Scale Your Application

Page Goal

Help users understand how to scale their applications on Temps, from vertical to horizontal scaling. Show that Temps can handle production traffic.

Target Persona

Growth Greg - A developer whose:

  • Application is getting traction
  • Experiencing performance issues or anticipating growth
  • Needs to handle more traffic
  • Worried about downtime
  • Values: Performance, reliability, cost-effective scaling
  • Questions: "Can Temps handle my traffic?", "How do I scale?"
  • Timeline: Proactive planning or reactive to current issues

Key Content to Include

1. What You'll Learn

  • Vertical scaling (bigger server)
  • Horizontal scaling (more instances)
  • Performance optimization
  • Cost vs performance tradeoffs
  • Time: 15-20 minutes

2. Understanding Scale

When to Scale:

  • Response times increasing
  • CPU/memory at capacity
  • Traffic patterns and spikes
  • Growth projections

Metrics to Monitor:

  • Response time
  • CPU usage
  • Memory usage
  • Request rate
  • Error rate

3. Vertical Scaling (Scale Up)

What it is:

  • Increase VPS resources
  • More CPU
  • More RAM
  • More disk

When to use:

  • Simple apps
  • Database-heavy apps
  • Memory-intensive processes
  • Quick fix needed

How to Scale Vertically:

Step 1: Monitor Current Usage

  • Check resource utilization
  • Identify bottleneck
  • Determine new requirements

Step 2: Upgrade VPS

  • With your VPS provider
  • Choose new tier
  • Plan migration timing
  • Usually requires brief downtime

Step 3: Migrate Temps

  • Backup configuration
  • Install on new VPS
  • Restore applications
  • Update DNS if needed

Limits:

  • Vertical scaling has ceiling
  • Cost increases quickly
  • Eventually need horizontal scaling

4. Horizontal Scaling (Scale Out)

What it is:

  • Multiple application instances
  • Load balancer distributes traffic
  • Redundancy and high availability

When to use:

  • High traffic applications
  • Need zero-downtime deployments
  • Geographic distribution
  • Cost-effective scaling

Architecture:

        [Load Balancer]
              |
    +---------+---------+
    |         |         |
[Instance 1][Instance 2][Instance 3]

How to Scale Horizontally:

Step 1: Multiple Temps Instances

  • Set up additional VPS servers
  • Install Temps on each
  • Deploy same application to each

Step 2: Load Balancer Configuration

  • Use Nginx, HAProxy, or cloud LB
  • Configure backend servers
  • Health checks
  • Session persistence (if needed)

Step 3: Shared Resources

  • External database (required for multiple instances)
  • Shared file storage (if needed)
  • Redis for sessions/cache
  • Centralized logging

5. Optimization Before Scaling

Often cheaper than scaling:

Application Optimization:

  • Database query optimization
  • N+1 query problems
  • Caching strategies
  • Code profiling
  • Bundle size reduction (frontend)

Caching:

  • Redis for application cache
  • CDN for static assets
  • HTTP caching headers
  • Database query caching

Database Optimization:

  • Indexes
  • Query optimization
  • Connection pooling
  • Read replicas

Asset Optimization:

  • Image optimization
  • Code splitting
  • Lazy loading
  • Compression

6. Auto-Scaling Strategies

Scheduled Scaling:

  • Known traffic patterns
  • Business hours vs off-hours
  • Seasonal traffic

Dynamic Scaling:

  • Monitor metrics
  • Scale based on thresholds
  • Automation scripts
  • Cloud provider auto-scaling

7. Cost Considerations

Vertical Scaling Costs:

  • Linear to exponential cost increase
  • $5 VPS → $10 → $20 → $40+

Horizontal Scaling Costs:

  • More linear cost scaling
  • 3x $5 VPS = $15 for 3x capacity
  • Load balancer cost
  • Complexity overhead

Optimization Costs:

  • Zero to minimal cost
  • Time investment
  • Often best ROI

8. Database Scaling

Since Temps doesn't host databases:

External Database Services:

  • Managed PostgreSQL (Digital Ocean, AWS RDS)
  • Managed MongoDB (Atlas)
  • Managed Redis (Upstash, Redis Cloud)

Database Scaling Strategies:

  • Vertical scaling (bigger DB instance)
  • Read replicas
  • Connection pooling
  • Caching layer

9. Real-World Scenarios

Scenario 1: Small App Growing

  • Start: $5 VPS
  • Problem: CPU at 80%
  • Solution: Upgrade to $10 VPS
  • Result: Handles 3x traffic

Scenario 2: High-Traffic App

  • Start: $10 VPS, 10k daily users
  • Problem: Peak hour slowdowns
  • Solution: 3x $10 VPS + load balancer
  • Result: Handles 50k daily users smoothly

Scenario 3: Optimization First

  • Start: Slow responses
  • Problem: 2s average response time
  • Solution: Add caching, optimize queries
  • Result: 200ms response time, no scaling needed
  • Cost: $0

10. Monitoring & Alerting

Set Up Monitoring:

  • Server metrics (CPU, RAM, disk)
  • Application metrics (response time, errors)
  • Traffic metrics
  • Alert thresholds

Tools:

  • Grafana + Prometheus
  • Uptime monitoring
  • Log aggregation
  • APM tools

11. Zero-Downtime Deployments

Blue-Green Deployments:

  • Two identical environments
  • Switch traffic between them
  • Instant rollback

Rolling Deployments:

  • Update instances one at a time
  • Always some instances serving traffic
  • Gradual rollout

12. Troubleshooting

Performance Issues:

  • Identify bottleneck first
  • Don't scale blindly
  • Monitor after changes

Scaling Doesn't Help:

  • Application-level issue
  • Database bottleneck
  • External API limits
  • Need optimization, not scaling

Success Metrics

  • User understands scaling options
  • User can make cost-effective decisions
  • User tries optimization before scaling
  • Clear path from small to large scale
  • Confidence in Temps for production

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