Inspiration
Solo engineers ship fast but get blindsided by incidents. I wanted an AI SRE co-pilot that predicts tomorrow’s outages from today’s logs.
What it does
- Ingests logs (paste/upload/sample)
- Scores risk via a Vultr worker with latency visible in UI
- Generates AI forecasts with chain steps and personalized actions
- Shows trends and history via SmartSQL
- Learns patterns with SmartMemory
How I built it
- Backend: Raindrop Platform (Hono), all 4 SmartComponents (SmartBuckets, SmartSQL, SmartMemory, SmartInference)
- Compute: Vultr Cloud Compute worker for risk scoring
- Frontend: Next.js 14 + Tailwind on Netlify
- Auth/Payments: WorkOS AuthKit, Stripe checkout
- SmartInference chain branching (critical/preventive/standard) + SmartBuckets context sampling + rate limiting + authz guard
Challenges I ran into
- Env propagation (c.env vs process.env) to reach Vultr worker in Raindrop
- Cloudflare/Vultr firewall blocking the worker → fixed via direct A record + gray-cloud
- Keeping UI fresh under caching; solved with always-visible refresh and loading states
Accomplishments that I am proud of
- All four Raindrop SmartComponents used meaningfully
- Vultr latency and health surfaced in the UI
- SmartInference chain branching with transparent chainSteps
- Auth + payments + production-ready safeguards (authz guard, rate limiting, friendly errors)
- Unit tests for core logic
What I learned
- How to orchestrate SmartInference with branching based on trend/risk
- Practical SmartBuckets usage (programmatic listing + context sampling)
- Operational hardening on Raindrop (env bindings, fallbacks) and Vultr connectivity
What’s next for CloudSage – AI Ops Oracle
- Real-time streaming via Vultr Valkey pub/sub
- Slack/Discord alerts for critical risk
- Deeper SmartMemory semantic context and RAG on logs
Built With
- authkit;
- cloudflare
- javascript
- next.js
- raindrop-platform-(hono)
- raindrop-smartbuckets
- smartinference;
- smartmemory
- smartsql
- stripe;
- tailwind;
- terraform
- typescript;
- vultr
- workos

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