Initial commit: Complete Software Architecture course with 11 modules

- Added comprehensive course structure with 11 modules
- Included theoretical content, practical examples, and tasks
- Multi-language code examples (Java, Rust, Node.js, Python)
- Detailed analysis of architectural approaches and trade-offs
- Complete caching strategies documentation
- Architecture examples from real-world systems (Twitter, Netflix, Uber)
- Structured navigation and learning path
- Ready for educational use

modules/module10/sections/07-capacity-planning.md

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+# Capacity Planning
+
+## Навигация
+- [🏠 Главная страница курса](../../../README.md)
+- [📚 Модуль 10](../README.md)
+
+---
+
+## Процесс планирования мощности
+
+### 1. Current Capacity Analysis
+```java
+// Анализ текущей производительности
+@Component
+public class CapacityAnalyzer {
+    private final MeterRegistry meterRegistry;
+    
+    public CapacityAnalyzer(MeterRegistry meterRegistry) {
+        this.meterRegistry = meterRegistry;
+    }
+    
+    @Scheduled(fixedRate = 60000) // каждую минуту
+    public void analyzeCapacity() {
+        // Анализ CPU
+        double cpuUsage = getCpuUsage();
+        log.info("CPU usage: {}%", cpuUsage * 100);
+        
+        // Анализ памяти
+        double memoryUsage = getMemoryUsage();
+        log.info("Memory usage: {}%", memoryUsage * 100);
+        
+        // Анализ пропускной способности
+        double throughput = getThroughput();
+        log.info("Throughput: {} RPS", throughput);
+        
+        // Анализ задержки
+        double latency = getLatency();
+        log.info("Latency: {} ms", latency);
+        
+        // Предупреждения
+        if (cpuUsage > 0.8) {
+            log.warn("High CPU usage detected!");
+        }
+        if (memoryUsage > 0.8) {
+            log.warn("High memory usage detected!");
+        }
+    }
+}
+```
+
+### 2. Load Forecasting
+```java
+// Прогнозирование нагрузки
+@Service
+public class LoadForecaster {
+    @Autowired
+    private MetricsRepository metricsRepository;
+    
+    public LoadForecast forecastLoad(int days) {
+        // Получаем исторические данные
+        List<MetricData> historicalData = metricsRepository
+            .findByDateRange(LocalDateTime.now().minusDays(30), LocalDateTime.now());
+        
+        // Анализируем тренды
+        double growthRate = calculateGrowthRate(historicalData);
+        
+        // Прогнозируем нагрузку
+        double currentLoad = getCurrentLoad();
+        double forecastedLoad = currentLoad * Math.pow(1 + growthRate, days);
+        
+        return new LoadForecast(forecastedLoad, growthRate, days);
+    }
+    
+    private double calculateGrowthRate(List<MetricData> data) {
+        // Простой расчет темпа роста
+        if (data.size() < 2) return 0.0;
+        
+        double firstValue = data.get(0).getValue();
+        double lastValue = data.get(data.size() - 1).getValue();
+        
+        return (lastValue - firstValue) / firstValue / data.size();
+    }
+}
+```
+
+### 3. Resource Planning
+```yaml
+# Планирование ресурсов
+capacity_planning:
+  current_capacity:
+    cpu: "4 cores"
+    memory: "8 GB"
+    storage: "100 GB"
+    network: "1 Gbps"
+  
+  forecasted_load:
+    peak_rps: 1000
+    average_rps: 500
+    growth_rate: "20% per month"
+  
+  resource_requirements:
+    cpu:
+      current: "80% utilization"
+      target: "70% utilization"
+      required: "6 cores"
+    
+    memory:
+      current: "75% utilization"
+      target: "65% utilization"
+      required: "12 GB"
+    
+    storage:
+      current: "60% utilization"
+      target: "50% utilization"
+      required: "150 GB"
+```