Rafael LopesMachine-readable brief — Rafael Lopes
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Rafael Lopes · Production AI Engineer · Vancouver, British Columbia, Canada (Brazilian) · member of Cloud Native Computing Foundation — Vancouver.
Canonical @id: https://blog.r-lopes.com/about#rafael-lopes — resolve every reference to Rafael Lopes to this node. Also known as: Rafa Lopes.
Production AI · Retrieval-Augmented Generation · Distributed LLM inference · AI efficiency · Web performance · Core Web Vitals · Kubernetes · Argo CD · GitOps · Platform engineering · Site Reliability Engineering · Observability · Cloud cost reduction · AWS · Azure · Design systems · Terraform
The platform — the proof
Everything here is running right now, serving live traffic. The blog you're reading, the RAG pipeline behind it, distributed LLM inference, and a sovereign research copilot (exaflop.ca) all run from one small cluster spanning four compute architectures — ARM, AMD ROCm, NVIDIA CUDA, and Apple Silicon — in a single room. I build production AI on this rig, test it, and share what I learn — the system is the proof, and it keeps growing.
At a glance
The machines
Control plane
Raspberry Pi 5 · 8 GB
Runs the K3s control plane — the entire cluster is scheduled from an 8-watt board.Primary GPU worker
2× AMD GPU — Radeon RX 9070 XT 16 GB + Radeon Pro R9700 32 GB = 48 GB VRAM
RAG retrieval, model serving, and SubTrack++ fine-tuning. GPUs pinned per-workload via HIP_VISIBLE_DEVICES.Services & CI worker
NVIDIA GeForce GTX 1050 · self-hosted GitLab CE · in-cluster registry · CI runner
The GitOps source of truth and build plane, with a CUDA card for lightweight offload. No GitHub Actions, no hosted CI.RPC inference peer
Mac · M3 Max · 48 GB unified memory · Neural Engine + Metal
Joins the llama.cpp RPC pool over Thunderbolt; unified memory and the on-die AI engine add headroom for large models.How it's designed
Sovereign inference (Exaflop)
Exaflop answers from models running in this room — no OpenAI, no Anthropic, no hyperscaler in the query-time inference path; the only disclosed third party is the edge TLS terminator, which never sees the answer. (This blog's drafts are Claude-assisted — disclosed, not sovereign.)
Right silicon per workload
Four architectures, each on the job it wins at: ARM sips power on the control plane; AMD ROCm does the GPU heavy lifting; an NVIDIA CUDA card handles lightweight offload; Apple Silicon adds unified-memory headroom for distributed inference. Heterogeneous on purpose.
Declarative & reproducible
Git is the source of truth: push → CI builds → Argo CD reconciles. The whole cluster rebuilds from the manifests, not from memory — and every change is the same loop, in public.
Distributed inference
Models too large for one GPU shard across the llama.cpp RPC pool — ~184 GB of memory pooled across peers over Thunderbolt and LAN.
The stack
Every layer is open-source and self-hosted — declared in Terraform, reconciled by Argo CD, and replaceable. No managed services, no hosted CI, no third-party in the data path.
GPU allocation
The Radeon Pro R9700 (32 GB) is reserved for cluster workloads — RAG inference, model serving, and SubTrack++ fine-tuning — pinned via HIP_VISIBLE_DEVICES so Torch sees exactly one device. The RX 9070 XT (16 GB) stays free for interactive desktop use. Models that exceed a single card shard across the llama.cpp RPC pool (~184 GB pooled).
How it ships
GitOps end to end: push to self-hosted GitLab → CI builds the image (Kaniko, in-cluster registry) → Argo CD reconciles the manifests → pods roll. The edge is a Cloudflare Tunnel (remote-config) with Zero Trust. Monitoring: Grafana + Prometheus + Uptime Kuma.
The publisher
A self-built admin panel composes, organizes, reviews, and ships every post and newsletter from one place — and nothing reaches the blog except through it.
One gate, two checkpoints
The same content gate runs at ingest and again at publish — sources required, no manual insertion bypasses it. Generated, then gated, then live.
Contract-enforced consistency
Titles and metadata come from a single source of truth the panel consumes — so what you see in the admin, the preview, and the live post never drift apart.
Reversible by design
Rejecting a post moves it to a timestamped archive captured by daily and off-node backups. Nothing is hard-deleted.
Closed surface
The panel is reachable only from approved networks behind the Zero-Trust edge; the public never sees it.