Cloud & Platform Engineer, DevSecOps
Kepler maintainer (CNCF) · measuring energy consumption in Kubernetes
I build and operate the infrastructure that serves GPU and LLM workloads in production, on hybrid cloud (on-prem plus AWS/Azure). I automate provisioning, secure the chain, and keep cost under control.
Hybrid cloud: AWS, Azure, on-prem, GPU bare metal and cloudKubernetes / Platform: k3s, Talos, Helm, GitOps (Flux, Argo), autoscalingIaC: Terraform, Ansible, reproducible pipelines, clean teardownDevSecOps: eBPF/NDR, hardening, supply chain, zero trustGPU / LLM serving: vLLM, FP16/FP8 quantization, DCGM, measured €/token cost
| Project | In short |
|---|---|
| gpu-inference-reliability-lab | SRE lab: vLLM on k3s, DCGM observability, measured €/token and energy, incident runbooks. |
| Talos_Bastion_DevSecOps | Talos Linux GitOps cluster: Cilium (eBPF), Traefik, ArgoCD, zero-trust access. |
| terraform-runpod-vllm | One terraform apply, a RunPod GPU serves an LLM over the OpenAI API. Budget guard, clean teardown. |
| mcp-scalpel | Semantic filtering proxy for the Docker MCP Gateway. Cuts catalog tokens per turn. |
| Azure-Pipeline-Custom-Image | Azure DevOps CI/CD: custom VM image deployed via Managed DevOps Pool. |




