Horizontal vs Vertical Scaling Simulator - Learn Scaling Strategies
Horizontal vs Vertical Scaling Simulator
Learn scaling strategies by managing traffic under real-world conditions
Scenario:
Speed:
Time: 0s / 200s
Current Traffic
0 req/s
Avg Response Time
0ms
Target: <200ms
Uptime
100.0%
Target: >95%
Monthly Cost
$0
Budget: $200
Budget Usage$0 / $200
Upgrade individual server specs. Note: Upgrades require ~30s downtime.
Pricing Reference (Monthly)
CPU Cores
2 cores$15
4 cores$30
8 cores$60
16 cores$120
RAM
4 GB$10
8 GB$20
16 GB$40
32 GB$80
64 GB$160
Disk Type
HDD$5
SSD$15
NVMe$30
Network
1 Gbps$0
10 Gbps$25
Traffic Pattern (Last 60s)
Start simulation to see traffic
Total Requests
0
Successful
0
Failed
0
Active Servers
0 / 0
Understanding Scaling Strategies
What You'll Learn
- Horizontal scaling (scale out) vs vertical scaling (scale up)
- When to use each scaling strategy based on workload
- Impact on performance, cost, and reliability
- Auto-scaling configuration and benefits
- Load distribution with horizontal scaling
- Budget management and cost optimization
Scaling Strategies
Vertical Scaling: Increase server resources (CPU, RAM, disk) - simple but limited
Horizontal Scaling: Add more servers with load balancer - unlimited but complex
Auto-Scaling: Automatically adjust capacity based on demand
Hybrid Approach: Combine both strategies for optimal results
💡 Real-World Applications
- • AWS EC2: Use Auto Scaling Groups with ELB for horizontal scaling
- • Kubernetes: Horizontal Pod Autoscaler (HPA) for container workloads
- • Databases: Read replicas (horizontal) vs larger instances (vertical)
- • Serverless: Automatic scaling without managing servers
🎯 Best Practices
- • Start with vertical scaling for simplicity, then scale horizontally
- • Use auto-scaling to handle traffic spikes cost-effectively
- • Set appropriate cooldown periods to avoid scaling thrashing
- • Monitor key metrics: CPU, memory, response time, error rate
- • Design stateless applications for easier horizontal scaling