We’re excited to announce the general availability of Console AI for commercial OCI customers – a conversational way to work with your cloud environment, built directly into the OCI Console.
Cloud operations often begin with a simple goal: create infrastructure, understand what is happening, or reduce cost. Reaching that goal can mean moving across services, resource pages, documentation, and support workflows.
With Console AI, describe what you want to accomplish, ask follow-up questions to explore the response, and review a proposed plan before approving a supported change. It’s a simpler path from question to understanding to approved action, within your existing OCI Identity and Access Management (IAM) permissions.
Console AI in action
Here are some examples of how Console AI can help you create resources, assess configurations, understand cost drivers, and investigate issues. Each starts with an everyday task and leads to a clearer answer or a change you can review.
Create and manage resources
Creating a resource often means configuring settings across more than one OCI service. Console AI brings those settings into one workflow, presenting proposed changes for review and applying them after approval.
Your team needs a private Object Storage bucket for application release artifacts, with versioning enabled and encryption using an existing customer-managed key in OCI Vault. You start by asking Console AI: “Create a private Object Storage bucket named release-artifacts. Show me the proposed configuration before creating it.”
Then you follow up to enable versioning and assign the team’s Vault key. You review and approve the proposed changes along the way.
Finally, you ask Console AI to read back the configuration. The summary confirms private access, enabled versioning, and the assigned customer-managed key. A setup that would otherwise involve separate steps across Object Storage and Vault stays in one conversation, from creation through configuration and verification.
Understand your environment and assess risk
Console AI helps you find overly permissive configurations and understand what needs to change, bringing the relevant settings and a proposed correction together so you can review and address the risk.
Before adding subnets and workloads to a VCN, you ask Console AI: “Review the security configuration of this VCN. Identify overly permissive rules, explain their potential impact, and recommend changes. Don’t make any changes yet.”
Console AI identifies a security-list rule allowing inbound traffic to every TCP port from any IPv4 address and brings the finding, supporting details, and recommendations into a canvas.
You ask Console AI to address the finding. It proposes removing the unrestricted TCP rule and explains which rules will remain. After you approve, it applies the change and shows the updated configuration for verification.
Understand and optimize cost
Console AI helps you focus your cost review by identifying the largest contributors and suggesting specific areas to investigate.
You’re reviewing your month-to-date costs and ask Console AI: “What contributed most to my OCI costs this month, and where should I look for optimization opportunities?”
Console AI presents a ranked breakdown of costs by service. Database and Block Storage account for most of the costs in this example, and its recommendations include checking for unattached storage volumes.
As a next step, you can ask Console AI to identify unattached volumes, then review their ownership, age, tags, and whether their data is still needed before deciding which are cleanup candidates.
Costs shown cover October 1–15, 2026.
Troubleshoot an issue
Console AI brings relevant network settings into the conversation, helping you move from a failed connection to a proposed correction without tracing each setting across resource pages.
Suppose one instance can’t reach an application running on another over TCP port 8080. You ask Console AI: “I can’t reach Instance B from Instance A on TCP port 8080. Investigate the OCI network configuration and propose a correction. Limit any new access to [approved source CIDR] and port 8080, preserve unrelated rules, and show me the plan before applying it.”
Console AI examines the network configuration and identifies a missing ingress rule in the subnet’s security list.
It proposes allowing port 8080 from the source subnet while preserving existing rules. You review the affected security list, port, and source range before approving the change. Console AI then checks the updated configuration, and you retry the connection. This time, the application responds.
Built on your existing permissions
Console AI works within your existing OCI IAM permissions; it cannot view or manage resources that you do not already have permission to access. For requests that modify resources, it presents a plan for you to approve or cancel. As with any AI-assisted tool, review responses and proposed changes before relying on them.
Tenancy administrators can add controls through OCI IAM deny policies. For example, they can restrict Console AI access for a group or compartment, or allow inspection while preventing resource-changing actions through Console AI. These controls do not change the user’s permissions through the Console, CLI, SDK, or API.
See Managing Access to Console AI for policy examples, setup requirements, administrator exemptions, and considerations for tasks that invoke other services.
Try Console AI
Open Console AI from the OCI Console header or Help menu and start with a question you already need to answer. If you’d like ideas, browse the starter prompts in the Guide to getting started. Ask follow-up questions to explore the response, and review proposed changes before approving them.
Then tell us how it went. Select Help Us Improve at the bottom of the chat window to share what helped and what could work better.
Console AI is currently available at no additional charge. Usage limits or throttling may apply, and pricing, availability, and limits may change over time. Check the release notes for availability details.
In the upcoming Console AI in Practice series, we’ll go deeper into complete workflows, including security investigations, compliance audit preparation, and cost optimization.