What problem does it solve?
This Skill helps you prevent performance breakdowns and operational outages as a TypeScript + Supabase product grows from thousands to millions of users by guiding when to measure, optimize, and scale safely.
Core Features & Use Cases
- Service-first architecture: separate thin request handlers from business logic and defer side effects so critical paths stay fast.
- Connection pooling for Edge Functions: use Supavisor/pgBouncer transaction-mode patterns to avoid exhausting Postgres connections.
- Read scaling & query hardening: select only needed columns, paginate results, add covering indexes, and cache invariant data before adding replicas.
- Async workloads via queues: move slow side effects (emails, third-party webhooks, heavy processing) off the synchronous path using durable queue patterns.
- Table partitioning strategy: partition large append-heavy tables (typically by time) only after measurable need, avoiding premature complexity.
- Scaling order + monitoring checklist: follow a disciplined sequence (cache → indexes → vertical → horizontal → partition) with instrumentation and alerts.
Quick Start
Apply the scalability checklist to your new high-traffic endpoint by mapping the flow to service layers, validating query patterns and indexes, choosing pooled connection settings for Edge Functions, and queueing any operation that would push p95 latency beyond your target.
