“Pager goes off. 03:47 in the NOC. A lone engineer in a hoodie leans toward the glow of three curved monitors. On the video wall, red and amber alerts ripple across half a dozen dashboards. Coffee, keyboard, command line. Another incident begins.”
For years we’ve all met (or been) that engineer: part traffic-cop, part detective, part historian. The job is equal parts watching, triaging, correlating, documenting, and handing off. Despite an arsenal of best-of-breed monitoring and observability tools, most of the NOC engineer’s day (or night) is still spent fetching data, cross-referencing systems, and piecing together what actually matters.
Those very workflows became the blueprint that has inspired what we’ve been building in NetBox Operator. We asked a simple question: “If large-language-model agents could shoulder the drudgery, could network and infrastructure teams move faster and aim human creativity at higher-value problems?” The answer – spoiler alert – was “yes.”
Seasoned engineers don’t start troubleshooting by staring at a blank shell – they start by deciding which tools (Prometheus, Splunk, Grafana, Zabbix, Jira, etc.) can answer which questions. NetBox Operator encodes that same muscle-memory as declarative tool calls.
Think of an agent orchestrating a series of function calls:
Under the hood, Operator’s extensible integration framework manages the available toolset for its environment, shares context with agents about how to relate entities across operational tools back to objects in NetBox, maps every tool call to the right API, and returns structured data the agent can immediately reason about – no handcrafted glue code required.
Let’s trace what happens the moment a monitoring alert or support ticket lands with NetBox Operator.
1. Event Trigger An external system raises an alert → Operator’s Event Loop spins up.
2. Context-Gathering Agent Goal: Orient. Actions:
3. Investigation Agent Goal: Gather the right telemetry for RCA. Actions:
4. Correlation Agent Goal: Decide if this is new or déjà-vu. Actions:
Within seconds, Operator produces a rich, linked timeline of what happened, why, and what to do next – leaving the human to choose the path forward instead of spelunking for data.
Specialization matters. Each agent in the coordinated Event Execution Loop is laser-focused on a single sub-task (orientation, investigation, correlation), yet they coordinate through shared memory, the semantic map of NetBox, and direct sharing of inputs and outputs. The result is:
We’ll share another “Exploring NetBox Operator” deep dive soon, in which we’ll unpack how Operator leverages NetBox as the living semantic map of your entire estate, giving every agent perfect orientation from its very first prompt. We’re also hosting a webinar in July demoin use cases and examples. You can register here.
Stay tuned – AI superpowers are just getting started.
NetBox Operator is in active development right now, and we’re working hand-in-hand with design partners to polish every agent and integration. If you’d like to help shape the future of AI-driven network & infrastructure operations – and banish 3 a.m. dashboard dives forever. Sign up below.