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docs(architecture): fix stale 5-node claim -> 7 nodes (k8s-node1..6) [ci skip]

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Cluster grew to 7 nodes (k8s-master + node1..6; node5/6 added ~10d ago)
but several docs still said "5 nodes". Corrected with live specs:

- overview.md: 7-node enumeration; node1 is 16c/48GB (doc wrongly said
  32GB), node2-6 are 8c/32GB general workers
- compute.md: "5-node" -> "7-node" cluster description
- dns.md: NodeLocal DNSCache DaemonSet "5 nodes" -> "7 nodes"
- mailserver.md: HAProxy backend diagram "node1..4" -> "node1..6"

Illustrative "0/5 nodes available" scheduler-error examples left as-is.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
Viktor Barzin 2026-06-05 20:03:58 +00:00
parent bf3608052b
commit c24b4a21d8
4 changed files with 6 additions and 6 deletions
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6
docs/architecture/overview.md
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@ -134,10 +134,10 @@ This three-tier network design isolates Kubernetes workloads from management inf
### Compute Layer
The Kubernetes cluster consists of 5 nodes:
The Kubernetes cluster consists of 7 nodes:
- **k8s-master (200)**: 8c/32GB control plane running kube-apiserver, etcd, controller-manager
- **k8s-node1 (201)**: 16c/32GB GPU node with Tesla T4 passthrough, tainted for GPU workloads only
- **k8s-node2-4 (202-204)**: 8c/32GB workers running general-purpose workloads
- **k8s-node1 (201)**: 16c/48GB GPU node with Tesla T4 passthrough, tainted for GPU workloads only
- **k8s-node2-6 (202-206)**: 8c/32GB workers running general-purpose workloads
GPU passthrough on node1 uses PCIe device 0000:06:00.0. The NVIDIA GPU Operator's gpu-feature-discovery auto-labels whichever node carries the card with `nvidia.com/gpu.present=true`; `null_resource.gpu_node_config` taints the same set of nodes with `nvidia.com/gpu=true:PreferNoSchedule`. No hostname is hardcoded — moving the card to a different node requires no Terraform edits.