Webinar
Building a Kubernetes Graph Engine for Agents
Kubernetes debugging often feels more like a procedural "treasure hunt" than a streamlined workflow. One simple question, like "what breaks if this node goes down?", usually turns into a dozen kubectl lookups across pods, services, and ingresses. Ariadne changes the game by turning live cluster state into a queryable Memgraph property graph.
In this technical session, Artavazd (Art) Balaian, Senior Lead Software Engineer at Agoda, reveals how he built Ariadne to replace procedural debugging with graph-based reasoning. You’ll see how Ariadne maintains a live Kubernetes state using incremental syncs and exposes that power to both engineers using Cypher queries and AI agents via the Model Context Protocol (MCP).
What You’ll Learn
In this technical session, Artavazd (Art) Balaian, Senior Lead Software Engineer at Agoda, reveals how he built Ariadne to replace procedural debugging with graph-based reasoning. You’ll see how Ariadne maintains a live Kubernetes state using incremental syncs and exposes that power to both engineers using Cypher queries and AI agents via the Model Context Protocol (MCP).
What You’ll Learn
- How to sync live K8s data into Memgraph while keeping nested metadata and irregular schemas intact.
- Watch Ariadne answer complex, multi-hop operational questions in a single query.
- How to use MCP as a secure boundary for AI agents to interact with cluster state.
- The validation layer needed to stop LLM "hallucinations" in Cypher generation.
