, inference, and reliability across engineering and operations. LLMOps and GenAIOps require clear scope, automation, and service-level discipline to function in production.
To win, your GenAI solutions must run with clearly defined operational ownership, automated pipelines, and enforceable service guarantees.
When LLM and GenAI operations are poorly defined, teams encounter systemic delivery and reliability risks:
- Unclear operational scope: Teams lack shared definitions of LLMOps and GenAIOps roles, responsibilities, and ownership boundaries.
- Fragmented lifecycle orchestration: Training, fine-tuning, and inference workflows are managed inconsistently across environments and teams.
- Weak operational handoffs: Engineering and operations transitions introduce delays, errors, and unclear accountability.
These gaps result in unreliable GenAI services, slow iteration, and escalating operational risk.
In this hands-on workshop, your team establishes a practical foundation for operating GenAI systems by aligning scope, workflows, and reliability practices.
- Define LLMOps and GenAIOps scope, roles, and ownership models using real-world operating scenarios.
- Map and orchestrate training, fine-tuning, and inference workflows across development and production contexts.
- Design effective handoff patterns between engineering and operations teams.
- Implement automation and monitoring pipelines that support repeatable and observable operations.
- Establish SLAs and SLOs aligned to GenAI service expectations and failure modes.
- Defining LLMOps and GenAIOps Scope and Roles
- Orchestrating Training, Fine-Tuning, and Inference
- Coordinating Engineering and Ops Handoffs
- Implementing Automation and Monitoring Pipelines
- Establishing SLAs and SLOs for GenAI Services
- Clearly define operational scope and ownership for LLMOps and GenAIOps initiatives.
- Orchestrate end-to-end GenAI workflows from training through inference.
• Improve collaboration and accountability between engineering and operations teams.
• Apply automation and monitoring patterns that support reliable GenAI services.
• Align GenAI system behavior to measurable service-level objectives.
Who Should Attend:
Solution Essentials
Facilitated workshop (in-person or virtual)
4 hours
Intermediate
GenAI platforms, automation pipelines, and monitoring tooling in a guided environment