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https://github.com/mizcausevic-dev/kinetic-gain-operator-console

Mission-control operator console for the Kinetic Gain Protocol Suite — interactive topology mesh, configurable SRE operator dashboard, audit-stream visualization, PDF export. Deploys to console.kineticgain.com.
https://github.com/mizcausevic-dev/kinetic-gain-operator-console

ai-governance audit-stream dataviz kinetic-gain kinetic-gain-protocol-suite operator-console react sre topology typescript vite

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Mission-control operator console for the Kinetic Gain Protocol Suite — interactive topology mesh, configurable SRE operator dashboard, audit-stream visualization, PDF export. Deploys to console.kineticgain.com.

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# Kinetic Gain Operator Console

> A mission-control operator console for the [Kinetic Gain Protocol Suite](https://github.com/mizcausevic-dev/kinetic-gain-protocol-suite) — interactive topology mesh, spec playground, audit-stream spine, AEO reference stack, MCP tool shield, and a fully configurable operator dashboard.

**Live:** [console.kineticgain.com](https://console.kineticgain.com)

![Operator Dashboard](screenshots/operator-dashboard.png)

## What it is

Six surfaces, one console, built for the person who *runs* a governed AI platform — not the person debugging a single prompt:

| Tab | What it shows |
| --- | --- |
| **Topology Mesh** *(v0.2)* | 9-node graph of the Suite's producers/consumers plus the three runtime gates (MCP Permission Broker, Azure OpenAI Governance Bridge, SQL Contract Enforcer), the hash-chained AuditStream spine, and an Incident Correlator. Four view modes — **flow**, latency **heatmap**, **ed25519 signature posture**, and **runtime-gate** overlay — plus **blast-radius tracing** (click a node → highlight every downstream-affected surface), per-node telemetry, and a node inspector |
| **Spec Playground** | Live exploration of the eleven Suite specifications |
| **AuditStream Spine** | Real-time governance event stream visualization over the hash-chained, tamper-evident log |
| **AEO Reference Stack** | The five-layer AEO consumption stack (SDKs → CLI → crawler → validator → graph explorer) |
| **MCP Tool Shield** | MCP tool-card governance + permission posture |
| **Operator Dashboard** | A configurable SRE control plane (below) |

### The Operator Dashboard

The showpiece. A configurable operator surface with:

- **Layout configurator** — savable runtime profiles (e.g. "Standard SRE Overview"), restore-to-template
- **Widget toggles** — Kinetic Data-Flow Visualizer, VPC Resource Metrics Matrix, Protocol Jitter Line Analyzer, Interactive SRE Alerts Portal
- **Three layout modes** — Bento Grid · SRE Split · Stack Flow
- **Simulation throttle** — 10% (quiet flow) → 100% (stress test)
- **Per-channel latency sliders** — Publisher→Agent, Agent→Answer, Answer→Auditor, Classroom→Agent
- **Force Packet Flood / Sync Nominal SLAs** controls
- **PDF export** of the current operator view (jspdf + html2canvas)

## Surfaces

| | |
| --- | --- |
| ![Topology Mesh](screenshots/topology-mesh.png) | ![Spec Playground](screenshots/spec-playground.png) |
| ![AuditStream Spine](screenshots/audit-stream.png) | ![AEO Reference Stack](screenshots/aeo-reference-stack.png) |

## Honest framing

**v0.2 is a high-fidelity simulation.** The telemetry, packet flow, node metrics, signature posture, and gate decisions are driven by `src/data.ts` (synthetic) — this is a *showcase and design reference* for what the governed-AI control plane looks like, not a live feed off production. The mesh topology, runtime gates, and blast-radius semantics mirror the real Suite architecture; the roadmap (below) wires individual panels to the live Suite services.

## Stack

React 19 · Vite · Tailwind CSS v4 · Framer Motion · lucide-react · jspdf + html2canvas (PDF export) · `@google/genai` (optional AI assist). The PDF-export deps are split into their own chunk so the initial load stays light (~121 KB gzipped main bundle).

## Run

```bash
npm install
npm run dev # http://localhost:3000
npm run build # production build to dist/
npm run preview # serve the build
```

Optional: set `GEMINI_API_KEY` in `.env.local` (see `.env.example`) to enable the AI-assist features. The console runs fully without it.

## Shipped in v0.2

- **Topology Mesh expansion.** The mesh grew from 5 to 9 nodes — producers/consumers plus the three runtime gates (`mcp-permission-broker`, `azure-openai-governance-bridge`, `sql-contract-enforcer`), the hash-chained AuditStream spine, and an Incident Correlator. Added a **blast-radius** mode (click any node → highlight every downstream-affected surface via directed-graph closure, mirroring `incident-correlation-rs`), **ed25519 signature-status** node coloring, and a **runtime-gate** overlay that marks every policy-enforced edge with a Decision-Card shield. Distinct node shapes per kind (gate, spine, incident).

## Roadmap

- **v0.3 — wire one panel to real data.** Point the AuditStream Spine at a live [`audit-stream-py`](https://github.com/mizcausevic-dev/audit-stream-py) SSE endpoint (`GET /events/stream`) so at least one surface shows the real, hash-chained governance log.
- **Animate producer→spine edges by the actual event-kind producers** off the live spine schema.
- **Lazy-load PDF export** at the call site so the chunk only loads on export.
- **Real MCP Tool Shield** wired to `mcp-kinetic-gain` tool metadata.

## Provenance

Cross-model build: scaffolded + visualized by **Google AI Studio (Gemini)**, then hardened, de-scaffolded, vocabulary-aligned (ed25519, not ECDSA), chunk-split, CI-gated, and shipped by **Claude Code**. See the [Kinetic Gain cross-model workflow](https://github.com/mizcausevic-dev/kinetic-gain-protocol-suite/blob/main/CROSS_MODEL_BRIEF.md).

## License

Apache-2.0.