My old homelab virtualization setup had grown organically. It worked most of the time, but maintenance windows were stressful and recoveries were too manual. In 2024, I redesigned around a small Proxmox cluster with one principle: stability before cleverness.

Stock photo source: Pexels , image reference: photo 17489163 .
Cluster goals
I kept goals intentionally narrow:
- predictable VM lifecycle,
- fast rollback path,
- usable backup and restore flow,
- simple enough networking to debug quickly.
I avoided chasing enterprise-grade patterns that did not match my hardware limits.
Hardware and role layout
The cluster used three nodes:
- node-a: primary workloads and automation,
- node-b: secondary workloads and failover target,
- node-c: lighter services plus quorum support.
I documented resource classes for each VM type so scheduling and expectations were explicit.
Storage decisions that actually worked
I tested shared storage options but found complexity high for my budget and risk tolerance. I landed on:
- local NVMe for active VM disks,
- scheduled backups to dedicated backup storage,
- replication only for selected critical workloads.
This gave me simpler failure behavior. When a node failed, I restored or restarted from known-good backups instead of depending on fragile storage assumptions.
Network segmentation model
I split traffic into VLAN-backed bridges:
- management,
- services,
- storage/backup,
- sandbox.
This reduced accidental cross-talk and made packet tracing easier during weird latency spikes.
Template and image strategy
I standardized golden templates for Debian and Ubuntu guests with:
- hardened base config,
- cloud-init support,
- monitoring agent pre-installed,
- backup hooks enabled.
VM provisioning became a versioned workflow instead of click-driven improvisation.
Backup discipline and restore drills
I used Proxmox Backup Server with tiered retention:
- daily snapshots for critical VMs,
- weekly for medium-priority VMs,
- monthly archives for low-change utility boxes.
Most importantly, I rehearsed restores monthly. The first drill exposed a missing post-restore DNS update step that had never been documented.
HA expectations and reality
I intentionally did not market this setup to myself as “high availability” in the enterprise sense. On limited hardware, the better framing was:
- faster and safer recovery,
- reduced manual chaos,
- bounded downtime.
That mindset kept design decisions honest.
Performance bottleneck I hit
In the first month, backup windows caused I/O contention on one node hosting both active services and backup-heavy workloads. Symptoms were latency spikes and occasional guest stalls.
Fixes:
- moved backup-heavy VMs to a different node,
- staggered backup start times,
- tuned compression and bandwidth limits.
After this, overnight backup impact dropped to acceptable levels.
Operational playbooks
I added playbooks for:
- failed node reboot,
- corrupted guest disk recovery,
- runaway VM resource usage,
- planned cluster patching.
Each playbook included verification commands and rollback checkpoints.
Upgrade and patching model
I switched from ad-hoc upgrades to phased maintenance:
- patch one non-critical node,
- run workload and network checks,
- patch second node,
- patch primary node last,
- run post-maintenance smoke tests.
This sequence prevented platform-wide surprise regressions.
Security hardening applied
I tightened:
- management network access control,
- API token scope,
- SSH key hygiene,
- audit logging retention.
The highest value change was separating daily operations credentials from high-privilege break-glass accounts.
What improved after two months
- VM provisioning became consistent and faster,
- restore confidence increased significantly,
- change windows became routine instead of risky,
- incident timelines were shorter because topology was documented.
Mistakes I would avoid next time
- trying too many storage experiments in the same month,
- underestimating backup I/O impact,
- leaving too many one-off VMs outside template discipline.
Practical rules I now keep
- Prefer reproducibility over feature novelty.
- Test restores, do not just trust backup success logs.
- Keep network segmentation simple and visible.
- Patch in phases with clear stop points.
- Document every manual recovery command used during incidents.
Proxmox gave me a stable foundation because I kept architecture conservative and operations disciplined. That was enough to support all the other lab services without turning platform maintenance into a second full-time job.