Skip to content
/scaleStable

Analyze application bottlenecks and recommend scaling strategies. Covers horizontal, vertical, and architectural scaling.

DevOpsPerformanceΒ· 2 min read

Quick import: Download the .md file and save it to .claude/commands/ (Claude Code), .cursorrules (Cursor), or paste as a system prompt in ChatGPT, Gemini, or any LLM API.

#What it does

The /scale skill analyzes your application architecture, identifies bottlenecks, and recommends concrete scaling strategies. It covers database optimization, caching layers, CDN configuration, queue-based processing, and auto-scaling rules.

#How to use

bash
/scale
/scale database
/scale for 10x traffic

#Workflow

  1. Profile -- Maps the architecture and identifies the current bottleneck (CPU, memory, I/O, database)
  2. Measure -- Estimates current capacity and the breaking point under load
  3. Recommend -- Proposes scaling strategies ranked by impact and effort
  4. Implement -- Applies the highest-impact changes with configuration
  5. Validate -- Provides load testing commands to verify improvements

#Scaling strategies it evaluates

  • Caching -- Add Redis/Memcached for hot data, HTTP cache headers, CDN for static assets
  • Database -- Connection pooling, read replicas, query optimization, indexing
  • Async processing -- Move heavy work to background queues (BullMQ, SQS, Celery)
  • Horizontal scaling -- Auto-scaling groups, container replicas, load balancer tuning
  • Edge computing -- CDN functions, edge caching, regional deployments
  • Architecture -- Database sharding, service decomposition, event-driven patterns

#Example

bash
> /scale for 10x traffic
 
# Current architecture:
Single Next.js instance, Postgres (shared connection), no caching
 
# Bottleneck analysis:
1. Database: 50 connections shared, query N+1 on /api/products (340ms avg)
2. No caching: identical queries repeated 12x/minute
3. Images served from origin (no CDN)
 
# Recommendations (by impact):
HIGH    Add Redis cache for product queries         -> 340ms to 3ms
HIGH    Fix N+1 with JOIN + batch loading           -> 12 queries to 1
MEDIUM  Configure CDN for static assets             -> 60% bandwidth reduction
MEDIUM  Add connection pooling (PgBouncer)          -> 10x connection capacity
LOW     Enable ISR for product pages (60s revalidate) -> eliminate SSR load
 
# Estimated capacity after changes: ~50x current traffic
Orel OhayonΒ·
View all skills