Enterprise AI & MLOps
Enterprise LLM Deployment Studio
Orchestrate scalable, GPU-accelerated environments for Large Language Models (LLMs). Generate production Kubernetes manifests, high-performance vLLM configurations, and Prometheus GPU dashboards dynamically.
⚙️ Model & Engine Configuration
☸️ Kubernetes & SRE Telemetry
Generate ingress manifests pointing to external endpoints with Cert-Manager annotations.
Export scraping rules targeting vLLM/Triton metrics endpoints to monitor KV Cache usage and queue delays.
💡 Interactive LLM Host Topology
Visual path representing how the client requests route to GPU cores.
HTTP Client Request
➔
Ingress Controller
➔
K8s Service (8000)
vLLM Engine Pod
➔
NVIDIA GPU (AWQ)
➔
Prometheus Scraper
.yaml
⚡ LLM SRE GPU Cheat Sheet
# Verify NVIDIA GPU device status on node:
kubectl exec -it-n llm-hosting -- nvidia-smi
# Query active request throughput from vLLM endpoint:
curl http://llm-service:8000/metrics | grep vllm