AI-Assisted Operations in Riverbed IQ Ops

Riverbed IQ Ops is built for operators who live in incidents, data, and runbooksClosed An automated workflow that executes a series of steps or tasks in response to a triggered event, such as the detection of anomalous behavior generating an incident, a lifecycle event, or a manually executed runbook. every day. The latest release brings AIClosed Artificial Intelligence. Technology that applies intelligence and automation to observe environments, detect anomalous behavior, and execute automated investigations. into that same workspace: a conversational assistant, a governed skill library, agents inside automation, and a feed that surfaces what still needs a human decision. You stay in Riverbed IQ Ops. The platform helps you move faster.

Why teams adopt it

Traditional operations tooling expects you to already know which runbook to open, which query to run, and which expert to ping. AI-assisted operations flip that model:

The result is a closed loop: discover and design with Chat, standardize with Skills, execute with Agents, and prioritize with Observation Feed.

Meet Q and the four interfaces

Riverbed Q (Q) is the Riverbed IQ Ops assistant you talk to in Chat. Q is backed by large language model services operated by Riverbed as part of your entitled platform (see models, data, and cost in Riverbed IQ Ops Chat). Q is not a separate product login. It is part of Riverbed IQ Ops when your tenant has the feature enabled.

Interface

What you gain

Chat

A full conversation workspace to investigate, draft runbooks, and invoke catalog commands. Riverbed IQ Ops Chat

Skills

Shared, versioned know-how your organization publishes for Q and automation. Skills and Commands

Agents

Runbook steps that call catalog agents through the Agentic AI node, including on-demand runbooks you place on a schedule. Agents

Observation Feed

Actionable observations in workspace dashboards. Observation Feed Widget

A day in the life

An operator sees a spike in user-impacting events on the Observation Feed widget, opens Chat, and asks Q how to triage similar incidents. Together they outline a runbookClosed An automated workflow that executes a series of steps or tasks in response to a triggered event, such as the detection of anomalous behavior generating an incident, a lifecycle event, or a manually executed runbook. approach. A lead author saves the troubleshooting steps as a skill, publishes a commandClosed Berkeley Packet Filter. A syntax for selecting which network packets are captured or harvested based on protocol, address, port, and other packet attributes. for on-call engineers, and adds an Agentic AI node so the runbook can call a catalog agent during the next incident. The next shift does not start from a blank screen. They start from a catalog, a runbook, and a queue that already knows what needs action.

What to expect today

AI-assisted operations are rolling out continuously. Today, Q does not automatically see everything on your screen (for example, the incident you are viewing or the entity selected in a chart). Include relevant details in your prompts until deeper context support ships. Chat, catalog, and agent features also depend on tenant entitlement. Contact Riverbed if you do not see Q, AI Agents, or AI Agent Skills in the left menu.

Personalization

Complete your profile on the User Profile page so Riverbed IQ Ops can tailor Chat, workspace recommendations, and the Observation Feed to your role and scope. A first-time onboarding wizard opens automatically when you have not saved a profile yet. Profile settings also drive the Filter based on persona option when you configure an observation feed widget. See Personalization and User Profile.

What's ahead

Riverbed is expanding embedded assistant surfaces (including runbook design), richer catalog governance, tighter links between observations and automations, and stronger platform context for Q. The four interfaces are the foundation, and more connective tissue is on the way.

Go deeper

AI-Generation disclaimer

When using Generative AI technologies to create and generate content, the target audience must be aware that the content is AI generated. We recommend adding a disclaimer to the output of the content generated using the GenAI node. For example, appending "AI-Generated content".