NVIDIA AI-Q Blueprint on Oracle Cloud Infrastructure showing cluster and volume storage requirements for AI workloads, highli

Editorial illustration for Prerequisites for NVIDIA AI‑Q Blueprint on OCI: Cluster and Volume Limits

Prerequisites for NVIDIA AI‑Q Blueprint on OCI: Cluster...

Prerequisites for NVIDIA AI‑Q Blueprint on OCI: Cluster and Volume Limits

By AI Daily Post Edited by Brian Petersen, Editor-in-Chief

June 26, 2026 • 3 min read

AI agents have sprinted forward in just two years. The first generation could answer a single query, then multi‑turn chat added a thin thread of context. Now long‑horizon agents can plot several steps, hand work to sub‑agents, preserve context across extended tasks, and run tools inside a sandbox.

NVIDIA’s AI‑Q Blueprint is an open‑source reference for that next‑gen behavior. It stitches together LangChain Deep Agents and the NVIDIA NeMo Agent Toolkit, letting you generate quick, cited answers or full‑blown research reports with sources.

This guide walks you through deploying AI‑Q 2.0 on Oracle Cloud Infrastructure. Using Terraform to spin up the OCI resources and Helm to land the workloads on OKE, you’ll end up with a live AI‑Q endpoint in your own tenancy. By the finish line you’ll also have a single command that tears everything down.

It’s aimed at developers and platform engineers who are comfortable with Kubernetes, Terraform and the shell, and who prefer an OCI deployment over a local laptop. Along the way you’ll see how AI‑Q’s multi‑agent architecture maps onto OCI services, and you’ll get the exact commands to provision, deploy and open the blueprint from start to finish.

Prerequisites Make sure you have: - OCI tenancy access with a compartment you can deploy into, and enough service limits for: - OKE: One enhanced cluster and one node pool - Block Volume: At least 10 GB (dynamically provisioned by the OKE CSI driver for the in-cluster PostgreSQL) - Load Balancer: One flexible - Vault: One vault plus secrets - API keys: - NGC API key from build.nvidia.com, format nvapi- … used both as the NVIDIA inference key and to authenticate to the NGC container registry (nvcr.io ). - Tavily API key from tavily.com, format tvly- … - NGC API key from build.nvidia.com, format - Local tools: terraform 1.5 or later, kubectl 1.28 or later,helm 3.x or later, the oci CLI set up with your API signing key - Some basic knowledge of Kubernetes, Helm charts, Terraform, and the shell.

Deploy a Production-Ready NVIDIA AI-Q Blueprint on Oracle Cloud Infrastructure - NVIDIA Developer Blog

Why this matters The NVIDIA AI‑Q Blueprint gives us a concrete, open‑source path to build long‑horizon agents on OCI, but the checklist is narrow. We must have an OCI tenancy, a deployable compartment, and specific service limits: one enhanced OKE cluster with a single node pool, a block volume of at least 10 GB provisioned by the OKE CSI driver for PostgreSQL, and an active load balancer. Those caps may be enough for a proof‑of‑concept, yet it’s unclear whether they scale to production workloads that demand multiple agents and extensive tool use.

The blueprint leans on LangChain Deep Agents and NVIDIA’s NeMo Agent Toolkit, signalling a convergence of existing frameworks rather than a brand‑new stack. For developers, the prerequisites are straightforward, but the reliance on OCI’s default limits could force early capacity requests. Founders should weigh the convenience of an out‑of‑the‑box reference against the overhead of managing OCI quotas.

Researchers get a ready‑made environment, yet the long‑term performance and cost profile remain uncertain. Our takeaway: the blueprint lowers the entry barrier, but we need to monitor how its modest resource assumptions hold up under real‑world demands.