Big picture first, sharp edges second.
I connect platform, network, identity, observability, and delivery so teams stop discovering architecture during incidents.
SRE-ish / automation-heavy / homelab-tested
I build calm systems for loud environments.
Infrastructure, automation, and AI workflows for people who prefer recovery plans over rituals.
No backup, no mercy. No signal, no story.
Fast signals
- No trackers
- Open-source first
- Observability before opinions
- DR is not a PDF
- Professional, weird enough
What I do
I turn messy requirements into systems that behave.
Not by magic. By mapping dependencies, removing toil, and making failure boring enough to rehearse.
If it repeats, it gets a button.
IaC, API integrations, GitOps patterns, and event-driven workflows that reduce manual heroics.
LLMs with guardrails, not vibes.
Practical AI experiments for documentation, operations, support flows, and internal tools.
$ runbook test --before-prod
alerts: useful | backups: verified | humans: caffeinated
Operating style
A little chaos, a lot of control.
- Break down the fog before touching production.
- Prefer boring building blocks with interesting outcomes.
- Make observability part of the feature, not a guilt purchase.
- Document the path back, not just the path forward.
Proof signals
The lab is not a toy. It is the proving ground.
Proxmox, containers, routing, storage, identity, and monitoring stitched into realistic failure scenarios.
Backup and DR ideas tested before they become slideware or bedtime stories.
Clear communication, reversible steps, and tooling that makes the next incident shorter.
Stack orbit
Tools I like when the room gets warm.
Linux
Proxmox
Docker
Kubernetes
Talos
GitOps
IaC
n8n
Authelia
Reverse Proxies
VLANs
BGP Concepts
CheckMK
Wazuh
Logging
LLM Tooling
API Integrations
Open channel
Got a system that smells like future incident?
Send context, constraints, and the part that keeps coming back as manual work.