Recommendations Tab: Guided Policy Analytics & Remediation
The Recommendations tab is the central UI for reviewing, understanding, and acting on security, cleanup, and optimization findings within your OCI tenancy. This tab synthesizes actionable insights from a pluggable, analytics-driven engine and presents them in an interactive, user-friendly dashboard.
How Does It Work?
Recommendations and related findings are dynamically generated by the Policy Intelligence engine, which evaluates your loaded policies, users, groups, and compartments against a suite of pluggable analytic strategies. These strategies identify risky, invalid, redundant, or overlapping policy statements and aggregate results into a unified model.
Key highlights:
Every section of this tab draws from live analytics and data overlays—there is no static “rules table.”
Intelligence strategies can be extended and updated without changing the UI or needing a redeploy.
You don’t need to interpret raw OCI policy text; instead, you get guided, actionable recommendations and insight into why they’re being surfaced.
If you’re interested in all the fine details—how the engine works, how plug-ins (strategies) are added, and what happens under the hood—see Further Reading: AI Context at the end of this guide.
Usage Tips & Workflow Suggestions
After loading data, always review the Summary Table for high-priority risks and limits issues first.
Use filters and sorts in every tab to focus on what’s most important for your tenancy or project.
Take Action on actionable issues directly from Cleanup/Fix—a fast route to trackable and auditable remediation steps.
Interpret why an issue is flagged by expanding details in each table—most analytics include clear rationale and recommended next steps.
Reload regularly: If you make changes in OCI Console or via CLI, clicking “Reload All” refreshes analytics and cleans up completed workbench items.
Curious about technical details? See below.
Further Reading: AI Context & Detailed Architecture
Curious about the deep technical contract behind this tab?
All analytic findings, dashboard subtabs, workbench logic, and extensibility are governed by a formal, pluggable overlay model and a set of modular strategy “plug-ins.” If you’re an advanced user, developer, or just want a full description of how analytics are constructed (with diagrams, wiring, and extensibility guides), see:
Policy Intelligence Engine & Recommendations UI — AI Context
context/project/CONTEXT_policy_intelligence_and_recommendations.md
This “AI Context” is the source of truth for the analytic and UI contract. It covers:
Overlay data model and all canonical output structures
Pluggable strategies and how to extend/reason about them
Control/data flow diagrams for engine, plug-ins, overlay, and UI
Extensibility/workbench details and all implementation references
Other Reading: