All insights
AIOpsIncidentsSecurity

AI for infrastructure operations: copilot yes, autopilot not yet

AI can gather evidence and propose mitigation. Giving it production permissions is a different conversation.

Jul 20266 min read2 sources reviewed

Where it already helps

An assistant can correlate alerts, summarize logs, retrieve runbooks and compare an incident with earlier cases. Microsoft research across tens of thousands of incidents shows the potential of LLM recommendations, but a recommendation is not a safe production action.

An autonomy ladder

  • Observer: queries data and summarizes evidence.
  • Assistant: proposes commands or changes for human approval.
  • Bounded executor: runs only approved, reversible runbooks.
  • Autonomous: reserved for low-impact actions with limits and full tracing.

Controls live outside the prompt

Least privilege, tool allowlists, sandboxes, parameter validation and rollback cannot depend on model behavior. They are infrastructure and application controls.

Choose the right first use case

Start with read-only work: build a timeline, gather recent changes or suggest queries. You can measure accuracy and utility without granting production write access.

Sources reviewed

This article is an original Nubent synthesis. The sources let you inspect the basis and explore each subject further.

  1. Microsoft Research / arXiv: Recommending Root-Cause and Mitigation Steps for Cloud Incidents using LLMs
  2. AWS Well-Architected: Agentic AI design principles

Let's work together

Schedule a technical consultation or write to us. We'll discuss your challenges and define an action plan.

Purpose-driven, method-driven, with Nubent.

Because the best solutions are built together.

We're ready whenever you are.

Nubent – ARG

Córdoba, Argentina

Nubent – ESP

Valencia, Spain
Enter at least 10 characters.
Security verification *