AI apps fail differently from normal apps: cost spikes, latency spikes, prompt regressions, model outages and missing rollback paths. These tools bring DevOps habits to LLM products.
6release checks
6AI health signals
4compose services
1incident runbook
LLMOps Release Guard
health endpoint exists
rollback plan documented
budget and token limits configured
model provider approved
observability enabled
required environment variables declared
AI Observability Kit
p95 latency
token usage
estimated model cost
success rate
error budget burn
slowest route and model pair
RAG Deploy Blueprint
config validator
Dockerfile and Compose with API, vector DB, Redis and worker