Traffic Estimation for Magento 2

Traffic Metrics

Key Metrics

Metric                  | Definition
------------------------|------------------------------------------
Page Views (PV)         | Total pages loaded
Unique Visitors (UV)    | Distinct users
Sessions                | Visits (includes returning)
Requests per Second     | Real-time load
Concurrent Users        | Users active at same time
Bandwidth               | Data transferred (GB)

Traffic Patterns

Daily Pattern:
00:00-06:00: Low (10% of average)
06:00-09:00: Ramp up (50%)
09:00-12:00: Peak (100%)
12:00-14:00: Slight dip (80%)
14:00-18:00: High (90%)
18:00-22:00: Evening peak (95%)
22:00-00:00: Decline (40%)

Weekly Pattern:
Monday: 110% of average
Tuesday-Thursday: 100%
Friday: 90%
Saturday: 80%
Sunday: 70%

Calculating ConcurrentUser

// Formula for concurrent users
$concurrentUsers = (
    $dailyUniqueVisitors
    × $averageSessionDuration
    × $peakHourPercentage
) / (24 × 60);

// Example:
$uv = 50000;
$sessionDuration = 5; // minutes
$peakPercentage = 0.25; // 25% of traffic in peak hour

$concurrent = (50000 × 5 × 0.25) / (24 × 60);
// = 87 concurrent users at peak

Traffic Growth Modeling

// Linear growth
function linearGrowth($currentTraffic, $growthRate, $months) {
    return $currentTraffic * (1 + ($growthRate * $months));
}

// Compound growth
function compoundGrowth($currentTraffic, $monthlyGrowthRate, $months) {
    return $currentTraffic * pow(1 + $monthlyGrowthRate, $months);
}

// Example: 5% monthly growth
$current = 100000; // daily PV
$future = compoundGrowth($current, 0.05, 12);
// 100000 × 1.05^12 = 179,586 daily PV in 12 months

Peak Traffic Calculation

Black Friday Estimation

// Historical Black Friday multiplier
$multipliers = [
    'normal_day' => 1.0,
    'black_friday' => 5.0,      // 5x normal
    'cyber_monday' => 4.5,      // 4.5x normal
    'christmas_week' => 3.0,    // 3x normal
    'flash_sale' => 8.0,        // 8x normal (1 hour)
];

// Calculate peak
$normalTraffic = 100000; // daily PV
$blackFridayTraffic = $normalTraffic * $multipliers['black_friday'];
// = 500,000 PV

// Requests per second
$peakRPS = $blackFridayTraffic / (24 * 3600) * 10; // 10x average RPS
// = 500000 / 86400 × 10 = 57.8 RPS

Peak RPS Calculation

function calculatePeakRPS($dailyPV, $peakMultiplier = 10) {
    $averageRPS = $dailyPV / 86400;
    $peakRPS = $averageRPS * $peakMultiplier;
    
    // Add buffer for spikes
    $burstRPS = $peakRPS * 1.5;
    
    return [
        'average' => round($averageRPS, 2),
        'peak' => round($peakRPS, 2),
        'burst' => round($burstRPS, 2)
    ];
}

// Example: 500K daily PV
$traffic = calculatePeakRPS(500000);
// average: 5.79 RPS
// peak: 57.87 RPS
// burst: 86.81 RPS

Response Time Impact

Concurrent Users vs Response Time:

Users    | Response Time | Status
---------|---------------|--------
10       | 200ms         | OK
50       | 250ms         | OK
100      | 350ms         | OK
200      | 800ms         | Warning
500      | 2000ms        | Slow
1000     | 5000ms        | Critical

Plan for 2x expected peak.

Capacity Buffer

Recommended buffers:
- Normal operations: 1.5x average
- Peak periods: 2x expected peak
- Critical events: 3x expected peak

Example:
Expected peak: 100 RPS
Required capacity: 200 RPS (2x buffer)
Critical capacity: 300 RPS (3x buffer)

Load Testing

k6 Script

import http from 'k6/http';
import { sleep } from 'k6';

export const options = {
  stages: [
    { duration: '2m', target: 100 },  // Ramp up
    { duration: '5m', target: 100 },  // Stay at 100
    { duration: '2m', target: 200 },  // Peak
    { duration: '5m', target: 200 },  // Stay at peak
    { duration: '2m', target: 0 },    // Ramp down
  ],
  thresholds: {
    http_req_duration: ['p(95)<500'],
    http_req_failed: ['rate<0.1'],
  },
};

export default function () {
  http.get('https://example.com/');
  sleep(1);
}

E-Commerce Seasonality

Annual Calendar

Month       | Traffic Index | Key Events
------------|---------------|----------------------------------
January     | 0.7           | Post-holiday lull
February    | 0.8           | Valentine's Day
March       | 0.9           | Spring collection
April       | 1.0           | Average
May         | 1.1           | Mother's Day
June        | 1.0           | Average
July        | 0.9           | Summer lull
August      | 1.0           | Back to school
September   | 1.1           | Fall collection
October     | 1.2           | Pre-holiday ramp
November    | 2.5           | Black Friday, Cyber Monday
December    | 2.0           | Holiday shopping

Planning for Seasonality

// Infrastructure scaling plan
$seasonalPlan = [
    'baseline' => [
        'servers' => 4,
        'db_replicas' => 1,
        'cache_nodes' => 2
    ],
    'peak' => [
        'servers' => 8,        // 2x baseline
        'db_replicas' => 3,    // 3x baseline
        'cache_nodes' => 4     // 2x baseline
    ],
    'black_friday' => [
        'servers' => 12,       // 3x baseline
        'db_replicas' => 5,    // 5x baseline
        'cache_nodes' => 6     // 3x baseline
    ]
];

// Cost impact
$baselineCost = 2000; // monthly
$peakCost = $baselineCost * 2;
$blackFridayCost = $baselineCost * 3;

// Annual cost
$annualCost = (
    $baselineCost * 8 +    // 8 normal months
    $peakCost * 3 +        // 3 peak months
    $blackFridayCost * 1   // 1 event month
);
// = 16000 + 6000 + 6000 = $28,000

Auto-Scaling Configuration

# AWS Auto Scaling Group
auto_scaling:
  min: 4
  max: 12
  desired: 4
  
  scaling_policies:
    - name: scale_up
      metric: CPUUtilization
      threshold: 70
      adjustment: +2
      cooldown: 300
    
    - name: scale_down
      metric: CPUUtilization
      threshold: 30
      adjustment: -1
      cooldown: 600

# Scheduled scaling for known events
scheduled_actions:
  - name: black_friday_ramp
    schedule: "0 6 25 11 *"  # 6 AM Nov 25
    min: 8
    desired: 10
    max: 12
  
  - name: black_friday_ramp_down
    schedule: "0 0 27 11 *"  # Midnight Nov 27
    min: 4
    desired: 4
    max: 12

Monitoring Traffic Patterns

// Track traffic patterns
$trafficMetrics = [
    'daily_pv' => $this->getDailyPageViews(),
    'hourly_distribution' => $this->getHourlyDistribution(),
    'weekly_pattern' => $this->getWeeklyPattern(),
    'monthly_trend' => $this->getMonthlyTrend(),
    'year_over_year' => $this->getYearOverYearGrowth()
];

// Forecast next month
$forecast = $this->forecastTraffic($trafficMetrics);
// Expected: 120,000 daily PV
// Peak: 180,000 daily PV (1.5x)
// Required capacity: 360,000 daily PV (2x buffer)

Server Sizing Based on Traffic

Web Server Sizing

// Rule of thumb: 1 server per 50 concurrent users
$concurentUsers = 200;
$serversNeeded = ceil($concurrentUsers / 50);
// = 4 servers

// Or per RPS: 1 server per 100 RPS
$peakRPS = 300;
$serversNeeded = ceil($peakRPS / 100);
// = 3 servers

// Use the higher estimate
$webServers = max(4, 3);
// = 4 servers

Database Sizing

Traffic Level      | DB Servers | Read Replicas | Connection Pool
-------------------|------------|---------------|-----------------
< 50K daily PV    | 1          | 0             | 50
50K-200K daily PV  | 1          | 1             | 100
200K-500K daily PV | 1          | 2             | 200
500K-1M daily PV   | 2 (cluster)| 3             | 300
> 1M daily PV      | 2 (cluster)| 5+            | 500+

Cache Sizing

Redis Memory Calculation:
- Session data: 1KB × concurrent users
- Cache entries: avg 5KB × cache keys
- Full page cache: 50KB × cached pages

Example:
- 200 concurrent users: 200KB sessions
- 10,000 cache keys: 50MB cache
- 1,000 cached pages: 50MB FPC
- Total: ~100MB
- Recommended: 2GB (20x headroom)

CDN Sizing

Static Content Bandwidth:
- Average page: 2MB (images, CSS, JS)
- Daily PV × 2MB = Daily bandwidth

Example:
- 100K daily PV × 2MB = 200GB daily
- Monthly: 6TB
- With 50% cache hit: 3TB origin

CDN Plan:
- 3TB monthly origin transfer
- 100GB storage
- 10M requests

Infrastructure Cost Estimation

$infraCosts = [
    'web' => [
        'type' => 'c5.xlarge',
        'count' => 4,
        'hourly' => 0.17,
        'monthly' => 0.17 * 730 * 4
    ],
    'db' => [
        'type' => 'r5.xlarge',
        'count' => 2,
        'hourly' => 0.25,
        'monthly' => 0.25 * 730 * 2
    ],
    'cache' => [
        'type' => 'cache.r5.large',
        'count' => 2,
        'hourly' => 0.126,
        'monthly' => 0.126 * 730 * 2
    ]
];

$totalMonthly = array_sum(array_column($infraCosts, 'monthly'));
// = 496.4 + 365 + 183.96 = $1,045.36