Infrastructure Sizing Estimator

Determine the recommended server specifications based on your traffic.

Traffic & Load

Recommended Instance Size

0 vCPU
Compute
0 GB
Memory

Rough estimation. Always load test.

The Science of Server Sizing

One of the most difficult questions for any DevOps engineer or startup founder is: "How big of a server do I need?"

Buy too small, and your site crashes during a viral moment. Buy too big, and you burn thousands of dollars on idle silicon. This estimator gives you a starting point based on industry-standard heuristics for web application performance.

Understanding the Metrics

1. Concurrent Users vs. Total Users

This distinction is vital.

  • Total Users: The number of people signed up (e.g., 10,000).
  • Daily Active Users (DAU): People who login today (e.g., 1,000).
  • Concurrent Users: The number of people clicking a button at the exact same second (e.g., 50).

You provision servers for Concurrency, not Total Users. A site with 1 million users might only have 500 concurrents if they are spread across 24 hours.

2. CPU-Bound vs. Memory-Bound

Different apps stress different parts of a computer.

  • CPU-Bound: Video encoding, encryption, AI inference, complex mathematical calculations. You need high-frequency cores (Successor: Compute Optimized instances like AWS c6g).
  • Memory-Bound (RAM): Caches (Redis), Databases (PostgreSQL), big data processing (Spark). You need massive RAM to keep data fast (Successor: Memory Optimized instances like AWS r6g).
  • I/O Bound: File uploads, logging, database writes. You need fast SSDs (IOPS).

The "20% Buffer" Rule

Never run your servers at 100% utilization. If a server hits 100% CPU, it becomes unresponsive, queuing requests until it times out (504 Gateway Timeout).

Best Practice: Aim for 60-70% utilization during peaks. This leaves a 30% "burst buffer" for unexpected spikes or background tasks (like cron jobs) that might run simultaneously.

Vertical vs. Horizontal Scaling

Vertical (Scale Up)

Buying a bigger server (e.g., moving from 2 CPU to 4 CPU).
Pros: Easy to do. No code changes needed.
Cons: Has a limit. Eventually, you can't buy a bigger computer. Requires downtime to upgrade.

Horizontal (Scale Out)

Buying more servers (e.g., adding 2 more 2-CPU servers).
Pros: Infinite scale. High availability (if one dies, others survive).
Cons: Complex. Needs a Load Balancer. Apps must be "stateless" (not saving sessions to local disk).

Frequently Asked Questions

How many users can a 1GB RAM VPS handle?

For a static HTML site? Thousands. For a heavy WordPress site with 50 plugins? Maybe 5 concurrent users. The bottleneck is usually PHP/Python memory usage per process.

What is a CPU Credit?

On small cloud instances (like AWS t3.micro), you don't get 100% of the CPU all the time. You earn "credits" when idle and spend them when busy. If you run out of credits, your performance is throttled to 5% baseline. Never use burstable instances for consistent production loads.

The Golden Rule: Calculation is just a guess. The only truth is Load Testing. Use tools like k6 or JMeter to simulate 1,000 users hitting your actual app and see when it breaks.