AI Kubernetes architecture diagram generator.
The topology is in the YAML. It is just spread across forty files and expressed as label matches.
Sources it reads
Plain manifests, Kustomize overlays and rendered Helm output. Rendering first matters: a chart full of unresolved template values produces a diagram of the template rather than of the deployment, which is accurate about the chart and useless for understanding the environment.
How Lucid Train draws one
Describe what you want, or point it at a repository. The agent emits a semantic graph of nodes and edges with no coordinates, and the ELK layout engine computes positions and orthogonal routing. That separation is the reason the output cannot come back with boxes overlapping or arrows crossing through cards, which is the characteristic failure when a language model is asked to place things on a canvas itself. It also means editing is editing the graph: change a component and the layout re-solves rather than drifting out of alignment.
Selectors become edges
The relationship between a Service and its pods is a label match, and label matches are precisely what humans misread: a selector matching nothing looks identical to one matching correctly. Drawing that relationship makes an orphaned Service obvious immediately, which turns this from a documentation exercise into a debugging one.
Stateful workloads drawn as data
StatefulSets with volume claims land in the data tier rather than sitting alongside stateless Deployments. That single distinction is the one people most need from a cluster diagram, because it answers what can be restarted freely and what cannot.
Local, offline, your models
It runs as a desktop application. Against a local Ollama model the whole thing works offline with no API key and no telemetry, which is the practical difference from every browser-based diagram tool: your architecture never leaves the machine.
Kubernetes resources in the diagram
| Resource | Drawn as |
|---|---|
| Deployment, DaemonSet | Application tier component |
| StatefulSet with PVC | Data tier component |
| Job, CronJob | Worker component |
| Service | The edge between selector and target |
| Ingress, Gateway API | Edge tier entry point |
| ConfigMap, Secret references | Edges to dependencies |
| Namespace | A section, when spanning several |
| HorizontalPodAutoscaler | A note on its target |
| NetworkPolicy | Read, noted, does not constrain drawn edges |
Try it
Questions
Does it connect to my cluster?
No. It reads YAML from disk, so no kubeconfig and no cluster access, which also means it works against clusters you cannot reach.
Does it work with Helm?
Yes, from rendered output. Render the chart with your values first and the diagram reflects the deployment rather than the template.
Can it diagram the whole cluster including system namespaces?
It can, and the result is dominated by components you did not write. Scoping to your own namespaces produces something a person will read twice.
Will it show the service mesh?
Mesh resources declared as manifests are drawn. Routing decisions made by the control plane at runtime are not in the YAML and therefore not in the diagram.
Related
- AI Microservices Diagram GeneratorThe interesting question is never how many services there are, it is which ones cannot be deployed without the others.
- AI Database Schema Diagram GeneratorThe physical view: tables, columns, keys and indexes, for when you need what is actually stored rather than the conceptual model.
- AI Infrastructure Diagram GeneratorWhere things run, what can reach what, and which boundaries the traffic crosses on the way.
- AI Architecture Diagram GeneratorDescribe the system, or point it at the repository and let it find out for itself.
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