MLOps and GenAIOps
How MLOps, LLMOps, GenAIOps, platform engineering, and agent operations relate to the five BROCS operating scopes.
MLOps and GenAIOps provide practices for repeatable AI development, deployment, evaluation, and monitoring. BROCS places those practices inside a broader enterprise operating model that also covers access, runtime ownership, change control, cost, security, and compliance evidence.
Existing operations still apply
Microsoft defines generative AI operations, or GenAIOps, as an extension of existing MLOps investments. The same guidance notes that GenAIOps is sometimes called LLMOps.1
Many generative AI workloads begin with a consumed foundation model. Their operating workload includes prompts, orchestration, grounding data, indexes, evals, application code, and sometimes agents. These artifacts need versioning, deployment, monitoring, and rollback alongside any model configuration.
Relation to BROCS
| Practice | Primary focus | BROCS relationship |
|---|---|---|
| MLOps | Data and model pipelines, experimentation, deployment, inference, and monitoring | Supplies practices mainly to Build, Run, Observe, and Control |
| GenAIOps or LLMOps | Prompts, orchestration, retrieval, grounding data, indexes, evals, and generative-model use | Extends Build, Run, Observe, and Control beyond the model artifact |
| Platform engineering | Shared tools, self-service paths, repeatability, and secure defaults | Supports organization-wide Build and Run capabilities |
| Agent operations | Tool access, state, traces, identity, authorization, action limits, and recovery | Requires coverage across all five BROCS scopes |
These labels overlap, but they emphasize different responsibilities. BROCS checks the work around them and the handoffs between teams. A strong MLOps practice can coexist with weak access control, an unsupported builder experience, missing agent traces, or compliance evidence assembled after an incident. In BROCS, agent operations means the runtime, identity, state, authorization, traces, action limits, and recovery required for agents that use tools or take actions.
Apply the crosswalk
For an existing AI workload, record the artifacts and services already governed by MLOps or GenAIOps. Then use the BROCS assessment to inspect the organizational responsibilities around that work, including supplier and business-team handoffs.
See enterprise AI operations for the wider operating model and adjacent practices for the DORA, SRE, platform, security, governance, and FinOps sources behind BROCS.
Microsoft, "Generative AI operations for organizations with MLOps investments", Azure Architecture Center, updated October 17, 2025. ↩︎