1.2 KiB
1.2 KiB
name, description, type, originSessionId
| name | description | type | originSessionId |
|---|---|---|---|
| DGX Spark Nodes | dgxmain and dgxsec - DGX Spark GB10 ARM nodes with full AI stack, Ollama, LiteLLM, credentials | project | f6f70bf9-8d74-459e-a0c1-f9f2333923d4 |
dgxmain (10.100.102.241, Tailscale 100.124.217.84)
- ARM Cortex-X925+A725, 20 cores, 122GB RAM, NVIDIA GB10 GPU
- 3.6TB NVMe (29% used)
- SSH: yohay / Biton24680#@
(login), Biton24680#@(sudo) - Ollama: running natively (systemd), port 11434
- Models: nemotron-3-super:120b, gpt-oss:120b, llama3:70b, deepseek-r1:70b, qwen3:32b, gemma3:27b, devstral:23.6b, gemma3:4b, nomic-embed-text
- LiteLLM proxy: port 4000, key sk-dgxmain-litellm-2026
- Docker containers: Dify stack, Open WebUI, Gitea, n8n, Portainer, Caddy, WordPress, ArangoDB, TensorRT-LLM, Kali
dgxsec (10.100.102.240, Tailscale 100.78.185.72)
- Same hardware as dgxmain
- 3.6TB NVMe (75% used - needs cleanup)
- SSH: yohay / Biton24680#@
(login), Biton24680#@(sudo) - Docker installed but was stopped, now started
- Ollama: not yet deployed
Why: These are the most powerful compute nodes in the cluster. Not in K8s due to ARM compatibility issues.
How to apply: Use standalone Docker Compose for GPU workloads. LiteLLM on dgxmain is the unified inference API for all services.