LLMOps
Manage prompt changes, model access, and cost with reproducible evaluation evidence and production context.
4 guides · Suggested reading order
Start here
What is LLMOps? From prototype to production
Understand development, evaluation, deployment, and feedback.
Next guides
- Read guide
Prompt versioning for production AI systems
Treat prompts as versioned artifacts with evaluation and rollback.
- Read guide
What is an AI gateway?
Understand routing, resilience, policy, and model access.
- Read guide
LLM cost monitoring: Measure cost per successful task
Relate model and tool costs to successful task outcomes.
Go deeper
How to evaluate LLM routers for cost, quality, and latency
Compare routing policies using task quality, latency, cost, and fallback behavior.
Fine-tune Mistral 7B with LoRA on Kubernetes
Connect LoRA training, GPU execution, evaluation, and versioned adapter packages.
Continuous AI red teaming in CI/CD
Turn reviewed security findings into versioned release checks.
How to evaluate LLM guardrails
Choose guardrails using both protection and legitimate application behavior.
Put the foundations into practice
Explore practical guides and resources to take the next step.