Bluesky For You Feed Scales to 72K Users on $30/mo Home Server
Run a recommendation feed for 72,000 Bluesky users using one Go process on SQLite in a living room PC (16 cores/96GB RAM/4TB NVMe), proxying via $7 VPS over Tailscale, for $30/mo total—scalable to 1M DAUs.
Lean Architecture Powers 72K Users
Build custom Bluesky feeds with a single Go server on consumer hardware: 16-core gaming PC with 96GB RAM and 4TB NVMe. Ingest the Bluesky firehose, store 90 days of data (419GB SQLite), and serve personalized feeds. Public requests hit a $7/mo OVH VPS, which tunnels via Tailscale to the home server—avoiding complex cloud setups while handling real traffic.
This setup proves you don't need Kubernetes or hyperscalers for social-scale recommendation; SQLite handles 419GB writes from firehose without sharding, as long as you prune to 90 days.
Likes-Driven Recommendations Without ML Hype
Core algorithm: Recommend posts liked by users whose like patterns match yours. No neural nets—just graph-like similarity on likes. spacecowboy tested multiple approaches, landing on the cheapest viable one that retains quality.
Trade-off: Relies on recent (90-day) data for recency, but scales horizontally if needed. Existing rig could support Bluesky's full 1M daily actives without changes.
$30/Mo Economics Beat Cloud Vendors
Breakdown: $20 electricity for home PC, $7 VPS, $3 domains. No engineers beyond one maintainer. Handles 72K users today; bottlenecks are algorithmic, not infra. Lesson: Start with Tailscale + VPS proxy for global access to local compute—cuts costs 100x vs. AWS equivalents while matching scale.
Proves custom feeds democratize algorithms: Anyone can compete with platform defaults using off-the-shelf parts.