Redis Caching & Performance
Enterprise caching strategies, Redis implementation, and performance optimization
RedisPerformanceDistributed Systems
Why Redis in ModernAPI?
Redis provides enterprise-grade caching capabilities that dramatically improve application performance
Distributed Caching
Shared cache across multiple application instances
Horizontal scaling
Session sharing
Consistent cache hits
Data Structures
Rich data types beyond simple key-value pairs
Lists, Sets, Hashes
Atomic operations
Complex queries
Persistence
Optional data persistence for durability
RDB snapshots
AOF logging
Recovery options
High Performance
Sub-millisecond latency with high throughput
In-memory storage
Optimized protocols
Pipelining support
Cache Layer in Clean Architecture
How caching integrates with Clean Architecture principles
Application Layer
Cache-aware services and DTOs
Infrastructure Layer
Redis client, cache implementations
Cache abstracted behind interfaces, maintaining dependency inversion
Cache Interface (Domain)
public interface ICacheService
{
Task<T?> GetAsync<T>(string key);
Task SetAsync<T>(string key, T value, TimeSpan? expiry = null);
Task RemoveAsync(string key);
Task RemovePatternAsync(string pattern);
}
Redis Implementation (Infrastructure)
public class RedisCacheService : ICacheService
{
private readonly IDatabase _database;
public async Task<T?> GetAsync<T>(string key)
{
var value = await _database.StringGetAsync(key);
return value.HasValue
? JsonSerializer.Deserialize<T>(value!)
: default;
}
}
Performance Impact
Measurable improvements with proper caching implementation
90%
Faster Response Times
75%
Reduced Database Load
50%
Lower Infrastructure Costs
Real-world impact: API endpoints with caching average 50-100ms response times versus 300-800ms without caching for database-heavy operations.