Azure GenAIOps Maturity Levels Hub¶
Last updated: 2026-07-27
List of references
Generative Artificial Intelligence Operations (GenAIOps), also known as large language model operations (LLMOps), applies engineering, evaluation, security, and operational practices to generative AI applications in production. This hub uses four maturity levels to help teams improve deliberately rather than trying to automate everything at once.
Warning
These guides are learning material. Confirm current Azure feature support, pricing, responsible AI requirements, and security controls in Microsoft's official documentation before production use.
Maturity model overview
Understand the four levels and how to assess your current operating model. Levels 1 and 2
Establish foundational model access, prompt design, application integration, and repeatable delivery. Levels 3 and 4
Operate monitored, governed services and then optimize through automation and continuous improvement. Automation
Use release controls, evaluation, analytics, and feedback loops to improve safely. Deployment checklist
Verify governance, evaluation, observability, and release readiness.
Understand the four levels and how to assess your current operating model. Levels 1 and 2
Establish foundational model access, prompt design, application integration, and repeatable delivery. Levels 3 and 4
Operate monitored, governed services and then optimize through automation and continuous improvement. Automation
Use release controls, evaluation, analytics, and feedback loops to improve safely. Deployment checklist
Verify governance, evaluation, observability, and release readiness.
Start here¶
| Need | Start with |
|---|---|
| Identify the current capability level | Maturity model overview |
| Build first Azure AI Foundry experiments | Level 1: Initial |
| Standardize delivery and evaluation | Level 2: Defined |
| Operate governed, observable applications | Level 3: Managed |
| Optimize with automation and feedback | Level 4: Optimized |