When production microservices fail, the root cause is rarely the service throwing the 500 error. GraphSentinel models infrastructure topology, team ownership, and past runbooks in FalkorDB—enabling autonomous agents to traverse multi-hop blast radii and resolve outages without guessing.
Vector databases calculate text cosine distance. But infrastructure dependencies aren't semantic similarity problems—they are directed acyclic graphs.
When payment-service throws 504 timeouts, a vector search retrieves fragmented wiki chunks mentioning "payments", "Stripe API", or "credit card".
order-service depends on payment-service, or that the failure will take down the API gateway.
The agent runs a single Cypher traversal following physical edges across the microservice mesh in 0.94 milliseconds.
Select an incident to simulate the agent's graph traversal:
MATCH path = (dependent)-[:CALLS|ROUTES_TO*1..3]->(target {id: 'payment-service'})
RETURN dependent.id AS ImpactedNode, length(path) AS Depth;
k8s_isolate_pod(target='payment-service') • Status: Executed
GraphSentinel interacts with FalkorDB using the standard Python client. No proprietary query wrappers or black-box abstractions.
Autonomous multi-hop reasoning. The agent executes Cypher path algorithms to calculate cascading blast radii and triggers MCP tools based on topology.
Persistent cross-session episodic memory. The agent stores incident resolutions as new graph edges, reusing verified runbooks with multi-tenant isolation.
Connects microservices, CVEs, team ownership, and on-call rotations (Team → Lead → Pager) with exact citations and provenance.