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Sentinel

The OpenAI-native master orchestrator and unified command center for the Sentinel platform—correlating Argus security evidence and Phoenix resilience outcomes through the Sentinel Operations Graph (SOG).

Architecture · Roadmap · Sentinel Platform

What Sentinel does

Sentinel sits above Argus (security) and Phoenix (resilience) — the master supervisor of the Sentinel platform. It doesn't detect threats or inject chaos itself; it watches the agents that do, and turns their raw event streams into fleet-wide situational awareness.

  • LangGraph supervisor — subscribes to the shared event bus, normalizes Argus + Phoenix events through the common schema, and routes them into scoring and reporting
  • Fleet risk scoring — a continuous per-datacenter/per-component score derived from MTTR, recovery rate, cascade-prevention rate, and live threat signals
  • Operational briefing — OpenAI-generated intelligence: simulated vs. actual threats, simulated vs. actual failures, heal success rate, MTTR trend, cascade-prevention rate, and the causal chains behind the day's notable events
  • Command-center dashboard — a 23-datacenter geospatial/grid heatmap with sparklines, a unified Argus + Phoenix + human-action timeline, a live component dependency graph with blast-radius pulse, and a daily insights panel — in the platform's dark command-center style

Build Week command center

The Build Week MVP includes a FastAPI aggregation layer and React command center with:

  • unified Argus + Phoenix evidence timeline
  • transparent fleet/component risk scoring
  • Sentinel Operations Graph topology and posture
  • autonomy trust and human-gated action visibility
  • honest disconnected/degraded source states
  • OpenAI Responses API operational briefings generated from live shared state

One-command complete platform demo

For the recommended judge path, keep the three checkouts in this layout and run the orchestrator from Argus:

Projects/
├── argus-k8s/                 # run the command here
└── sentinel-stack/
    ├── phoenix/
    ├── sentinel/
    └── sentinel-platform/

The recommended judge path is cluster-free. It needs Docker or OrbStack for one disposable Redis container, but does not need Kubernetes, kubectl, Cilium, Falco, or Chaos Mesh. Run the non-mutating doctor:

make -C ../../argus-k8s doctor

Launch the complete platform:

make -C ../../argus-k8s demo-platform

The command installs missing dependencies; starts a disposable local SOG and real local Argus, Phoenix, and Sentinel services; seeds an explicitly synthetic three-node, multi-namespace topology; and verifies multiple cross-agent incidents through Sentinel. A bounded replay/simulator feed makes counters, timelines, freshness, and risk views change during the presentation. Open Argus at http://127.0.0.1:5173, Phoenix at http://127.0.0.1:5174, and Sentinel at http://127.0.0.1:5175. Every synthetic entity and finding is labeled; no Kubernetes API or live Chaos Mesh fault is used. Ctrl-C stops the local services and removes the disposable Redis container.

For the guarded real three-node k3s proof:

kubectl config use-context argus
make -C ../../argus-k8s doctor-live
make -C ../../argus-k8s demo-platform-live

The doctor is read-only and ends with a READY/NOT READY verdict plus an exact next action. The live command requires the exact context and the phrase INJECT LIVE FAULT, creates only sentinel-live-demo, and continuously probes a two-replica HTTP target. It waits for observed Argus/Falco evidence, asks Phoenix to create one real Chaos Mesh PodChaos, verifies the replacement and full readiness, and then requires Sentinel to expose the correlated incident with observed + live_chaos provenance. The scorecard contains measured availability and recovery time; Ctrl-C deletes only the isolated namespace.

Open the resulting correlated incident to see the canonical resilience proof: Healthy → Fault injected → Detection → Decision → Human approval → Recovery → Verification. Live runs include measured detection time, recovery time, HTTP availability, and evidence sources. Every record is assigned exactly one visible label: Live Observed, Synthetic Simulator, Live Chaos Mesh, or Replayed Evidence. Older records without stage evidence display unavailable steps instead of inferred data.

Before presenting, expand Presentation Preflight at the top of Sentinel. The panel checks Argus, Phoenix, Sentinel, SOG, OpenAI, Kubernetes, Cilium, Falco, Kyverno, and Chaos Mesh through read-only endpoints. Portable mode marks cluster-only systems N/A; live mode reports actual Ready pod counts from the authorized kubectl context. Every failure includes its evidence and an exact remediation. The platform demo commands will not declare success unless this panel reports Ready to present.

Sentinel-only development

Run the Sentinel Operations Graph service first, then:

cp .env.example .env
make setup-local
set -a; source .env; set +a
make demo-local

Open http://127.0.0.1:5175.

The top-bar product switcher uses the explicit VITE_ARGUS_URL and VITE_PHOENIX_URL values from .env. The reserved local console ports are Argus 5173, Phoenix 5174, and Sentinel 5175; deployed environments should replace those values with their public URLs.

Stack

FastAPI aggregation/orchestration service, OpenAI Responses API for operational briefing, React + TypeScript + Vite + Tailwind dashboard, real-time via WebSocket/SSE. Subscribes to the Redis-streams event bus defined in sentinel-platform and reuses the existing Prometheus/Grafana/Loki + Cilium stack from argus-k8s — no duplicate infrastructure.

Related repos

Repo Role
argus-k8s Security agent — eBPF threat detection, policy enforcement, AI reasoning
phoenix Resilience agent — chaos injection, synthetic provisioning, self-healing
sentinel-platform GitOps layer — shared schema, Helm umbrella chart, deploy harness

License

Apache License 2.0 — see LICENSE and NOTICE.

About

Master orchestrator and command-center for the Sentinel platform — a LangGraph supervisor that aggregates Argus and Phoenix events, scores fleet risk, and generates daily intelligence reports through a real-time dashboard.

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